Fantasy Football: The Template for Effective CPM & BI
By Denis McFarlane, Chief Executive Officer
Best Practices in Action
It’s that time of year again. Tens of millions of fantasy football players around the country are eagerly preparing for their drafts and indulging annual preseason dreams of beating their buddies and securing bragging rights.
Winning at this complex, data-driven game requires visibility into an incredible range and volume of data – offensive and defensive statistics for all the NFL teams and hundreds of individual players. However, compared to their counterparts in business, fantasy football players aren’t likely to drown in data. Why? Because they have the powerful tools, reliable infrastructure and high-quality data they need to make good decisions and optimize performance.
In fact, anybody interested in corporate performance management (CPM) and business intelligence (BI) best practices should take up fantasy football as a hobby, or at least spend some time on the leading fantasy sports sites. The depth, breadth and granularity of information are truly impressive. But what’s most amazing is what you can do with data –manipulate it to test strategies, run scenarios and gauge the competition. The bottom line is that fantasy football sites fulfill the grand promises of CPM and BI. That is, users can quickly and easily predict performance using fundamental, bottom-line metrics, but also gain extra ad-hoc insight into valuable measures and information as they devise strategies and make real-time tactical adjustments.
Data You Want, When You Want It
Using any number of popular Web sites, owners of fantasy football teams can rate NFL players across scores of statistical categories ranging from the traditional (rushing yards, passing yards, touchdowns) to the obscure (quarterback efficiency, passes defensed, hurries). Fantasy teams in a league compete based on these statistical categories, acquiring points for rankings or going "head-to-head" with another team each week in a simulated game (much like in "real" football).
Further, depending on league rules and formats, they can find the players (both superstars and journeymen) who are most likely to help them score bonus points for making relatively rare plays (50+ yard runs, 40-49 yard FGs made, blocked punts). If it happens in an NFL game, these sites can measure the outcomes and translate them into scoring categories.
Once the season starts, you can track your team’s performance in day games vs. night games, home vs. away, variance against league averages, and so on. You can compare current vs. historical, and actual vs. forecasted, and project performance for the entire season. Updates from the "real" world (e.g., game-time weather forecasts and injury reports) are also useful for last-minute tweaks to starting line-ups. "BOOM" (as John Madden would say), a few clicks and it’s all right there.
All of the information is extraordinarily well organized in easily digestible formats; it is current (usually up-to-the-minute) and, most importantly, easily accessible. Players can get the information whenever and wherever they want – even on cell phones. It is no wonder that fantasy football geeks spend so much of their free time (and some considerable work time, too) immersing themselves in terabytes of data and obsessing over seemingly minor metrics.
Fantasy vs. Reality
Now compare that situation to the decision support challenges faced by typical C-level executives or line managers. Let's say you want to compare supply chain data from last quarter with historical levels, and cross-reference it with marketing or sales data. At many companies, it's not a matter of how many clicks it takes to find the data, but rather of how many days or weeks. First, you have to call and email around the company to find out if the data exists. Then there's the laborious task of accessing some dusty old database. You might be forced to learn some ancient, custom-developed application.
Or maybe, if you're lucky, somebody at the company has a huge Excel document with dozens of nested worksheets that has just the data you want. Assuming all the formulas are accurate, all you have to do is scan across hundreds of tables to find the handful of data points you need to contextualize a decision with cross-functional implications.
Of course, some people have all the data they need (and then some), but lack consensus or clarity about which big-picture metrics are best to track overall performance. Or, there's disagreement about the meaning of metrics or the best data sources – the classic "one version of the truth" problem. Or, it's impossible to access tactical data points to make targeted decisions within the necessary timeframes.
The point is, many information-age executives must make decisions without good information. And these decisions are a heck of a lot more important than choosing running backs.
Doing Something with the Data
The richness, availability and effective organization of fantasy football data are all great, but it’s what can be done with the information – the "actionability" – that’s likely to make business executives jealous of fantasy football players. On a broad level, leagues can mix and match different measures to create custom formats and their own scoring criteria. Individual users can easily modify their view of the data to frame specific strategic or tactical issues – deciding which categories to compete in, assessing competitors’ weaknesses, making trade offers, or choosing the best free agent to replace an injured or underperforming player. And you can make these decisions with confidence in your data.
While some fundamental metrics don’t change, gaining extra visibility into more subtle or nuanced data (like composite measures of "quarterback efficiency," a key, but constantly evolving metric.) gives the little edge that fantasy football players (just like their counterparts in business) are looking for as they build and manage their teams. It’s not just individual data points that matter, but rather how they interrelate and potentially impact the big picture (like points scored or return on invested capital).
As for setting the metrics, many large enterprises struggle to agree on KPIs to measure overall performance. Even if different lines of business or functions reach consensus on the best way to track performance, they may not have the data they need to track them. So they end up evaluating performance and making decisions based on whatever data they can capture and get into a report in time for the next board or executive committee meeting. Here again, the fantasy world, with its "build-your-own" tools and hybrid metrics, offers a better BI/CPM model.
The Edge of Insight
Everybody has the same data, but that extra bit of visibility or insight that comes through the modeling and cross-referencing can be a real difference maker. To reach those insights while there’s still time left in the game (or quarter or fiscal year) to impact results, you need effective tools, an agile architecture and the right data flows. While nearly all fantasy football sites have those capabilities, many companies simply do not.
Lots of companies can capture and distribute basic data, but very rare are those that can synthesize different types of information to project the impact of various scenarios, analyze past performance, or spot emerging trends. You know that sales have been up, down and flat the last three quarters – but why? Which macroeconomic, regulatory or competitive factors were involved? What will happen next quarter and beyond? And what’s more likely to work – more staff, discounts or new marketing? In solving such riddles, the fantasy sports community is far ahead of the reality-based business community.
If you think I’m straining the analogy, consider that the appeal of fantasy football rests largely in its similarity to running a business; competitors operate in a world of finite resources and the winners are usually those that spot opportunities in the broad market (league), most effectively allocate capital and deploy resources, and determine the few categories (strategic sourcing, say, or rushing yards) that matter the most. Just like in business, management boils down to understanding a universe of choices, analyzing all the relevant data, and then choosing investments (technology upgrades, R&D or a new quarterback) that deliver maximum value.
The Bottom Line: Information Helps, But is No Guarantee
Just because you have high-quality and well-organized information at your fingertips doesn't mean you automatically make good decisions. Plenty of fantasy footballers make moves based on emotions or play hunches not supported by the data right in front of them. But at least they have the information they need.
At a huge number of organizations, the data required to make objective, fact-based decisions simply isn't readily accessible. In an ideal world, executives could take full responsibility for their choices – all the credit or all the blame would be theirs, because they couldn't blame missing or faulty data. Most executives I know would love to be in this situation, which would put them on par with your average fantasy sports geek.
