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5 Ways to Get ROI From Your Analytics Efforts

Imagine this - it’s 3pm on Friday, you’re planning your weekend in your head: “Golf on Saturday morning, Football on Sunday afternoon.” You’ve got it all set, that is, until you receive that email from your boss with the headline, need to see you real quick. Your gut drops, and you want to pick up the phone to make a quick call to the boss seeing if you can get out of it “real quick” and answer a question while you grab your jacket to start the weekend early. You pick up the phone and dial, you hear your boss say, “Hey, come by my office, I was asked about some of these BI expenses and need to put together an ROI plan for our analytics team by Monday.” You hang up, shed a little tear and take the walk of death knowing you have no idea how you are going to come up with an ROI.  As you walk, you think, maybe I can see if Gartner has an article, or hey I’ll contact Wayne Eckerson and see if the Eckerson group has some ideas on this.  While those are great options, start with these five things, and it may alleviate this predicament in the first place.

The very first thing to recognize is that looking at ROI for the analytics team is the wrong question to begin with.  It’s the equivalent of saying what’s the ROI of our bathroom or the ROI of your closet space. At the end of the day, no one cares about the “performance” of a BI team. What matters is does the business feel supported and are they able to move the car forward with your analytics team as the engine. With that being said, let’s dive into these suggestions.

1. What is the Question?

Many times, we think of BI in terms of BI itself.  Let’s face it, we’re geeks. We love hearing about machine learning and predictive analytics. This may come as a surprise; our customers could not care less.  And when we are asked in terms of ROI, we should put our business hats on and think differently.  ROI should be in terms of business questions being asked.  What does your tech allow the company to “DO” or to “SELL” that wasn’t possible before and why is that a big deal? By the way, this is what the COMPANY can DO, not what your software or dashboard has on it.  Start thinking differently.

2. Ask Why

I’ve written much about the "5 Whys" and it’s always worth mentioning here as well. When creating an award-winning analytics team, you should constantly ask the question of "Why?".  Why are these numbers on the dashboard? What’s the importance of these KPIs on the scorecard? Asking yourself and your customers these why’s may short circuit anyone ever asking the question of what the ROI is in the first place, and if they do, you will have a list of real world problems you and your team are solving.

3. Turn it on Itself

Your BI and analytics programs are fantastic, now prove it by turning it on itself. BI for BI is important, and necessary.  Things such as trends on usage of reports, unused reports, errors etc. Getting ahead of the game and knowing your program will make a big difference.  This will allow you to know when and how your program is being used and more important, when it’s not.

4. Get the Right Data

Making sure you have the right data to begin with can not only help answer the ROI question, it may stop it from coming up in the first place.  If you have the right data, you can answer the right questions. What is the right data? Go back to the earlier sections of this article dealing with business questions and make sure you are capturing the data to answer those questions.  The business will begin to ask ROI questions especially when they don’t see any answers to the questions they are asking, but the bill in IT is escalating.

5. Get the Data Right

We’ve all heard of GIGO (Garbage in, Garbage out). This is throwback term from the previous century but just as relevant now as ever. Data cleansing in your data warehouse is imperative.  Also use the tools in your analytics teams to find the issues of data quality and report those back to the front-end systems teams.

Keep in mind that if someone is asking about ROI, something is probably wrong.  It signifies that there is a question of if this is worth it because someone doesn’t see the value.  Once this question is being asked, you are behind the curve.  When was the last time you attending a meeting and had to put together a chart on the effectiveness and return on investment for the toilet paper in your office? Most likely never, because everyone knows the value of the toilet paper, and your analytics department should be just as  important and uncontested.  Follow these 5 steps and you too could be just as indispensable.


DeWayne Washington

DeWayne Washington is a senior consultant with 20+ years of experience in BI and Analytics in over 2 dozen verticals. He is the author of the book More About DeWayne Washington