Course: Degree Project in Supply Chain Management, the Business Administration and Economics Programme, 4FE19E Authors: Matilda Engblom and Katarina Nyberg Supervisor: Arash Kordestani Examiner: Helena Forslund Title: Following the Recipe Brings Franchisees to the Table - A Case Study Consolidating Purchasing and Calculating Cost Savings at Franchisees Background: As a franchisor, Company X does not have insight or control in purchasing at their franchisees. Spend analysis is a tool used to identify current purchased volumes and costs. An aim with spend analysis is to decrease the cost and analyse the spend. There are four different types of consolidation that can consolidate the current purchased volumes and create purchasing cost savings. They are article, volume, supplier and transport consolidation. However, identifying the current situation can be hard in the franchise concept and therefore hard to create purchasing cost savings. It is therefore of need for the franchisor to have insight and control over their franchisees in purchasing. Purpose: The purpose of this study is mainly to identify how the current purchased volumes can be consolidated to create purchasing cost savings for the franchisees of Company X in the Middle East. In addition, calculate the purchasing cost savings that consolidation could lead to. As well as, investigate how a franchisor can regain insight and control in purchasing over their franchisees. Methodology: This case study had a mixed research strategy of explanatory sequential design. Empirical data was collected by both unstructured, semi-structured and structured interviews. The analytical methodology was based on pattern matching. Confidentiality has been of great focus during the study for ethical considerations. Conclusion: The current purchased volumes and costs were identified, enabling different types of consolidation and calculations for purchasing costs. The consolidation model (Figure 28, p. 43) illustrates four different types of consolidation, article, volume, supplier and transportation, which should be followed. Lastly, Table 38 (p. 85) presents actions for regaining insight and control over franchisees.

Uppsala municipality has set a goal in line with the UN’s 2030 Agenda for sustainable development to be fossil-free by 2030. To achieve this a lot of local companies have signed the Uppsala Climate Protocol. One of these companies is the municipal facility management company AB Uppsala Kommun Industrihus, Ihus. This project aimed to help Ihus map their emissions connected to facility maintenance and management and to enable them to reach their goal of becoming climate neutral by 2030.  The daily facility management was split up into the categories gardening, ventilation and installation, cleaning and facility work, materials and products, renovations, and painting. A sustainability spend analysis was performed on Ihus’ organisation and emissions per spent MSEK were calculated for each category by researching Ihus’ suppliers. By using those emission intensities, the two categories with the highest emissions could be identified as renovations and materials and products with intensities of 84.48 and 57.56 tonnes CO2e/MSEK, respectively. The remaining categories all had intensities below 3 tonnes CO2e/MSEK.  Sensitivity analyses were performed on the results by tweaking the values of which the emissions were based on. The results showed that to lessen Ihus’ climate impact the areas of improvement are life cycle assessments for their facilities and overseeing transports.

Artificial Intelligence technology has become increasingly important from a business perspective. In strategic sourcing, the technology has not been explored much. However, 67% of CPO:s in a survey showed that AI is one of their top priorities the next 10 years. AI can be used to identify patterns, predict prices and provide support in decision making. A qualitative case study has been performed in a strategic sourcing function at a large size global industrial company where the purpose has been to investigate how applicable AI is in the strategic sourcing process at The Case Company. In order to achieve the purpose of this study, it has been important to understand the strategic sourcing process and understand what AI technology is and what it is capable of in strategic sourcing. Based on the empirical data collection combined with literature, opportunities of applying AI in strategic sourcing have been identified and key areas for an implementation have been suggested. These include Forecasting, Spend Analysis & Savings Tracking, Supplier Risk Management, Supplier Identification & Selection, RFQ process, Negotiation process, Contract Management and Supplier Performance Management. These key areas have followed the framework identified in the literature study while identifying and adding new factors. It also seemed important to consider factors such as challenges and risks, readiness and maturity as well as factors that seems to be important to consider in order to enable an implementation. To assess how mature and ready the strategic sourcing function is for an implementation, some of the previous digital projects including AI technologies have been mapped and analysed. Based on the identified key areas of opportunities of applying AI, use cases and corresponding benefits of applying AI have been suggested. A guideline including important factors to consider if applying the technology has also been provided. However, it has been concluded that there might be beneficial to start with a smaller use case and then scale it up. Also as the strategic sourcing function has been establishing a spend analytics platform for the indirect team, there might be a good start to evaluate that project and then apply AI on top of the existing solution. Other factors to consider are ensuring data quality and security, align with top management as well as demonstrate the advantages AI can provide in terms of increased efficiency and cost savings. The entire strategic sourcing function should be involved in an AI project and the focus should not only be on technological aspect but also on soft factors including change management and working agile in order to successfully apply AI in strategic sourcing. / Artificiell Intelligens har blivit allt viktigare ur ett affärsperspektiv. När det gäller strategiskt inköp har tekniken inte undersökts lika mycket tidigare. Hursomhelst, 67% av alla tillfrågade CPO:er i en enkät ansåg att AI är en av deras topprioriteringar de kommande tio åren. AI kan exempelvis identifiera mönster, förutspå priser samt ge support inom beslutsfattning. En kvalitativ fallstudie har utförts i en strategisk inköpsfunktion hos ett globalt industriföretag där syftet har varit att undersöka hur tillämpbart AI är i strategiskt inköp hos Case-Företaget. För att uppnå syftet med denna studie har det varit viktigt att förstå vad den strategiska inköpsprocessen omfattas av samt vad AI-teknologi är och vad den är kapabel till inom strategiskt inköp. Därför har litteraturstudien gjorts för att undersöka hur man använt AI inom strategiskt inköp tidigare och vilka fördelar som finns. Baserat på empirisk datainsamling kombinerat med litteratur har nyckelområden för att applicera AI inom strategiskt inköp föreslagits inkluderat forecasting, spendanalys & besparingsspårning, riskhantering av leverantörer, leverantörsidentifikation och val, RFQ-processen, förhandlingsprocessen, kontrakthantering samt uppföljning av leverantörsprestation. Dessa nyckelområden har följt det ramverk som skapats i litteraturstudien samtidigt som nya faktorer har identifierats och lagts till då de ansetts som viktiga. För att tillämpa AI i strategiska inköpsprocessen måste Case-Företaget överväga andra aspekter än var i inköpsprocessen de kan dra nytta av AI mest. Faktorer som utmaningar och risker, beredskap och mognad samt faktorer som ansetts viktiga att beakta för att möjliggöra en implementering har identifierats. För att bedöma hur mogen och redo den strategiska inköpsfunktionen hos Case-Företaget är för en implementering har några av de tidigare digitala projekten inklusive AI-teknik kartlagts och analyserats. Det har emellertid konstaterats att det kan vara fördelaktigt för strategiskt inköp att börja med ett mindre användningsområde och sedan skala upp det. Eftersom strategiska inköpsfunktionen har implementerat en spendanalys plattform kan det vara en bra start att utvärdera det projektet och sedan tillämpa AI ovanpå den befintliga lösningen. Andra faktorer att beakta är att försäkra datakvalitet och säkerhet, involvera ledningen samt lyfta vilka fördelar AI kan ge i form av ökad effektivitet och kostnadsbesparingar. Därtill är det viktigt att inkludera hela strategiska inköps-funktionen samt att inte endast beakta den tekniska aspekten utan också mjuka faktorer så som change management och agila metoder.