Sales development and performance management of key accounts portfolio through data-driven model

Abstract

This report summarizes an external consultancy project conducted by the Vlerick group at the CSI department at the DHL headquarters in Bonn, Germany. DHL Group provides an international service portfolio in the areas of express delivery, freight transport, supply chain management, e-commerce solutions, and letter and parcel dispatch. CSI is DHL's commercial and innovation unit that works across departments to develop new products and services for the DHL group. The unit is responsible for managing about 100 of DHL's largest and most important customers on behalf of all of DHL's business units. The main goal of this project is built on last year's project and is mainly to increase the effectiveness of the whole process, with the primary goal of increasing the efficiency and accuracy of the nominated customer's selection for the CSI portfolio. This goal is translated into the following objectives: Update the annual financial figures of the CSI customer portfolio. Research the new set of customers that have been added since last year. Improve and enhance the analytical framework that is used by DHL to evaluate the potential fit of any DHL customer to be nominated and included in the CSI top customers Portfolio. Redesign the visualization tools in the dashboard to increase usability and make it readable for non-data experts. The Vlerick team successfully completed the project's objectives by firstly: researching and collecting the financial figures of the CSI portfolio customers, using the customer's annual reports, financial statements, and analyst reports. By accomplishing this, the team managed to build the foundational data needed to achieve the remaining objectives. Secondly, the team re-evaluated the Key Performance Indicators (KPIs) and their weights executed through both primary and secondary data. Literature research on academic studies and industry data sets, as well as interviews with industry experts and constant collaboration with the CSI unit management and analysts. Therefore, the team recommends the following: 1. Discarding three different KPIs from the model. After a comprehensive analysis of these 3 KPIs and consultation with account strategists, the team came to a conclusion that there is no added value to the model but instead spread of the weights, which results in lowered accuracy. Re-consider the weighting of the KPIs, which is based on subjective conclusions. Instead, the team recommends the usage of the level-based weight assessment (LBWA). The weights of the KPIs in the current model were not empirically verified, which negatively impacted the accuracy of the model. Consequently, the team resolved the issue by applying a data-based framework to determine the weight coefficients of each KPI. Usage of the visualization tools developed by the team to increase usability and make the dashboard user-friendly. By applying these recommendations, the goal of this project is accomplished, which was to increase the effectiveness of the whole process by increasing the efficiency and accuracy of the potential CSI Customer Attractiveness Model.