I’m on my way back from the MIT Sloan Sports Analytics conference in Boston. I’ll post a review and thoughts on the conference later on when I have a chance to compile my notes.
Something that came up in conversation during the conference and during the reception afterwards was the definition of EPM. Basically, EPM is something that I’ve heard tossed around in the last few years and is a term that has been defined and redefined by just about every services firm, software company, industry analyst and talking head on the planet. I’ve personally heard it defined as “Enterprise Performance Management” and equally as much as “Enterprise Performance Measurement”.
Now, here’s a disclaimer. There are numerous wonderful books out there that try to help people define and establish EPM practices for their business. These books are fantastic in that if you’re ever having a problem sleeping at night pick up one of these. Problem solved. (I would especially recommend the Norton/Kaplan books.)
What I also find comical about these books is that you would really trust your knowledge (and your organizations health) to the concepts presented in a book! I would compare that to having your teenager read the owner’s manual of your car to learn how to drive.
Here’s what I can add to the already muddied waters though. This is based purely on experience as I myself have fallen asleep on many of the above-mentioned book.
Performance measurement is the process by which you define measures to help you analyze the effectiveness of your business. This “effectiveness” ratio can be financial, operational, managerial or any other “ial” that you feel is of value to your business (I’ll provide a simplistic example below).
Performance management on the other hand, is taking the information provided by performance metrics (as defined in the previous paragraph) and doing something that then (hopefully) has a positive impact.
One of the most common examples is a simple inventory management example. Let’s say a major retailer has 50 white t-shirts on the shelves at a local store. Based on what someone can see in the inventory management system the quantitative observation can be made that the inventory level is 50. But, WHAT DOES 50 MEAN? Is 50 good, bad or about right?
This is one of the main elements of a performance measurement system – the difference between quantitative data and qualitative information.
Back to our example. If the “ideal” inventory level for those white shirts is 50 then we’re right where we should be. If the ideal level is 10 then we are 5x in an overstock condition (not tragic, but not good). If the ideal level is 200, then we are woefully under stocked which could potentially end up in a dreaded “out of stock” condition which results in a direct loss of revenue – which is obviously a bad thing.
A scoring possibility in this scenario and one that is commonly employed in the retail space is a scale of –10 to 10 with zero being a neutral middle ground. -10 would report a dangerous understock condition and 10 would report an overstock, very high level. Now we have a qualitative analysis that qualifies as a performance measurement and can be subsequently used in performance management.
Advanced performance measurement systems (like what Real Sports Analytics is based on) can take the inventory levels for all of the these t-shirts and for that matter everything in the store, compare them against their ideal levels and produce usable information on the inventory health of the product, the department, the store, a region of stores, a distribution center, etc, etc, etc.
Now, let’s explore how this concept fits into sports. Let’s say a very talented wide receiver makes a 10 yard catch. Great, we have quantitative data similar to the 50 t-shirt example above. But, what does that 10 yards mean? Was the play supposed to go for 15 yards and the receiver ran an improper route? Was the play only supposed to go for 5 yards and he picked up extra yards on effort? Was this near the end of the game and it was 3 and 8 and they needed the ten yards for a first down and the possibility of running out the clock? Or did he need to get out of bounds to stop the clock and didn’t make it?
These are all factors that allow us to take this simple 10 yard catch and, usually with the help of coaches or scouts, put a qualitative value on this action.
When you observe this activity over hundreds or (hopefully) over thousands of observations you can readily pick out the noise and put a quality metric on the performance of any player, set of players, offensive, defensive or complete team. This is valid whether it’s a wide receiver, quarterback, offensive linemen or defensive player. You just need to define the right metrics for YOUR organization.
When these metrics are defined correctly and adjusted over time you can create a very, very effective performance management systems that can have direct, measurable results on the playing field.
So, what metrics are of the most value to your organization?
