Purchasing and Digitalization in an era of Turbulence

Abstract (Swedish)

Background: This research delves into the uncertainties and challenges encountered in global supply chain operations, exacerbated by unpredictable events such as the COVID-19 pandemic and the 2021 Suez Canal obstruction. These disruptions can lead to stock-outs, poor capacity utilization, and the need for expensive buffers. The study centers on Duni, an international company present in over 20 countries. The thesis evaluates Duni's purchasing practices through the lens of digitalization, examining operational processes, digital tools used, turbulence impact, and potential AI automation opportunities. It employs a qualitative approach, building on prior research, but uniquely scrutinizes the impact of turbulence on digitalization of operational activities.

Problem formulation: The thesis underscores the critical role of digitalization in managing these disruptions and discusses its impact on diverse stakeholders - suppliers, governments, retailers, financial institutions, and customers. Effective digitalization can create sustainable competitive advantage, reinvent procurement processes, and enhance transparency, contributing to profitability. However, if poorly implemented, it could sub-optimize the ordering process, damaging trust relationships.

Purpose: The purpose of this Master Thesis is to explore and map the purchasing practices of Duni through the following four lenses of; the operational process, the role of the digitalization tools used, the impact of turbulence, and lastly, possibilities of AI automation.

Methodology: The approach to this research paper is done through the usage of a multiple-case study framework. A data collection protocol is developed using an semi-structured interview guide that covers the different areas of this research paper. Lastly, Data analysis and discussions about limitations is done to touch on the subject of quality of research. This research paper is mainly of a qualitative nature.

Conclusion: The research centered on three main questions regarding Duni's supply chain. Firstly, it investigated the operational procurement process, discovering that while Duni uses two Enterprise Resource Planning systems, human intervention remains necessary to accommodate unpredictable factors in the supply chain. Secondly, the research focused on how Duni evaluates delivery performance. It found that while traditional metrics such as delivery date compliance and order quantity compliance are used, there is a lack of a formal, quantitative supplier delivery performance rating system. Lastly, the research sought to understand the role of digitalization and automation in ensuring adequate delivery performance and mitigating risk. It found that balancing automated systems with human intuition is crucial, particularly in managing unpredictable events that impact the supply chain. There's an opportunity for automation in supplier delivery performance measurement, and handling endogenous turbulence, while exogenous turbulence requires more manual adjustment due to its complexity.

Popular Abstract (Swedish)

Our master’s thesis studied how the digitalization tools used in the purchasing processes of Duni Group contribute to the performance results of specific parameters. Our research was divided into four parts, the practical operational process of purchasing, the role of digitalization tools in it, the occurrence of turbulence that disrupts the purchasing process. Lastly, as an addition to digitalization tools, the perspective of Artificial Intelligence implementation was lightly studied.
The methodological approach in this research paper was of a multiple-case study, specifically four cases were included. Two suppliers, and two purchasers. All the information from the cases was collected from interviews.
From the perspective of what the operational purchasing process consisted of, Duni mainly utilizes single order contracting, meaning that Duni’s contract length with suppliers was of a short nature, with the contract being that of one specific order with one corresponding delivery date.
From the perspective of the digitalization tools used in the Duni supply chain, similar software solutions were used throughout the cases. These software’s were JAGGAER, SAP, APO, and the specific case of a customized software solution called Farben. With Farben being an interesting outlier, it indicated to be able to produce exceptional results. The main differences in the other usage of software’s were the specific functions used within the software solutions.
From the perspective of AI and automation, it was shown that the functions within the software’s can automate processes to varying degrees, with the specific automation degree depending partly on the leadership of the case study.

Regarding turbulence, the findings show that there is no one specific problem that has an exceptional impact on the supply chain. Furthermore, turbulence originating from outside the supply chain is less frequent but more impactful, compared to turbulence within the supply chain.
Lastly, the two main measured parameters for performance (KPI) were shown to be the ability of a supplier to deliver for a specific date, with a specific order quantity. The supplier delivery performance evaluations were independently evaluated between cases through informal discussion with some quantitative measuring using the mentioned KPI.
The recommendation of this thesis is to establish a general methodology of evaluating suppliers’ delivery performance with the help of the two currently measured KPI’s and thereafter look for possibilities of automation and centralizing the storage of information to increase data-driven decision making.

• author: Sarajlic, Emil and Natesan, Vishal
• supervisor: Louise Bildsten
• organization: Engineering Logistics
• course: MTTM05 20231
• year: 2023
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering
• keywords: Supplying, digitisation, digitalization, Artificial Intelligence, Turbulence, Delivery performance, Duni Group
• report number: 5989
• language: English
• id: 9123068
• date added to LUP: 2023-06-10 17:02:18
• date last changed: 2023-06-10 17:07:13