Traditional spreadsheet-based methods and analytical engines cannot accurately forecast sales, capital expenditures, workforce or supply chain planning. The client needed to capture multivariate factors and complex relationships to achieve a higher performing forecasting method.
We analyzed a large volume of multi-dimensional data using deep topological modeling to create a combinatorial library of models. This allowed for identification of critical parameters that impact business objectives through targeted variables.
Our forecasting platform uses real-time data to provide a full understanding of behavior patterns over time with visibility at the lowest level of business activity. This situational awareness enables organizations to implement faster and more agile actionable insights to optimize objectives within and across business segments.