The 162 games of a MLB season are beautifully objective. The team with the most runs wins, full stop. Not every competition in baseball is cut and dried.
Every year around this time, each team faces a new kind of competition -- one among themselves. There is a finite budget, and each department is trying to get a bigger slice - marketing, human resources, scouting, player development, medical, and analytics, to name a few. Like any other business, it would be extremely rare for a department head to walk into a budget meeting and volunteer to give money back.
In this competition, there is no scoreboard, which makes deciding winners much more difficult. From an admittedly biased perspective, it seems obvious that hiring analysts is a smart move. A good analyst could find the next superstar or save you from signing an overpriced bust, and the cost of an analyst is a sliver of the multi-million dollar contracts that MLB players command. Yet, many teams struggle to justify expanding their analytics teams. Why?
The difference is attribution. By signing a player, that player will accumulate performance stats that are directly relatable to wins and losses. It's easy to judge the effect of that investment. An analyst doesn't have performance stats. That distance from the field, literally and figuratively, makes the attributed value of an analyst hard to determine, and thus under-invested.
Does this story sound familiar to the incentive business? Imagine a typical brand budget meeting -- there will be heads of each department there - television, radio, social media, digital video, display, SEO/SEM, promotions, incentives, just to name a few. You already know how it is going to go. Each department head will explain how successful they were last year and ask for an increase in budget and headcount for next year. No one is giving money back, everyone is asking for more.
Incentive programs suffer the same problem as analytics on a baseball team -- attribution. Each of the digital channels has user-level data that can prove how many conversions they are driving. The television and radio departments have billion-dollar companies such as Nielsen and comScore, built just to measure their effects.
This scenario is where data and measurement are critical for the incentive industry. Each incentive program has to be its own Nielsen. Further, you must show that decision-making executive the numbers he or she will care about -- not just how many people opened an email, clicked on the site, or earned some points. The only thing that is going to move the needle at the executive level is true, no-caveats, analytically-bulletproof lift.
The scoreboard in that budget meeting is ROI, and if you aren't proving your program scores on that metric, then your team has already lost.
ROI is where analytics has to go beyond traditional reporting and dashboarding. Our industry is hard to measure because the best program participants earn the most rewards. There will always be a chicken-or-egg question in that executive's mind and if you don't have a good way of answering it, you will lose out to those other departments in the offseason budget game.
On a recent project with an automotive client, my team armed our client contact with data and visuals, which showed the program was driving millions in incremental sales and was rising over time. Our client strolled confidently into meetings with his executive team, and walked away with an expanded budget for 2018. That's a win for everyone involved.
Proving ROI is the first step, communicating that ROI is the next. We often fall in love with our programs, and want to tell the whole A-to-Z story about that weird spike you saw in June, how many participants signed up for your holiday promotion, or how this year's prize trip to Hawaii was marred by rain. All of that needs to hit the cutting room floor. You should prepare as if you have five minutes of attention. Make three to five killer ROI slides, put everything else in the appendix, and if they ask questions that drag it to 10, 20, 60 minutes, then good for you.
The game between the lines is beautiful in its objectiveness and simplicity. The one in the boardroom is neither, but the closer you can make objective ROI and communicate it simply, the better chance you have to compete and win some of next year's budget.
Jesse Wolfersberger leads the Decision Sciences team for Maritz Motivation Solutions, and specializes in merging the fields of behavioral science and artificial intelligence. Contact him to discuss if you are using data in your programs to make them smarter at [email protected].