Optimizing Commercial Teams and Territory Design Using a Mathematical Model Based on Clients’ Values: A Case Study in Canada

Ana Miguel Carvalho (), Cristina Lopes (), Manuel Cruz (), Jorge Santos, Sandra Ramos, Filipa Vieira and Pedro Louro
Additional contact information
Ana Miguel Carvalho: Nors Group, S.A., 4149-010 Porto, Portugal
Cristina Lopes: LEMA, ISEP, Polytechnic of Porto, rua Dr. António Bernardino de Almeida, 4249-015 Porto, Portugal
Manuel Cruz: LEMA, ISEP, Polytechnic of Porto, rua Dr. António Bernardino de Almeida, 4249-015 Porto, Portugal
Jorge Santos: LEMA, ISEP, Polytechnic of Porto, rua Dr. António Bernardino de Almeida, 4249-015 Porto, Portugal
Sandra Ramos: LEMA, ISEP, Polytechnic of Porto, rua Dr. António Bernardino de Almeida, 4249-015 Porto, Portugal
Filipa Vieira: Nors Group, S.A., 4149-010 Porto, Portugal
Pedro Louro: Nors Group, S.A., 4149-010 Porto, Portugal

Mathematics, 2025, vol. 13, issue 18, 1-16

Abstract: This study, set in Nors Construction Equipment ST in Canada, addresses logistical challenges by enhancing commercial team evaluation and market sectorization. Traditional performance assessments relied only on sales, lacking other efficiency measures. This research proposes a mathematical function to combine diverse Key Performance Indicators (KPIs) to better evaluate team effectiveness. Additionally, it aims to optimize the sales territory assignment, improving resource allocation across Canada’s expansive, sparsely populated regions. Customer segmentation was conducted using the RFM model, classifying clients into Low-, Mid-, and High-Value groups based on purchasing behavior. For incorporating multiple KPIs in the evaluation of commercial teams’ performance, the Analytic Hierarchy Process (AHP) was used. Sectorization was modeled as a linear programming problem to minimize travel distances while ensuring compact sales territories. Constraints included balancing sales opportunities and customer types across assigned territories. As a result, the proposed optimization model significantly improves operational efficiency through better-balanced sales territories and reduced travel. Improved sectorization enhances market penetration and customer coverage, which is expected to lead to increased sales and support the company’s growth objectives. The mathematical models developed in this study allowed for a deeper understanding of the performance and provided management with tools to refine sales strategies and allocate resources more effectively. The article ends with a discussion on the possibility of ChatGPT being used to replace a mathematician in performing this analysis for the company. It was observed that ChatGPT (version GPT-4o) provided an extremely incomplete solution, evaluating the commercial teams solely based on profit and sales and not addressing the sectorization problem at hand.

Keywords: performance analysis; sectorization; modeling, simulation, and optimization; sales territories; machinery and construction equipment; linear programming model; analytic hierarchy process; customer segmentation; ChatGPT; AI (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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