Dr. Deming

Dr. Deming

The Seven Deadly Sins of metrics programs are:

  1. Pride – Believing that a single number/metric is more important than any other factor.
  2. Envy – Instituting measures that facilitate the insatiable desire for another team’s people, tools or applications.
  3. Wrath – Using measures to create friction between groups or teams.
  4. Sloth – Unwillingness to act on or care about the measures you create.
  5. Greed – Allowing metrics to be used as a tool to game the system.
  6. Gluttony – Application of an excess of metrics.
  7. Lust – Pursuit of the number rather than the business goal.

In the end, these sins are a reflection of the organization’s culture. Bad metrics can generate bad behavior and reinforce an organizational culture issues. Adopting good measures is a step in the right direction however culture can’t be changed by good metrics alone. Shifting the focus on an organizations business goals, fostering transparency to reduce gaming and then using measures as tools rather than weapons can support changing the culture. Measurement can generate behavior that leads towards a healthier environment.  As leaders, measurement and process improvement professionals, we should push to shape their environment so that everyone can work effectively for the company.

The Shewhart PDCA Cycle (or Deming Wheel), set outs of model where measurement becomes a means to an end rather than an end in their own right. The Deming wheel popularized the Plan, Do Check, Act (PDCA) cycle which is focused on delivering business value. Using the PDCA cycle, organizational changes are first planned, executed, checked by measurement and then refined based on a positive feedback model. In his book The New Economics Deming wrote “Reward for good performance may be the same as reward to the weather man for a pleasant day.” Organizations that fall prey to the Seven Deadly Sins of metrics programs are apt to incent the wrong behavior.

(Thank you Dr. Deming).

3068483640_328b020efa_bGluttony is over-indulgence to the point of waste.  Gluttony brings to mind pictures of someone consuming food at a rate well beyond simple need.  In measurement, gluttony then can be exemplified by programs that collect data that has no near-term need or purpose.  When asked why the data was collected, the most common answer boils down to ‘we might need it someday…’

Why is the collection of data just in case, for future use or just because it can be done a problem?  The problems caused by measurement gluttony fall into two basic categories.  The first is that it wastes the effort of the measurement team, and second because it wastes credibility.

Wasting effort dilutes the measurement team’s resources that should be focused on collecting and analyzing data that can make a difference.  Unless the measurement program has unlimited resources, over collection can obscure important trends and events by reducing time for analysis and interpretation.  Any program that scrimps on analysis and interpretation is asking trouble, much as a person with clogged arteries.  Measures without analysis and interpretation are dangerous because people see what they like in the data due to clustering illusion (cognitive bias). Clustering illusion (or clustering bias) is the tendency to see patterns in clusters or streaks of in a smaller sample of data inside larger data sets. Once a pattern is seen it becomes difficult to stop people from believing that the does not exist.

The second problem of measurement gluttony occurs because it wastes the credibility of the measurement team.  Collecting data that is warehoused just in case it might be important causes those who provide the measures and metrics to wonder what is being done the data. Collecting data that you are not using will create an atmosphere of mystery and fear.  Add other typical organizational problems, such as not being transparent and open about communication of measurement results, and fear will turn into resistance.   A sure sign of problems is when you  begin hearing consistent questions about what you are doing, such as “just what is it that you do with this data?” All measures should have a feedback loop to those being measured so they understand what you are doing, how the data is being used and what the analysis means.  Telling people that you are not doing anything with the data doesn’t count as feedback. Simply put, don’t collect the data if you are not going to use it and make sure you are using the data you are collecting to make improvements!

A simple rule is to collect only the measurement data that you need and CAN use.  Make sure all stakeholders understand what you are going to do with the data.  If you feel that you are over-collecting, go on a quick data diet.  One strategy for cutting back is to begin in the areas you feel safest [SAFEST HOW?]. For example, start with a measure that you have not based a positive action on in the last 6 months. Gluttony in measurement gums up the works just like it does in a human body; the result of measurement gluttony slows down reactions and creates resistance, which can lead to a fatal event for your program.

 

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In Christianity, the seven deadly sins are the root of all other sins. This concept has been used as an analogy for the ills or risks for many professions.  The analogy fits as well for software metrics; focusing attention on the behaviors that could sap your program’s integrity, effectiveness and lifespan. Here we will look at the deadly sins from the point of view of a person or group that is creating or managing a metrics program. As with many things in life, forewarned is forearmed, and knowledge is a step towards avoidance.

Here are the seven deadly sins of metrics programs:

  • Pride – Believing that a single number/metric is more important than any other factor.
  • Envy – Instituting measures that facilitate the insatiable desire for another team’s people, tools or applications.
  • Wrath – Using measures to create friction between groups or teams.
  • Sloth – Unwillingness to act on or care about the measures you create.
  • Greed – Allowing metrics to be used as a tool to game the system for gain.
  • Gluttony – Application of an excess of metrics.
  • Lust – Pursuit of the number rather than the business goal.

All of the deadly sins have an impact on the value a metrics program can deliver.  Whether anyone sin is more detrimental than another is often a reflection of where a metrics program is in it’s life cycle. For instance, pride, the belief that one number is more important than all other factors, is more detrimental than sloth or a lack of motivation as a program begins whereas sloth becomes more of an issue as a program matures.  These are two very different issues with two very different impacts, however neither should be sneezed at if you value the long-term health of a metrics program. Pride can lead to overestimating your capabilities and sloth can lead to not using those you have in the end self-knowledge is the greatest antidote.

Over the next few days we will visit the seven deadly sins of metrics!

Gluttony is over-indulgence to the point of waste.  Gluttony brings to mind pictures of someone consuming food at a rate well beyond simple need.  In measurement, gluttony then can be exemplified by programs that collect data that has no near-term need or purpose.  When asked why the data was collected, the most common answer boils down to ‘we might need it someday…’

Why is the collection of data just in case, for future use or just because it can be done a problem?  The problems caused by measurement gluttony fall into two basic categories.  The first is that it wastes the effort of the measurement team, and second because it wastes credibility.

Wasting effort dilutes the measurement team’s resources that should be focused on collecting and analyzing data that can make a difference.  Unless the measurement program has unlimited resources, over collection can obscure important trends and events by reducing time for analysis and interpretation.  Any program that scrimps on analysis and interpretation is asking for just as much trouble as a person with undiagnosed clogged arteries.  Measures without analysis and interpretation are dangerous because people see what they like and it becomes difficult to change their minds.

The second problem of measurement gluttony occurs because it wastes the credibility of the measurement team.  That loss of credibility builds resistance to measurement and analysis from those being measured because they don’t know what is being done the data. Collecting data that you are not using will create an atmosphere of mystery and fear.  Add other typical organizational problems, such as the compartmentalization of the communication of results, and fear will turn into resistance.  A sure sign of problems is when you  begin hearing consistent questions about what you are doing, such as “just what is it that you do with this data?” All measures should have a feedback loop to those being measured so they understand what you are doing, how the data is being used and what the analysis means.  Telling people that you are not doing anything with the data doesn’t count as feedback. Simply put, don’t collect the data if you are not going to use it and make sure you are using the data you are collecting to make improvements!

A simple rule is to collect only the measurement data that you need and CAN use.  Make sure all stakeholders understand what you are going to do with the data.  If you feel that you are over-collecting, go on a quick data diet.  One strategy for cutting back is to begin in the areas you feel safest. For example, start with a measure that you have not based a positive action on in the last 6 months. Gluttony in measurement gums up the works just like it does in a human body; the result of measurement gluttony slows down reactions and creates resistance, which can lead to a fatal event for your program.