The Seven Steps of Performance Measures

The Seven Steps of Performance Measures Performance Measures is the seventh attribute (the seventh step) of Excellent Management

(Phase 1)

This is a Free Service for those Interested in Excellent Management This site is always under construction

Prepared by Craig A Stevens PMP CC and his Students and Other Professionals

The Number One Enemy of Good Quality (or productivity) Are the Words ldquoI Thinkrdquo and ldquoI Know That is making decisions based on something other than data and fact

Based on the works of Dr Jerry Westbrook The following information is a summary of the Seven Steps to performance measures developed By Craig Stevens in the early 1990s The Seven Steps to Performance Measures is Element 7 of the Mobile of Excellent Management Click on the Up button to see the Mobile of Excellent Management

FOR A FREE GERONIMO STONE eBOOK on the Seven Attributes of Excellent

Management go to wwwgeronimostonecom

Two Types of Performance Measures

1 Performance Measures of Programs Projects and Operations are changing Organizations are moving to a more complete form of performance measures Accounting performance measures are not the only performance measures that count The government started this process under the first Clinton Administration and we were involved in the Department of Energys first efforts of understand and implement this process of using performance measures

2 Performance Manages for People are changing Organizations are moving away from the long-established one-on-one appraisal or performance review with a boss once per year They are designing performance management systems that provide an individual with more frequent feedback from many points of view including peers direct reporting staff members and the boss The process known as 360-degree feedback provides a more balanced set of observations for the employee

STEP 1 Know the Principles and Objectives

YouTube Video PerfM1 - The Laws of Performance Measures

Know Why You Measure PerformanceYou cannot manage what you cannot measure

Tuttle TC Strategic Performance Measurement Conference Proceedings Sixth Annual National Conference on Federal Quality Federal Quality

Institute Presidents Council on Management Improvement American Society for Quality Control

Association for Quality and Participation and Quality amp Productivity Management Association 1993 pp

537-545

To understand and improve PampQ it must be measured Measurements of both efficiency and effectiveness must be done to make decisions concerning problems with the service organization

Stanleigh M Accounting for Quality CA Magazine Volume 125 October 1992 pp 40-42

Know Some of the Benefits of Performance Measures1 Enhance Ability to Recognize and Reward

Extraordinary Individual Performance 2 Enhanced Capacity for Individual Cooperation 3 Satisfied Customers 4 Effective and Satisfied Employees 5 Continuous Process Improvement 6 Increased Profits 7 Enhanced Reputation 8 Innovation 9 Effective Management

Know the Measuring Principles and ObjectivesWhat make sports or work fun Everyone Knows The Rules and Everyone Knows the Score

Victor Dingus of Tennessee Eastman in 1990

Measure what is important Concentrate on the main strategic priorities Several things may be important so a family of measures will allow different even conflicting objectives to be considered

Thor CG Performance Measurement in a Research Organization Productivity and Quality Management Frontiers -III edited by Sumanth Edosomwan Sink

and Werther 1991 Institute of Industrial Engineers

A system of measures must be used to avoid sub-optimization of elements

Salemme T Establishing Metrics for Service Based Work Conference Proceedings Sixth Annual National Conference on Federal Quality Federal Quality Institute Presidents Council on Management

Improvement American Society for Quality Control Association for Quality and Participation and Quality amp Productivity Management

Association 1993 pp 528-536

Measures are useless if the results are not used as feedback to someoneThor CG Performance Measurement in a Research Organization

Productivity and Quality Management Frontiers -III edited by Sumanth Edosomwan Sink and Werther 1991 Institute of Industrial Engineers

Simple usable metrics must be developedShycoff DB Key Criteria for Performance Measurement Comptroller

of the Department of Defense Directorate for Business Management 1992

You have to measure things that are basic If its not simple not easily understood nor easily tracked then dont bother measuring it because nobody will ever use it

Gould L Measuring Business Reengineering is Part of Its Success Managing Automation May 1993 pp 45-47

Know Some of the Performance Measurement Problems to Avoid1 Using superfluous data to continue improvement does not work

2 Avoid the problems of parameters not selected being viewed as unimportant

3 Avoid the misconception that everything must be measured 4 Avoid the easily measurable syndrome measuring easy not what is

important 5 Avoid focusing on the measurements and not processes 6 Avoid the discredited if not sophisticated syndrome 7 Avoid redundant or elaborate systems that can erode respect for

your system 8 Avoid not involving everyone This can cause resistance 9 You can not use measures to punish people and expect it to work

People will naturally hide bad news

Step 2 Understand Organizational GoalsThe starting point of measurement is a set of clear organizational goals Make sure the system ensures what you want done Connect Everything to Goals The principle purpose of performance measures is to gauge progress against stated program goals and objectives presupposing that the strategic program objectives are known

Shycoff DB Key Criteria for Performance Measurement Comptroller of the Department of Defense Directorate for Business Management

1992

Find the system and ask if it is doing what it is suppose to do When improving customer relations measuring the amount of desk time will likely work against the amount of time spent with the customer

Peter M Senge The Fifth Discipline The Art amp Practice of The Learning Organization Currency Doubleday 1994

YouTube Video PerfM2 - More Steps of Performance Measures

Step 3 Select and Weigh The Criteria

Keep the END in Mind What are the important Criteria related to the Goals Think first about Effectiveness (Doing the Right Things) and second about Efficiency (Doing Things the Right Way) Getting a Report out quicker -- is only efficiency

Example of Goal Improve or Maintain Customer Satisfaction (both internal and external)Example of Criteria Improve Quality Cost and Speed

Go to this link to see a selection tool for weighing criteriaFor the workshop attendees Remember Craigs story about the first attempts at Performance Measures by the US DOE

Step 4 Select the Performance Indicators1 Look at one Criteria at a time 2 List Potential Indicators 3 Screen the Indicators 4 Rate the Indicators and 5 Start with the Highest

Step 5 Collect Data

You will collect both Quantitative (Numbers) and Qualitative (Non-numbers) Data More information will be added here later For a link to websites where you can find statistical data go here httpwwwwestbrookstevenscomlinks_to_othershtm

Step 6 Process and AnalyzeOne way to process data is with statisticsSee Link for Statistical Analysis Tools

Step 7 Use the InformationBegin with a reasonable set of metrics and refine them as data is collected and experience is gained do not insist on the perfect set of metrics at first




MBO 360 Performance Appraisals and the Deming Management Method

(Deborah Irons TNU 4430 2008)

Business success depends on several key elements including willing workers and

leaders who coach and energize To produce results these two elements are essential However management methods and performance appraisals have long led to disgruntled employees and frustrated leaders This article looks at Management by Objectives (MBO) and compares it with 360 Performance Appraisal utilizing knowledge attained from the Deming Management Method

Performance appraisals provide a comprehensive assessment of a workerrsquos

employment activities for a predetermined interval These assessments often tie employee performance to expected outcomes for the organization Performance problems are determined solely by the manager or jointly with the employee and developmental strategies designed to resolve these problems Several forms of performance appraisals exist The two discussed here are Management by Objectives and 360 Performance Appraisals

Management by objectives is a process by which the goals and objectives of an

organization link with the performance appraisal in quantifiable terms First outlined by Peter Drucker in the early 1950rsquos MBO fundamentally allows for the identification of common goals by managers the outlining of goals for each individual and the utilization of measures to assess each memberrsquos performance [1] The MBO Cycle begins with a review of organizational goals and objectives Through managerial and employee participation employee objectives are established Throughout the cycle progress is monitored goals eliminated and incorporated and feedback given in relationship to established aspirations At predetermined intervals managers perform progress evaluation often with rewards for goal completion The cycle continues with shared revision of goals

The model of the 360 Performance Appraisals solicits performance feedback from

several sources instead of just management thus the name (360 degrees) These viewpoints may include customers peers or anyone who interacts with the employee These perspectives of employee performance provide employees and management with performance improvement goals rdquoMost results for an employee will include a comparison of their ratings to the ratings of their supervisor and average of the ratings from othersrdquo[2] Problems may arise when sources of the feedback have no knowledge of job description or performance plan At this point a comparison is made of these two types of appraisals utilizing the Deming Management Method Dr W Edwards Deming offered this method as a tool to improve industry It provides ldquoPointsrdquo to enhance management activities and ldquoSeven Deadly Diseasesrdquo which may be fatal to an organization This article will incorporate several of these to evaluate the MBO and the 360 Performance Appraisals

Dr Demingrsquos first point is ldquocreating constancy of purpose for improvement of

product and servicerdquo[3] Deming communicated that a company must invest today for the future The MBO provides for this constancy of purpose through the goals proposed for employees This approach also provides for the goals and objectives of the organization

The 360 provides a broad view of the employee including their performance training needs and customer satisfaction skills Both methods of appraisal appear to support this point

Point Five of the Deming Management Method is to ldquoimprove constantly and forever

the system of production and servicerdquo[4] This point provides for teamwork customer satisfaction and problem solving The MBO may be better suited for teamwork as it provides an effective way to maintain employee motivation support and all-around goal setting Though not always the case the 360 may decrease team building effectiveness due to the confidential input by peers Both types of appraisal promote customer satisfaction though it is more obvious in the 360 Where the MBO supports self-proposed goals increasing problem-solving skills the 360 does not This however may be a need considered for further training by the 360

Dr Demingrsquos sixth point is ldquoinstitute leadershiprdquo[5] According to Deming many

supervisors hired have no knowledge of how to supervise Whichever form of appraisal utilized leadership is essential In the MBO accomplishing objectives cannot happen without proper leadership Moreover how will a manager with no knowledge of the job complete the 360-performance evaluation The depiction of performance objectives may not be logical and employees have very little participation in deciding these objectives Without excellent leadership skills neither of these appraisals will be highly regarded ldquoDysfunction in one area will affect other areas Ultimately the organizational culture suffers which affects teams and stifles excellencerdquo[6]

After comparing these appraisal processes with the Deming Management Method be

aware that Dr Deming considers ldquoevaluation of performance merit rating or annual reviewrdquo as one of his ldquoSeven Deadly Diseasesrdquo[7] According to Dr Deming performance appraisals discourage ldquolong-term planningrdquo and ldquoincrease reliance on numbersrdquo[8] He believes this sort of evaluation leaves employees competing with instead of working with other team members ldquoThe greatest accomplishments of man Dr Deming says have been accomplished without competitionrdquo[9]

