A Fortune 1000 retail company wanted to improve the accuracy of its merchandise forecasting. With better forecasting, this retailer hoped it could also increase sales and profits.
But greater accuracy required better data — and better analysis.
The retailer turned to g2o because of our experience helping businesses to better understand their customers and with turning data into actionable strategies.
Visibility into this retailer’s process was limited, from testing to final order, and drivers of variance were not well understood.
g2o’s predictive analytics team created an algorithm that objectively predicts sales and reduces variance.
In the end, the retailer uncovered key controllable sources of variance between its plan and actual sales. By finding these sources of variance, the retailer could achieve its goal to improve the accuracy of its merchandise forecasting.