Download Can incentives improve labor scheduling decisions Evidence from a

Can incentives improve labor scheduling decisions?
Evidence from a quasi-experiment
More than ever, brick-and-mortar retailers are now facing enormous competitive pressures from their
online peers. The cost structure of brick-and-mortar retailers driven by store-related expenses is an
important contributor to this challenge. Of the different store-related expenses, labor-related costs are one
of the largest (Ton 2009). For example, Kesavan et al. (2014) find that store labor costs account for over
85% of controllable expense for the retailer in their study. In attempts to curtail labor expenses, many
retailers appear to go too far as there are numerous anecdotes of understaffed stores leading to dissatisfied
customers. For example, understaffed Wal-Mart stores resulted in empty shelves causing customers drift
to its competitors such as Target and Costco, leading to over $3 billion of lost sales (Dudley 2014). It is
not surprising, therefore, that retailers spend considerable effort to ensure that they have the right amount
of labor in the store.
In order to have the right amount of labor in the store, it is vital to have accurate sales forecasts,
schedule associates appropriately, and execute to the plan. To aid store managers with these tasks,
retailers have begun investing significantly in technology that helps in forecasting and labor scheduling.
According to the recent report (Marketsandmarkets.com 2015), the global market of workforce
management solutions is estimated to grow from $4.9 billion in 2015 to $7.7 billion by 2020. Even with
such large investments, the role of the store manager in making labor decisions is not diminished as these
software decisions may potentially be improved by store managers. As a consequence, the key challenge
to retailers is to find ways to motivate store managers to expend the effort to make the right decisions.
One commonly employed method is to tie store managers’ compensation to store sales and profits (van
Donselaar et al. 2010). So far, it is unclear whether these incentives lead to better labor decisions in retail
stores. More importantly, it is unclear whether stronger incentives have differential impact on forecasting,
scheduling and execution decisions of store managers.
Over the past several decades, the role of incentives in improving performance has been widely
debated. On the one hand, theoretical literature on agency theory, expectancy theory, and goal-setting
theory argue that incentives make agents to exert more effort and thus to improve performance (Bonner
and Sprinkle 2002). These theoretical predictions have been validated by empirical research in economics,
accounting, and marketing which have demonstrated that financial incentives improve performance due to
increase in effort as well as selection mechanism (for example, Lazear 2000). On the other hand,
psychologists and behaviorists have provided a contrary viewpoint. Based on a meta-analysis of over one
hundred experimental studies, Deci et al. (1999) conclude that in most instances extrinsic rewards have a
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negative effect on intrinsic motivation. More importantly, the impact of incentives on performance
depends upon the type of tasks (Libby and Lipe 1992). For example, forecasting accuracy is not found to
improve with incentives (Remus et al. 1998). Despite the large empirical research around pay-forperformance in other streams, we are unaware of empirical research in operations management that has
examined the role of financial incentives on improving operational decisions.
In this paper, we examine if incentives are effective in improving labor decisions using a quasiexperimental setting at a retailer that changed its incentive plan for store managers from strong financial
incentives to meeting labor budget to almost zero financial incentives to meeting labor budget. The labor
budget was calculated based on the actual sales. Using weekly sales (actual and forecasts from manager,
financial plan, and software) and labor (actual, scheduled, and budget) data for 75 stores over 47 weeks,
we test whether introduction of new weakened financial plan is associated with worsening of forecast
accuracy, labor scheduling, and execution decisions.
Our primary findings are as follows. First, we find that store managers make more accurate labor
decisions under the strong incentive scheme, indicating that incentives for store managers indeed help
improve labor scheduling decisions. The total error in labor decision, measured by absolute percentage
deviation between actual labor and labor budget, is 6.8% larger under the weak incentive scheme
compared to the strong incentive scheme period. This is a substantial difference as the average total error
in labor decisions is 5.3% in our data. So, the weak incentives have resulted in over 100% worsening of
labor decisions by managers. Similar to economics literature that has found huge impact of incentive on
productivity (see survey in Prendergast 1999), we find that financial incentive significantly affects store
managers’ labor decisions.
Second, we find that the impact of financial incentives on labor decision occurs mainly due to
effort effect instead of selection mechanism. By considering stores without change in managers during
study period, the total error in labor decision is 6.18% larger under the weak incentive scheme. This result
is comparable to the prior literature (Lazear 2000; Banker et al. 2000) where studies the impact of
incentive on individual workers’ productivity and reports significant effect of sorting mechanism in
addition to effort effect. By showing that labor decisions become worse-off due to decreasing effort, our
results demonstrate that incentives play a vital role in making managers exert more effort in the content of
labor decisions.
Third, we find that the effect of financial incentives on labor decision is mainly driven by effort
on scheduling and execution, but not forecasting. The scheduling error, measured by absolute percentage
deviation between scheduled labor and labor budget, is 4.64% larger under the weak incentive scheme.
Comparing to 5.11% of the average scheduling error, this result shows that weakening incentives have
resulted in significant (above 90%) worse-off on scheduling decisions. Using econometrics technique, we
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quantify that the weak incentive has resulted in reducing one type of execution effort on adjusting in the
last mile according to new information either about demand or associates’ availability by 31.58%. On the
contrary, consistent with prior literature in the lab setting (Remus et al. 1998), there was no evidence that
incentives improve manager adjusted sales forecast as managers tend to go with the system forecast. Our
results show that financial incentives have differential impact on forecasting, scheduling and execution
decisions of store managers as each task may require different types of effort and have different
sensitivity to effort (Libby and Lipe 1992). Retailers may benefit by taking them into account when they
design incentives.
References
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