Demand forecasting is a technique that demand planners and supply chain professionals use to estimate the probable demand for a product or service in the future, based on historical data. When done correctly, demand-forecasting can help businesses make informed decisions and overcome supply chain constraints. Some factors that can affect demand forecasting are seasonality (on-season vs. off-season), geography, competition, economic conditions and types of goods. Some types of demand forecasting include:
Accurate demand forecasting helps managers allocate resources effectively, control costs and compare actual performance with expected performance. Demand forecasting allows top management to determine if the business is ready for expansion. It helps in devising sales and marketing plans and budgets.
Improper demand forecasting can do more harm than good. It can result in wastage and negatively affect a company’s profit margins and cash flow. To help you demand forecast accurately, we have compiled a list of some common demand forecasting mistakes to avoid. Take a look.
Although analyzing the past is usually a reliable way to predict future demand, you should not base your forecast solely on historical data. If you sold more units of a product than usual last year, try to find out the factors that led to an increase in demand and determine how relevant they are in the present situation, instead of automatically assuming that the demand for the product will continue to rise the next year. One of the biggest names in the camera industry – Kodak – filed for bankruptcy in 2021 (INTERNAL QUESTION: is this the year they filed? Or was it much earlier than this?, because the top management refused to adapt Kodak’s business strategy. The 2000s saw the rise of digital cameras, but the company stubbornly clung on to its traditional cameras. The top management wrongly assumed that Kodak’s outdated cameras would sell like hot cakes despite the evolving market.
One way to ensure the accuracy of your demand forecast is to pay close attention to the reasons consumers buy your product. When the demand for a product decreases, many companies automatically assume that there’s something wrong with it. Before arriving at a conclusion, businesses should analyze every factor that drives the demand for the product. Coca-Cola learned this the hard way. As part of the ongoing Cola wars, Pepsi launched the Pepsi Challenge in 1975. Participants were asked to take a sip of two unlabeled drinks – Coke and Pepsi – and then pick the drink that, according to them, tasted better. Most participants picked Pepsi. Coca-Cola automatically assumed that the product was the problem and launched a new drink. A retaliatory campaign was also rolled out. Coca-Cola’s campaign involved measuring the new drink’s effectiveness through blindfolded taste tests. The strategy backfired and consumers rejected the new drink (dubbed the New Coke). As a result, Coca-Cola was forced to bring back the original drink in less than three months.Coca-Cola made a big mistake by automatically assuming that the original drink was not up to the mark. Had Coca-Cola dug deeper, it would have found a fundamental error in the methodology. People who took the Pepsi Challenge were asked to take a sip of the drinks. It turned out that consumers felt differently about them when they took multiple sips of the drinks.
Base your forecasts on both qualitative and quantitative research. If you do not have past sales records, study the market. Conduct market research and analyze the factors that contribute to your competitor’s success. In 2020, former Disney chairman, Jeffrey Katzenberg launched the streaming platform Quick Bites, popularly known as Quibi. The platform delivered short-form scripted and unscripted content to mobile devices. In just seven months, Quibi was forced to shut down. A fundamental mistake that Quibi’s top management made was building demand forecasts around ideal sales. Quibi failed to stay grounded in reality. The management overestimated the amount required for production and paid the price.
Here are our top tips to steer clear of demand forecasting mistakes:
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