What if I told you we could save your company millions of dollars? Together we identify which marketing actions are delivering revenues and which ones are not. Among the revenue drivers, we calculate the return on investment, and find ways to make less efficient campaigns better. In your new marketing plan, you scale up the hardest working media and campaigns (and reward the people behind them), improve the efficiency of other revenue drivers and cut out ineffective media and actions. Your proposed budget saves your company millions. Our predictions are mostly right, your company increases top line revenues, bottom line profits and its stock price.
Why would you not want to go ahead with this scenario? Lots of managers do not in my experience. Here are a few reasons, and what leading companies do to get around them:
1) Risk aversion: a U.S. manager told me: “I am 99% convinced that our analysis is correct in cutting our TV marketing budget by half. But if we are right and the company saves millions of dollars, I don’t get a penny more. If we are wrong and I would lose half of a market share point, I’ll be fired”
Solution: trust in profit and credit sharing: leading companies such as Procter & Gamble reward employees for taking calculated risks and punish those that fail to act on great opportunities. Managers experiment to demonstrate the effectiveness and efficiency of marketing actions. The results are a matter of public record and shared company-wide in success and failure stories. See chapter 13 in ‘It’s not the Size of the Data, It’s How You Use It’ www.notsizedata.com
2) Fear of math models: a European CEO of a midsized company was interested in marketing analytics, but feared he would never get the mathematics behind the model results. How could he (ask his employees) to take action based on results that did not fully corresponded to simple intuition?
Solution: dashboards: to drive your car, you don’t need to know precisely how your car’s engine works. In “Smarter Marketing with Analytics and Dashboards”, you learn how to translate models into user-friendly dashboards. This allows decision makers to run ‘what-if’ scenarios on their laptops and get comfortable with various scenarios…developing trust in the underlying model without seeing the math.
3) Fear of losing face: an Asian manager got very excited when she realized her most challenging problems were a perfect fit for marketing analytics. Unfortunately, she did not know for sure where or from whom to obtain the perfect data in her company, and she did not want to look bad in the eyes of the consultant or her boss.
Solution: demonstrate to your employees that data need not be perfect to improve decision making. In marketing, it is better to be vaguely right than precisely wrong: getting good-enough proxies on all important factors is better than not trying at all, and helps you improve your measurement over time.
So what have we learned? Risk aversion, the fear of models and the fear of losing face keep your employees from acting on insights and making/saving your company millions. Embrace a culture of accountability, train them in analytics and dashboards and show them that small improvements with small data outshine big errors with big data. Above all, walk the talk and lead the way!
Prof. Koen Pauwels