Event Details

Webinar

The abstract: Artificial Intelligence and Machine Learning (AI/ML) reign high on the Gartner hype cycle, promising new business models, and capturing the imagination of many industry executives well outside the digital industries of Facebook, Google and Uber. However, despite dozens of Proof-of-Concept studies in demand planning, AI/ML is struggling to prove significant increases in planning accuracy. One limiting factor, we will argue, is that the underlying data for demand planning is fundamentally limited. After a very brief introduction into AI/ML we will explore the fundamental difference in data between image/voice/video recognition and typical pharmaceutical demand planning, where we data size and data labels are often very sparse. As this limits the benefit of the AI/ML algorithms of Google & co, we will show a case study where we have enhanced limited datasets in demand panning and thus showed promise in using AI/ML for Janssen (a Johnson & Johnson company). We will close by showing more favourable data conditions and successful AIML forecasts in container shipping for Hapag-Lloyd, forecasting consumer demand for FMCG manufacturer Beiersdorf, and beverage forecasting for beer Manufacturer Anheuser-Busch InBev, which have been forecasting with AI for up to 10 years.