Whatever the type of appraisal utilized good managers keep goals in mind while

taking responsibility for performance planning and coaching They provide ongoing evaluations verified through day-to-day feedback There should be no ground shaking observations made during the performance review With MBO an employeersquos readiness to participation in goal setting requires careful assessment Some employees may need a more structured review With the 360 more standardization may be necessary Perhaps Dr Deming was correct about performance appraisals When not used correctly they can be ldquoDeadly Diseasesrdquo

Citations

[1]Hersey Paul Kenneth H Blanchard and Dewey E Johnson Management of Organizational Behavior New Jersey Prentice Hall 8th ed 2001 139

[2]ldquo360 Performance Appraisalrdquo httpwwwcitehrcomviewtopicphpt=10 [3] Walton Mary The Deming Management Method New York New York Berkley Publishing

Group 1986 34 [4] Walton Mary The Deming Management Method New York New York Berkley Publishing


Group 1986 70 [6] Steincamp Donna and Eileen Tremblay ldquoEvaluating Performance Evaluationsrdquo httpwwwwestbrookstevenscomperformance_measureshtm [7] Walton Mary The Deming Management Method New York New York Berkley Publishing



Group 1986 91

EVALUATING PERFORMANCE EVALUATIONS

By Donna Steinkamp and Eileen Tremblay (TNU 2005)The idea of performance evaluations often sends shudders through supervisors and workers alike Just mention the subject and you will hear a chorus of groans As a result evaluations take low priority until a call comes from the Human Resources Department Worse yet is when an employee calls or walks in your office and says ldquoI just want to remind you that my evaluation was due a month agordquo Should you care whether your performance review process is working or not Yes Here is why If administered properly the entire performance evaluation system can act like an organizations backbone tying company goals to employee performance Performance evaluation systems connect with almost every facet of an organization Organization guru Craig Stevens model for excellent management helps to illustrate this connection

The performance evaluation system positively affects every component of the excellent management model It allows Leadership to establish a rational framework for tying employee performance to organizational goals The constructive environment infuses the organization culture Teams thrive because excellent employee performance = excellent team performance = excellent organizational performance Problem Solving improves because employees focus on what is important in their job and to the organization The organization engages in Continuous Improvement because performance evaluations promote quality and help to identify training and development needs The ability to meet organizational goals enhances performance measures In short good performance evaluation systems help management achieve excellence How does setting goals for performance evaluation relate to organizational objectives The old saying goes You cannot manage what you cannot measure Setting organizational objectives is like drawing a blueprint Employee performance goals are the individual systems that make up and support the plan Employee performance becomes a function of continuous improvement How can an organization create an environment conducive to a positive performance evaluation process It is a function of team building requiring support and commitment at all levels The leadership must create a culture that is accepting of the performance evaluation system This establishes the commitment level from the lowest to highest levels It requires continuous communication vertically and horizontally throughout The feedback from manager to employee and vice versa must be honest productive and open In this environment success can become inevitable The organization lives the mantra

Effectiveness is doing the right thing and efficiency is doing it the right way The other side to the positive performance evaluation experience is the wholly ineffective system A poorly designed or implemented system can be as unproductive as having no system at all It starts with unclear standards and poorly defined responsibilities Leadership loses its focus and commitment to the process Employees fail to meet goals which ripple through to the organizations objectives Employee morale drops and management loses trust and respect Dysfunction in one area will affect other areas Ultimately the organizational culture suffers which affects teams and stifles excellence In the ineffective system employees view performance evaluations as an annual event linked to an expected sum of money Performance evaluations can and should be much more than an exercise linked to compensation More than 50 years ago behavioral scientist Frederic Herzberg said ldquoIf you want people to do a good job give them a good job to dordquo Herzberg found that achievement and recognition are motivators (Hersey Blanchard Johnson) Pay becomes an issue only when it is inadequate A positive performance evaluation will focus on improving performance and helping employees develop their maximum potential Many an organization has seen good valuable employees pick up their belongings and make for the rumored greener pastures of some other organization While salary and benefits may have much to do with these employee migrations there are plenty of losses directly attributed to failing to help employees develop their performance Smart healthy progressive companies do everything they can to give managers and employees a comfort level with the evaluation process They emphasize that performance evaluations are a part of an on-going work process and not just an annual event

KEEPING THE PEOPLE WHO KEEP YOU IN BUSINESS

Checklist of targeting employee retention through

the performance management system

Both employee and manager participate in appraisals working together to set goals

Give employees the resources to excel ndash knowledge is power Training

employees improves their skills and performance and sends the message that employees are valued

Seek performance feedback through a more balanced set of observations

ie 360-degree feedback upward appraisals Train both the employees and managers on performance evaluation

criteria competencies and appraisal format Often managers particularly new to the management arena do not have the necessary skills

Train employees through experience understanding and encouragement It is an effective way to maintain employee motivation alignment and goal setting

Give everyone a voice Employees who know their ideas and work are

valued will push their own abilities beyond their comfort zone and display creativity and innovation Most employees will embrace the opportunity to reach for higher goals especially if they have a say in setting the goals

Encourage collaboration but give employees ldquoownershiprdquo of the project Set clear performance standards Identify those standards for a particular

job and be specific about the outcomes that characterize outstanding (as well as unacceptable) performance

Identify performance barriers Start with performance looking in turn at

behavior system variables and individual variables Define responsibilities clearly When employees know their roles it

reduces confusion and gives them a better sense of how to meet their objectives

Create an environment that encourages employees to respect one another

Never criticize an employee in front of others offer corrective feedback only in private

Recognize and reward results Money does not always have to be a

motivator Always expect the best from employees Maintain ongoing communication and feedback Continuous feedback

includes reinforcing an employee who exhibits what the organization believes will help it achieve business goals Foster a culture with communication and feedback integrated into the day-to-day work

Encourage the spirit of play Play is vital to creativity and innovation and

many people need this kind of stimulus to keep the mental gears turning

Ultimately performance evaluation is just one component of the overall strategy for assessing performance in an organization Performance management is directly linked to every area of an organization all of which need to be included to add value to the organization The competition to attract and retain quality staff is only going to increase Having an effective performance evaluation system that recognizes employees as the most valuable resource of an organization can be a powerful weapon in your arsenal

Works Cited

Westbrook Stevens LLC The Linked Management Models ldquoBuilding a Foundation with the Seven Attributes of Excellent Managementrdquo August 2 2005 httpwwwwestbrookstevenscomstep_1htm Hersey Paul Kenneth H Blanchard Dewey E Johnson Management of Organizational Behavior Leading Human Resources New Jersey Prentice-Hall Inc 2001

Management by Objectives (MBO) Although viewed by many as risky leaders use MBO to integrate the goals and objectives of an organization to all individuals This concept designed by Peter Drucker begins when senior and junior managers identify common goals together define each individual or departmentrsquos responsibility and measures results by the guidelines initially designed by the managers Before managers form any objectives they must clarify all of the common goals with those involved Furthermore those responsible must periodically compare progress with the actual goals Organizations regardless of size practice this concept on many different levels and achieve successful outcomes Unfortunately other organizations find this concept unsuccessful When considering this route of leadershipPerformance Measurements managers should carefully monitor goals and provide employees with the necessary resources to meet their objectives and provide input (Hersey 139)

Eric Dunford (TNU 2006)

Paul Hersey and Kenneth H Blanchard Management of Organizational Behavior Leading Human Resources 8th Ed Upper Saddle River Prentice Hall 2001

The Values and Pitfalls of MBOA Review of the article ldquoThe Values and Pitfalls of MBO rdquo by James Owens

By Pamela Cohea Caterpillar Insurance Services Corporation (TNU 2007) Mr Owens introduces the reader to the managerial technique MOB (Management by Objectives) and gives some historical background information He states that MBO has been praised as the ultimate solution to managerial problems in

some organizations However some organizations reject the technique and decided that MBO did more harm than good to their organization Mr Owens proposes the question to the readers ldquoWhy did MBO work miracles in some organizations while failing in othersrdquo He reviews the essential elements of a typical MBO Program in stages Stage One -Management defines the Organizational Goals

The top management team set specific and measurable goals for the program

Stage Two ndash Organizational Goals are Delegated

The goals of the program are to prioritize support achieve and analyze each personrsquos contribution to the organization

The assignments of the program are delegated to each unit for completion Decisions are made as to who will do what when and with what degree of authority within the program

The management team should be participative supportive and provide the data and resources needed for the program The management team must include all peers and subordinates assigned to the program in the decision-making process

Stage Three ndash The Agreement Phase of the Performance Contract

A performance contract is drawn up between the manager and their subordinate The contract states the agreement of specific job performance goals functions tasks responsibilities authorities and resources All of the goals should be listed that will need to be met during the duration of the contract The performance contract is the most important part of the MBO program The manager communicates hisher goals for the subordinate and then the subordinate communicates their version of what goals and results that heshe can deliver They also note the authority and resources that they will need to be successful The manager and the subordinate begin discussing the variations between the two versions of the contract The goal of the discussion is for the two people to arrive at an agreement that both persons believe are realistic and obtainable for the stated contract period

Stage Four ndash Implement the Plan

The MBO program will have numerous performance contracts throughout the organization Each contract should be a contributing factor in the success of the

MBO program

The managerrsquos role in this stage includes helping the subordinate fulfill their performance contract obligations Their help and assistance can include counseling coaching and training efforts

The overall theme is a relationship between managers and subordinates that enables the organization in hitting their performance targets Stage Five - Review Results

The subordinate should assess their actual performance to the performance agreed upon in the contract using a process of self-examination If a deviation or discrepancy is detected the subordinate needs to acknowledge the gap and seek the help and assistance of their manager in correcting the issue in a timely manner

If the failure to meet the goals of the performance contract is due to changes in the situation and not that of the subordinate the manager and subordinate should abandon the existing performance contract and re-negotiate a new contract The new contract should be inline with realistic goals As soon as a problem or failure surfaces both parties need to frankly discuss and realistically resolve the issue Failure to address the shortfalls of the performance contract will have a negative outcome and may increase tension between the two parties

