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Improved purchase order forecasting & expense category volatility to create reliable forecasting regimen
About the client
A leading US healthcare provider
Problems:
The customer was witnessing a significant variance in the Purchase order (PO) issued and total spend at the hospital level resulting in incorrect capital allocation.
Lack of granular forecasting of PO submissions by its hospital partners broken down by on-contract, off-contract, and expense categories (EOCs)
Poor understanding of PO volatility across expense categories (i.e., EOCs) for each hospital
Solution:
Innover developed ensemble ML model (XGB + Seasonal ARIMAX) to accurately capture the Total PO trend, including weekly/monthly growth and seasonality.
Incorporated lagged values of the previous three weeks to account for recency effect
Addressed week-to-week volatility through noise component adjustment
Developed causal models to estimate EOC level share of expense and the week-over-week volatility index
Impact Delivered:
50%
Improvement in forecasting accuracy
Partners
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