Every person who takes a salary to tell governments and organizations how they ought to best allocate scarce resources to make this world a better place needs to sign up for fantasy football. It will teach one humility, and open one’s mind to the possibility that the world is not as predictable as any group of experts is.
Given any group of “Experts” on any subject, you will find they usually reach a consensus opinion with greater frequency than nature does. (Example: “If you can flip a coin, can you be an expert?” on HuffPost)
Top 5 reasons aid experts should play fantasy football:
- The winner will not be the player with the most knowledge, nor will it be the one who spends the most time deliberating among choices. These things help, but the complexity of the real world will always play a much bigger role in the outcome than people expect.
- The winner will not be the one with the best players. The corollary to this rule is the Madden Curse. Literally, every year since 2000, EA’s Madden Football has picked the best player by expert consensus to put on the game cover. And each year that player has ended up with a career altering injury or similar misfortune, making them an all-around fantasy football liability.
- The winner will not be the player who is chasing last week’s superstar. From week to week, there are always obscure semi-superstar standout players who excel. And each week, one of the fantasy league’s players invariably picks these guys up and starts them, only to be disappointed. By week three, this player has dropped last week’s flavor on favor of the next player. Chasing trends in fantasy football is just like chasing trends in the stock market; it if worked, we’d be rich.
- The winner will make at least one significant gutsy call against the trend. There has never been a week without upsets, nor a season where the best teams in August met in the January Super Bowl. In the last 2 seasons these were my risky moves, and my rationale:
- Grabbed Deion Branch – the week he moved from Seattle back to the Patriots, I predicted he would go from a non-factor to a #2 receiver. (Correct!)
- Grabbed Cam Newton – after week 1, we was still untested and therefor free. I thought I was done for the year because I had Peyton Manning (who suddenly was seriously injured the day after my draft and gone for months), but now I had nothing to lose by picking up Cam Newton. Since then Cam has become the #2 overall passing quarterback in 2011 over Week 1 and 2. (Not sure if starting him will win my league, but guessing it will)
- Grabbed Greg Olsen – he was a great player in a Mike Martz Bears offense that did not use Tight Ends. By moving to Carolina (opposite Jeremy Shockey) in an offense that features the Tight End, I predict we will be an all-pro tight end.
- Grabbed Cadillac Williams (Week 2)- he was suddenly the #1 running back because a real star was injured. Not sure if he will be huge, but he was value left behind by a changing game environment.
- (#5): The winner will recognize the constantly changing game environment, and use this to his advantage. More than anything else, Fantasy Football is a prediction game set against a complex and dynamic game environment. The situations that form the basis for previous assumptions change, and therefore the predictions must also change.
Breaking down the parallels with international aid work:
Expertise isn’t everything (reason #1):
Knowledge is power, but power is not work. Knowledge is only part of the equation that yields success. To assume that one can “deliberate” his way into a kind of wisdom that is only found through repeated experimentation (and a bit of failure) is folly. What I embrace is “successful failure” – where risky moves are structured around systems that will definitively yield better knowledge for the next round. To guess and not learn is the worst form of incompetence. In contrast, doing something and not knowing whether it will work, but knowing that the experiment will yield such knowledge, is the closest form of “do-gooding” we have to actual science.
Capacity isn’t everything (reason #2):
Replace “best players” with “best funded organizations” or “most valuable experts” in the Fantasy Football analogy and you have a very important life lesson: It ain’t what you got, it’s how you use it! If organizational capacity was all that mattered, then impact would flow mostly from the biggest organizations with the most resources, and governments would be having the biggest positive impact of all. More lives are changed by some good people and good ideas that spread beyond what money can do. Likewise, some of this year’s Fantasy Leaders will be people you’ve never heard of (yet).
Thoughtfulness is everything (reason #3):
“Buzz chasing” and working from a rigid worldview might seem like opposite problems, but both are forms of the same problem. In both cases organizations are making decisions (either to embrace or reject something new) through a lack of thoughtfulness. Thoughtful organizations are curious organizations that continued to push, never settling, determined to improve things when the reasons to act are there. I had a clear reason for each of my fantasy changes – and typically a change in the game environment warranted the decision.