Mr Owen continued to discuss the values and benefits of a MBO program in an organization He believes that when an organization introduces the spirit of a MBO program to the workforce in a positive manner it can be successful Recent research confirms that when people understand the goals set before them they then become motivated to meet the goals People who are given vague goals usually lack interest in the program and do not meet their personal potential However if a person is given clear and concise goals and can focus their attention and energy to meeting the goals They can be very success and valuable team members in the organization A MBO program can improve an organizationrsquos team-building skills The management team needs to create an atmosphere of honesty participation trust and openness The mutual help and cooperation the MBO program can be a very successful tool for the organization

Work Cited Owens James The Values and Pitfalls of MBO

OTHER INTERESTING

PERFORMANCE MEASURES INFORMATION

Performance Measures Links

1 httpwwwfpmcomjournalmattisonhtm (found by Josiah Wedgewood UoP 2005)

2 httpwwwsmallbiz-enviroweborgperfmeasperfhtml (found by Josiah Wedgewood UoP 2005)

Management By Objectives (MBO)

MBO According to the Wikipedia dictionary ldquoManagement by Objectives (MBO) is a process of agreeing upon objectives within an organization so that management and employees buy in to the objectives and understand what they arerdquo ( httpenwikipediaorgwikiManagement_by_objectives ) ldquoMBOrdquo lays the foundation for the manager and the employee to work toward the objective together This concept allows the leaders and employees to set their sights on the same goal for the organization MBO sets guidelines for both employee and leader to follow that provides instruction to reach any given objective This concept helps to develop unity within the organization and create a synergy between employee and manager According to the article ldquoThe Values and Pitfalls of MBOrdquo by James Owen there are three stages of an MBO program and they are management defines organizational goals organizational goals are delegated down the hierarchy manager and subordinate agree on the subordinatersquos contract implement the plan and review results

Darla Sansom (TNU 2005)United States Wikipedia the free encyclopedia

httpenwikipediaorgwikiManagement_by_objectives

Other possible MBO stages

Management By Objectives (MBO) is a type of performance measuring tool However there are a lot of problems with MBO and most of it relates to the lack of involvement by the employees

Management by Objectives (MBO)

Eileen Tremblay (TNU 2005)

Peter Drucker introduced the business world to the concept of goal setting and measurement MBO requires managers to identify the goals they share and how each unit will work to meet those goals Performance toward meeting the goals becomes the benchmark to assess how the organization is progressing The system works properly when managers and employees jointly develop employee goals and team or group goals for a specified period The goals may be output variables or intervening variables or some combination of the two (Hersey 139) The goals are set and at the end of the specified period and performance analyzed to reach the goals Before anything else happens establish the organizations goals Only then can individual supporting goals be set Measurement should be on going Monitor progress during the period and make adjustments if needed Some goals may be unworkable or unattainable

The negative side of MBO is that employees are sometimes skeptical of the process MBO may also involve more work for employees to document goals and progress If goals are too easy to reach or do not seem relevant to the work the process will quickly be rejected As stated in class managers should concentrate on goals and measure what is important They should definitely not measure everything

Project Management Related Performance Measures

Earned Value

BCWP - budgeted cost of work performed ACWP - actual cost of work performed BCWS - budgeted cost of work scheduled STWP - scheduled time for work performed ATWP - actual time of work performed Four Types of Variances Used in EV Analysis bull AV (accounting) = BCWS - ACWP bull SV (scheduling) = BCWP - BCWS bull CV (cost) = BCWP - ACWP bull TV (time) = Review Date - date BCWP = BCWS Performance Indices to Assess Projectrsquos Progress

bull SPI (Schedule Performance Index) = BCWP BCWS bull CPI (Cost Performance Index) = BCWP ACWP bull TPI (Time Performance Index) = STWP ATWP bull Variances are also formulated as ratios rather than differences Good when comparing different projects bull

EXAMPLE

Total Project Budget BCAC = $100k bull At Review Date bull Budgeted Cost for Work Scheduled BCWS = $60k bull Actual Cost for Work Performed ACWP = $80k bull Actual Work Completion = 83 bull Budgeted Cost for Work Performed BCWP = EV act BCWP = 083 x BCWS = 083 x $60k = $50k

Eight Steps to a New Performance Measurement SystemPerformance is an important part of any measurement based management system

by Bjoslashrn Andersen and Tom Fagerhaug

This eight-step process for creating a new performance measurement system is based on our experiences with a number of organizations

Before you start your organization should establish a core team to carry the performance measurement system design process forward Though the system is never finished it should take only a year or so to get something in place

The eight steps of the design process are

1 Understand and map business structures and processes This forces those setting out to design a performance measurement system to think through and reacquaint themselves with the organization its competitive position the environment it exists in and its business processes After participating in this exercise most managers agree the effort is a welcome break from day to day operations and an opportunity to revisit some of the organizations strategic issues

2 Develop business performance priorities The performance measurement system should support the stakeholders requirements from the organizations strategy through to its business processes This order of priorities must be in place well before the process enters the actual design phases

3 Understand the current performance measurement system Every organization has some kind of measurement system in place For this reason there are basically two ways to approach the design and implementation of a new performance measurement system You can either scrap the old system and introduce the new one as a replacement or you can redevelop the existing system Both approaches can work but the former approach is more likely to lead to trouble People will cling to the old measurement system and either use both systems simultaneously or use the old one and simply go through the motions of the new one You can eliminate this outcome by taking the latter approach

4 Develop performance indicators The most important element of a performance measurement system is the set of performance indicators you will use to measure your organizations performance and business processes This is the point in the design process where the top-down cascading approach meets the bottom-up design approach and where the broad masses of the organization become involved The purpose of this step is to develop the performance measurement system with an appropriate number of relevant and precise performance indicators

5 Decide how to collect the required data Developing perfect performance indicators that will tell you everything you ever wanted to know about what goes on in your organization is one thing but being able to collect the data required to calculate these performance indicators is a completely different matter This issue must initially be ad-dressed during the development of the performance indicators so you avoid selecting those that can never actually be measured Remember the proliferation of modern enterprise resource planning systems has turned this into an exercise in figuring out which data can be extracted from the systems data warehouses

6 Design reporting and performance data presentation formats In this step you decide how the performance data will be presented to the users how the users should apply the performance data for management monitoring and improvement and who will have access to performance data After you finish you should have a performance measurement system that has a solid place in your organizations overall measurement based management system

7 Test and adjust the performance measurement system Your first pass at the performance measurement system will probably not be completely right--there are bound to be performance indicators that do not work as intended conflicting indicators undesirable behavior and problems with data availability This is to be expected In this step you should extensively test the system and adjust the elements that do not work as planned As a result you will have a system where the main quirks have been eliminated however your system will still not be perfect A performance measurement system should be construed as a never ending journey toward perfection

8 Implement the performance measurement system Now its time to put your system to use This is when the system is officially in place and all can start using it This step involves issues such as managing user access training and demonstrating the system is important and will be used

Remember this is not an absolute process that needs to be followed to the letter to work In some cases one or more steps may be superfluous in others additional steps may be needed You know your organization better than we do so its up to you to make the necessary adjustments to the process to maximize the probability of the systems success

BJOslashRN ANDERSEN is a research director at SINTEF Industrial Management in Trondheim Norway a professor at the Norwegian University of Science and Technology and a member of ASQ

TOM FAGERHAUG is a research scientist at SINTEF Industrial Management in Trondheim Norway and a member of ASQ

Note This column is adapted from the authors book Performance Measurement Explained published by ASQ Quality Press in 2002

If you would like to comment on this article please post your remarks on the Quality Progress Discussion Board on wwwasqorg or e-mail them to

Performance measurement is the process whereby an organization establishes the parameters within which programs investments and acquisitions are reaching the desired results[1]

Performance Reference Model of the Federal Enterprise Architecture 2005[2]

This process of measuring performance often requires the use of statistical evidence to determine progress toward specific defined organizational objectives

Contents[hide]

1 The reason for measuring performance 2 Performance Measurement topics

3 Practice

4 See also

5 References

6 Further reading

7 External links

[edit] The reason for measuring performance

Fundamental purpose behind measures is to improve performance Measures that are not directly connected to improving performance (like measures that are directed at communicating better with the public to build trust) are measures that are means to achieving that ultimate purpose (Behn 2003)

Behn 2003 gives 8 reasons for adapting performance measurements

1 To Evaluate how well a public agency is performing To evaluate performance managers need to determine what an agency is supposed to accomplish (Kravchuk amp Schack 1996) To formulate a clear coherent mission strategy and objective Then based on this information choose how you will measure those activities (You first need to find out what are you looking for)

Evaluation processes consist of two variables organizational performance data and a benchmark that creates a framework for analyzing that data For organizational information focus on the outcomes of the agencyrsquos performance but also including input environment process output- to have a comparative framework for analysis It is helpful to ask 4 essential questions in determining organizational data

Outcomes should be directly related to the public purpose of the organization Effectiveness Q did they produce required results (determined by outcomes)

Cost-effective efficiency Q (outcome divided by input)

Impact Q what value organisation provides

Best-practice Q evaluating internal operations (compare core process performance to most effective and efficient process in the industry)

As in order for organization to evaluate performance its requires standards (benchmark) to compare its actual performance against past performance from performance of similar agencies industry standardpolitical expectations

2 To Control How can managers ensure their subordinates are doing the right thing

Today managers do not control their workforce mechanically (measurement of time-and-motion for control as during Taylor) However managers still use measures to control while allowing some space for freedom in the workforce (Robert Kaplan amp David Norton) Business has control bias Because traditional measurement system sprung from finance function the system has a control bias

Organisation create measurement systems that specify particular actions they want execute- for branch employess to take a particular ways to execute what they want- branch to spend money Then they want to measure to see whether the employees have in fact taken those actions Need to measure input by individual into organisation and process Officials need to measure behavior of individuals then compare this performance with requirements to check who has and has not complied

Often such requirements are described only as guidelines Do not be fooled These guidelines are really requirements and those requirement are designed to control The measurement of compliance with these requirements is the mechanism of control

3 To Budget Budgets are crude tools in improving performance Poor performance not always may change after applying budgets cuts as a disciplinary actions Sometimes budgets increase could be the answer to improving performance Like purchasing better technology because the

current ones are outdated and harm operational processes So decision highly influenced by circomstance you need measures to better understand the situation

At the macro level elected officials deciding which purpose of government actions are primary or secondary Political priorities drive macro budgetory choices Once elected officials have established macro political priorities those responsible for micro decisions may seek to invest their limited allocation of resources in the most cost-effective units and activities

