What is a demand forecast?
A demand forecast is the prediction of what will happen to your company's existing product sales. It would be best to determine the demand forecast using a multi-functional approach. The inputs from sales and marketing, finance, and production should be considered. The final demand forecast is the consensus of all participating managers. You may also want to put up a Sales and Operations Planning group composed of representatives from the different departments that will be tasked to prepare the demand forecast.
Determination of the demand forecasts is done through the following steps:
• Determine the use of the forecast
• Select the items to be forecast
• Determine the time horizon of the forecast
• Select the forecasting model(s)
• Gather the data
• Make the forecast
• Validate and implement results
The course aims to give participants an appreciation of modern business forecasting methods. More explicitly, it aims to ensure that the successful participants are capable of developing a validated quantitative set of forecasts using both extrapolative and causal forecasting methods (Econometric method: Electricity Demand versus Country GDP and Population). By the end of the course participants should be able to apply a simple forecasting method to support demand management.
Who should attend:
In the second part of the course, you learn to identify, demand forecasts and market uncertainty, and develop corresponding forecast scenarios rising from market uncertainty using commonly statistical tools and computer software applications for time series and econometric models.
Our training is supported with a delegate manual to provide each participant with all notes, exercises and activities included so the participants can refer to it during the programme performance and in the future.
Participants will learn by highly active participation during the programme through a combination of lectures, training videos, practical exercises, group discussions of ‘real life’ issues that are based on actual systems/accidents relevant to their organizations role- playing in a workshop environment (especially, for electricity utility). At the end of the programme there will be self and peer assessments for a personal action and personal development plan.
2. Forecast Analysts
3. Strategic Planning Analysts
4. Director of Forecasting and
5. Director of Value Chain
6. Analysts in the Supply Chain
7. Inventory Planners
8. Operations Planners
9. Financial Analysts
10. Director of Logistics
11. Director of Customer Service
What is demand planning & forecasting?
Demand planning and forecasting is a set of business processes that involve predicting future demand and aligning production and distribution capabilities to meet that forecast. Involving a number of different business functions this requires the sharing of timely data, the accurate processing of that data, and agreement on joint business plans.
The process consists of three parts:
1. Demand forecasting: The art in the process for creating a statement of projected, unconstrained, demand for a product or service over time
2. Demand planning: The science involved in restricting (or increasing) a forecast to reflect known constraints and associated impacts of capacity (production or logistics) or changing priorities or the impact of external events
3. Demand management: The creativity involved in influencing the demand by the addition (or cancellation) of activity, the increasing or reducing of price, the rationing or allocation of stock, etc.
4. Strategic planning (short, medium and long term)
How is demand forecast determined?
There are two approaches to determine demand forecast –
(1) The qualitative approach,
(2) The quantitative approach. The comparison of these two approaches
A- The time series model and
B- The causal model (especially, Econometric model).
Syndicate exercise: Working in small groups.
Qualitative Forecasting Methods
Your company may wish to try any of the qualitative forecasting methods below if you do not have historical data on your products' sales.
Qualitative Method Description
Jury of executive opinion The opinions of a small group of high-level managers are pooled and together they estimate demand. The group uses their managerial experience, and in some cases, combines the results of statistical models.
Sales force composite Each salesperson (for example for a territorial coverage) is asked to project their sales. Since the salesperson is the one closest to the marketplace, he has the capacity to know what the customer wants. These projections are then combined at the municipal, provincial and regional levels.
Delphi method A panel of experts is identified where an expert could be a decision maker, an ordinary employee, or an industry expert. Each of them will be asked individually for their estimate of the demand. An iterative process is conducted until the experts have reached a consensus.
Consumer market survey The customers are asked about their purchasing plans and their projected buying behavior. A large number of respondents is needed here to be able to generalize certain results.
