Case Study: a top 100 industrial group achieves 82.6% sales forecast accuracy with BizAcuity self-service analytics

Client achieves 82.6% sales forecast accuracy with BizAcuity

The client, one of the world's top 100 industrial groups, faced a complex challenge in planning production capacity for windshield glasses. They needed to accurately forecast car sales, which depended on numerous macro and micro variables, but their process was slowed by IT dependencies for continuous model building. Vendor BizAcuity was engaged to address this sales forecasting need.

BizAcuity's solution involved collating and cleansing data from disparate sources, using R & Shiny for analysis, and applying feature engineering to identify key predictor variables like GDP and fuel prices. They implemented a framework allowing business users to run various forecasting algorithms independently. This self-service analytics approach reduced IT dependency, sped up decision-making, and achieved an 82.6% forecast accuracy within six months, with accuracy expected to increase over time through machine learning.

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