Introduction to Forecasting and Demand Planning 上海市信息技术培训中心 021-52550057 www.sittc.com Agenda 1. Forecasting basics. 2. The demand management process. 3. The demand planning cycle. 4. Maintaining a high quality forecast. Agenda Forecasting basics. The need for a forecast. The forecast dilemma. The principles, components, aggregation, sources of data and KPIs of a forecast. The demand management process. The demand planning cycle. Maintaining a high quality forecast. The show stoppers. The Need for a Forecast Forecasting in FMCGs is of a great importance to the business: 1.It gives the organization the needed Visibility to future demand and requirements, hence capacities, budgets and utilizations can be planned. 2. Forecast is used to ensure products availability OTIF(On Time In Full Delivery). 3. Used to estimate the Financial Forecast. 4. Used by business partners in both the upstream and downstream to better Plan their resources ahead. The Forecast Dilemma Different functions have different views of the forecast where the chances of selling more are equal to the chances of selling less. A conservative forecast can result in out-of-stocks and missing sales opportunities, while an optimistic forecast can result in higher stocks level and SLOBs Forecasting Basics Components All forecast consists of four components that shape it: 1.The basic value: Which controls the vertical placement of the forecast. Forecasting Basics Components All forecast consists of four components that shape it: 1.The basic value. 2.The seasonality: Which reflect the seasonality of the demand. Seasonality doesnt only mean weather seasonality, but any event affecting the demand seasonality in general. It usually repeats itself year on year. Examples include: The back to school season. The Dubai shopping festival season. Christmas Forecasting Basics Components All forecast consists of four components that shape it: 1.The basic value. 2.The seasonality. 3.The trend: It controls the growth of the demand and usually governed by the market growth rates and the organizations market share growth rates. Forecasting Basics Components All forecast consists of four components that shape it: 1.The basic value. 2.The seasonality. 3.The trend. 4.The business cycle: Cycle are usually long term, and are generally very hard to predict and are macro trends. Forecasting Basics -Aggregation Aggregation of forecast is very important especially since the forecasted units are usually too many. Aggregated products should share the common characteristics and demand patterns. Aggregation will not only provide more accurate forecast, but it will save lots of time too. Forecasting Basics Sources of Data Obtaining data is an integral part in building a quality forecast. Using fact-based assumptions helps in validating qualitative inputs and quantifying. Documenting assumptions is an important task that DP must apply. Forecasting Basics KPIs Forecast bias Forecast accuracy Month-on-month forecast changes Agenda Forecasting basics. The demand management process: The four components of demand management. The S which is cannibalization. An innovation and promotional grid must be always in place to insure that the big picture is there, and in order to be able to asses cannibalization effect properly. The Demand Planning Cycle Forecast is a cross-functional responsibility, hence final demand plans must be aligned with the team. Demand consensus is an integral part for a successful S&OP process. The Demand Planning Cycle Communicate the demand to the supply side of the organization as an unconstrained demand plan. The Demand Planning Cycle Include the supply constraints to reflect reality to your “Constrained demand plan” The Demand Planning Cycle Now as the plans are agreed, communicate to the sales team the companys agreed plan Agenda Forecasting basics. The demand management process. The demand planning cycle. Maintaining a high quality forecast: 10 steps for improved bias & accuracy Classification of the losses Maintaining a Quality Forecast Maintaining a quality forecast is an endless journey: Validate your baselines statistical model using historical data. Validate the assumptions related to your events building blocks. Validate the assumptions related to market & economic insights. Regularly update and correct your forecast. Work on improving your FA & FB. How to Minimize Bias? Start by analyzing your data along with the assumptions. 1.Investigate top-down VS bottom-up. 2.Investigate VS previous periods and growth rates. 3.Insure sustainable supply for products with bad stock-out history. How to Minimize Forecast Error? 1.Eliminate sources of bias. 2.Start a housekeeping cleaning activity. 3.Investigate at a brand level looking for cross- cannibalization. 4.Review your products proportional factors. 5.Analyze your time buckets sales. 6.Post analyze your promotions and innovations. 7.Rationalize your p