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REPLAY for Webinar: How (not) to use AI for predictive data

By Garvis - Aug 10, 2021 3:09:43 PM

The environment of organisations is changing at an unprecedented rate. Traditional forecasting methods, that rely heavily on historical data, are under pressure. Digitization brings a huge amount of forward looking data, which could be the solution to maintain forecasting accuracy in this age of change.


But is all data as predictive as we think it is? If we don’t have the bandwidth to deal with the history, how are we supposed to deal with this huge amount of new data?


More and more organizations are looking at AI and Machine-learning algorithms to use this data to create a better plan for the future. But, as promising as these technologies may look on the surface, they will fail if not used properly. The most common AI solutions are primarily non-transparent (“black box”) and require a lot of tuning, whereby explainability and accountability are essential in the demand planning process. Moreover, these are expensive systems that quickly become outdated. Their implementation takes months. The preparation and aggregation of datasets can also be an enormous burden.


In this 30min webinar, Piet Buyck, CEO at Garvis, gives an overview of the latest technological evolutions and techniques available to help organizations understand predictive data and better plan for the future. He will introduce the concept of ‘Bionication’, in which the planner keeps both the implementation and the actual AI decision-making process under control as well as he can eliminate the usual disadvantages of AI.


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What will I learn?



The following topics will be discussed:

  1. Which challenges in the planning process can be tackled with AI?
  2. What are the latest technological advancements in AI and ML?
  3. Which demand signals and data are there and what is their predictive power?
  4. Which tactics are used to make sense of historical and forward looking data?
  5. What is the concept of 'bionication', and how does it allow to overcome the typical downsides of AI? (Cost/Implementation time/Transparency)
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Piet BuyckWhom will I listen to?


Piet Buyck is a global technology executive with over 30 years of success in managing and positioning high-value IT-applications that are disruptive to current practices. He is well known as an influential, strategic, business thought leader with significant achievements and expertise in artificial intelligence, demand sensing and demand planning. As CEO of Garvis, Piet is on a crusade to make artificial intelligence for forecasting easy, accessible, and explainable while keeping the planners in control.



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