In allocating budgets managers in response to macro budget allocations (driven by political objectives) determin alloactions at the micro level by using measures of efficiency of various activities which programs or organisations are more efficient at achieving the political objectives Why spend limited funds on programs that do not guarantee exceptional performance

Efficiency is determined by observing performance- output and outcome achieved considering number of people involved in the process (productivity per person) and cost-data (capturing direct cost as well as indirect)

4 To Motivate Giving people significant goals to achieve and then use performance measures- including interim targets- to focus peoplersquos thinking and work and to provide periodic sense of accomplishment

Performance targets may also encourage creativity in developing better ways to achieve the goal (Behn) Thus measure to motivate improvements may also motivate learning

Almost-real-time output (faster the better) compared with production targets Quick response required to provide fast feed-back so workforce could improve and adapt

Also it is able to provide how workforce currently performing

Primary aim behind the measures should be output managers can not motivate people to affect something over which they have little or no influence

Once an agencyrsquos leaders have motivated significant improvements using output targets they can create some outcomes targets

ldquooutputrdquo- focuses on improving internal process ldquooutcomerdquo- motivate people to look outside the agency (to seek way to collaborate with

individuals amp organisations may affect the outcome produced by the agency)

5 To Celebrate Organisations need to commemorate their accomplishments- such ritual tie their people together give them a sense of their individual and collective relevance More over by achieving specific goals people gain sense of personal accomplishment and selfworth (Locke amp Latham 1984)

Links from measurement to celebration to improvement is indirect because it has to work through one of the likes- motivation learning

Celebration helps to improve performance because it brings attention to the agency and thus promotes its competence- it attracts resources

Dedicated people who want to work for successful agency Potential collaborators

Learning-sharing between people about their accomplishments and how they achieved it

Significant performance targets that provide sense of personal and collective accomplishement Targets could ones used to motivate In order for celebration to be a success and benefits to be a reality managers need to ensure that celebration creates motivation and thus improvements

By leading the celebration

6 To Promote How can public managers convince political superiors legislators stakeholders journalists and citizens that their agency is doing a good job

(National Academy of Public Administrationrsquos center for improving government performance- NAPA 1999) performance measures can be used to validate success justifing additional resources earn customers stakeholder and staff loyalty by showing results and win recognition inside and outside the organisation

Indirectly promote competence and value of goverement in general

To convince citizens their agency is doing good managers need easily understood measures of those aspects of performance about which many citizens personally care

(ldquoNational Academy of Public Administration-NAPArdquo in its study of early performance- measurement plans under the government performance and results Act) most plans recognized the need to communicate performance evaluation results to higher level officials but did not show clear recognition that the form and level of data for these needs would be different than that for operating managers Different needs Department head Executive Office of President Congress NAPA suggested for those needs to be more explicitly defined- (Kaplan amp Nortan 1994) stress that different customers have different concerns(1992)

7 To Learn Learning is involved with some process of analysis information provided from evaluating corporate performance (identifying what works and what does not) By analysing that information corporation able to learn resons behind its poor or good performance

However if there is too many performance measures managers might not be able to learn anything (Neves of National Academy of Public Administration 1986)

Because of rapid increase of performance measures there is more confusion or ldquonoiserdquo than useful data

Managers lack time or simply find it too difficult to try to identify good signals from mass of numbers

Also there is an issue of ldquoblack boxrdquo enigma (data can reveal that organisation is performing well or poorly but they donrsquot necessarily reveal why) Performance measures can describe what is coming out of ldquoblack boxrdquo as well as what is going in but they do not reveal what is happening inside How are various inputs interacting to produce the output What more complex is outcome with ldquoblack boxrdquo being all value chain

Benchmarking is a traditional form of performance measurement which facilitates learning by providing assessment of organisational performance and identifying possible solutions for improvements

Benchmarking can facilitate transfer of knowhow from benchmarked organisations (Kouzmin et al 1999)

Identifying core process in organisation and measuring their performance is basic to benchmarking Those actions probably provide answer to issue presented in purpose section of the learning

Measurements that are used for learning act as indicators for managers to consider analysis of performance in measurementrsquos related areas by revealing irregularities and deviations from expected data results

What to measure aiming at learning (the unexpected- what to aim for)

Learning occurs when organisation meets problems in operations or failures Then corporations improve by analysing those faults and looking for solutions In public sector especially failure usually punished severely- therefore corporations and individuals hide it

8 To Improve What exactly should who- do differently to improve performance In order for corporation to measure what it wants to improve it first need to identify what it will improve and develop processes to accomplish that

Also you need to have a feedback loop to assess compliance with plans to achieve improvements and to determine if those processes created forecasted results (improvements)

Improvement process also related to learning process in identifying places that are need improvements

Develop understanding of relationships inside the ldquoblack boxrdquo that connect changes in operations to changes in output and outcome

Understanding ldquoblack boxrdquo processes and their interactions

How to influence control workforce that creates output

How to influence citizens customers that turn that output to outcome (and all related suppliers)

They need to observe how actions they can take will influence operations environment workforce and which eventually has an impact on outcome

After that they need to identify actions they can take that will give them improvements they looking for and how organisation will react to those actions ex How might various leadership activities ripple through the ldquoblack boxrdquo

Principles of performance measurement

All significant work activity must be measured

Work that is not measured or assessed cannot be managed because there is no objective information to determine its value Therefore it is assumed that this work is inherently valuable regardless of its outcomes The best that can be accomplished with this type of activity is to supervise a level of effort

Unmeasured work should be minimized or eliminated

Desired performance outcomes must be established for all measured work

Outcomes provide the basis for establishing accountability for results rather than just requiring a level of effort

Desired outcomes are necessary for work evaluation and meaningful performance appraisal

Defining performance in terms of desired results is how managers and supervisors make their work assignments operational

Performance reporting and variance analyses must be accomplished frequently

Frequent reporting enables timely corrective action

Timely corrective action is needed for effective management control

If we donrsquot measure helliphellip

How do you know where to improve How do you know where to allocate or re-allocate money and people

How do you know how you compare with others

How do you know whether you are improving or declining

How do you know whether or which programs methods or employees are producing results that are cost effective and efficient

Common problems with measurement systems that limit their usefulness

Heavy reliance on summary data that emphasizes averages and discounts outliers Heavy reliance on historical patterns and reluctance to accept new structural changes (or re-

design of processes) that are capable of generating different outcomes like measuring the time it takes them to do a task

Heavy reliance on gross aggregates that tend to understate or ignore distributional contributions and consequences

Heavy reliance on static eg equilibrium analysis and slight attention to time-based and growth ones such as value-added measures

[edit] Performance Measurement topics

Most of us have heard some version of the standard performance measurement cliches ldquowhat gets measured gets donerdquo ldquo if you donrsquot measure results you canrsquot tell success from failure and thus you canrsquot claim or reward success or avoid unintentionally rewarding failurerdquo ldquo if you canrsquot recognize success you canrsquot learn from it if you canrsquot recognize failure you canrsquot correct itrdquo ldquoif you canrsquot measure it you can neither manage it nor improve it but what eludes many of us is the easy path to identifying truly strategic measurements without falling back on things that are easier to measure such as input project or operational process measurements

Performance Measurement is addressed in detail in Step Five of the Nine Steps to Successreg methodology In this step Performance Measures are developed for each of the Strategic Objectives Leading and lagging measures are identified expected targets and thresholds are established and baseline and benchmarking data is developed The focus on Strategic Objectives which should articulate exactly what the organization is trying to accomplish is the key to identifying truly strategic measurements

Strategic performance measures monitor the implementation and effectiveness of an organizations strategies determine the gap between actual and targeted performance and determine organization effectiveness and operational efficiency

Good Performance Measures

Focus employees attention on what matters most to success Allow measurement of accomplishments not just of the work that is performed

Provide a common language for communication

Are explicitly defined in terms of owner unit of measure collection frequency data quality expected value(targets) and thresholds

Are valid to ensure measurement of the right things

Are verifiable to ensure data collection accuracy

[edit] Practice

Several performance measurement systems are in use today and each has its own group of supporters For example the Balanced Scorecard (Kaplan and Norton 1993 1996 2001) Performance Prism (Neely 2002) and the Cambridge Performance Measurement Process (Neely 1996) are designed for business-wide implementation and the approaches of the TPM Process (Jones and Schilling 2000) 7-step TPM Process (Zigon 1999) and Total Measurement Development Method (TMDM) (Tarkenton Productivity Group 2000) are specific for team-based structures With continued research efforts and the test of time the best-of-breed theories that help organizations structure and implement its performance measurement system should emerge

Although the Balanced Scorecard has become very popular there is no single version of the model that has been universally accepted The diversity and unique requirements of different enterprises suggest that no one-size-fits-all approach will ever do the job Gamble Strickland and Thompson (2007 p 31) list ten financial objectives and nine strategic objectives involved with a balanced scorecard

Problems in Performance Appraisals

discourages teamwork

evaluators are inconsistent or use different criteria and standards

only valuable for very good or poor employees

encourages employees to achieve short term goals

managers has complete power over the employees

too subjective

produces emotional anguish

Solutions

Make collaboration a criterion on which employees will be evaluated Provide training for managers have the HR department look for patterns on appraisals that

suggest bias or over or under evaluation

Rate selectively(introduce different or various criteria and disclose better performance and coach for worst performer without disclosing the weakness of the candidate) or increase in frequency of performance evaluation

Include long term and short term goals in appraisal process

Introduce MBO(Management By Objectives)

Make criteria specific and test selectivelyEvaluate specific behaviors or results

Focus on behaviors do not criticize employees conduct appraisal on time

Steps To Develop A Quality Assurance Plan The objective of quality assurance plan is to develop and design the activities related to

quality control project for the organization Actually it is a composite document containing all the information related to the quality control activities This is used to schedule the reviews and audits for checking different business components and also to check the correctness of these testing procedures as defined in this plan The quality management team is totally responsible to build up the primary design of the plan To develop this plan the quality manager and his team have to go through certain steps which are described below

o The first step of quality assurance plan is to define the quality goals for the processes These goals will be accepted unconditionally by the developer and the customer both These objectives are to be clearly described in the plan so that both the parties can understand easily the scope of the processes The developers might also set a standard to define the goals If possible the plan can also describe the quality goals in terms of measurement This will ultimately help to measure the performance of the processes in terms of gradation

o The next step in quality assurance plan is to define the organization and the roles and responsibilities of the participant activities It should include the reporting system for the outcome of the quality reviews The quality team should know where to submit the reports directly to the developers or somebody else In many cases the reports are submitted to the project review team who in turn delivers the report to the subsequent departments and keeps it in storage for records Whatever is the process of reporting it

should be well defined in the plan to avoid disputes or complications in the submission process for reviews and audits

o The quality assurance plan also includes the list of other related plans describing project standards which have references in any of the process These subsidiary plans are related to the quality standards of several business components and how they are related to each other in achieving the collective qualitative objective This information also helps to determine the different types of reviews to be done and how often they will be performed Normally the included referenced plans are identified below

