KPI overload. Most enterprises suffer from it, but very few know how to overcome it. While some BI analysts recommend that a single report or dashboard should have no more than fourteen KPIs, most managers struggle to keep their KPI count below fifty. It’s no wonder that business intelligence projects are often perceived as having little or no business value.
Not only are most managers today tracking KPIs that provide little insight, but most are also measuring the wrong KPIs (we’ll cover this issue in a separate blog post).
After teaching thousands of students around the world how to use the BI Dashboard Formula methodology to manage their KPIs, below are five key areas that you should focus on to determine if it’s time to purge your useless KPIs!
1. KPI has no goal… making it hard to measure success
The real reason why a KPI was derived in the first place, usually gets lost throughout the requirement gathering process. That’s why in our BI Dashboard Formula methodology, we teach companies how to validate the ‘why’, ensure their KPIs are visible to all users, and proactively review them every 30-90 days to track progress.
If you’re having trouble with establishing the ‘why’, here’s a hint. It’s not important enough, purge it!
2. KPI has multiple definitions… leaving it open for assumptions
With a clear goal, the next step is to identify the ‘what’? What does this KPI mean? While this may seem simple, it’s incredible how hard it is to get end users to agree on the single definition of a given KPI. When overlooked, this one factor can tank user adoption and force users to create new reports in silos. Our recommendation when defining your KPIs is to use the K.I.S.S. method. Keep it Simple Superstar!
Once you’ve established a single, clear KPI definition, be sure to make it visible on the report or dashboard where it will be used. The only thing worse than not having a clear KPI definition is having each user assume their own. If you are having trouble with this step, it’s a good sign that your KPI is too complicated. Either revisit step #1 or purge it!
3. KPI data source is unknown… so no one trusts it
Similar to the ‘why’, we recommend 100% transparency of the data sources on all of your business intelligence applications. We also recommend a continuous effort to keep data hygiene a priority. The worst thing to have a user find is incorrect KPI data! Good luck on regaining full trust. As with all other steps, if you can’t use sources with good, reliable data, it may be time to purge this KPI!
4. KPI name is vague… so no actions are taken
- If this KPI is tracking positively, what action do you want your team to take?
- If this KPI is tracking negatively, what action do you want your team to take?
Managers cannot assume that by using common KPI names such as ‘Sales’ or ‘Customer Service Calls’, their team will automatically understand what to do with the KPI. To fix this, here is an example of how to modify your KPI name to instantly add clarity and value. Instead of naming your KPI ‘Customer Service Calls’, if the goal is to reduce the number of calls, how about renaming the KPI to ‘Decrease Customer Service Calls’. This new KPI name makes the goal crystal clear. If you are finding it hard to add an actionable adjective to the KPI name, either start from step #1 or purge it!
5. KPI is hard to visualize…so it’s stuffed in a report
If you are having trouble visualizing your KPIs, it’s either because it lacks a clear goal or definition and/or has no action associated with it. We recommend starting from the top of this list. If that does not help, purge it!
Where to find out more?
I’d love to hear from you? How many KPIs were you able to purge by following these steps?
- It’s almost time for #BI2017 #HANA2017 in Orlando - February 16, 2017
- 16: BI Awareness and Adoption Tactics that Work with Lestor Meadows of Kimberly-Clark - August 23, 2016
- 15: Why the Key to a Data-Driven Culture is Community with Shawn Rogers - July 4, 2016
- It’s about that time for #BI2016 #HANA2016 in Vienna - June 10, 2016
- Ep #14: The Four Step Path to Success with GIS and Analytics with Matt Sheehan - May 31, 2016