Moneyball – The Business of Social Games and Casino

The next three years of this blog

After 500+ blog posts, I have decided to pivot my blog in a slightly different direction. While I will continue to write about newsworthy items in the gaming space, over the next three years I will primarily document my learnings and journey as I pursue a DBA (Doctor of Business Administration). I recently started the DBA program at Grenoble Ecole de Management, a three-year program that I will be doing in addition to my full-time job. I will use my blog to share both the key learnings from my research as well as insights into pursuing a DBA.

As part of the DBA, my research will focus on how tech companies prioritize new, innovative projects, particularly those that appeal to a new market (Blue Ocean). As these projects are new and unique, building projections and a P&L is more guesswork than science. In my experience, there is never a lack of great ideas for new projects but there is very little methodology around how to prioritize and which to greenlight. Many projects proceed due to a persuasive champion (or get killed for lack thereof) rather than actual data, very similar to how baseball operated in the pre-Moneyball days. The spreadsheets people build to “scientifically” determine ROI are so filled with assumptions, given that they are looking at a virgin space, that they are less than useless.

In addition to the traditional hurdles in prioritizing new, innovative projects, the evolving state of the industry adds a new challenge. I will layer on to my research how the Metaverse will impact the gaming space and what we should be building. While I am far from an expert currently on the Metaverse, so are the so-called experts (I’m looking at you Zuck). Rather than wild claims, I will break down how the key drivers around the Metaverse and how they will impact our business.

Overall, I plan to use my DBA research to advance the practice of prioritizing new games and technology projects and help everyone commit resources to best satisfy customers (current and future). As I learn best practices and new techniques, I will share them here for those who are interested.

Ignorance is a competitive advantage

I recently had a conversation with a gaming industry CEO whom I deeply respect that reinforced a MIT Sloan Management Review article, “Embrace Your Ignorance” by Michael Schrage, about how the savviest leaders promote and embrace ignorance. The thesis for both Schrage and the CEO was that you cannot accurately predict what your customers will want, like or need. Thus, you need to embrace this ignorance and run experiments to get the data.

Moneyball and The Innovator’s Dilemma

I have seen many companies where the leadership “felt” they understood the customer and would develop new products for these customers. It leads to project green light meetings very similar to the draft room in Moneyball, where people argue based on their experience which initiatives have the most potential. It is also one of the biggest contributors to the huge number of failed projects, particularly in the gaming space where we typically see more than 8 out of 10 new games fail.

This issue is actually often a bigger problem with executives who have had past successes. Even if they knew their existing or past customers very well, they do not necessarily know what a broader or new market wants. Even their existing data can skew innovation effort, which is the core point of the Innovator’s Dilemma: Companies that have been leap-frogged often create innovations for existing markets rather than new markets.

You already are ignorant—accept it

In Schrage’s article, he discusses how Microsoft’s Ronny Kohavi (a pioneer in online experimentation) challenges tech-savvy audiences when he speaks. Kohavi shows screenshots of actual A/B tests that Microsoft has run for website design. He then asks his audience to predict the outcome of the tests. Although the audience is sophisticated, they almost always fragment with different opinions. Kohavi then advises, “stop debating…it’s easier to get data.” Continue reading “Ignorance is a competitive advantage”

Moneyball finally comes to VC

I have been intrigued for years that a huge financial sector has continued to rely on intuition while industry after industry has discovered that using analytics give you a better chance to succeed. Moreover, it is a sector that brags about the fact that it fails 99 percent of the time yet fails to embrace methods to improve those odds. I am talking about venture investing, the venture capital industry.

Moneyball and the venture community

For those who have seen the movie or read the book Moneyball, which I have written about multiple times, one of the most poignant scenes is the Oakland A’s smoke filled draft room where scouts with years of experience determine the best prospects to select based on their gut of what makes a great baseball player. When I first read about it, the parallels to how game company executives select what games to green light were incredibly apparent and I was certain you would see a similar transformation of the game industry. We did, with analytics driven social game companies putting many old school game companies out of business.

The venture capital space has uncanny parallels to the pre-Moneyball baseball industry. You have investors with years of experience sitting in Red Bull filled rooms deciding which investments to pursue based on intuition. The claim that they are investing in the management team is another way of saying they are selecting those leaders who feel like rock stars; who they think look like a star. They are basing it on measurable that they feel are important but have not proven empirically are the keys to success (just as baseball executives undervalued walks and over-valued defense).

Correlation Ventures, the Billy Beane of VC

A recent article in Forbes, “Venture By Numbers,” shows this situation is changing. Correlation Ventures started in 2011 with the philosophy to bring a quant-based approach to venture investing. Their mission was to stockpile 25 years of data on every venture deal consummated, evaluate this data with proprietary algorithms and then pick investments via pattern-matching software. Continue reading “Moneyball finally comes to VC”

Lifetime Value Part 10: Incorporating qualitative data into your LTV predictions and game development

Most of my posts about the reasons and methodology for creating accurate customer lifetime value (LTV) predictions have focused on the numbers and metrics, but a key element to predicting accurately LTV is observational (qualitative) data. It all comes down to more data is better, so predictions with qualitative data are going to be more accurate than those that rely solely on quantitative data. A mistake that is commonly made in the analytics world, and particularly in gaming, is to disregard anything that is not a quantitative value.

Some examples of incorporating effectively qualitative data

The example that had the most impact on me is that Billy Beane and the Oakland A’s, the subject of Moneyball (and multiple blog posts by me), has one of the highest scouting budgets in baseball. Scouts provide data on variables, like mental make-up and desire to win, that are not evident in the historical metrics. So although Beane makes personnel decisions based on metrics, he has also invested large sums in getting qualitative data (scouts watch players and prospects and then report on how they perceive the player’s skills). This approach has proven successful, as Beane’s A’s again surprised people by winning their division last year. What Beane has mastered is finding a way to incorporate the scouting reports with the available quantitative metrics. Continue reading “Lifetime Value Part 10: Incorporating qualitative data into your LTV predictions and game development”

Great books for social game companies

I have hesitated in publishing a “reading list” because often when I see them on other blogs, they are little more than the author’s effort to get some referral income. As many of you know, I do not monetize this blog at all (there is no advertising and I have refused all sponsorship offers) and the links in this post are not tied to any monetization. With that in mind, I wanted to share some books that have made me much more successful and I think will help anyone in the gaming ecosystem (and probably any other business). Given that we all have very limited time, even to read, I have listed the books by how much of an impact they have had for me. Continue reading “Great books for social game companies”

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Moneyball and The Innovator’s Dilemma

You already are ignorant—accept it

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Moneyball and the venture community

Correlation Ventures, the Billy Beane of VC

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Some examples of incorporating effectively qualitative data

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Runs = LTV

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Silver and Moneyball

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