1 Documentation Plan

2 Measurement Plan

3 Risk Measurement Plan

4 Problem Resolution Plan

5 Configuration Management Plan

6 Product Development Plan

7 Test Plan

8 Subcontractor Management Plan etc

o The last step of quality assurance plan is to identify the task and activities of the quality control team Generally this will include following reviews

1 Reviewing project plans to ensure that the project abide by the defined process

2 Reviewing project to ensure the performance according to the plans

3 Endorsement of variation from the standard process

4 Assessing the improvement of the processes

It is the responsibility of the quality manager to fix the schedule for the reviews and audits to conduct quality control This schedule is also documented within the plan so that task control can be done at an individual level

Thus the entire process of quality control is documented within the plan This helps as a guideline for the reviewers and developers simultaneously For any future reference this could be used as a practical evidence of total quality control

Related Postso Your Career in Quality Assurance o Developing A Quality Assurance Plan

o The Steps of Quality Assurance Process

o How To Find Cheap Real Estate

o Terms and Conditions for Self Storage Customers

o Pros and Cons of a Wooden Self Storage Building

o Guide to Buy Real Estate

o Quality Assurance Manager In The Software Industry

o 5 Things Self Storage Renters Should Know

o Steps In Quality Assurance Process

STATISTICAL PROCESS CONTROL

FOCUS AREA QUALITY - Measurement

Definition and Summary Applying statistical process control (use of control charts) to the management of software development efforts to effect software process improvement

Statistical Process Control (SPC) can be applied to software development processes A process has one or more outputs as depicted in the figure below These outputs in turn have measurable attributes SPC is based on the idea that these attributes have two sources of variation natural (also known as common) and assignable (also known as special) causes If the observed variability of the attributes of a process is within the range of variability from natural causes the process is said to be under statistical control The practitioner of SPC tracks the variability of the process to be controlled When that variability exceeds the range to be expected from natural causes one then identifies and corrects assignable causes

SPC is a powerful tool to optimize the amount of information needed for use in making management decisions Statistical techniques provide an understanding of the business baselines insights for process improvements communication of value and results of processes and active and visible involvement SPC provides real time analysis to establish controllable process baselines learn set and dynamically improve process capabilities and focus business on areas needing improvement SPC moves away from opinion-based decision making

These benefits of SPC cannot be obtained immediately by all organizations SPC requires defined processes and a discipline of following them It requires a climate in which personnel are not punished when problems are detected and strong management commitment

DESCRIPTION OF THE PRACTICE

SUMMARY DESCRIPTION

Statistical Process Control (SPC) can be applied to software development processes A process has one or more outputs as depicted in the first figure below These outputs in turn have measurable attributes SPC is based on the idea that these attributes have two sources of variation natural (also known as common) and assignable (also known as special) causes If the observed variability of the attributes of a process is within the range of variability from natural causes the process is said to be under statistical control The practitioner of SPC tracks the variability of the process to be controlled When that variability exceeds the range to be expected from natural causes one then identifies and corrects assignable causes

The key steps for implementing Statistical Process Control are

o Identify defined processeso Identify measurable attributes of the processo Characterize natural variation of attributeso Track process variationo If the process is in control continue to track

o If the process is not in control- Identify assignable cause- Remove assignable cause- Return to ldquoTrack process variationrdquo

DETAILED DESCRIPTION

Statistical Process Control (SPC) can be applied to software development processes A process has one or more outputs as depicted in Figure 1 These outputs in turn have measurable attributes SPC is based on the idea that these attributes have two sources of variation natural (also known as common) and assignable (also known as special) causes If the observed variability of the attributes of a process is within the range of variability from natural causes the process is said to be under statistical control The practitioner of SPC tracks the variability of the process to be controlled When that variability exceeds the range to be expected from natural causes one then identifies and corrects assignable causes Figure 2 depicts the steps in an implementation of SPC

Figure 1 Statistical Process Control

Figure 2 How To Perform SPC

In practice reports of SPC in software development and maintenance tend to concentrate on a few software processes Specifically SPC has been used to control software (formal) inspections testing maintenance and personal process improvement Control charts are the most common tools for determining whether a software process is under statistical control A variety of types of control charts are used in SPC Table 1 based on a survey [Radice 2000] of SPC usage in organizations attaining Level 4 or higher on the SEI CMM metric of process maturity shows what types are most commonly used in applying SPC to software The combination of an Upper Control Limit (UCL) and a Lower Control Limit (LCL) specify on control charts the variability due to natural causes Table 2 shows the levels commonly used in setting control limits for software SPC Table 3 shows the most common statistical techniques other than control charts used in software SPC Some of these techniques are used in trial applications of SPC to explore the natural variability of processes Some are used in techniques for eliminating assignable causes Analysis of defects is the most common technique for eliminating assignable causes Causal Analysis-related techniques such as Pareto analysis Ishikawa diagrams the Nominal Group Technique (NGT) and brainstorming are also frequently used for eliminating assignable causes

Table 1 Usage of Control Charts

Type of ControlAttribute Chart

Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67

Not clearly stated 167

From Ron Radicersquos survey of 25 CMM Level 4 and Level 5 organizations [Radice 2000]

Table 2 Location of UCL-LCL in Control Charts

Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24

From Ron Radicersquos survey of 25 CMM level 4 and level 5 organizations [Radice 2000]

Table 3 Usage of Other Statistical Techniques

Statistical Percentage

Technique

Run Charts 228

Histograms 211

Pareto Analysis 211

Scatter Diagrams 105

Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105


Control charts are a central technology for SPC Figure 3 shows a sample control chart constructed from simulated data This is an X-chart where the value of the attribute is graphed Control limits are graphed In this case the control limits are based on a priori knowledge of the distribution of the attribute when the process is under control The control limits are at three sigma For a normal distribution 02 of samples would fall outside the limits by chance This control chart indicates the process is out of control If this control chart were for real data the next step would be to investigate the process to identify assignable causes and to correct them thereby bringing the process under control

Figure 3 A Control Chart

Some have extended the focus of SPC in applying it to software processes In manufacturing the primary focus of control charts is to bring the process back into control In software the product is also a focus When a software process exceeds the control limits rework is typically performed on the product In manufacturing the cost of stopping a process is high In software the cost of stopping is lower and few shutdown and startup activities are needed [Jalote and Saxena 2002]

SPC is one way of applying statistics to software engineering Other opportunities for applying statistics exist in software engineering Table 4 shows by lifecycle phase some of these uses of statistics The National Research Council recently sponsored the Panel on Statistical Methods in Software Engineering [NRC 1996] The panel recommended a wide range of areas for applying statistics from visualizing test and metric data to conducting controlled experiments to demonstrate new methodologies

Table 4 Some Applications of Statistics in Software Engineering

Phase Use of Statistics

Requirements Specify performance goals that can be measured statistically eg no more than 50 total field faults and zero critical faults with 90 confidence

Design Pareto analysis to identify fault-prone modules Use of design of experiments in making design decisions empirically

Coding Statistical control charts applied to inspections

Testing Coverage metrics provides attributes Design of experiments useful in creating test suites Statistical usage testing is based on specified operational profile Reliability models can be applied

Based on [Dalal et al 1993]

Those applying SPC to industrial organizations in general have built process improvements on top of SPC The focus of SPC is on removing variation caused by assignable causes As defined here SPC is not intended to lower process variation resulting from natural causes Many corporations however have extended their SPC efforts with Six Sigma programs Six Sigma provides continuous process improvement and attempts to reduce the natural variation in processes Typically Six Sigma programs use the ldquoSeven Tools of Qualityrdquo (Table 5) The Shewhart Cycle (Figure 4) is a fundamental idea for continuous process improvement

Table 5 The Seven Tools of Quality

Tool Example of Use

Check Sheet To count occurrences of problems

Histogram To identify central tendencies and any skewing to one side or the other

Pareto Chart To identify the 20 of the modules which yield 80 of the issues

Cause and Effect Diagram

For identifying assignable causes

Scatter Diagram For identifying correlation and suggesting causation

Control Chart For identifying processes that are out of control

Graph For visually displaying data eg in a pie chart

Figure 4 Shewhart Cycle

CHARACTERISTICS OF IMPLEMENTATION

SUMMARY CHARACTERISTICS

NO DATA CURRENTLY AVAILABLE

ANTICIPATED BENEFITS OF IMPLEMENTATION

SPC is a powerful tool to optimize the amount of information needed for use in making management decisions [Eickelmann and Anant 2003] Statistical techniques provide an understanding of the business baselines insights for process improvements communication of value and results of processes and active and visible involvement SPC provides real time analysis to establish controllable process baselines learn set and dynamically improve process capabilities and focus business on areas needing improvement SPC moves away from opinion-based decision making [Radice 2000]

These benefits of SPC cannot be obtained immediately by all organizations SPC requires defined processes and a discipline of following them It requires a climate in which personnel are not punished when problems are detected It requires management commitment [Demmy 1989]

DETAILED CHARACTERISTICS

The processes controllable by SPC are unlimited in application domain lifecycle phase and design methodology Processes need to exhibit certain characteristics to be suitable for SPC (as shown in the table below) In addition a process to which SPC is applied should be homogeneous For example applications of SPC to software inspections have found that inspections must often be decomposed to apply SPC effectively Florence [1999] found for instance that the inspection of human machine interface specifications should be treated as a process separate from the inspection of application specifications in the project he examined Weller [2000] found that inspections of new and revised code should be treated as separate processes in the project he examined A trial application of SPC is useful

in identifying homogeneous sub processes Issues other than identifying defined homogeneous processes arise in implementing SPC A second table presents such implementation issues

Criteria Of Processes Suitable for SPC

Well-defined

Have attributes with observable measures

Repetitive

Sufficiently critical to justify monitoring effort

(Based on [Demmy 1989])

