Developing internal logistics in a make-to-order environment : case Gardner Denver Oy

Abstract

The optimization of internal logistics holds a sizeable societal importance as efficient logistics contributes to the timely delivery of goods to customers, increasing customer satisfaction. By developing these processes, companies build trust and transparency in their operations, pivotal for any prosperous business environment. The study aims to enhance the make-to-order internal logistics of the Tampere plant of Gardner Denver Oy, by improving an array of key performance metrics, primarily the delivery reliability and through the enhancements in reliability, also inventory turnover, inventory value, capital turnover ratio and timeliness of invoicing and collection process.

The thesis focuses on the logistics processes at the end of the supply chain, where the finalized products await to be dispatched to the customers. By utilizing the current state of the company, using quantitative data in the form of open sales data and invoicing data, and qualitative data in the form of interviews conducted with professionals in different departments of the case company, the study develops a process model to improve delivery reliability through delivery date estimates, having an impact on the other key performance metrics as well. In studying potential causes of deteriorated delivery reliability, the research found four key variables, the order size, the number of days between the delivery date requested by the customer and the promised delivery date, the payment or pick-up risk of the shipment, and the country of origin of the customer.

The cause and effect of the key variables are thoroughly studied in support of the peer-reviewed theoretical literature to validate any recommendations in the proposed process model. The proposed process model anticipates improving the other key performance metrics by offering actionable recommendations for the case company to pinpoint and improve the internal logistics processes, eventually enhancing the overall efficiency of the supply chain and resulting in a functioning process model that the case company can develop through future data utilization and find additional variables that cause an effect on the overall delivery reliability and through future research on the subject affect the other key performance metrics researched as well.