How a market leader in the heavy duty truck industry, serving well over 100 international markets, improved their forecast accuracy by 57%.

How a market leader in the heavy duty truck industry, serving well over 100 international markets, improved their forecast accuracy by 57%.

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5 mins
CATEGORY
Articles
Published on
October 4, 2022

As a market leader in the heavy duty truck industry, serving well over 100 international markets, the manufacturer was interested in forecasting the number of registered trucks in Europe weighing over 6 tons. Beyond that, they needed to have the ability to plan for optimal capacity to meet market turns and shifts. To do so, they required accurate forecasts of their aggregated sales volumes.

However, this was currently not the case.

Their forecast accuracy was low and this led to an inability to detect trend shifts. This subsequently hindered them from optimizing capacity planning. Additionally, due to a dependency on building models in Excel, suboptimal decisions were made.

What were their challenges

Lack of accurate forecasting

Their Excel-based forecasting methodology resulted in low forecast accuracy and an inability to detect trend shifts. This subsequently hindered them from optimizing capacity planning

Aligning forecasting globally

There was a requirement to extend forecasting coverage to more markets for both demand and production needs. Due to a heavy reliance on a scarce team covering multiple markets globally, this was not possible.

Meet market shifts

They needed to have the data to adapt production capacity efficiently and ahead of time to meet market turns and shifts, and to date, this was not possible.

What did they want to achieve?

01 Minimize forecast error margin

02 Identify new market drivers, evaluate new policies, and their impact on the market

03 Extend coverage of more markets for both demand and production

They were able to detect trends shifts 1-2months earlier than before. This meant that they were able to minimize the discrepancy gap between what was internally forecasted and the market reality.

Here were the results:

Gained the ability to detect market shifts

With Indicio, they were able to detect trends shifts 1-2months earlier than before. This meant that they were able to minimize the discrepancy gap between what was internally forecasted and the market reality. This ensured that cost management and resource planning were optimized.

Improved forecast accuracy

With the application of econometrics forecast models, the manufacturer achieved a double-digit MAPE forecast accuracy improvement.

Aligned forecasting globally

Successfully established a structured process across all markets and ease of sharing forecasts ensured that they worked in the same way, and enabled them to share information seamlessly.

Download the full case study here.

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