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Commercial prediction (Schneider Electric)

Schneider Electric Norway AS has proposed master projects that will be co-supervised by them and will involve real and challenging ICT problems in their organisation. Part of the work will be done at their offices at Ryen. 

Schneider Electric Logo

Schneider Electric Logo

Commercial prediction

Problem description

  • Today, we rely for a large part on a bottom-up information flow to understand where the market is going (mostly from our partners, our customers, our sales representatives.
  • We complete this information with historical data such as sales pipeline, sales historical data
  • This information source is both very diffuse, unconnected and very subjective.

Scope of project

  • Identify all existing sources of information, both internal and external
  • Identify ways to structure this information so that it can be used to predict in which way the market is evolving
    • Who are our tomorrow’s customers?
    • Where are they located?
    • What do they want?
    • Which market segment do they belong to?
    • What competences do we need to anticipate this demand?

Potential solutions

  • Machine learning
  • Can also be a student from Mathematics and Statistics.

This project would suit a student with an interest in data science and applied statistics. A student with interest in entrepreneurship and management would also be suitable, with a sufficient background in statistics. Machine learning methods, and other suitable statistical methods should be examined as a means to develop a predictive support system for sales and commercial data.

Emneord: Machine Learning, Statistical modelling, Entrepreneurship
Publisert 5. okt. 2017 09:03 - Sist endret 16. mai 2018 09:47

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