Assessing the impact of operational performance improvement on business partners' profitability - the case of a luxury fashion e-commerce

The present dissertation proposes a model that translate an improvement of the fulfillment operations performance of Farfetch partners into a growth of their profitability. Farfetch itself does not have direct control of the order fulfillment process, so, having operational efficient partners is key for the long-term success of the company. The Fulfillment Development team, where the current project was developed, focuses on reducing the gap between Farfetch and the order fulfillment process, by providing free operational consulting services to its boutique partners. Many times, convincing these partners to engage on these projects may represent a difficult task as they may not understand how they can benefit from it. The described model, that did not exist before, addresses this issue to more easily convince partners to improve performance. Many are the variables that affect the partner’s profitability, but without having deep insight of each partner’s resources and structure it would be impossible to build a scalable model. Hence, the proposed model focuses on the two factors that Farfetch has visibility on: sales volume and Service 4.0. return. Initially, the boutiques were segmented into groups that have similar demand for their stock, by creating two segmentation variables to characterize each boutique’s stock. The two variables are: Value Score represents the attractiveness of the boutique’s stock in terms of value transacted; and Demand Score represents the demand generated by the boutique’s stock in terms of order volume. After obtaining such segments, benchmark techniques were applied on actually comparable parts, so one could identify the partner to benchmark for a poor operational performer boutique and understand how the improvement of the operational metrics could affect the orders’ growth. After understanding how a poor operational performer boutique could have performed, in the past, in terms of orders volume, matching the benchmark’s operational performance, a forecasting was applied to each boutique’s actual and obtained potential orders, creating the boutique’s baseline and potential orders. The difference between the two forecasts are the incremental orders due to an improvement of operational performance by the partner. Finally, the incremental orders were translated into profitability, in addition to the return obtained by the incentive service created by Farfetch Service 4.0. that was computed for both scenarios maintaining the same operational performance or improving to match the benchmark. The difference between each boutique’s baseline and potential revenues are the benefits due to the improvement of operational performance, resulting on model that estimates these incremental cash flows. The expected investment costs required by the boutique, to achieve such operational performance, are an input to obtain some financial metrics, such as ROI. Given the financial metrics, the boutique can then decide whether it is beneficial or not to engage on a consulting service provided by Farfetch to improve operational performance.