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Performance Measure Development Sheets

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StrategyDriven Organizational Performance Measures Best Practice ArticleEffective performance measurement systems consist of high-quality individual measures associated with a strongly interrelated framework. Using this deliberately developed framework, leaders ascertain organizational performance quickly and accurately. The system itself should be economic to maintain and provide readily available updates typically necessitating a degree of automation. Quality systems present the same view of performance to a broad number of individuals within the organization concurrently. To achieve all of these qualities, each measure must be well thought-out and developed individually and then integrated into the collective system.[wcm_restrict plans=”41747, 25542, 25653″]

Individual performance measures should be constructed such that they are both individually and collectively informative. Using a predefined performance measure development sheet drives developers to think though both individual metric qualities as well as how it relates and supports the other measures within the overall system.

Performance measure development sheets define the individual qualities and interrelationships producing high quality metrics. These sheets support more rapid and thorough development, speed system integration, and allow technology enablement. Performance measure development sheets should include the following information:

  • Technical Data (see StrategyDriven Organizational Performance Measures Best Practice article – Performance Metrics Inventory Database)
  • Stylistic Information (see StrategyDriven Organizational Performance Measures Best Practice article – Style Sheets)
    • Business Unit/Fleet Level Executive Dashboard
    • Department/Facility Level Executive Dashboard
    • Individual Performance Measure

Final Thought…

One of the easiest to use and most effective performance measure development sheet designs is one that mirrors the metric style sheet to be used. Metric characteristics and parameters are overlaid on the underlying stylesheet making their associations readily observable and consistently interpreted by those implementing and updating the metric.[/wcm_restrict][wcm_nonmember plans=”41747, 25542, 25653″]

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Additional Information

Additional information on the individual characteristics of quality performance measures and their construction can be found in the following StrategyDriven articles and documents:

Articles

Documents

  • Organizational Performance Measures – Types
  • Organizational Performance Measures – Construction

About the Author

Nathan Ives, StrategyDriven Principal is a StrategyDriven Principal and Host of the StrategyDriven Podcast. For over twenty years, he has served as trusted advisor to executives and managers at dozens of Fortune 500 and smaller companies in the areas of management effectiveness, organizational development, and process improvement. To read Nathan’s complete biography, click here.

Style Sheets

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StrategyDriven Organizational Performance Measures Best Practice ArticleA performance measure’s value evolves from its ability to instigate and/or influence action. To do this, the measure must accurately reflect materially important performance parameters and present that information in a timely, readily understandable manner. It is to this later characteristic that performance metric style sheets are critically important.[wcm_restrict plans=”41741, 25542, 25653″]

General Performance Metric Style Sheet Characteristics

Style sheets reflect the graphic manner in which a performance metric is presented. These sheets should be aligned among types of measures and general characteristics so to consistently represent information to their readers thereby minimizing the chance of misinterpretation. Furthermore, they should possess several best practice display characteristics to maximize the metric’s value including:

Types of Style Sheets

Performance measures tend to aggregated information relative to the organizational level of the individuals for whom they are intended. Thus, the metrics presented to senior executives tend to aggregate vast amounts of information where metrics intended for first line managers tend to be very granular. Consequently, the style sheets associated with the various aggregations of performance data reflect the above characteristics each in a different manner. The sections below illustrate three different types of performance measure style sheets reflective of increasingly granular metrics presentations.

Business Unit/Fleet Level Executive Dashboard Style Sheet

StrategyDriven Organizational Performance Measures Best Practice ArticleBusiness unite/fleet level executive dashboards are collections of ‘window’ type performance indicators typically provided to the most senior executives. These dashboard style sheets possess the following characteristics (see Figure 1):

  1. Show the past three months high-level performance rating color with the most recent month to the right. This reveals a quarterly performance trend.
  2. Fleet average and facility level indicators reflect both the business unit’s performance as well as that of its individual components.
  3. Individual window indicators are color coded, reflecting the performance against established standards, as well as providing an actual performance value. Clicking on a window takes the user to the next lower level dashboard or indicator thereby providing additional performance details.

