A management science approach for developing a decision model for portfolio rationalization of consumer personal computers

Commoditization of the PC market has led to a shift in strategy at Dell away from customization towards defining specific consumer configurations ahead of time. This shift creates new planning and decision processes around which configurations to select. Given configurations are defined before true demand can be measured, variability leads to selection of configurations based on imperfect knowledge. The existing variety of configurations has imposed substantial complexity costs on Dell. Modeling this selection process as a Newsvendor "life-time buy" includes this variability while optimizing for profit. Estimated costs of overage, costs of underage, and complexity costs are used as inputs. This thesis seeks to develop a framework informing configuration selection decisions based on demand variability and expected profit. A heuristic model uses configuration volume estimates, profit margin estimates, and historical regional bias in submitted forecasts to score and rank potential configurations. This heuristic determines which configurations to select within a fixed maximum total number of configurations limit, based on the business's market share growth and profit goals. This maximum limit is set by Dell's Vice Chairman Jeff Clarke. The results of this heuristic show a decrease in decision process time, an increase in process transparency, and increase in expected profit. A what-if scenario analysis shows an annual increase of 3.4% in profit which amounts to several million dollars. These results were gathered through implementing the model in November 2014 and comparing the heuristic-based decisions against past process decisions.

Department dc:contributor.department

Leaders for Global Operations Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2015

Author dc:creator

• Whigham, Paul Alexander

Advisor dc:contributor.advisor

• Özalp Özer and Bruce Cameron.

• Sloan School of Management.
• Engineering Systems Division.
• Leaders for Global Operations 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/1721.1/99038

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/99038