I am a huge proponent of using analytics and other metrics to drive business decisions, but I repeatedly see people making a huge and avoidable mistake. Instead of using the data to determine the best strategy, they use data to justify their intuition. A good analyst can use data to draw virtually any conclusion and if the analyst is pushed in a certain direction by the business leader, all the data does is provide people with cover for the decision rather than leading you in the optimal direction.
The same situation applies to financial analysis. I have seen people frequently manipulate numbers, often with the approval or even encouragement of the target audience, to tell the story people want to hear. I have seen this manipulation in sales, in corp dev and in internal forecasting. In all situations, it is actually just a rationale to make a decision the person already wants to make.
The first part of the problem is manipulating the data. I am not talking Enron here, but more subtly and maybe not even intentionally. People will often select the data that supports their position while discounting the other information. If you want to greenlight a certain feature, you may look at the impact on retention while neglecting the impact on monetization and rationalize it by saying it is a retention feature. Regardless of whether it is a retention or monetization, your goal is to optimize lifetime value (LTV) so you need to look at the data holistically. Continue reading “Changing the numbers does not change the reality”
I previously wrote about how Bayes’ Rule is the foundation of good decision making and last month posted about how it could be applied to your green light process, today I will address another application of Bayes’ Rule: Applying it to corporate development (mergers and acquisitions). As discussed in my first two posts about Bayes’ Theorem, it shows how to use past data to optimize your decision making process. There are three areas of corporate development in which Bayes’ Rule can help optimize your strategy: building a company for exit, selling to the right partner and acquiring companies that improve your value.
Creating a company for exit
Many founders start and build their business for eventual exit (e.g., sale or IPO) but if they fail to take into account Bayes’ Rule they are not optimizing their chances for a successful one. If your goal in launching a business (or pivoting your business) is to sell it, then you need to look at past data. The best indicator of whether you will be able to sell—and for how much—is other M&A (mergers and acquisitions) activity. You may have a great idea for a business, and it may be unique, but if it is in a space where there is no M&A activity you are not likely to sell eventually the company (however, that is not to say you should not start it, if your goal is something other than a sale).
To show how Bayes’ Rule applies, let’s consider two opportunities. One is a building a game company in a space where 60 percent of the companies are selling to larger companies. You have a decent idea and good team but it is not great; looking objectively you have a 50 percent chance of success. Conversely, you have a fantastic idea for a different type of game company. You are convinced that in that space you have a 90 percent chance of success. Buyers, however, are not showing much activity there and only one percent of companies in that space have an exit. Bayes’ Rule shows that if your goal is an exit, then you should launch the company where you have a 50 percent chance of success (you will have a 30 percent chance of selling your company versus less than 1 percent for starting the company that is much more likely to succeed).
My personal experience reaffirms this math. At Merscom, we were a very successful casual game publisher (downloadable games targeting women sold primarily on Big Fish and Real) . There, however, was not much M&A activity in the space. So we decided to abandon a profitable, highly successful business in 2009 to enter the social gaming space because there was an acquisition almost every week. A few months after our pivot, we were acquired by Playdom, and a few months after we were acquired, Playdom was acquired by Disney.
Continue reading “Bayes’ Theorem Part 4: Making the right decisions in corporate development”