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.
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- 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?
- 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.