Analyzing the accountability, systems and efficiency of demand planning processes in a consumer products environment

As consumer products companies like P&G strive to achieve a consumer driven supply network, the value of forecast accuracy comes into question. Many companies push for faster cycle times and shorter supply chains, driving towards make-to-order production. These trends may appear to reduce the importance of forecasts. However, a closer look into P&G and their business reveals that sales forecasts are still very important and have a far reaching impact stretching from the supply network through to Wall Street. This thesis evaluates the forecasting process in a company like P&G. The thesis delves into the accountability around sales forecasts and proposes a top-down, statistical process for creating and tracking forecast accuracy which was implemented across P&G's global organization. Another analysis is conducted on the evaluation of a new demand planning system which provides more granular input data for generating forecasts, and the implications from this trial on the demand planning process. Finally, an assessment on the efficiency of current systems is also detailed.

Department dc:contributor.department

Leaders for Manufacturing Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Prilutski, Christy A

Advisor dc:contributor.advisor

• Jonathan Brynes and Donald B. Rosenfield.

• Sloan School of Management.
• Civil and Environmental Engineering.
• Leaders for Manufacturing Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/37237

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/37237