Department/Facility Level Executive Dashboard Style Sheet

StrategyDriven Organizational Performance Measures Best Practice ArticleDepartment/facility level executive dashboards are simplified individual metrics collections typically provided to the directors and managers. These dashboard style sheets possess the following characteristics (see Figure 2):

Title Area

  • Window Indicators: A = month -2, B = month – 1, C = current month

Graphic Area

  • Easy to read graphic representation of the data with readily observable or indicated trend (typically bar chart, line graph, or combo)
  • Direction of ‘good’ indicated
  • Goals are shown on / incorporated into the graphic (colored background or embedded lines)
  • Numeric Y-axis has zero reference, units of measure label, and units shown
  • Date X-axis typically starts on the calendar year or 12 months ago and reflects data monthly
  • Legend is provided

Individual Performance Measure Style Sheet

StrategyDriven Organizational Performance Measures Best Practice ArticleIndividual performance measures are the most granular representations of organizational performance typically used by those managers and supervisors directly responsible for the indicated performance. These dashboard style sheets possess the following characteristics (see Figure 3):

Title Area

  • Owner (with contact information) and Maintainer (with contact information)
  • Window Indicators: A = month -2, B = month – 1, C = current month

Graphic Area

  • Easy to read graphic representation of the data with readily observable or indicated trend (typically bar chart, line graph, or combo)
  • Direction of ‘good’ indicated
  • Goals are shown on / incorporated into the graphic (colored background or embedded lines)
  • Numeric Y-axis has zero reference, units of measure label, and units shown
  • Date X-axis typically starts on the calendar year or 12 months ago and reflects data monthly
  • Legend is provided

Tabular data for the months shown including subdivisions and totals if used (common for stacked bar charts)

Analysis Area

  1. Definition, both written and mathematical
  2. Performance Measure Goals including basis and numeric values
  3. Analysis of current performance and trend
  4. Actions being taken to improve performance, if needed

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About the Author

Nathan Ives, StrategyDriven Principal is a StrategyDriven Principal and Host of the StrategyDriven Podcast. For over twenty years, he has served as trusted advisor to executives and managers at dozens of Fortune 500 and smaller companies in the areas of management effectiveness, organizational development, and process improvement. To read Nathan’s complete biography, click here.

Direct Use of Production System Data for Organizational Performance Measures

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StrategyDriven Organizational Performance Measures Warning Flag ArticleData access frequently challenges metric developers. Consequently, they may resort to using the most readily available performance data; data that can be obtained through a user defined production application query and downloaded into a Microsoft Excel spreadsheet or Access database. While such practices may be appropriate when developing proof-of-concept metrics, direct use of production data typically leads to metric instability resulting in low metric confidence and driving unintended organizational behaviors.

Why Production Data is Unsuitable for Organizational Performance Measures

Production data possesses qualities making it unsuitable for use in developing longer-term organizational performance measures. Primary among these is the dynamic nature of the data itself. By its very nature, production data is transactional and subject to frequent ongoing change – additions, deletions, and revisions. Consequently, metrics monitoring a series of period-based performance (such as monthly performance periods reflected in one metric covering a rolling 12 month year) can have a given historical period’s performance change from one publication of the metric to the next.

Another significant issue associated with using production data is extraction timing consistency. To consistently measure performance within defined time intervals necessitates data to be extracted at the same end time for each period such as 11:59:59 pm (23:59:59) on the last day of the week, month, quarter, year, etcetera. Not only is it highly unlikely that a manually timed extraction could occur with such timing precision but few individuals work at midnight and fewer at midnight on weekends and holidays where a period will occasionally end.

Benefits of Using a Data Historian

Data historian applications solve the issues associated with using production data as an input to organizational performance measures. Such applications extract a ‘data image’ at a consistent, specified period end time (eliminating extraction timing issue). These moment-in-time data images preserve performance as it was known at the time of extraction. Subsequently, metrics can be derived from a collection of data images – one for each reflected period – ensuring indicated period performance remains constant from one report publication to the next (eliminating the data variability issue).