Yet thoughtfulness can be overdone in development. Log frames attempt to reduce thoughtfulness to a series of logical syllogisms when we operate in a complex non-logical world. Hence log frames become a replacement for real thoughtfulness, a crutch no better than listening to ESPN Fantasy experts tell you which moves to make.
Consistency of action should go hand in hand with thoughtfulness, and yet consistency is absent most of the time in funding agencies! Case in point: During fundraising workshops for GlobalGiving, I ask for a show of hands of orgs who have (a) written grant proposals, (b) been awarded a grant, and (c) received grant funding for at least 3 consecutive years from the same funding organization. The results are 90%, 15%, and 5% for (a), (b), and (c) respectively. So nearly everyone is asking for money, a few are getting it, and nobody is being given much time to change the world.
Even in Fantasy Football, coaches give players a larger portion of their short careers to prove themselves than NGOs are given by grantmakers.
By the numbers: The average NFL contract is 3 years. The average NFL career is 8. Two thirds of players ultimately succeed within the first 4 years of a career. So nearly all players have a chance to reach their potential, if they remain healthy.
If the typical intervention to solve a complex social problem requires 10 years to succeed, then 95% of grants out there are investing in less than a quarter of a solution.
Risk aversion is killing development (reason #4):
Organizations are afraid of taking risks, because they don’t look for ways to structure those risks into learning. Microloans are no longer risky because somebody came up with a way to structure these risks. So what risks are people not taking? Organizations rarely trust communities they serve enough to give them real control of the projects, like giving them funds to spend as they choose. Governments could test direct democracy, using SMS to let voters determine tax rates and budgets for agencies, but they don’t. Game theory will one day prevent “gaming” of these direct democracy methods, but we’ve got decades of denial to trudge through before governments admit they have a problem here. NGOs rarely give worthy individuals “do some good” grants with no strings attached. We accept the reality that 80% of small businesses fail in a capitalist economy, but fear that 50% of our interventions to alleviate poverty might fail. (Yet if every failed business owner walks away with a lot more knowledge on how to succeed, capitalism isn’t really failing 80% of the time in the long run. However, communities are rarely given this same power to fail (or succeed) that business owners are given. That’s risk aversion in the extreme, and exactly why the conservative approach creates a systemic failure in the long run).
And while I’m on this point, Randomized Controlled Trials in development are not risky. They’re extremely conservative. That’s why the FDA relies on them exclusively to determine what’s healthy for the public. But drug companies DON’T rely on RCTs – they use rapid drug screening of thousands of candidates and miss some miracle drugs, but cheaply and quickly find just as many strong candidate drugs to test by more conservative means. Local NGOs are like the “drug companies” of development, and must take risks to solve problems that are eating at the fabric of society. If science was as conservative as international development (and the NSF/NIH grantmaking process in particular), we would have 19th century medicine, no internet, no space flight, and a million other things that are built on risky investments in unproven scientific ideas. Luckily they’re not. I’d predict that NIH grant committees would decimate World Bank economists in a head-to-head fantasy football match-up. (Side note: both agencies have about the same size budget, but no one question’s the NIH’s massive contribution to health and quality of life.)
In Fantasy Football, the draft equalizes each fantasy player’s resources, and the only way to win is to take risks. Are NGOs so resource-rich that they do not need to take similar risks in order to derive at a “game changing” solution or innovation?
Complex Environment (reason #5):
Those organizations that are trying to work off predictions and models of the future too often fail to understand the complex environment in which those solutions will play out. Bill Belicheck’s offense under Tom Brady’s control is a model of near-perfection. And yet should one or two key players get injured, or a freak mistake cause a fumble, turnover, and touchdown, any team could beat them – even Kansas City – in 2011. How much more complex and deserving of a flexible prediction model do you think real-world poverty alleviation programs must be to work?
I, for one, want to find out. That’s why I’m trying to figure out what a “flexible prediction model” looks like – using 20,000 stories from East Africa as a starting point.
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