The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
Aalto

Information Sharing and Collaborative Forecasting in Retail Supply Chains

Johanna Småros

Dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Department of Industrial Engineering and Management for public examination and debate in Auditorium TU1 at Helsinki University of Technology (Espoo, Finland) on the 16th of September, 2005, at 12 o'clock noon.

Dissertation in PDF format (ISBN 951-22-7828-6)   [815 KB]
Errata (in PDF format)
Dissertation is also available in print (ISBN 951-22-7827-8)

Abstract

Demand distortion, also known as the bullwhip effect, is an important problem encountered in a wide range of supply chains. To counteract this problem, it has been recommended that downstream sales data be shared with upstream members of supply chains. Furthermore, it has been suggested that even greater benefits would be attained through the implementation of collaborative forecasting in supply chains. In practice, however, many companies have found it difficult to realize the suggested benefits of information sharing and the adoption rate of collaborative forecasting remains low.

This thesis examines the benefits and challenges of information sharing and collaborative forecasting in retail supply chains. It consists of six individual studies: two simulation studies and one case study examining the value of manufacturer access to downstream sales data; one case study on collaborative forecasting; and two case studies comparing company experiences of information sharing and collaborative forecasting. The research context is the relationship between grocery retailers and consumer goods manufacturers.

Three research questions are addressed:

  1. In what situations does sharing of downstream sales data with upstream supply chain members enable increased efficiency?
  2. What are the prerequisites for upstream supply chain members to be able to benefit from access to downstream sales data?
  3. What additional benefits and costs are associated with moving from sharing of downstream sales data to collaborative forecasting in supply chains?

In relation to Question 1 it is discovered that access to different types of downstream sales data, e.g. point-of-sale data or customer sell-through data, has different value depending on whether the aim is to reduce demand variability amplification or delay in conveying a change in demand. In addition, it is found that the replenishment frequency between the echelons of a supply chain has an important impact on the value of information sharing.

In relation to Question 2 it is shown that the manufacturer's production, planning, and purchasing frequencies limit the attainable benefits of information-sharing efforts. In addition, it is found that the manufacturer's forecasting process and level of internal integration may present obstacles to the effective use of downstream sales data. Moreover, it is demonstrated that the fashion in which downstream sales data is used in production and inventory control has an important impact on the resulting benefits.

Finally, in relation to Question 3 it is discovered that many grocery retailers currently lack the forecasting capabilities required for effective forecasting collaboration. Investing in acquiring these capabilities for the sole purpose of enabling collaboration is, in light of the attainable benefits, not feasible. However, the results of the research indicate that a great deal of the benefits of collaborative forecasting can be attained by synchronizing planning activities and by sharing more accurate sales data in the supply chain.

Keywords: bullwhip effect, collaborative forecasting, collaborative planning forecasting and replenishment (CPFR), information sharing, point-of-sale (POS) data, retail, supply chain management (SCM), vendor-managed inventory (VMI)

This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.

© 2005 Helsinki University of Technology

Last update 2011-05-26