By partnering with First Insight, a technology provider that specializes in consumer data analytics, Puma was able to incorporate consumer feedback into their demand planning process.
First Insight’s technology collects real-time consumer feedback on potential products, allowing Puma to gain insights into consumer preferences and behavior. This data was then used in conjunction with machine learning algorithms to create more accurate demand forecasts. The system uses both structured and unstructured data, including point-of-sale data, inventory levels, social media metrics, and consumer feedback to develop predictions.
Let’s admit that one of the major challenges faced by organizations is the instability of demand. After all, the buyer regularly changes their mind. Like everything else, this has an impact on business. The effect of social media influencers, alterations in the economy like inflation or recession, and a lot of multiple factors affect the purchasers’ buying decisions. A global epidemic could cause problems similar to COVID-19 in 2020. Sadly, there is no magic wand that can foretell such events. So, here the concept of demand forecasting comes into the picture.
What is demand forecasting?
Demand forecasting is the estimation of the future demand for a product or service how much will it be needed and when. This term is interchangeable with demand planning and demand sensing.