“Firms should budget about one percent of their sales revenues for the forecasting effort.” - Scott Armstrong

What is it? Forecasting is the estimation of the value of variables at some future point in time.

Most of us use forecasting on a daily basis when we listen to weather forecasts. This information allows us to better plan our day and prepare for surprises. Business forecasts are even more important for organizations to help plan and manage their operations.

Business forecasting often uses historical data and is usually performed with the aid of computer software. Forecasting methods can be classified into several different categories: qualitative methods, regression methods, multiple equation methods, and time series methods. Although developing a rudimentary forecast is relatively straightforward, there can be substantial payoff to using (and combining) sophisticated techniques to generate accurate forecasts.

Present Day

Unpredictable demand is in many organizations, their most costly problem. Low forecast accuracy, or no forecast, often results in low service levels, frenzied schedules and poor performance. This costs the organization millions of dollars in safety stock, unneeded inventory, and lead to an unstable Supply Chain.

Companies that are 30% better at demand forecasting average*:

• 35% shorter order-to-cash cycle times


• 15% less inventory.


• 17% stronger perfect order fulfillment.


• 10% of the stockouts of their peers.

Typically, a 1% point improvement in demand forecast accuracy yields a 2% point improvement in perfect order fulfillment capability.

*Statistics quoted from "Consumer Products Industry Outlook: Profitable Growth Requires DDSN Strategies," by
Kara Romanow, AMR Research Report, August 2004. Copyright 2004 by AMR Research, Inc.

Plan better using advanced forecasting solutions.

 

Forecasting – Success Stories

Some ground-breaking applications of forecasting models:
• DNATA, the largest airport terminal cargo operator in the Middle East, to forecast workloads and streamline productivity.
• Entergy Solutions to manage risk and forecast energy costs and demand in a fast-growing deregulated retail environment.
• Kirin Brewery Company of Japan to accurately forecast inventory levels.
• Reliant Energy, a Houston-based supplier of wholesale and retail natural gas and electricity around the world, to help the company meet customer demands reliably and at low cost.
• Salt River Project (SRP), the third-largest public power utility in the United States, to improve retail electricity rates using forecasting capabilities.
• Staples to calculate sales forecasts for nearly 1,100 existing stores and for the 5,000 potential real estate sites annually, using historical sales data and customer demographics.

1. Consultation
• Co-client exploration of the decision-making problem at hand.
• Determination of the relevant factors that may affect the forecast, such as weather, season, day, time, economy, trend.
• Assess data availability and requirements
  
2. Modeling
• Data is transformed to meet certain linearity constraints.
• The best forecasting method, or a set of them, are selected.
• The forecasting engine generates the forecast for the desired time frame.
• An inverse transformation is performed if required.
  
3. Analyses
• The forecast is tested for integrity and accuracy.
• The different forecasting methods are benchmarked by means of a variety of accuracy measures, such as MSE, MAD, MAPE, BIC or AIC, and often using a hold-out sample.
• The forecast may be performed using different initial assumptions.
• A confidence interval may be determined to not only obtain a mean value, but also the expected minimum and maximum -- values crucial to best/worst case planning, which are too often ignored.
  
4. Solution Delivery
• The forecasted values are presented in both tabular and graphical form.
• The forecasting engine may be built into a custom software tool to repeatedly and flexibly perform organization-wide forecasts.
• The forecasting model is delivered to the client, accompanied by a detailed user guide describing how to interact with the tool and a technical document explaining the construction of the model.
  

Long-term Forecasts help you survey what’s to come

• Improve strategic planning and budgeting


• Provide multi-dimensional aggregation and summary of forecasted (and historical) sales data by product, region, and time.
• Determine investments in production capacity, employment levels, facilities, etc.


• For collaborative planning, advanced planning, best-practice replenishment and inventory solutions, to:
• Improve customer service


• Provide a common, consistent forecast to be used by all departments and shared with customers/suppliers if needed


• Be proactive with the status of your Supply Chain

Medium term forecasts assist in preparation

• Achieve efficient operational planning


• Determine employment levels required


• Improve Network Planning, Master Scheduling and Finite Scheduling


• Automate exception reporting and highlight problems before they occur

Short term forecasts allow you to deliver the best product or service

• Reduce uncertainty for NPIs, ventures and product lines


• Determine the most effective promotional mixes


• Perform untenable market research

>>Download our Forecasting Information Sheet