Case study

How a company in the commodities sector improved their forecasting process & accuracy by more than 50%

Here's how they did it.

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What were their forecasting challenges?

What did they want to improve?

#1 Unclear on the relevancy of their indicators

Previously, their forecasting process was generally static in nature - this meant that it was tricky to know with certainty that the leading indicators selected were the correct indicators.

In the absence of a dynamic interplay between selecting the right indicators and internal data, this meant that it was tricky to know if the leading indicators selected were indeed the correct indicators to take into consideration.

#2 Inefficient & manual forecasting process

Time is a valuable asset in dictating the level of resources you need to allocate to make decisions that move the needle. Previously, their forecasting process involved manual, almost administrative work associated with importing different files, and constantly updating them.

“If there is a change, we can clearly see the indicators that are valued higher, either with a pronounced higher contribution or higher influence, and when they do change in position."

This was not limited to demand planning forecasting

“There were a couple of cases where they (the Market Intelligence) were working on defining their market size prognosis, and they came across one or two indicators that were relevant to their forecasts. They were then adamant to get more insight into the trajectory of prices, and what market size they could forecast

Easy rollout and implementation across departments

Time is a valuable asset in dictating the level of resources you need to allocate to make decisions that move the needle. Previously, their forecasting process involved manual, almost administrative work associated with importing different files, and constantly updating them.

Results: A leap to improved forecasting methodology

Using Indicio’s methodology of selecting leading indicators, they have now successfully moved from using the same 5 indicators, to testing a set of indicators and getting immediate feedback on which indicators to use or consider for each forecast.

They now also has the capacity to drill down into a month-to-month forecast. The key demand planner and forecast analyst at this organization explains, “If there is a change (either an upturn or downturn), we can clearly see the indicators that are valued higher, either with a pronounced higher contribution or higher influence, and when they do change in position.

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