Final Thought…

As previously eluded to, use of production data benefits the development of proof-of-concept metrics. Production data’s ease of extraction enables developers to more rapidly and cost effectively create and test these pilot metrics. That said, use of production data based organizational performance measures should be limited and done with a full understanding of their potential variability defects so as to not diminish confidence and drive inappropriate behaviors before the metric is properly implemented.

About the Author

Nathan Ives, StrategyDriven Principal is a StrategyDriven Principal and Host of the StrategyDriven Podcast. For over twenty years, he has served as trusted advisor to executives and managers at dozens of Fortune 500 and smaller companies in the areas of management effectiveness, organizational development, and process improvement. To read Nathan’s complete biography, click here.

StrategyDriven's organizational performance measures catalogEnterprise Performance Measurement

We can work with you to assess and improve your performance measurement system; yielding metrics and reports that are operationally relevant, organizationally consistent, and economically implemented. The resulting system helps improve managerial decision-making, organizational alignment, and individual accountability. Learn more about how we can support your implementation and upgrade efforts or contact us for a personal consultation.

Do Your Business Process Metrics Measure Up?

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  1. Are we doing things right?
  2. Are we doing the right things?

Peter Fingar, co-author of Business Process Management: The Third Wave, then asks these measurement corollaries in his 2013 article “How Do Your BPM Metrics Measure Up?”

  1. Are we measuring things right?
  2. Are we measuring the right things?

But what are these right measurements? John Dixon, Gartner analyst, articulates seven best practices:

  1. Focus on Outcomes – Measure the results, not the completion of steps or milestones to get there.
  2. Limit the Number of Measures – Not fifteen, but just a few.
  3. Set Clear, Specific Goals – The leaders must have clear goals and they need to articulate them.
  4. Link Metrics to Strategy – The metrics need to show how work impacts the company’s strategy.
  5. Measure Current Performance – Know how you are doing today, so you can see if anything changes in the future.
  6. Look Ahead, Not Just Back – Metrics are not just to see what happened historically. Metrics should cause action today.
  7. Make Metrics Visible and Accessible – Having workers, managers, supervisors, and executives see metrics helps employees make decisions and take action. If only executives see them on a monthly dashboard, it is too infrequent, too late, and too inaccessible.

And the next question is – How do you really do all this? Below are examples of TIPS from my 20 years of practice to select measurements that are meaningful and have an impact on results:

  1. Focus on Outcomes – Select measures that track the outcomes of the process from a product standpoint and customer standpoint. These should be results that provide value to the customer.
  2. Limit the Number of Measures – I say limit it to two or three. Start with that number and use them.
  3. Set Clear, Specific Goals – Starting a BPM Project successfully means creating a Project Charter with the Process Owner, Executive Sponsor, Project Lead and Team Facilitator. And in that charter are specific Improvement Targets; for each Improvement Target there needs to be one metric.
  4. Link Metrics to Strategy – It’s not only the metrics that should link to the strategy. The Improvement Targets need to be aligned with the strategy. So you need to discuss that with the Process Owner and Executive Sponsor.
  5. Measure Current Performance – This starts with gathering baseline data for the metrics designated for each Improvement Target.
  6. Look Ahead, Not Just Back – All metrics must drive decisions and action. If you measure something and don’t do anything with the measure, it’s no good. So think carefully about what action you will take with any metric, and discard it if no action is identified.
  7. Make Metrics Visible and Accessible – Metrics should be visible on the shop floor, or on the wall, or if on the desktop with mechanisms to have alerts about changes or concerns. A file on the desktop is not visible enough unless it is naturally accessed frequently.

About the Author

Shelley SweetShelley Sweet, the Founder and President of I4 Process, and author of The BPI Blueprint, is a highly respected BPM Practitioner. She provides consultation, workshops and training programs for clients ranging from start-ups to Fortune 500 companies, educational institutions, and government organizations. Her programs are based on a unique 3-PEAT method of modeling processes and analyzing data that accelerates operational improvements, and builds leaders and employees who sustain operational excellence. Want to learn more about BPM metrics? Email Shelley at: [email protected]

Time Matters

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StrategyDriven Organizational Performance Measures Best PracticePerformance measures record specified outcomes achieved either at a specified time or within a defined interval and so, by their very nature, are time dependent. Consequently, a performance measure alters the behaviors of those being monitored not only in relationship to what is being monitored but also to when the outcome is being monitored. Additionally, ambiguity and misinterpretation of a performance metric’s time-based characteristics diminishes decision-making, performance, and moral.

