AI-based planning can reduce forecast errors by more than 30% and releases demand planners from tedious data processing work, so they can focus more on data interpretation and applying their strategic business knowledge and creativity.
It’s a common misbelief that, to leverage this power of AI, organizations need to have a high level of IT maturity and in-house data science expertise and will require long and costly implementations that put a high burden on planning teams.
However, thanks to the latest technological developments, and a process developed by Garvis called ‘Bionication’, the barrier to start planning with AI could be much lower than expected.
We are hosting a free, 30-min webinar in which our Chief Product and Customer Officer, Anupam Aishwarya, will share his insights on how a one-day implementation is possible and what a day in the life of a planner looks like afterwards.
Session 1: 9AM Central European Time (Recommended for the eastern hemisphere)
Session 2: 4PM Central European Time (Recommended for the western hemisphere)
What will I learn?
- In which ways does AI bring value to the planning process?
- Which skills are required for (planning) knowledge workers in Industry 4.0?
- How to start the journey to AI based planning?
- How does it look like at organizations of different sizes and different levels of IT maturity? (Real-life examples)
- What does it mean for planners, and how does it impact their day-to-day life?
- What is ‘bionic planning’ and what does it mean for my planning process? (The 3 C’s of Assumption based planning: Customer – Competition - Causals)
- How can I stay in control and why should I adopt transparent AI over Black box?
Who will I listen to?
Chief Product & Customer Officer at Garvis
Anupam is a global business leader and entrepreneur with a deep expertise in forecasting, business planning and supply chain. He has over a decade of unique experience in combining mathematics, AI, and human intelligence to creatively solve business problems and create tangible value across many Fortune 1000 companies.