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How to Use Metrics and KPIs to Model and Analyze BI Requirements

Rachael Wilterdink Rachael Wilterdink  |  
Jul 18, 2019
 
If you’re involved in eliciting, modeling, analyzing, or consuming requirements for Business Intelligence projects, this post is for you. This is the eighth technique in our blog series on 10 Techniques for Business Analysts (BAs) to model and analyze Business Intelligence (BI) requirements.
 
Metrics and KPIs are among the primary techniques for anything related to Business Intelligence. If you can measure it, you can report on it. The “key” is picking the right metrics and KPIs. 
 

What Are Metrics and KPIs?

The official definition of this technique, according the International Institute of Business Analysis (IIBA®) is: “Metrics and key performance indicators measure the performance of solutions, solution components, and other matters of interest to stakeholders.” - BABOK® v3.0
 
Some further definitions include:
 
Metric: quantifiable levels to measure progress
 
Indicator: numerical measurement representing degree of progress toward:
 
  • Goal
  • Objective
  • Output
  • Activity
  • Further Output
 
KPI: metric used for strategic purposes
 

What are the Elements of Metrics and KPIs?

 
Indicators:
  • Clear
  • Relevant
  • Economical
  • Adequate
  • Quantifiable
  • Trustworthy / Credible
 
Metrics: quantifiable
 
Structure:
  • Reliable
  • Valid
  • Timely
 
Reporting: visual output
 

How are Metrics and Key Performance Indicators Used?

 
  • To compare baseline metrics against current ones, to target difference in both relative and absolute terms
  • To identify credible trends
  • To visually and effectively represent and explain data
  • To inform business decisions
 
kpi report sample
 

Pros

Having good intelligence about a business or organization helps the organization run. It helps leaders identify trends so they can predict what might happen in the future. It helps companies improve their performance and manage their operations. Being able to get meaningful visuals based on accurate data can dramatically help companies make better business decisions.
 

Cons

You must trust the integrity of the data that drives your metrics and KPIs. If you have dirty data, you’ll have dirty results.
 
Getting data in the right place and properly related is a difficult job. Users of the data must also understand these relationships, or they could possibly misuse or misreport on something. Your data users need to be knowledgeable about what the data means.
 
Once you start measuring something, you start influencing people’s behavior. This is something you need to be aware of because it is human nature to start to “game the system”.
 
Operational and transactional data is about things that have already happened, and you can’t change history. However, you can use these numbers to anticipate the future so you can make informed plans based on insights you glean from the data.
 

Conclusion

Metrics and KPIs are important for most organizations to help them optimize and improve their business operations and make better business decisions. For it to work, though, the underlying data must have integrity and be trusted.
 
Next up in this blog series: Process Modeling.

 

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References:
“IIBA Home.” IIBA | International Institute of Business Analysis, www.iiba.org/.
“PMI.” PMI | Project Management Institute, www.pmi.org/.
 
Business AnalysisBusiness Intelligence

 

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