I Talk Wed. At Harvard

Next Wednesday I’ll talk at Harvard business school on “Toward Information Accounting“:

What gets measured, gets done. Today, organizations account in great detail for revenue and the costs of materials and time, but have only crude informal accounting of info contributed to key organizational decisions. Because info cost and value are poorly measured, info production is neglected.

Can we use prediction markets to do better? Imagine speculative betting markets on many key organizational questions, and two key changes in business practice. First, let the division responsible for each decision declare lower-bound estimates of the value of more info on each related question. A division might, for example, declare that 1% lower error in estimating 3rd quarter sales of product X is worth at least $5000. There are standard ways to calculate such info value in specialized situations, such as inventory management.

Second, let trader accounts be denominated in a new “color of money.” Instead of doing zerosum betting, the market for each question would be subsidized at a level matching its declared info value. As a result, the subsidy amounts lost to traders as prices become more accurate would on average correspond to that question’s declared info value. For example, on 3rd quarter sales of product X, its 0.7% lower error might have earned a $3500 subsidy, going to George who gained $2000, Sue who gained $1500, Sam who gained $1000, and Fred who lost $1000.

Given these two new practices, trader account gains could be interpreted as noisy estimates of the info value those accounts transmitted via their trades. Losses could be interpreted as info destruction. Simple statistics applied to the pattern of changes in an account over time could estimate its consistent gains, amid its temporary fluctuations. The total consistent gains for the accounts of a division could be credited to that division in its ordinary cost accounting, while that same amount is debited from the divisions who declared info value on those questions.

When one created an account with an initial cash deposit, and authorized an individual or team to trade that account on specific questions, one would in essence say: “Try to show us that you can consistently add info value here via your trades. We’ve started you out small, but if you can show consistent gains we may give you more to work with. At annual review time we’ll credit your account’s consistent gains (or losses) to you (and your division) as value you transmitted to this organization, to be compared with your time and other costs of participation.”

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  • Robert Eaton

    Hi Robin: I live in the Boston area; will your talk be open to the public?

  • Rick

    Robin, I’m interested in hearing more about this idea. I work for a large management consulting firm and I have often thought about how to quantify value-add in terms of input and strategy provided.

    If the discussion is being recorded, please post a link once it has been uploaded.

  • trader

    Isn’t there already similar prediction markets? If you think that this company makes poorer decisions than a competing one, you change jobs.

    • what a weak comment.

      Seems like a great place for you to give a talk. I encourage you to work in some thoughts on managing against existential risk.

  • Buck Farmer

    Cool idea. I’d love to get it implemented. Distorted information flows within orgs bother me to no end.

  • RJB

    If I were attending I’d have two questions:

    1. Is trading profit the best measure of information provided to help decision-making. If I am the only one with a crucial piece of information, I maximize my profit by trading in a way that impounds my information into price as slowly and incompletely as possible. If the goal is to reward people who provide information, rather than simply to get the best information aggregator, wouldn’t it make more sense to use a different type of incentive in the market, or a different device (such as a delphi process)?

    2. Are you assuming that the value of the incentive for prediction-market gains (however calculated) is very small relative to the incentive for better managerial decision-making and outcomes. If not, what unintended consequences should we worry about? For example, would managers conceal information from their colleagues in order to increase the trading value of their information, to the detriment of making decision-making?