A use case for what-if tool - Long horizon forecasting example The need for long-horizon forecasting Long-horizon forecasting involves predicting a situation 1.5-2 years in advance. Some businesses need such horizons for procurement of raw materials, ensuring the availability of staff and labour to meet demand and supply, expense management...

COVID-19 impact on the retail industry While COVID-19 spreads globally, the retail industry braces for the outbreak’s fallout. From the slowdown in sales at the moment to not being able to move inventory and an increase in demand from the consumer market, here’s everything you need to know about the...

Factors to keep in mind while Forecasting A famous quote coined by Paul Saffo, a consultant associate professor at Stanford University who has been a technology forecaster for more than 35 years now, says that- “The goal of forecasting is not to predict the future but to tell you what...

Inventory rebalancing - Part 2 In part 1, we built a crucial foundation to understand problem of inventory imbalance. Here, in part 2, we will dig deeper into the solution to the presented problem and how we can implement the presented solution in practice with a set of business constraints....

Confidence Intervals What are the confidence intervals? In statistics, it is almost always impossible to deal with the entire population as a whole. When I say population, I mean considering each and every possible value of a variable under consideration - be it sales of a commodity or the number...

Inventory rebalancing Introduction Any retail chain organisation, operating multiple stores across multiple states and cities, and sometimes in multiple countries, has to optimise its supply chain to meet varying customer demand. Outline Why does inventory imbalance happen? How to identify inventory imbalance across stores? Imbalance metrics Why does inventory imbalance...

Product recommendations using HRNN E-commerce websites are a common goto destination for us and thus we all are very well aware of the importance of recommendations provided by them. We find recommendation engines almost everywhere, be it Amazon, Netflix, Facebook or LinkedIn. Amazon uses it for product recommendation, Netflix for...