SPC Implementation Issues

Define Process Consistent measurements cannot be expected from software processes that are not documented and generally followed

Choose Appropriate Measures

Measures need not be exhaustive One or two measures that provide insight into the performance of a process or activity are adequate especially if the measures are related to the process or activity goal Measures that can be tracked inexpensively are preferable

Focus on Process Trends

Control charts should be constructed so as to detect process trends not individual nonconforming events

Calculate Control Limits Correctly

Straightforward formulas exist for calculating control limits and analyzing distributions Introductory college courses in statistics usually do not address process-control techniques in detail

Investigate and Act

SPC only signals the possible existence of a problem Without detailed investigations as in an audit and instituting corrective action SPC will not provide any benefit

Provide Training

Problems in following the above recommendations for implementing SPC can be decreased with effective training SPC training based on examples of software processes is to be preferred

(Based on [Card 1994])

RELATIONSHIPS TO OTHER PRACTICES

The Figure below represents a high-level process architecture for the subject practice depicting relationships among this practice and the nature of the influences on the practice (describing how other practices might relate to this practice) These relationship statements are based on definitions of specific ldquobest practicesrdquo found in the literature and the notion that the successful implementation of practices may ldquoinfluencerdquo (or are influenced by) the ability to successfully implement other practices A brief description of these influences is included in the table below

Process Architecture for the Statistical Process Control Gold Practice

Summary of Relationship Factors

INPUTS TO THE PRACTICE

Determine which attributes at what levels should be controlled

Statistical Process Control can only be effective if the most critical processes are identified and addressed using the technique Practices that help establish clear goals and decision points and are based on meaningful metrics and attributes based on specific program or technical goals stand to gain the most payback from using SPC SPC techniques need not be restricted to the present ie planning for the insertion of new technology later in the life cycle should also plan for the use of SPC to ensure that processes are controlled and reliability of the resulting software artifacts is optimized

Define whether environment is appropriate for process control

Practices such as Performance-Based Specifications and Commercial SpecificationsOpen System can imply the generation and collection of data Such data may serve as appropriate input to SPC techniques such as control charts Therefore an environment that is data-rich provides an excellent opportunity to leverage the benefit statistical process control techniques

Provide data upon which decisions can be based

An initial step in applying SPC is often to discover controllable and homogeneous processes Past performance data can be used for this purpose Formal inspection processes and processes for leveraging COTSNDI explicitly call for metrics to be collected These metrics can be used as the basis for SPC

OUTPUTS FROM THE PRACTICE

Assess progress towards process control

SPC can be used not only to control processes but also to determine if quantitative requirements on software processes are being met The results of SPC then provide valuable data and information that can be used to manage progress towards achievement of software requirements Part of this ability to manage progress is supported by the quantitative progress measurements that are inherent in the SPC process primarily in the form of defect tracking and correction against specific quantitative quality targets

Communicate progress towards controlling processes

Management gono-go decisions can be based on whether development processes are under control SPC presents graphical displays supporting such decisions The number and types of available graphical formats that can be used as part of the SPC process provide accessible visibility into progress being made to all program stakeholders Demonstration-based reviews provide an excellent vehicle for communicating the progress being made in controlling processes through the use of SPC

Improve Testing Efficiency and Effectiveness

By providing control over software development processes SPC will result in more predictable and more reliable software Rigorous testing that is guided by specifications and supported by well-documented and accurate operational and usage-based models will be much more effective under the controlled processes resulting from SPC

RESOURCES

Websites

0 httpwwwasqorg American Society for Quality

0 httpwwwasq-softwareorg Software Division of the American Society for Quality

0 httpwwwsixsigmaforumcom Six Sigma Forum established by the American Society for Quality (ASQ)

0 httpwwwisixsigmacom A Web portal devoted to Six Sigma programs

0 httpwwwqualitydigestcom Quality Digest A magazine

0 httpwww2umassdeduSWPI Software Process Resource Collection

0 httpwwwpsmsccom Practical Software and Systems Measurement Sponsored by the US Department of Defense and the US Army

0 httpdemingengclemsonedu A page at Clemson University for Continuous Quality Improvement including software and tutorials

0 httpwwwstatsoftinccomtextbookstathomehtml An online textbook in statistics

0 httpwwwmathuahedustat Virtual Laboratory in Probability and Statistics (Kyle Siegristrsquos tutorial)

Tools and Methods

Tools for plotting control charts plotting other graphs and calculating various statistics support SPC Common spreadsheets such as Excel provide much of the needed capabilities but a number of vendors have produced tools customized for SPC Some are listed below

httpwwwunidoorgendoc4268 Measurement Control Chart Toolkit (MCCT) A toolkit for SPC available from the United Nations Industrial Development Organization

httpdemingengclemsonedu A page at Clemson University for Continuous Quality Improvement including software and tutorials

httpwwwqualityamericacom A company providing SPC software training and consulting

httpwwwqualitrancomSPC_Softwarebody_spc_softwarehtml A windows-based SPC and Process Improvement software tool sold by Qualitrain Professional Services Incorporated

httpwwwspc-software-packagecom A software package provided by the company To The Point

httpwwwcseiitkacinusersjaloteSDAhtml Pankaj Jalotersquos Software Process Design and Analysis page Includes an applet for computing control limits in control charts

ExpertsContact Points

0 httpwwwreifercom Donald Reifer a consultant

0 httpwwwrspacom R S Pressman and Associates

0 httpwwwsqecom Software Quality Engineering A private company providing training and consulting

0 httpwwwqualityamericacom A company providing SPC software training and consulting

Training Opportunities

httpwwwseicmueduproductscoursesspc-swhtml Software Engineering Institute (SEI) course on SPC


httpwwwsqecom Software Quality Engineering A private company providing training and consulting

Bibliography

[Bertolino et al 2002]

A Bertolino E Marchetti R Mirandola G Lombardi and E Peciola ldquoExperience of Applying Statistical Control Techniques to the Function Test Phase of a Large Telecommunications Systemrdquo IEE Proceedings ndash Software V 149 N 4 August 2002 pp 93-101

[Card 1994] D Card ldquoStatistical Process Control for Softwarerdquo IEEE Software V 11 No 3 May 1994 pp 95-97

[Cobb and Mills 1990]

R H Cobb and H D Mills ldquoEngineering Software under Statistical Quality Controlrdquo IEEE Software V 7 No 6 November 1990 pp 44-54

[Dalal et al 1993]

S R Dalal J R Horgan J R Kettenring ldquoReliable Software and Communication Software Quality Reliability and Safetyrdquo Proceedings of the 15th International Conference on Software Engineering 17-21 May 1993

[De Lucia et al 2002]

A De Lucia A Pannella E Pompella S Stefanucci ldquoEmpirical Analysis of Massive Maintenance Processesrdquo Proceedings of the Sixth European Conference on Software Maintenance and Reengineering (CSMRrsquo02) 2002

[Demmy 1989] W S Demmy ldquoStatistical Process Control in Software Quality Assurancerdquo Proceedings of the IEEE National Aerospace and Electronics Conference (NAECON 1989) 22-26 May 1989 pp 1585-1590

[Florac and Carleton 1999]

W A Florac and A D Carleton Measuring the Software Process Statistical Process Control for Software Process Improvement Addison-Wesley 1999

[Florac et al 2000]

W Florac A D Carleton and J R Barnard ldquoStatistical Process Control Analyzing a Space Shuttle Onboard Software Processrdquo IEEE Software V 17 no 4 JulyAugust 2000 pp 97-106

[Florence 1999] A Florence ldquoSEI CMM Level 4 Quantitative Analysisrdquo Twenty-Fourth Annual Software Engineering Workshop

[French 1995] V A French ldquoApplying Software Engineering and Process Improvement to Legacy Defence System Maintenance An Experience Reportrdquo Proceedings of the International Conference on Software

Maintenance 12-20 October 1995

[Gardiner and Montgomery 1987]

J S Gardiner and D C Montgomery ldquoUsing Statistical Control Charts for Software Quality Controlrdquo Quality and Reliability Engineering International V 3 1987 pp 40-43

[Hayes 1998] W Hayes ldquoUsing a Personal Software Process to Improve Performancerdquo Proceedings of the Fifth International Software Metrics Symposium 20-21 November 1998

[Ishikawa 1982]

K Ishikawa Guide to Quality Control UnipubQuality Resources 1982

[Jacob and Pillai 2003]

A L Jacob and S K Pillai ldquoStatistical Process Control to Improve Coding and Code Reviewrdquo IEEE Software V 20 No 3 MayJune 2003 pp 50-55

[Jalote and Saxena 2002]

P Jalote and A Saxena ldquoOptimum Control Limits for Employing Statistical Process Control in Software Processrdquo IEEE Transactions on Software Engineering V 28 N 12 December 2002 pp 1126-1134

[NRC 1996] Panel on Statistical Methods in Software Engineering of the National Research Council Statistical Software Engineering National Academy Press 1996

[Paulk et al 1995]

M C Paulk et al The Capability Maturity Model Guidelines for Improving the Software Process Addison-Wesley 1995

[Prowell et al 1999]

S J Prowell C J Trammell R C Linger and J H Poore Cleanroom Software Engineering Technology and Process Addison-Wesley 1999

[Radice 2000] R Radice ldquoStatistical Process Control in Level 4 and 5 Organizations Worldwiderdquo Proceedings of the 12th Annual Software Technology Conference 2000 (Also at httpwwwsttcom)

[Turner 2002] R Turner Implementation of Best Practices in US Department of Defense Software-Intensive Systems Dissertation George Washington University January 2002

[Weller 2000] E F Weller ldquoPractical Applications of Statistical Process Controlrdquo IEEE Software V 17 no 3 MayJune 2000 pp 48-55

APPENDICES

DEFINITIONS

An application of statistics to controlling industrial processes including processes in software development and maintenance Statistical Process Control (SPC) is used to identify and remove variations in processes that exceed the variation to be expected from natural causes

The purpose of process control is to detect any abnormality in the process

- [Ishikawa 1982]

SOURCES (Origins of the Practice)

Walter Shewhart developed Statistical Process Control (SPC) in the 1920s Shewhart sought methods applying statistics to industrial practice Acceptance testing and SPC grew out of this work Shewhart proposed the use of control charts a core technique for SPC in a historic internal memorandum of 16 May 1924 at Bell Telephone Laboratories

