Our team collaborated with AMECO, a construction service company, to address their challenge of aligning actual profit margins with targeted goals. Based on past years sales performance, AMECO is experiencing a constant decline in profit. The target profit is achieved by selling their products at their target profit margins. Therefore, we approached this problem by two steps: validation of current target profit margins and prediction of appropriate target profit margins. We first validated the existing target profit margins using exploratory analysis and statistical tests, identifying under- or over-performing product classes at different time points and customer categories. Then based on the internal correlations and external influences, revealed through our analysis, we developed predictive models including machine learning and time series models to forecast more accurate profit margins for some particular product classes.
Students
