Practice Activities

  1. Use Table 13-1 to assess whether your project or organization is already caught in any of these 10 wtraps. If so, think of ways to get out of that trap. If you aren’t already trapped, do you see warning signs looming ahead? If so, think of how you might avoid getting caught in the trap.

  2. Table 13-2 summarizes the symptoms of each trap described in this chapter. Rate each symptom to indicate whether it poses a risk for your organization. Mark the Green column if you see no signs of that symptom in your organization. Mark the Yellow column if you see hints of that symptom appearing. Mark the Red column if you’re already experiencing problems from that symptom.

Table 13-1. Your Metric Traps

Trap

Are You Caught?

Do You Spot Symptoms?

#1: Lack of Management Commitment

  

#2: Measuring Too Much, Too Soon

  

#3: Measuring Too Little, Too Late

  

#4: Measuring the Wrong Things

  

#5: Imprecise Metrics Definitions

  

#6: Using Metrics Data to Evaluate Individuals

  

#7: Using Metrics to Motivate, Rather Than to Understand

  

#8: Collecting Data That Isn’t Used

  

#9: Lack of Communication and Training

  

#10: Misinterpreting Metrics Data

  

Table 13-2. Metric Symptoms Assessment

Trap

Symptom

Green

Yellow

Red

#1: Lack of Management Commitment

  • Management opposes measurement.

   
 

  • Management doesn’t provide input into metrics program design.

   
 

  • Management doesn’t require people to report data.

   
 

  • Management doesn’t drive program deployment.

   
 

  • Management doesn’t share data with other stakeholders.

   

#2: Measuring Too Much, Too Soon

  • A long list of metrics is selected initially.

   
 

  • It’s not clear why some metrics are being collected.

   
 

  • Participants resist because collecting data takes too much time.

   
 

  • You get more data than you can analyze.

   
 

  • Stakeholders are overwhelmed with charts and reports.

   

#3: Measuring Too Little, Too Late

  • Data collected doesn’t provide enough information.

   
 

  • Participants change their behavior to optimize what is being measured.

   
 

  • Managers don’t get the data they need.

   
 

  • Reluctant practitioners don’t report all required data.

   
 

  • Data is reported much later than requested.

   

#4: Measuring the Wrong Things

  • Metrics don’t relate to business success strategies.

   
 

  • Managers don’t get the information they need to manage projects and people.

   
 

  • You can’t tell if process changes are working.

   
 

  • Inappropriate surrogate measures are used.

   

#5: Imprecise Metrics Definitions

  • Individuals interpret the definitions to mean different things.

   
 

  • People ask many questions about metrics definitions.

   
 

  • People measure the same things but get different results.

   
 

  • Data is hard to interpret because of different local measurement conventions.

   

#6: Using Metrics Data to Evaluate Individuals

  • Metrics data is used for performance evaluations.

   
 

  • Developers are ranked based on their productivity or other results.

   
 

  • People fake or conceal the data to avoid being hurt.

   
 

  • Managers can attribute all data to individuals.

   
 

  • People fear the metrics program.

   

#7: Using Metrics to Motivate, Rather Than to Understand

  • Managers say, "We can use metrics to drive desired behaviors."

   
 

  • Public tracking charts are labeled as being good or bad.

   
 

  • Managers try to get "the numbers" where they want them.

   
 

  • The project results aren’t consistent with desired goals.

   
 

  • People change their behavior to avoid being penalized by data.

   

#8: Collecting Data That Isn’t Used

  • Data is reported, but no one learns how it is used.

   
 

  • Charts aren’t shared with the team.

   
 

  • Practitioners don’t have access to the public metrics repository.

   
 

  • Management doesn’t seem to care if they have the data or not.

   

#9: Lack of Communication and Training

  • Participants don’t understand what is expected of them.

   
 

  • There is confusion about what and how to measure and what to do with the results.

   
 

  • You hear much opposition to the program.

   
 

  • People are afraid the data will be used against them.

   

#10: Misinterpreting Metrics Data

  • Small blips in charts lead to overreactions.

   
 

  • Trends warning of problems are not taken seriously.

   
 

  • Trend changes are attributed to the wrong root causes.

   
 

  • Calculations or analyses based on metrics data lead to erroneous conclusions.

   
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