analytics
What’s Your Magic Number?
Wednesday, January 14th, 2009 | Compensation Plans, EIM, SPM, Uncategorized, analytics | No Comments
Some time ago I read an article by Inc. columnist, Norm Brodsky, discussing unique indicators or as he dubbed them, magic numbers. Magic numbers are described as particular statistics discovered by business operators to have special correlations that can be used to predict future business performance. Examples in the article include a restaurateur who predicts his nightly receipts by the length of wait for a table at 8:30 p.m. and Mr. Brodsky himself who uses the current number of new boxes to forecast a period’s sales within his records storage business. What makes these magic numbers extremely valuable beyond their correlation with traditional business performance measures is that they are easier to obtain and/or available well before their lagging counterparts. Once identified and monitored, the numbers can allow earlier more accurate business operations decisions. In the referenced article, Mr. Brodsky describes how he, using the afore mentioned indicator, slowed his company’s hiring rate well ahead of when he had the quarterly sales totals which he previously used to drive this decision; this allowed him to not over hire rather than being forced to lay off personnel -nice!
This concept is not unique to business. Doctors use indicators like blood pressure, cholesterol test, blood cell counts that have shown to correlate with certain conditions. Using these statistics they predict and take steps to prevent health issues before other symptoms may present. Car owners and mechanics may watch miles per gallon or RPM values in the same manner. How does any of this relate to EIM / SPM systems?
First, EIM / SPM systems, because of their early access to order and customer account data, are a gold mine for finding magic numbers that correlate with sales or other key business statistics. You may find that the commissions system’s transaction count on a particular day of a pay period correlates with that period’s eventual sales commission payout total or perhaps an increase in the percentage of sales of a particular type of product is a leading indicator of an upswing in your company’s market.
Additionally, there are likely magic numbers that can help assess the health of your incentive compensation plans or the EIM / SPM system. These can help IT, administrators, and compensation analysts make EIM / SPM related decisions and adjustments earlier than they might otherwise. The number of sales representative disputes per week might correlate to sales plan health or the number of credits awarded per sale may help administrators detect system inaccuracies before your sales reps or auditors find them.
So how do you go about finding the appropriate magic numbers? Well obviously they should be easier to obtain and available earlier than what you hope they will predict (otherwise what would be the point?). Beyond that, you will need to become very familiar with your system and / or business and watch candidate numbers over time, sometimes a lot of time; you shouldn’t hope to find valuable indicators until you have adequate history to test correlations. Brodsky describes a process of understanding “the relationships between the numbers” which sounds to me like relying on your gut. The statisticians among you might suggest ANOVA or other tests of correlation as magic number discovery techniques; unfortunately (or is it fortunately?) it’s been far too long since my last stats class to address these. Whether it’s via gut feel or a more scientific approach, hope you find some magic!
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Analytics: You absolutely must have it, now tell me what it is
Friday, January 9th, 2009 | Compensation Plans, EIM, SPM, analytics | No Comments
Analytics can save the world. More specifically it can revolutionize the way you do business, which could at least save your world. Analytics is the Holy Grail of Sales Performance Management. If you work with SPM you already know that because the term “analytics” has been a buzzword within SPM solutions since I can remember. It’s amazing how the latest and greatest concept can stay “latest and greatest” for a decade or more. The sad fact is analytics is re-revealed as a new milestone every couple of years. I suppose that means nobody is ever getting there. It’s right up there with El Dorado and Atlantis.
So what is “Analytics”?
Analytics
An`a*lyt”ics\, n. The science of analysis.
Does that clear it up? I doubt it. It turns out that the term analytics is more a guide post than a destination. It’s like saying you are going to “the city”. If you live in Long Island “the city” is Manhattan. But if you live in Pullman, WA, New York probably never enters the brain. In my opinion the reason we never seem to get to this mythical land of analytics is simple. Nobody knows where it is. Or to put a different way, we don’t all necessarily agree on what it looks like and what it does for us.
It makes sense to say that analytics are going to depend on the organization. What’s less obvious is something that I’ve seen many times at different clients. Definitions of analytics within the organization will vary depending on the role of the individual doing the defining
Macro-Analytics vs. Micro-Analytics
The most common divide is a concept I like to call macro vs. micro. When putting together an analytics tool the most important element is the data and how it’s structured. Often times you need to tweak your source systems in order to produce data at the level desired for your analyzers. Here’s where the conflict occurs.
Let’s take a Global Compensation Director. She would like to look at her data at a summary level based on role, country, etc. She wants to reconcile compensation data from the SPM system with data from the accounting system and the sales reporting system. Global Directors want to view metrics like a captain of a cruise ship. Cruise ships can drift a few feet off course as long as the captain can avoid the ice burgs.
Now let’s take the Compensation Analyst assigned to the Northeast New Jersey territory in the retail business unit. He wants account level and product level metrics. Analysts need to know the specific rate paid on specific orders. They are looking to find deviations at a micro-level. They need to answer questions related to the setting of quotas and the effect of vacation time. Analysts deal with individuals and their paychecks, there is no place for estimations, averages and summaries when it comes to paychecks.
So where is the “analytics” City of Gold? Every company needs to draw their own map. Certainly there are many ideas out there that can be reused as starting points or templates. However, when it comes down to it every stake holder needs to identify what they want to see. This isn’t a case where you buy a tool and it triggers a wave of game changing analytical analysis that you’ve never heard of. What a nice analytics tool gives you is built-in adaptability. You might start with one vision and change it later after a period of use.
However, if you don’t start with some sort of a vision and/or goal you will probably be dissatisfied with the results conversely, a common mistake is to try and have too many goals. As the saying goes, “a tool that does everything does nothing well.” Then three years from now you will learn again about this latest and greatest concept named “Analytics” and get all excited yet again.
Later we can create a roadmap to successfully building an analytics tool. Stay tuned…
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- Sales compensation program change considerations - MichaelStus