Quantitative Forecasting Methods
There are two forecasting models here – (1) the time series model and (2) the causal model. A time series is a s et of evenly spaced numerical data and is obtained by observing responses at regular time periods. In the time series model, the forecast is based only on past values and assumes that factors that influence the past, the present and the future sales of your products will continue.
On the other hand, the causal model uses a mathematical technique known as the regression analysis that relates a dependent variable (for example, electricity demand) to an independent variable (for example, GDP, population, price, etc.) in the form of a linear equation. The time series forecasting methods are described below:
Time Series Forecasting Method Description
Naïve Approach Assumes that demand in the next period is the same as demand in most recent period; demand pattern may not always be that stable
If July sales were 50, then Augusts sales will also be 50
Time Series Forecasting Method Description
Moving Averages (MA) MA is a series of arithmetic means and is used if little or no trend is present in the data; provides an overall impression of data over time
A simple moving average uses average demand for a fixed sequence of periods and is good for stable demand with no pronounced behavioral patterns.
F 4 = [D 1 + D2 + D3] / 4
F – forecast, D – Demand, No. – Period
(see illustrative example – simple moving average)
A weighted moving average adjusts the moving average method to reflect fluctuations more closely by assigning weights to the most recent data, meaning, that the older data is usually less important. The weights are based on intuition and lie between 0 and 1 for a total of 1.0
WMA 4 = (W) (D3) + (W) (D2) + (W) (D1)
WMA – Weighted moving average, W – Weight, D – Demand, No. – Period
(see illustrative example – weighted moving average)
Causal Forecasting Method Description
Econometric Approach Regression analysis is conducted for each consumption sector (sales) with respect to its economic and demographic factors.
The regression equation used for each consumption sector is expected to be according to the following equation:
E (i) : Sector energy consumption at the year (i)
GDP(i) : Sector GDP at the year (i)
POP(i) : Population in million inhabitants at the year (i)
a, b and c : Regression coefficients
Data Analysis for Demand Forecasting
Measuring forecast Performance
Measuring forecast accuracy
The key to good forecasting is stability in the accuracy, as this will help set correct inventory levels, thus avoiding over-stocks and out-of-stocks. Where forecasts are consistently higher than the actual sales, inventory levels will rise; where forecasts are consistently lower than actual sales, the service levels issues will increase.
Problem Solving, exercises and case studies
Group exercises and discussions
Ashraf Salah Eldin - Professor of Economics and Finance
Dr. Ashraf is considered an expert in the Fields of Research for several subjects such as Export Finance and Promotional Schemes, Investment, Managerial Finance, Financial Institutions Management, International Economics and Trade Agreements, Money & Banking, International Banking, Feasibility Studies, Public Finance, Tax Systems and Economics of Resources and Environmental Issues.
Moreover, he masters most of the commonly used statistical tools and computer software used for econometric applications such as SPSS, TSP, Micro Stata, GAMS, etc. Furthermore, he is a Professional user of the Computer Model for Feasibility Analysis and Reporting (COMFAR), developed by the United Nation.
Dr. Ashraf received his PhD in Economics from the University of Manchester, UK, Master of Social Science (MSocSc) in Money Banking and Finance from the University Of Birmingham, UK.
Dr. Ashraf is approved consultant and trainer with PROJACS and several well-reputed universities. He also provided training and consultations for many multinational private and government organizations in different parts of the World.
He provided various number of Feasibility Studies in Saudi Arabia and other Arab countries for companies, groups and organizations. He is a consultant for Trade Finance Maps, International Trade Center (ITC), UNCTAD-WTO in Geneva, Switzerland. Export finance and feasibility studies consultant for a number of local and international companies and organizations such as; Industrial Modernization Center (IMC), UNIDO, Elmadina Elmonaoura City Council (Saudi Arabia) and Ministry of Planning (Kuwait). Finally, a consultant, reviewer and advisor for the Fulbright Commission and the Fulbright Exchange Program.
** In the event of uncontrollable circumstances, we may have to change main lecturer(s) for reasons out of control but replacement will always meet global standards of PROJACS International.