FINESSE: Fair Incentives for Enterprise Employees

Service enterprises typically motivate their employees by providing incentives in addition to their basic salary. Generally speaking, an incentive scheme should reflect the enterprise wide objectives, e.g., maximize productivity, ensure fairness etc. Often times, after an incentive scheme is rolled out, non-intuitive outcomes (e.g., low performers getting high incentives) may become visible, which are undesired for an organization. A poorly designed incentive mechanism can hurt the operations of a service business in many ways including: (a) de-motivating the top performers from delivering high volume and high quality of work, (b) allowing the mid-performers not to push themselves to the limit that they can deliver, and (c) potentially increasing the number of low performers and thereby, reducing the profit of the organization. This paper describes FINESSE, a systematic framework to evaluate the fairness of a given incentive scheme. Such fairness is quantified in terms of the employee ordering with respect to a notion of employee utility, as captured through disparate key performance indicators (KPIs, e.g., work duration, work quality). Our approach uses a multi-objective formulation via Pareto optimal front generation followed by front refinement with domain specific constraints. We evaluate FINESSE by comparing two candidate incentive schemes: (a) an operational scheme that is known for non-intuitive disbursements, and (b) a contender scheme that is aimed at filling the gaps of the operational scheme. Using real anonymized dataset from a BPO services business, we show that FINESSE is effectively able to distinguish between the fairness (or lack thereof) of the two schemes across a set of metrics. Finally, we build and demonstrate a prototype dashboard that implements FINESSE and can be used by the business leaders in practice.