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Demand Planning

Demand Forecasting


We have developed the first parameter-driven, Demand Forecasting solution designed to improve forecast accuracy through collaboration between analysts and planners.

Built on decades of forecasting experience and numerous successful engagements, our unique solution creates a closed loop environment of People, Process, and Analytics. This approach enables planners and analysts to work hand-in-hand to improve accuracy throughout the planning cycle.

We start by producing a reliable baseline forecast using advanced statistical techniques and tools. Your planners then enrich the forecast by integrating business knowledge and expertise through a user- friendly interface, alleviating the need for coding or advanced statistical knowledge.

To maximize the value of the solution, only a low level of support is required from statistical analysts, reducing the learning curve as well as the time the planners spend manipulating data. This frees them to spend more time analyzing and planning profitability, significantly increasing their productivity.

Planner input to the statistical forecast will lead to an improved baseline forecast and fewer planner overrides, enabling:

  • Increased forecast accuracy
  • Improved customer service levels
  • Reduced inventory, safety stock, and raw materials
  • Reduced supply chain cycle times
  • Improved procurement decisions
  • Reduced waste and improved sustainability

 

Suggested Order


Our suggested order solution builds off of our leading edge demand forecasting platform. Dynamic aggregation, UPC consolidation, promotional modeling, and a full suite of diagnostics are a few of the components of this comprehensive solution designed to produce the best possible weekly demand forecast at the store UPC level. This weekly forecast combined with our customizable replenishment logic produces a suggested order recommendation that takes into consideration the frequency of delivery, capacity constraints, and other factors.

Our dynamic solution has been implemented, with great success, in multiple Direct Store Delivery (DSD) environments within the Beverage and Snacks vertical. Resulting benefits have included a healthy reduction in out-of-stocks (up to 12 points), significantly lower back room inventory (up to a 10 point reduction) and a more efficient delivery process (as much as 20% reduction in head count).

If you want to gain control over out-of-stocks, excess inventory, or just now entering the DSD space, Prognos’ Suggested Order solution gives you a head start to profitability .

Forecast Value-Add


Two common questions that should be asked of any Demand Forecasting process are:

  • Does our Forecasting Process actually improve the accuracy?
  • How well are we forecasting compared to best practices?

 

We determine the value-add of your statistical models or forecasting process is to measure the accuracy attained at each stage of the forecast process, and confirm that each stage actually improves accuracy, therefore, adding value.

At the same time we benchmark forecast accuracy against a cross industry data set. In order to achieve a fair comparison we measure the variability of the forecast item and compare its forecast accuracy to items with similar variability.

At the conclusion of our study your organization will be able to prioritize resources on the forecasting processes that offer the greatest potential improvements.