Forecasting Demand for New Products - Ep 15

Forecasting product launches is inherently difficult. However it is a vital part of the product lifecycle and must be carefully planned in order to capitalise upon the spike in demand that often follows a products release. In this episode we discuss how to forecast for new products given the amount of unknowns there are and the lack of data that exists. We find out how deep learning compares to more classical forecasting techniques and if we can have any confidence in the results of forecasts.

One of the reasons companies can have high stock levels is due to launching a new product that was unsuccessful. This results in poor cashflow and drains valuable resources.We understand the impact of product cannibalisation and how new products can skew the results of whole forecasts. Finally we discuss the future impact of more sophisticated forecasting techniques which utilise images and product descriptions to group the attributes of various products.

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Episode Map
0:00:00 - Introduction
0:00:30 - Can we forecast for new products?
0:01:55 - Why the “time series approach” does not work?
0:03:41 - Can you actually forecast for something that is completely new?
0:07:16 - With the advances in deep learning technology, is there anything that can be applied to look at these attributes in more detail?
0:11:47 - How can we have confidence in these new product forecasts?
0:14:23 - When we produce our forecasts we are looking at business decisions across a whole catalogue, will new products not skew our whole forecasts?
0:18:02 - Is there any way of producing multiple forecasts to work out what that sensitivity of price will be?
0:21:50 - What can we see in the near future in terms of forecasting new products in terms of technology advancements?

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Learn more: https://www.lokad.com/forecasting-technology
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Видео Forecasting Demand for New Products - Ep 15 канала Lokad