Here at Greycon our highly experienced team of developers have designed a sophisticated forecasting tool with you in mind. 

Greycon's Forecasting solution is designed specifically for the Paper & Board, Plastic Films & Flexible Packaging, Nonwovens, Metals and Converting industries. 

Our solution uses advanced forecasting algorithms, in an innovative, Excel-based front end, backed by multi-user capabilities in a SQL Server back end. It uses advanced statistical algorithms and built-in demand management best practices to help reach your corporate goals.

Greycon Forecasting takes into account actual demand history, external causal factors and collaborative market intelligence input and produces an accurate forecast. Along with the rest of the Greycon products you will achieve sales and service level increase, lower inventory, lower distribution costs and lower production costs.

Features & Benefits

Greycon Forecasting will bring numerous benefits to your company some of which are:

  • Intelligent Demand Netting stops production from producing extra stock by avoiding customer order/demand misalignments
  • Advanced segmentation and accurate forecast accuracy statistics and confidence intervals provide better information for setting inventory policies thus reducing inventory
  • Budget Gap Analysis features anticipate mismatches with budgets, quotas and targets and drive timely gap-closing activities thus helping towards meeting financial targets

Greycon Forecasting in Short

  • Integrated Platform for Business Intelligence & Demand Planning
  • Based on the Microsoft SQL Server BI Stack
  • Combines flexibility of Excel with reliable, centralised data, shared reports and full data security
  • Packaged state-of-the-art statistical algorithms and best-practice S&OP processes
  • Power-BI reports and dashboards for modern BI experience

Integration with opt-Studio

Greycon Forecasting integrates seamlessly with Greycon's premier advanced scheduling system, opt-Studio.

Greycon Forecasting creates consensus forecasts which are automatically imported into opt-Studio for demand & capacity balancing and inventory replenishment:

The final results sent to opt-Studio are usually disaggregated into daily buckets, taking into account the weekly distribution of previous years.

The forecast and the existing customer orders form the demand which is used in opt-Studio to generate an optimised capacity/block plan combined with an optimised inventory replenishment plan for each SKU, taking into account:

  • inventory policy (min and max inventory targets)
  • inventory costs
  • customer service, i.e. orders already in the system
  • transport times and costs
  • production aspects such as switchover and production costs

For each SKU, opt-Studio will display the estimated inventory profile for the time horizon being considered, as follows:

As new orders arrive, Greycon Forecasting will apply a “netting” process to subtract the incoming volume from the forecast. The forecast imported to opt-Studio is actually the result of this process: the net forecast.

In the netting process, the system can examine adjacent time periods or even similar products if the volume of the arriving orders is more than what was forecasted. For example, if a new order for a basis weight of 250 g/m2 arrives, which was not anticipated, the system can check if there is a forecast for 240 g/m2 or 230 g/m2 and reduce that one instead.

Statistical Forecast Generation

Greycon Forecasting uses a collection of statistical algorithms to generate the statistical forecast. This is blended with advanced methods in selecting forecast levels and managing sparse data when delivering and publishing the final statistical forecast.

The user does not have to decide these levels, as the system automatically determines the most appropriate ones (too low a level and there isn’t enough data vs. too high a level and the sub-sectors differences are not captured). The resulting data cube is available at all levels of aggregation.

Working Forecast Collaborative Edits

The statistical forecast can then be analysed using either the Microsoft Excel add-in or Power BI at any aggregation level desired. The Microsoft Excel add-in allows forecast overrides in a similar fashion to historical overrides. The Greycon Forecasting application maintains the core statistical forecasting outcome for accuracy reporting. It also maintains a working forecast each month, calculated using the latest statistical forecast and two types of supported overrides. The two types of override are:

  • The market intelligence (MI) override is added on top of the statistical forecast like an upward or downward correction. If the statistical forecast is re-run and changes, the working forecast will re-adjust as well. MI overrides can be created directly in the Pivot Table reports using the writeback feature or can be imported from external systems in the form of upward or downward percentages.
  • The forecast override (OVR) override is exactly what its name suggests: it overrides the statistical forecast to an absolute value. So regardless if the statistical forecast changes, this will remain fixed. Allocation rules can be configured to also not allow MI overrides applied at higher levels affect fixed overrides defined below.

The collaborative process is usually is part of a monthly S&OP process cycle. At the end of the demand part, the working forecast is finalised into a final forecast for the specific scenario and the overrides are rolled forward to affect the next scenario.

Forecast Accuracy & Confidence Intervals

Greycon Forecasting can suggest a confidence interval related to the statistical forecast. Also available are other forecast accuracy measures, such us forecast bias (%) or forecast absolute percent error. These measures indicate how successfully the specific combination was forecasted previously, how accurate it was, whether it was positively or negatively biased and what is the confidence interval for the specific value returned. The confidence interval is calculated using the forecast standard error from past forecast scenarios that were generated in the same distance (or lag) that the month under review has from the current month.

The Forecast Bias % is commonly used to identify forecast accuracy. As shown in the screenshot below, the user could calculate many such measures for a given month with actual shipments depending on which forecast scenario it compares them with.

Determining which accuracy measure is best can be confusing. The system therefore offer another measure, called Forecast Offset. This is the forecast for a specific product/ship-from location that was created during a scenario X-months before, where X is the number of months of lead time for the specific product/ship-from combination. Hence analysing the Forecast Offset Bias % (now a single measure) the users can see the error in their forecast that was actually used during replenishment or production decisions in the supply chain.

Read-only Reports & Analytics

Read-only reports from the  Greycon Forecasting application are created using the Microsoft Power BI solution (free with Office 365). Power BI reports can be created using an easy-to-use free application and can be published and distributed as reports or dashboards to Power BI enterprise users on web browsers, tablets and mobile phones. Sample Power BI report screenshots created using the Greycon Forecasting Cube are shown below: