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Integration of Machine Learning Insights into Organizational Learning: A Case of B2B Sales Forecasting

In: Blurring the Boundaries Through Digital Innovation

Author

Listed:
  • Marko Bohanec

    (Salvirt ltd.)

  • Mirjana Kljajić Borštnar

    (University of Maribor)

  • Marko Robnik-Šikonja

    (University of Ljubljana)

Abstract

Business-to-Business (B2B) sales forecasting can be described as a decision-making process, which is based on past data (internal and external), formalized rules, subjective judgment, and tacit organizational knowledge. Its consequences are measured in profit and loss. The research focus of this paper is aimed to narrow the gap between planned and realized performance, introducing a novel approach based on machine learning techniques. Preliminary results of machine learning model performance are presented, with focus on distilled visualizations that create powerful, yet human comprehensible and actionable insights, enabling positive climate for reflection and contributing to continuous organizational learning.

Suggested Citation

  • Marko Bohanec & Mirjana Kljajić Borštnar & Marko Robnik-Šikonja, 2016. "Integration of Machine Learning Insights into Organizational Learning: A Case of B2B Sales Forecasting," Lecture Notes in Information Systems and Organization, in: Fabrizio D'Ascenzo & Massimo Magni & Alessandra Lazazzara & Stefano Za (ed.), Blurring the Boundaries Through Digital Innovation, pages 71-85, Springer.
    • Handle: RePEc:spr:lnichp:978-3-319-38974-5_7
    DOI: 10.1007/978-3-319-38974-5_7
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