For a long time SPC was most widely adopted in Japan not the United States Shewhart mentored W Edwards Deming and Deming went on to introduce quality technologies into Japanese industry The rdquoGuide to Quality Controlrdquo Ishikawa [1982] first published in 1968 in Japanese is a guide to quality control techniques that became prevalent in Japan after World War II Corporations in the United States began adopting quality technology including SPC more widely in the 1980s Recently many United States corporations have instituted Six Sigma programs These programs through continual process improvement attempt to reduce the natural variation in industrial processes

Some began applying SPC techniques to software in the 1980s Gardiner and Montgomery [1987] report an example Software inspections seem to provide the processes that are most commonly monitored with SPC in software Some recently proposed software process models include opportunities for SPC The spiral lifecycle provides a natural time for tuning software processes namely before the start of the development of each increment SPC yields analyzed data that managers can use in selecting processes to tune Cleanroom software engineering combines incremental development and software inspections with other technologies such as reliability modeling The Software Engineering Institute (SEI) Capability Maturity Model (CMM) mandates that SPC be used in Level 4

organizations

RECOMMENDING SOURCES

Capability Maturity Model Version 11

SPC is described as part of the Key Process Area Quantitative Process Management in the CMM This Key Process Area must be implemented to achieve Level 4 Managed in the CMM

ldquoThe purpose of Quantitative Process Management is to control the process performance of the software process quantitatively Software process performance represents the actual results achieved from following a software process

Quantitative Process Management involves establishing goals for the performance of the projectrsquos defined software process which is described in the Integrated Software Management key process area taking measurements of the process performance analyzing these measurements and making adjustments to maintain process performance within acceptable limits When the process is stabilized within acceptable limits the projectrsquos defined software process the associated measurements and the acceptable limits for the measurements are established as a baseline and used to control process performance quantitativelyrdquo [Paulk et al 1995]

This process area is renamed Organizational Process Performance at Maturity Level 4 in the CMMI Version 11

Turner R ldquoImplementation of Best Practices in US Department of Defense Software-Intensive Systemsrdquo Dissertation George Washington University January 2002

Turner surveyed a sample of 35 software experts from academia industry and government participating in various software-intensive working groups The survey partitioned 32 best practices into four focus areas Statistical Process Control a best practice identified by Donald Reifer was grouped into the Measurement focus area The best practices were ranked based on the 23 survey respondentsrsquo individual rankings rating of effectiveness and groupings into the eight best practices eight worst practices or otherwise SPC was ranked thirtieth out of the 32 best practices

Cleanroom Software Engineering

Cleanroom alludes to a technique used in semiconductor fabrication to prevent defects and is a methodology for software development that integrates several software engineering technologies

0 Incremental development

0 Formal specifications

0 Stepwise refinement

0 Structured programming

0 Formal verifications

0 Formal reviews

0 Statistical testing

0 Certification (reliability) measurement

Incremental development supports SPC

Incremental development is based on the engineering principle of controlled iteration in product development Rather than a single pass through the development process incremental development involves a series of smaller cumulative development passes Each pass (increment) is cumulative involving all work in previous increments plus some new workhellip

In addition to the benefits of intellectual control customer feedback and risk management incremental development enables the project team to employ statistical process control Product quality is measured at the end of each increment and is compared with the teamrsquos quality goals The deviation between actual results and goals is used to determine whether the project is under control A minor deviation confirms that the project is on track whereas an unacceptable deviation occasions a careful performance review If problems are identified the team can make process changes to improve performance in the next increment [Prowell et al 1999]

GLOSSARY

c-Chart A control chart displaying counts per item where the range of the counts is fixed Contrast with a u-chart

CE Diagram Cause and Effect diagram A diagram developed by Kaoru Ishikawa that resembles a fish skeleton The diagram shows the causes and sub causes leading to an effect

CMM Capability Maturity Model

Control Chart A graph with limit lines that is used to detect changes in the process from the graphed data is collected [Ishikawa 1982]

Fishbone Diagram

See CE Diagram

Histogram A graph showing for defining intervals the number of values in a sample or the percentage in that interval A visual display of a probability distribution

Ishikawa Diagram

See CE Diagram

Kiviat Chart A chart in the shape of a circle with evenly spaced radii where each radius represents the value of a (non-negative attribute) Attributes are often plotted with respect to user-defined thresholds

LCL Lower Control Limit Used in constructing a control chart

NGT Nominal Group Technique

Pareto Analysis The use of a bar chart that displays by frequency in descending order the most important defects Proper use of this chart will have the cumulative percentage on a second y-axis (to the right of the chart) If the Pareto principle is evident about 20 of the categories on the far left will have about 80 of the impact on the problem

p Chart A control chart in which a fraction formed from the ratio of discrete variables (eg fraction of items defective) is plotted against time

Pie Chart A graph in which the percentage in one of a small number of categories is displayed as an area in a circle

Radar Chart See Kiviat Chart

Regression Analysis

A statistical technique for determining the best mathematical expression describing the functional relationship between one response and one or more independent variables (From httpwwwsixsigmaforumcomtermsrhtml)

Run-Chart A performance measure of a process over a specified period of time used to identify trends or patterns

Scatter Diagram A plot in which two attributes of the data are plotted one on the abscissa and the other on the ordinate Useful for detecting a relationship between the two attributes

SEI Software Engineering Institute

SPC Statistical Process Control

u-Chart A control chart displaying counts per item (eg total defects per thousand source lines of code) where the range of the counts is not fixed Contrast with the c-chart

UCL Upper Control Limit Used in constructing a control chart

X-Chart Individual control chart

Xbar Chart A control chart in which the average for subgroups of data is plotted by subgroup

Xbar-mR Chart A control chart in which both the average and the range for subgroups of data are plotted by subgroup

XmR Chart Individual and Moving Range control chart

z-Chart A control chart in which the plotted data has been transformed to be from a normal distribution if the process is under control

CASE STUDIES FROM THE LITERATURE

The table below summarizes recent experiences of a number of organizations with SPC

Examples of the Use of SPC

SPC Technique

Application ProcessAttributes DiscussionResults Reference

Control chart

Military software unit maintaining almost 380000 source lines of code

Defects per Person-Day and Defects per Thousand Lines of Code

SPC techniques introduced along with software engineering project management techniques inspections and metrics Process improvement resulted in 20 more code being produced than on previous version rework

[French 1995]

in Integration and Test dropping from 47 to 009 person-years

X Control Chart

Process automation and consumer electronics projects in C++ ranging from 150 to 400 Function Points

Defects per Thousand Lines of Code for code review and testing Lines of Code per Hour for inspection preparation

Illustrates how using control charts identified out-of-control processes Corrective actions were implemented to remove assignable causes


XmR Control Chart

GCOS 8 (an operating system)

Inspection review rate and defect-detection effectiveness of software inspections

Identified sub processes (inspections of new code and revised code) Demonstrated inspections were under control Estimated defects remaining in the code

[Weller 2000]

XmR Control Chart and u-Chart

Space Shuttle Onboard Software

Inspection review rate defect-detected in inspections and test

Trial study of SPC Identified inspection sub processes and natural variation of these processes

[Florac et al 2000]

Z-Chart A sample of 298 engineers training in the Software Engineering Institutersquos Personal Software Process (PSP)

Defects discovered in design reviews

Process control charts presented in the context of metrics collected by engineers going through PSP training Demonstrations of the effectiveness of the PSP based on size estimation accuracy effort estimation accuracy defects per source line remove early in the lifecycle and

[Hayes 1998]

productivity

Confidence intervals based on statistical models of failures

Ericsson Lab Italy

Effectiveness in failure detection of function testing

Pilot study Concluded process control for function test can be based on examined models


Regression model Outlier analysis Box plot

Large Y2K maintenance project Part of a major international software enterprise in Caserta Italy

Size and productivity metrics during maintenance

Study analyzed correlation characterized patterns of variations developed regression model to predict impact of maintenance Concluded that maintenance process is predictable repeatable and suitable for SPC


Statistical Process Control

o Top of Page

o Description of Practice

Summary

Detailed Description

o Characteristics of Implementation

Summary

Detailed Characteristics

o Relationship to Other Practices

o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions

Origins of the Practice

Recommending Sources

Glossary

Case Studies from the Literature

o Case Studies

Reviewhttpwwwiconcoza~tqmaThe 10 Stepsgif

Submit

o Data

o Survey

Results

Submit

o Download Printable Version

o GP HomePage

o DACS HomePage

DACS Gold Practice Initiative ROI Dashboard

Acquisition Process Improvement

Architecture-First Approach

Assess Reuse Risks and Costs

Binary Quality Gates at the Inch-Pebble Level

Capture artifacts in rigorous model-based notation

Commercial Specifications and StandardsOpen Systems

Access benefit data from software technical and management improvements including SEI CMMI PSPTSP Cleanroom Inspections and Agile Development

View the ROI Dashboard

Defect Tracking Against Quality Targets

Develop and Maintain a Life-cycle Business Case

Ensure Interoperability

Formal Inspections

Formal Risk Management

Goal-Question-Metric Approach

Integrated Product and Process Development

Manage Requirements

Metrics-based Scheduling

Model Based Testing

Plan for Technology Insertion

Requirements Trade-OffNegotiation


Track Earned Value

The 10 steps are the things to do to make Improving Quality a reality They provide the system that will enable you to work together however it is not a rigid mechanical system that must be followed by the numbers

Eventually you will take part in all 10 steps - but not in any special order or even at the same time

Which steps to be taken next and practice most often will depend on your individual work situations - on the problems identified and the actions that are most effective in solving those problems

STEP 1 COMMITMENT

Commitment is the core or hub of Improving Quality With Commitment you must support the other nine steps

A Commitment is a personal pledge of action Management must make it clear where they stand on quality Management and staff must demonstrate commitment It will change the way you do your job therefore it is a commitment you must make personally and individually Commitment will ensure participation and support improvement

The intent of this step is met when quality becomes as important as cost and delivery in your daily operation when you take the time to do it right the first time when defective work is returned to suppliers rather than accepted when you always ask why when an error occurs and when you take permanent corrective action

STEP 2 IMPROVEMENT TEAMS

Commitment is personal and individual but nobody works completely alone Your jobs and skills interlock in ways that make you mutually dependent For that reason working in teams is important to Improving Quality