Performance Measure Timing Impacts

Performance measures depict observable outcomes at a specified time or within a defined timeframe. Because individuals tend to act in a manner that is positively reflected by measures documenting their performance, this time dependence tends to place intended and unintended productivity pressure on those monitored.

Intended Impacts

In addition to driving a specific desired behavior based on what is monitored, the metric’s time-based dependency:

  • Reinforces the need to meet established productivity quotas
  • Encourages identification of productivity improvement opportunities

Unintended Impacts

However, this time-based dependency can promote undesirable behaviors including:

  • Implementation of unauthorized shortcuts that diminish quality in order to enhance measured counts
  • Employment of severe overtime to increase production by the measurement date
  • Manipulation of processes, such as dumping stock in customer warehouses, to achieve a better measured outcome

All performance metrics exert desired and undesired influence on behaviors. Therefore, it is important for executives and managers to anticipate these influences and implement counterbalancing metrics to ensure that only desired results are achieved. (See StrategyDriven articles, Organizational Performance Measures Best Practice – Diverse Indicators, Documenting Performance Measure Drivers.)

Time-based Characteristics Impacts

Ambiguity and misinterpretation of a performance metric data diminishes decision-making, performance, and moral. Because the time-based characteristics of performance measures are less visible, the likelihood of errors resulting from the misunderstanding of these parameters increases.

Ambiguous Time-based Parameters

Ambiguous time-based metric parameters can also adversely affect reflected performance. This is especially true when the specified measurement time is itself expressed as an interval. For example, work management processes frequently refer to ‘T-weeks,’ where the T-week number reflects the number of weeks before the execution or T-0 week. Measurements associated with T-week activities must specify whether the activity is to be assessed before, during, or at the conclusion of the T-week lest there be a 7 day ambiguity in when the action is to occur.

Misinterpreted Time-based Parameters

Misinterpreted time-based metric parameters routinely occur because of a lack of ‘field-level’ definition specificity and/or a failure to communicate the ‘field-level’ definition. For example, the time required to correct a deficiency can be anchored on several different start and stop times, each impacting the metric reflected outcome. Does the correction interval start at the time of deficiency occurrence, time of deficiency identification, time of work start, or some other time? Does the correction interval stop at the time of work completion, time of paperwork closure, time of work tracking system status update, time of work financial closure, or some other time?

Ambiguity and misinterpretation of a performance measure’s time-based characteristics can lead to diminished performance at all levels of the organization. Without time-based characteristic definition specificity and/or communication of the definition, the same metric may be implemented differently by various workgroups within an organization and those whose performance is measured may become frustrated and confused because their perceived performance and metric reflected performance differs. Additionally, when decision-makers lack clarity on what is being measured, they misinterpret the resulting information diminishing the quality of their decisions.

Final Thought…

A performance measure’s time-based characteristics profoundly affect its reflected outcomes. Consequently, it is advisable to develop and conduct trials with inexpensive test metrics prior to the implementation of more costly, permanent metrics as a need to adjust the less visible time-based characteristics often arise. (See StrategyDriven article, Organizational Performance Measures Best Practice – Ad Hoc Reports First, Metrics Second.)

About the Author

Nathan Ives, StrategyDriven Principal is a StrategyDriven Principal and Host of the StrategyDriven Podcast. For over twenty years, he has served as trusted advisor to executives and managers at dozens of Fortune 500 and smaller companies in the areas of management effectiveness, organizational development, and process improvement. To read Nathan’s complete biography, click here.

StrategyDriven's organizational performance measures catalogEnterprise Performance Measurement

We can work with you to assess and improve your performance measurement system; yielding metrics and reports that are operationally relevant, organizationally consistent, and economically implemented. The resulting system helps improve managerial decision-making, organizational alignment, and individual accountability. Learn more about how we can support your implementation and upgrade efforts or contact us for a personal consultation.

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