Back to overviewIn this webinar, Luis Castro, Data Scientist at MicroTechnologies and part of a team leading Digital Transformation, will share why they decided to use AI in their demand planning process and the results.
MicroTech provides micro-machining solutions and OEM component manufacturing to a wide variety of industries. They were facing the following difficulties:
- Many of their customers don’t share a weekly or monthly demand forecast, negatively impacting their demand plan accuracy.
- They need to buy raw materials & supplies to manufacture the products, but with Covid-19 and container crises, they need to know well upfront what the demand will be.
- MicroTech’s internal Prophet model didn’t allow them to forecast at the desired granularity level (by week, by part number, by customer id) and had the tendency to overestimate.
With the use of Garvis, they’ve been able to forecast more accurately at the desired level of granularity. They have evolved from a subjective forecast to an automated demand forecast for all of their customers.
What you'll learn:
- Why it was a priority to transform the demand planning process
- How Microtechnologies forecasted in the past
- Their experience with the implementation of AI
- Enhancing the forecast with the planner’s knowledge
- Forecast accuracy improvement at MicroTechnologies
- How Garvis can be implemented and applied in less than a day at manufacturing companies.
Whom will I listen to?
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Luis Castro, Data Scientist at MicroTechnologies and part of a team leading Digital Transformation.