Different kinds of teams are needed each with different capabilities Some are permanent others are temporary ad hoc teams that will disband when their task is completed Among the different types of teams that exist are are for example a Management Team for policy and guidance Quality Councils in each area for planning Quality Improvement Teams for implementing and monitoring and Corrective Action Teams for identifying root causes of problems and implementing preventive solutions

Special training will often be required for effective team operation This must be provided

This step is being carried out when everybody is willing to serve on teams and volunteer to do so when teams are formed and are meeting regularly when everyone on teams attends and participates and when you ask why if teams are not being formed or arent functioning well

STEP 3 EDUCATION

Improving Quality could be new to you That means you need education Everybody must learn about Improving Quality through various courses available each made up of several class sessions

The courses must be focused on all levels within the organisation from top management down to shop floor A common understanding [language] of quality must be instilled within the whole organisation for success to be achieved

View the courses available for further information

Education and training reflect the nature of Improving Quality itself There is no finish line Improving Quality renews itself so does education with updated and new courses and seminars to meet new developments

The intent of this step is met when there is a training plan when everybody completes these courses when new staff members are inducted and being trained as they join your organisation and when everybody takes advantage of additional skills training

STEP 4 MEASURE DISPLAY amp REVIEW

Measuring is a primary technique for Improving Quality If you dont measure it you cannot manage it It helps individuals and teams reduce the rate of errors making everybodies work more effective for each other In most organisations you cant work on everything at once Measuring the rate of errors for two or three of your operations is the best way to concentrate your efforts

Display and review of what you measure is just as important as what you measure Everyone must understand exactly what is being measured so that you are all talking the same language and pulling in the same direction - and so that progress in reducing errors is readily visible to everyone in the organisation or group Trends must be identified and reviewed and actions taken to ensure pre-determined performance standard close the gap process

The intent of this step is being met when teams have found ways to identify and track errors when they see the charts as an aid not a threat and when they identify and suggest error rates to be measured and displayed

STEP 5 COST OF QUALITY

Doing work wrong doing it over checking for errors and preventing errors all have costs attached to them These are large costs and they rob you of the time and resources you need - never mind your diminishing bottom-line

The cost of quality action requires that you set up procedures to measure the cost errors add to our work as a basis for identifying problems understanding the requirements and setting priorities for removing those problems

This step is not used for individual performance reviews or to compare one team to another Focusing on the real cost of errors is a positive tool that enables each team to gauge its own improvement

The intent of this step is being met when information collection procedures are set up and reports are published regularly when you recognise the true cost that errors add to achieving quality and when the cost of quality is going down

STEP 6 COMMUNICATION

This step ensures that you share information as directly and completely as you can

Communication is most effective person-to-person face-to-face Therefore regular meetings that focus on problems and improvements in and around your departments are the keystone of this action

Successful communication requires candid talk willingness to listen as well as speak and concentration on the clear exchange of information It is helpful to use the language and terminology of Improving Quality in your day-to-day discussions

The intent of this step is met when meetings are disciplined and held regularly and when a sound plan for mass communication is in operation

STEP 7 CORRECTIVE PREVENTIVE ACTION

This step is the front lines of Improving Quality When you find that you have made an error your first responsibility is to understand why and to take corrective action to make sure it doesnt happen again

The basic assumption of corrective action is that most errors are not caused by people they are caused by defect processes Processes that are not meeting requirements Therefore the objective of corrective action is simply to set up a process to identify and eliminate errors The process should be a closed loop- that is the problem stays in the system for feedback and continual re-evaluation until there is positive proof that it is solved [prevention]

The large problems that corrective action focuses on usually involve more than one area so the process provides for Corrective Action Teams (CATs) that represent different teams and skills

Documentation is a key part of corrective action This means keeping a written record so that nothing is left to chance or memory and so that other teams can learn from your experience when they face similar problems

Everybody can do four things to support corrective action

Identify and analyse the cause(s) of errors in your individual jobs and create your own preventive processes

For problems that involve others report the problem and ask that a Corrective Action Team be formed

Join Corrective Action Teams and be willing and active members

Record the analysis process decisions and changes that are implemented in order to document the results of corrective action Communicate these changes to those concerned

The intent of this step is met when everybody takes responsibility for reporting problems and for finding permanent [preventive] solutions to them

STEP 8 RECOGNITION

This step has two objectives to encourage participation in Improving Quality and to reward individual and team contributions to improvement

Recognition is a difficult step to implement In an organisation where everyone does a good job and tries hard how do you single out certain people The key is fairness Recognition must be based on consistent guidelines for recognising individuals and teams Accomplishments must be documented And the guidelines and reasons for recognition must be communicated clearly to everyone

The award programs should be defined by the organisation There are various ways of doing this The important thing is the recognition itself and the personal or collective satisfaction it brings

The intent of this action is being met when a recognition plan is in place to appreciate those who achieve and participate and when recognition is a way of life

STEP 9 EVENT

This step is in a sense the flip side of recognition Since you recognise special contributions to Improving Quality you should also recognise the total effort with an event

The event occurs after you have made substantial progress toward Improving Quality It provides an occasion to review accomplishments and to rededicate yourselves to Improving Quality in an informal and enjoyable environment

This step should occur when the first eight actions are in place and when there is general agreement that Improving Quality is actually changing your behavior

STEP 10 GOAL SETTING amp CONTINUOUS IMPROVEMENT

This step calls on you to set goals for Improving Quality

It may seem odd that this Action comes last because most of you are accustomed to setting goals first However since the basic purpose of Improving Quality is to change the way we do things setting goals at the beginning would be unrealistic Only when you have mastered the new ways to identify problems understand the requirements measure them and take corrective action to solve them can you set achievable goals

Your Improving Quality goals should be specific - such as aiming for a particular percentage decrease in an error rate - and obtainable within a specific time frame When you meet that goal you can go on to a new one again and again

The intent of this step is being met when everybody is routinely setting personal goals and taking part in setting team goals for continuous business improvement

Quality is - Never having to say youre sorry

[Home] [Contact Us] [Why Change] [Business Strategy] [Business Quiz] [TQM Phases] [Benefits of TQM] [Educ amp Trg] [Links] [ISOampTQM] [ISOampSAP]

[Business Profile] [Client Feedback] [Business Opportunities] [Membership] [ISO 90012000] [Quality News] [ Best Practice Model]

[Vision 2000] [Discussion Forum]

Eight Steps to a New Performance Measurement System

Contents



[edit] Practice

Steps To Develop A Quality Assurance Plan

Related Posts

APPENDICES

Two Types of Performance Measures

1 Performance Measures of Programs Projects and Operations are changing Organizations are moving to a more complete form of performance measures Accounting performance measures are not the only performance measures that count The government started this process under the first Clinton Administration and we were involved in the Department of Energys first efforts of understand and implement this process of using performance measures

2 Performance Manages for People are changing Organizations are moving away from the long-established one-on-one appraisal or performance review with a boss once per year They are designing performance management systems that provide an individual with more frequent feedback from many points of view including peers direct reporting staff members and the boss The process known as 360-degree feedback provides a more balanced set of observations for the employee







537-545




























1992









Step 5 Collect Data




























Citations








Group 1986 91






























Works Cited

















MBO program







OTHER INTERESTING
















Earned Value



EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES







537-545




























1992









Step 5 Collect Data




























Citations








Group 1986 91






























Works Cited

















MBO program







OTHER INTERESTING
















Earned Value



EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES


























1992









Step 5 Collect Data




























Citations








Group 1986 91






























Works Cited

















MBO program







OTHER INTERESTING
















Earned Value



EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES






Step 5 Collect Data




























Citations








Group 1986 91






























Works Cited

















MBO program







OTHER INTERESTING
















Earned Value



EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES




















Citations








Group 1986 91






























Works Cited

















MBO program







OTHER INTERESTING
















Earned Value



EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES







Group 1986 91






























Works Cited

















MBO program







OTHER INTERESTING
















Earned Value



EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES




























Works Cited

















MBO program







OTHER INTERESTING
















Earned Value



EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES











MBO program







OTHER INTERESTING
















Earned Value



EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES
















Earned Value



EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES


EXAMPLE























Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES






















Contents[hide]


3 Practice

4 See also

5 References

6 Further reading

7 External links



























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES
























































































[edit] Practice









too subjective


Solutions















2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES










2 Measurement Plan





7 Test Plan

























SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES















SUMMARY DESCRIPTION












Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES









Percentage

Xbar-mR 333

u-Chart 233

Xbar 133

c-Chart 67

z-Chart 67




Location Percentage

Three-sigma 16

Two-sigma 4

One-Sigma 8

Combination 16

NoneNot Clear

24




Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES

Technique

Run Charts 228

Histograms 211

Pareto Analysis 211


Regression Analysis

70

Pie Charts 35

RadarKiviat Charts

35

Other 105















Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES













Tool Example of Use




















Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES











Well-defined


Repetitive











Investigate and Act


Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES

Provide Training





















RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES














RESOURCES

Websites











Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES


Tools and Methods

















Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES

Bibliography






[Dalal et al 1993]







[Florac et al 2000]








[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES





[Ishikawa 1982]







[Paulk et al 1995]







APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES

APPENDICES

DEFINITIONS



- [Ishikawa 1982]





organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES

organizations
















0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES



0 Formal reviews






GLOSSARY





Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES

Fishbone Diagram

See CE Diagram


Ishikawa Diagram

See CE Diagram








Regression Analysis
















SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES












SPC Technique


Control chart




[French 1995]


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES


X Control Chart





XmR Control Chart




[Weller 2000]





[Florac et al 2000]




[Hayes 1998]

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES

productivity


Ericsson Lab Italy










o Top of Page


Summary



Summary



o Resources

Websites

Tools and Methods



Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES

Bibliography

o Appendix

Definitions



Glossary


o Case Studies


Submit

o Data

o Survey

Results

Submit


o GP HomePage

o DACS HomePage













Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES




Formal Inspections




Manage Requirements


Model Based Testing




Track Earned Value




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES




STEP 1 COMMITMENT









STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES






STEP 3 EDUCATION































STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES




























STEP 8 RECOGNITION





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES





STEP 9 EVENT














Contents



[edit] Practice


Related Posts

APPENDICES










Contents



[edit] Practice


Related Posts

APPENDICES

The Seven Steps of Performance Measures

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Transcript of The Seven Steps of Performance Measures