The Nelson Touch Blog: Team Incentives and the Free Rider Problem

Team incentives, where an individual’s compensation is based on the team’s performance, are notoriously difficult to implement. Yet more and more work in companies large and small is being done through formal or informal teams. What do we need to know in order to design better team incentives?




Standard economic theory is a good place to start (though it will not provide all the answers). Economic theory assumes that people prefer leisure to work and are self-interested. Team incentives therefore fall victim to the “free rider” problem.

If all team members are rewarded for the team’s output, then there is little incentive for a self-interested, leisure-seeker to contribute toward the team goals. Since the “shirker” cannot be excluded from the reward, he becomes a free rider – enjoying the rewards without adding any effort. Game theory predicts that all team members look around and decide that their best strategy is not to work either, so the team ends up not working at all. The group incentive has led to a completely undesirable result.

Of course, this is a rather extreme portrayal, but it drives home the point and illustrates why any good compensation professional will tell you “be careful what you pay for.” There are a few ways of dealing with the free rider problem.

The simplest solution is to introduce a way of monitoring effort so that you share in the reward only if there is evidence that you have worked hard enough or well enough. This is what performance management is all about. The monitoring can be done by the firm (e.g., the manager) or by other members of the team. The latter is only practical if the team is small and each member’s effort is observable and measurable.

The situation can be saved if there is repeated interaction among the team members. If there are multiple opportunities for the team to work together for a reward in the future, then team members will be more likely to co-operate in the current project and work.  If they don’t, they may lose future earning opportunities. There may be reputational consequences for poor individual effort. This works out well if teams are formal (i.e., not ad hoc and one-time) and long-lived.

Another dimension to this is if there are social sanctions available. Groups that work together might also “play” together – i.e., have relationships beyond the confines of the team situation. Members can put pressure on team-mates to shape up or ship out.

When team members are close-knit, they internalize each others’ welfare. This builds a positive, co-operative, stable equilibrium. This approach jibes with Jon Katzenbach’s observation of high-performing teams (what he calls “real teams”): that team members become invested in each others’ development and well-being.

Given the above discussion, we can say that the factors that influence whether team incentives will work or not include team longevity, size and composition.

The longer a team stays together, the more powerful the measures of peer pressure, social sanction and internalized welfare.

The larger the team gets, the less members are able to monitor each other, reach a collusive equilibrium, exert social sanctions or internalize each others’ welfare. Other, external factors will play a more prominent role. Also, there will be fewer opportunities to measure relative performance since there will be fewer similar teams for comparison.

Team composition is an important factor. Allowing teams to form autonomously has risks: the team may play well internally but may not play well with other teams. On the other hand, teams of like-minded individuals who have self-selected into the team knowing who they will be working with are likely to perform better. Heterogeneity in team composition is a good thing and is supported by Katzenbach’s notion of complementary skills.

So what is to be done with respect to team incentives? You clearly have to be very careful to avoid the free rider problem. Ownership can play a large role, as can other ways to build and sustain high commitment to a team’s objectives. Even though everyone is not the perfectly rational economic agent that economic theory assumes, you still need to model the game-theoretic or strategic outcomes in order to thwart team members’ efforts at “gaming” the team incentive.

Quota Restriction and Goldbricking in a Machine Shop

 

gold·brick (gldbrk) Slang
n. A person, especially a soldier, who avoids assigned duties or work; a shirker.
v. gold·bricked, gold·brick·ing, gold·bricks
v.intr. To shirk one's assigned duties or responsibilities.
v.tr. To cheat; swindle. -- Goldbrickers definition from Free Dictionary

I came across a mention of Donald Roy's article in James Surowiecki's The Wisdom of Crowds and so I went online to do some research.
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A first-hand account of the behavioral response to monetary incentives.

by Donald Roy, American Journal of Sociology, 1952

From an article by Roger Martin on Monetary Incentives:

Donald Roy’s machine shop was a classic piece-work shop of its day. Its machine tool operators fabricated a wide variety of items at their stations, with each assigned a point value based on management’s assessment of the level of difficulty required to produce the item, as assessed by engineers from the ‘timing department’. If an operator turned in 125 points in an hour, he (all were male) would earn $1.25 for that hour of work.

The company provided the operators with base pay of $0.85 per hour, such that if the points they turned in were lower than 85, they would still earn the minimum amount. For anything over 85 points per hour, the direct monetary incentive was that one more point generated one more cent in hourly compensation.

Roy observed that the incentives embedded in the compensation structure generated behaviours that at first seemed quite odd. The largest fraction of work turned in (47 per cent of total hours) was for point totals between 115 and 134.The second largest fraction (24 per cent) was between 35 and 54 points. Every other range had tiny proportions of the total hours (see Exhibit One).

What caused these two high-frequency ranges at such odd levels? It turns out that amongst the workers, jobs associated with these ranges were referred to as ‘gravy’ and ‘stinker’, respectively.‘Stinker jobs’ were so difficult – i.e. their point totals were too low in relation to the work required – that the operator declared defeat immediately and slacked off – or ‘goldbricked’ to use the vernacular. But why not goldbrick entirely, not turn in 35 to 54 points?

As Roy found out, any operator who turned in less than 35 to 54 points in an hour risked being fired for incompetence. So the extreme of goldbricking was in the range of 35-54 points per hour, which netted the basic $0.85 compensation.

In contrast, ‘gravy jobs’ were so easy in relation to their point values that the minimum could be reached with only a modicum of effort. But why stop at accumulating 134 points per hour?

Roy found out – by himself hitting 150 on a gravy job and being accosted by angry coworkers – that whenever a job yielded more than about 134 points per hour, the timing department would descend on the shop and lower – often dramatically – the point value for the job. So while the monetary incentive to keep working until accumulating 134 points was high, the monetary disincentive to go even a point past 134 was even higher. As a result, the operators engaged in ‘quota restriction’, by which they would work at an artificially slow pace or loaf for hours at a time to restrict themselves from turning in a point total over the informal maximum.

Exhibit One overlays the true compensation structure – including threat of termination below 35 points per hour and threatened re-timing above 134 points per hour – on the distribution of work to demonstrate the power of monetary incentives to drive behaviour patterns that appear inexplicable at first blush. Roy estimated that goldbricking and quota restriction – which, within a month of joining the shop, he engaged in as dutifully as his co-workers – caused the machine shop to work at approximately half of its potential productivity, all a direct function of the structure of the monetary incentives.”

 


How could the managers do better? (I assume that removing the guaranteed payout is not an option due to minimum wage laws.) A lot of the problem comes from the fact that the managers don’t commit to the piece rates. Committing to piece rates for the gravy jobs would solve the incentive problem on the upper end, even though it might result in overly generous compensation, but what about the lower end?

One option would be to commit to only revise piece rates upwards, not downwards. (Note that you would effectively get a real piece rate decrease by not changing the point value if there is inflation.) But even that is not really ideal, since the managers don’t know what the “correct” piece rate is in the first place.

That last statement is actually the crux of the problem. How on earth are managers supposed to get an objective measure of how long things take or how hard they are? This is where thinking about the incentives of others becomes so important. You don’t want to ask current employees to be the guinea pigs for timing the tasks, since they have an incentive to make the tasks seem like they take longer than they actually do.

It’s hard (read, expensive) to bring in random people off of the street to time the tasks, since you would need to train them to do the job all the while having them know that they would not be employed by the firm in the long term.

Economists refer to incentives where people can’t game the system as “strategy-proof.” Is there a strategy-proof incentive that could be offered in this case?

Dilbert and Wally do the Goldbricker's Celebration Dance.

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