Custom demand-planning engine with estimated annual savings of $30m to $50m
Company Information
A leading US specialty retailer sought to overhaul its demand-planning process to enhance forecast accuracy and reduce inventory inefficiencies. The challenge was to integrate complex inputs across marketing, product supply, market intelligence, sales, and finance into a cohesive forecasting model. ProCogia was engaged to develop a custom solution that would not only refine the retailer’s demand forecasting but also translate these improvements into substantial cost savings and inventory optimization.
The Challenge
The retailer faced several issues with its existing demand-planning process, including inconsistent forecasting across product categories, untimely incorporation of external trade inputs, and an outdated initiative management process. These challenges led to overstocked and understocked SKUs, resulting in lost sales and unnecessary inventory costs. The goal was to implement a more accurate and responsive forecasting engine capable of driving significant savings and reducing non-productive inventory.
Procogia’s Approach
ProCogia collaborated with the company’s leadership to implement:
A cross-functional team with accountability for marketing, product, supply, market intelligence, sales, and finance
A standardized statistical demand-forecast process across categories
Timely incorporation of trade inputs from external sources
A revamped Dates and Gates process for new team initiatives
The Results
ProCogia’s customized forecasting and ordering solutions:
Improved forecast accuracy for 20-25% of SKUs
Yielded estimated savings $230,776 for 170 POC SKU’s
Yielded estimated annualized savings (considering all SKUs) in the range of $30m to $50m
Non-productive inventory reduced in more than 50% of SKUs
Lost sales savings = $103,800
Over stock savings = $126,976
Services Used
Data Consultancy
We provide data consultancy to organizations to optimize your investment in people, processes, and technology. This is typically through data strategy engagements, roadmaps, transformations, and independent technology advice.
Data Science
We use open source technology to leverage the full potential of your data. Predictive and prescriptive results are actioned using AI and Machine Learning (ML).
Conclusion
ProCogia’s development of a custom demand-planning engine for the US specialty retailer represents a transformative approach to demand forecasting and inventory management. By integrating cross-functional insights and applying sophisticated statistical models, ProCogia not only enhanced forecast accuracy but also drove significant cost savings and operational efficiencies. This case study underscores ProCogia’s capability to deliver complex, high-impact data solutions that drive strategic growth and operational excellence.
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