- 5 May 2017
- Written by: Supply Chain
- Categories: eLearning, Supply Chain
The presence of various internal and external risks such as high competition, inflation, recession and industry changes has resulted into challenging situations for businesses. Risks and uncertainties have an adverse impact on the evolution of organizations in terms of profitability and sustainable growth. One way to better cope with these complex situations is by implementing an effective forecasting plan. For instance, demand forecasting can help to predict what will happen to the company’s existing product sales. In other words, a company can lessen the adverse effects of risks by determining the demand or sales prospects for its products and services in the future. In this way, there is a better control on the business operations which encourage productivity as well as profitability, leading to competitive advantage.
Demand forecasting is a systemic process which gives businesses valuable information about the markets in which they operate and the markets they plan to pursue. If businesses do not use an effective demand forecasting and estimation, they risk entering markets that do not need their products. History is filled with stories of companies that have made serious strategic errors because of inaccurate industry-wide demand forecast.
For instance: The petroleum industry invested $500 billion worldwide in 1980 and 1981 because it expected oil prices to rise 50% by 1985. The estimate was based on forecasts that the market would grow from 52 million barrels of oil a day in 1979 to 60 million barrels in 1985. Instead, demand had fallen to 46 million barrels by 1985. Prices collapsed, creating huge losses in drilling, production, refining, and shipping investments (Source: Harvard Business Review). Such an example emphasizes on the importance for organizations to ensure that an effective and precise demand forecasting plan is put into place to be able to make accurate decisions about pricing, business growth and market potential.
Demand forecasting is indeed an area of high significance; that is why organizations are increasingly investing in training and development programs to train employees in this area. Demand forecasting training using modern learning solutions such as e-learning, webinars, gamifications and simulations, can prove to be as effective as instructor-led training. Nowadays, more and more large corporations are opting for modern learning solutions due to its practicality, flexibility and accessibility. For example: At Procurement Academy, demand forecasting training is delivered in the form of interactive methods such as scenario-based training and simulations where employees have the ability to practice the skills they are learning and apply it directly to their job roles. Such training bridges the gap between theory and practice where employees are more apt to apply their knowledge and skills to their jobs.
An effective training and development program in demand forecasting certainly upskills employees to the expected level so as they can cope with any situation. Having an accurate demand forecasting in place can lead to several advantages:
- Increase customer satisfaction
- Inventory Control
- Scheduling production more effectively
- Lowering safety stock requirements
- Managing shipping better
- Improving pricing and promotion management
- Negotiating superior terms with suppliers
- Plan sales strategies
To achieve all these benefits, organizations should first make sure that they have proper resources to make it happen. One of the most important elements is the presence of competent employees who have the required skills and knowledge to deliver positive outcomes. Upskilling employees through training and development programs can prove to be a good way to make them reach this level. For example: the demand forecasting training at Procurement Academy provides an in-depth approach to make learners understand the essence of demand forecasting and how to implement different strategies for optimum results. The courses include the following:
- Demand Forecasting – Definitions: Learn about all the key considerations of making a forecast by seeing a real example. Understand the different types of forecasting methods – both quantitative and qualitative. Learn how to make decisions to ensure that the forecasts you make have the most impact. Understand how different departments use the forecast so that they best meet the organization’s needs.
- Demand Forecasting – Quantitative Methods: Demand, in many cases, follows a pattern. Learn how to make accurate forecasts by using trends, cyclicality and seasonality. Learn to apply critical thinking to separate patterns from noise. Learn how to use quantitative forecasting methods such as the naïve, average, moving average, weighted moving average, and exponential smoothing. Learn when, and when not to use each method.
- Demand Forecasting – Qualitative Methods: Use the inside information of experts, executives, and customers themselves to make your forecasts more complete. Especially when launching new products or existing products in new markets, relying on historical sales data will not provide the complete picture – you will also need to use qualitative methods. Learn how to use qualitative forecasting methods such as the Jury of Executive Opinion, Delphi, and Salesforce composite. Understand when to use customer surveys and test marketing to enhance forecasts. Learn to spot when personal incentives can bias forecasts and how to correct it.
- Creating consensus forecasts: Learn how to create a highly accurate consensus forecast – that is, one that combines different sources of information. You will learn about top-down and bottom-up forecasts including the advantages and disadvantages of each. You will understand key decisions such as the forecasting horizon, interval and level.
- Measuring Forecast Accuracy: Forecasting accurately is one of the most important competences an organization can develop. And, you cannot improve your forecasting unless you measure accuracy. You will learn how to determine how large (Mean Absolute Percentage Error) and in which direction (forecast bias) your errors are. You will learn which forecasts to measure – that is which time span, how often to measure, and which levels to measure. You will learn about potential causes of forecast error and how to correct them.
- Improving Forecast Model accuracy: The business environment is constantly changing…is your forecasting model changing with it? Are you using demand data to make your forecast…or sales data? In this course you will learn about how to improve your forecasting model by keeping it updated, using the right data, separating out products with different patterns, and more. Watch as the team solves real issues with their forecasting model leading to consistently accurate forecasts.
- Improving the forecasting process: Go beyond just forecasting demand to pro-actively shaping it! The truth is that no matter how good your forecasting techniques, models and processes are, you will never have a 100% accurate forecast, so reduce your dependence on it. Also, learn how to influence business practices that may be the root cause of forecast inaccuracy (hint: practices that contribute to the Bullwhip effect). In this advanced level course, you will learn how to diagnose and solve problems in the process of demand forecasting. You will also learn how to use Big Data and the Internet of Things to improve forecasting accuracy.
- Advanced Time Series Methods: This course explains advanced methods such as Holt’s 2-factor method, and the Holt-Winters method in a simple, clear way. Trends tend to slow down over time, so this course explains how to use damped trends to ensure your forecasts stay accurate longer. Full mathematical calculations and complete example calculations are provided in downloads within the course, providing learners with everything they need to apply these methods.
- Using Simple Regression in Forecasting: Improve the accuracy of forecasts by identifying factors such as advertising that affect demand, and calculating the impact they have on demand.
- Using Multiple Regression in Forecasting: Further improve the accuracy of forecasting by accounting for many different causal factors, such as advertising, discounts, and the state of the economy. Test how good your forecasting model is.
Sound predictions of demands and trends are now necessities for organizations to cope with seasonality, sudden changes in demand levels, strong competition, strikes or recession. An effective and accurate demand forecast comes with a performing training and development program which is capable to upskill employees for best practices. This will positively impact the bottom line of the business; ensuring that business operations run smoothly, boosting growth and profitability.