Demand forecasting as part of better supply chain management
Demand forecasting is crucial to any highly effective supply chain management strategy. Done right, it can bring about cost-savings, opportunities for growth, and more resilience in times of economic turmoil. Here’s everything you need to know to understand how to improve your demand forecasting capabilities.
Efficient supply chain management is an important factor in operational health at all times, but it’s especially critical in times of economic uncertainty. It can help businesses lower costs, boost profitability, and ensure that available working capital is used to optimum effect. But, perhaps most importantly, it can increase supply chain resilience – protecting against market risks and making it easier to adapt to changing conditions.
Supply chain management comprises parts including supplier management, sourcing, procurement, the accounts payable process, manufacturing, and the delivery of finished products. Fundamentally, it’s all about organizing supply chain activities to meet customer demand.
Finding ways to fine-tune your supply chain’s output to better align with demand is one of the most effective ways to bring about operational efficiency. With the ability to accurately forecast future demand, you can optimize supply chain activities for revenue, consistently meet customer expectations to drive loyalty, and avoid costly overproduction.
What is demand forecasting?
Demand forecasting is the process used by businesses to predict future demand for a product or service. With improved demand forecasting, businesses can estimate future demand more effectively. As a result, they can make better-informed decisions across procurement, manufacturing, inventory management, and more.
A systematic approach is needed to create accurate and relevant forecasts. As such, the process typically involves the following steps:
- Setting objectives
- Determining duration
- Selecting the method
- Collecting data
- Analyzing the results
There are various demand forecasting methods, but they invariably rely on data. This can take the form of historical sales data or insights gathered through proactive research. The more available data, the more likely it is that demand forecasting efforts will be accurate and valuable.
Why demand forecasting is important in supply chain management
Without effective demand forecasting as part of their supply chain management process, businesses lack the information they need to plan procurement and manufacturing optimally. This, in simple terms, exposes them to cash flow risks.
Accurate demand forecasting predicts the quantity of finished inventory required to meet market demand. This means businesses can optimize their inventory management strategy to avoid over or under-stocking, which can be costly, and minimize inventory carrying costs.
But demand forecasting also allows for improved decision-making in other areas of operation. Knowing how much you need to spend on inventory to meet demand means you can more confidently make the most of whatever working capital is left over.
It’s essential for businesses whose products feature fluctuating demand throughout the year, whether cyclical or seasonal factors affect them. In these cases, demand forecasting provides a much-needed insight into how to adjust supply chain activities strategically to ensure minimized costs during downtime and maximized order fulfillment when things are busy.
Types of demand forecasting in supply chain management
Supply chain demand forecasting can be approached in various ways. Four of the most popular forecasting models used in predicting demand are:
Trend projection is the most straightforward method of demand forecasting, involving projecting future demand based on historical sales data. However, since this method assumes that the factors responsible for past trends will continue in the future, historical anomalies need to be considered, and a degree of uncertainty is inherent.
Demand can be forecasted through surveying customers or conducting other types of primary research. This comes with the added benefit of providing insights into customer demographics, which can be leveraged in marketing. However, collecting and analyzing the information can be costly and time-consuming – and the results may also be skewed by respondents’ biases or small sample sizes.
Sales force composite
The sales force composite method leverages the expertise of internal sales teams – who are arguably closest to the market – to create a demand forecast. This approach can provide valuable insights and may be broken down into specific products and geographic locations. On the other hand, sales force composite forecasts are subjective, based on individual opinions, and they come with the risk of sales agents deliberately depressing projections in the hope that lower sales targets will be set.
Barometric forecasting creates a rounded demand forecast using a combination of leading indicators (predicted future events), lagging indicators (historical data), and coincidental indicators (indicators that rise or fall in line with economic activity). However, this approach requires the indicators to be analyzed accurately. Variations may hinder the forecast accuracy in the lead time between different indicators.
How to forecast demand more accurately
There is a range of ways businesses can work towards improving the accuracy of their demand forecasting. They include striving to:
Understand the factors that influence demand
Demand can be impacted, sometimes significantly, by various external factors, including levels of employment, consumer confidence, seasonality, the rate of inflation, and interest rates. Demand can also be stimulated by increased market competition and the consequent lowering of prices. It is, therefore, essential that businesses understand these factors and account for them in their forecasts.
Make full use of available data sources
All available data should be leveraged in supply chain demand forecasting, including historical sales data, demand trends, market competition figures, and digital analytics. The more data plugged into forecasts, the more accurate they’ll be. Improving the accuracy of each individual data input can also help to improve the accuracy of the forecast.
Align forecasts with business plans
Existing business plans should also be integrated into demand forecasting. For example, businesses can generally expect demand to increase if a marketing push has been planned for a certain period. To properly understand the internal factors that will impact demand, businesses must proactively share information between sales, marketing, procurement, and finance.
Learn from the process
The accuracy of previous demand forecasts can inform future efforts. If a business has been consistently underestimating demand, a closer inspection of the data might provide clues as to the reasons why. The best demand forecasting programs are iterative – in other words, they are refined over time to ensure that the results become more accurate.
The benefits of better demand forecasting
Demand forecasting in supply chain management is essential for all businesses. For one thing, a better understanding of future demand can help businesses optimize their inventory levels. By ensuring that inventory is maintained at the correct levels, they can minimize carrying costs without adversely affecting the fulfillment of orders.
In addition, businesses can improve customer loyalty and satisfaction by accurately predicting upcoming demand spikes and uptrends or factoring in seasonal fluctuations to maximize timely order fulfillment. This, in turn, helps to maximize sales and revenue.
Finally, effective demand forecasting can also support better working capital management. With a more accurate prediction of future demand and expected inventory and manufacturing costs, companies will be better placed to put their working capital to the best use, from optimizing returns on excess cash to investing in growth.