EMEA / Consumer Electronics

Using statistical modelling to aid strategic sales decisions

"As a result of the statistical modelling work, we were able to reduce the clients sales forecasting process from 2 weeks to a matter of hours."

Business issue

The client, a global consumer technology company, was faced with a significant challenge concerning the processing of EMEA sales data to aid forecasting.

Their existing solution, involving consolidating vast amounts of disparate sales data, typically took up to 2 weeks to turnaround and exposed them to the risk of inaccuracy due to human error.

They needed a solution which would help them to streamline their existing process whilst still providing insights which would guide forecasting.

Our solution

Using Python, we created bespoke scripts which automated the creation of the forecasting template. This involved using various Python capabilities and libraries, including Pandas and OpenPyxl.

We were also able to harness Python’s statistical modelling features, providing the client with access to improved predictive functionalities and statistical forecasting capabilities.

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Impact

As a result, we were able to reduce the clients sales forecasting process from 2 weeks to a matter of hours. Alongside this, our solution enabled them to benefit from more granular insights.

We increased the sales team’s efficiency, reduced the risk of human errors and provided a solution which could adapt to a dynamic and ever-changing market.

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