What is Demand Forecasting?
Demand forecasting is a business’s way of having a crystal ball to tell what will happen in the future! It is the art of forecasting the consumer’s future needs for a particular product or service. Businesses consider it the magic trick as it helps them perform excellent inventory management and make the necessary projections for production to achieve optimal profit.
However, according to a report by Supply Chain Dive in 2023, 73% of companies experience problems with accurate demand forecasting. These reports showcase the importance of mastering demand analysis skills given the current high rate of market changes.
Types of Demand Forecasting
Understanding market needs is very important for business planning. Demand forecasting helps companies plan their warehousing operations better. Thus, it is noteworthy that various types of demand analysis are used to determine the demand for different periods and industries. Here are the main types of inventory forecasting:
Short-term Forecasting:
Also known as the Sprinter of Demand Analysis, short-term forecasting is valid for up to three months. It is used for seasonal products such as Halloween costumes or Valentine’s Day chocolates. Meesho seller, Myntra, and other e-commerce platforms use short-term forecasting to increase their sales during festive seasons.
Mid-term Forecasting:
Long-term forecasting ranges from 3 months to 24 months. Car manufacturers use this demand forecasting type to plan the production of their cars and order spare parts accordingly.
Long-Term Forecasting:
Often referred to as the Marathon Runner of Demand Analysis! Long-term demand forecasting remains valid for over two years. Long-Term Forecasting is typically applied in those areas where large-scale planning is required and a good amount of necessary investments must be estimated. Aerospace and real estate are such industries that use it.
Active Forecasting:
Active demand forecasting continually updates the forecasts depending on real-time information. Best suited to industries that are characterized by high fluctuation. For example, the technology sector or the clothing industry. They use it to swiftly alter their production or order more stock as required.
Passive Forecasting:
In Passive forecasting, data changes occur less frequently and are based on historical data. Passive Forecasting stands ideal for industries that do not require them to m an increased amount of product in a short time gap. For example, in the utility and primary necessity industries.
Quantitative Forecasting:
This type of demand forecasting remains dependent on equations and probability theory. Quantitative forecasting is Most useful for industries where large amounts of data are collected. For example, finance, logistics companies and e-commerce as they need to gain the ability to make precise data-backed decisions.
A Mind-Blowing Fact: For context, Amazon processes 1 billion data points every day with the help of a demand forecasting algorithm. That enables them to forecast customer demand and offer products that suit their needs with 90% precision, as the MIT Technology Review noted.
Shocking Statistic: McKinsey & Company’s study shows that companies with accurate demand forecasts can decrease inventory costs by about 25%. That’s a total game-changer for profit margins!
Methods of Demand Forecasting: Demand Forecasting Techniques
Demand forecasting techniques stand out as the essential aspect for anticipating future B2C and B2B market trends and planning accordingly.
Variable methods of inventory forecasting serve different sorts of data and industry requirements. Take a look at some of the key techniques of demand forecasting:
Time Series Analysis:
This demand forecasting technique is like a time machine that allows you to count time intervals. It applies a historical dataset to identify patterns and development. Giants like Walmart use this among all the demand forecasting methods to anticipate their spike in seasonal sales.
Delphi Method:
This is one of the core demand forecasting techniques. In this method, the expert members of the panel contribute their predictions while remaining unidentified to the others. Afterwards, the panel members can adjust the data according to the opinions of the rest of the group members. Tech firms often employ it to forecast future demand for products to be produced by tech companies.
Regression Analysis:
This demand forecasting method focuses on the intensity of the associations between two or more variables. Airlines companies use Regression Analysis to anticipate the likelihood of ticket sales based on factors like economy and climate.
Expert Opinion:
This demand forecasting method involves the opinions and insights of various experts in the field on future demand. The expert opinion method is usually employed where there is little statistical history data, like startup ventures and small businesses.
Market Research:
Surveys and focus groups are considered to collect information on consumer preferences and their buying decisions. Market research methods of demand analysis are another essential method that is commonly applied—used by retailers and FMCG manufacturing companies– to know the overall market trends.
Econometric Models:
In Econometric models, economic theories and statistical methods are applied to forecast the demand. Governments and large companies apply econometrics models to make decisions on new policies or improvements in existing strategies or policies.
Barometric Method:
This demand forecast method uses key indexes to indicate future trends that help it plan its operations. Financial organizations frequently employ the barometric method to make forecasts of the cycles and markets.
Fascinating Fact: A study by Insider Intelligence shows that Netflix saves $1 billion per year from its supply chain by accurately predicting the demands of consumers. They calculate how a viewer would act or what would appeal to them as a way of helping with content generation!
Importance and Benefits of Demand Analysis in Ecommerce Businesses
- Inventory Optimisation: There will be no more stockouts and overstocking. Demand forecasting assists in ensuring that the right proportion of what is exactly needed in the business is ordered and held.
- Improved Customer Satisfaction: Happy customers lead to profitable business! Thus, meeting demand also implies that goods will be available in the market when customers demand them.
- Cost Reduction: Cut that which is not necessary! Product forecasting helps the firm avoid huge logistics and warehousing costs and spoiled items.
Eye-Opening Statistic: The Gartner report reveals that ecommerce companies with good demand planning practices enjoy 15% higher customer satisfaction rates.
Challenges Companies Face in Demand Analysis and Forecasting
- Data Quality Issues: What goes in, goes out! It may be distressing and unmanageable if one ends up with poor or incomplete data for their forecast.
- Market Volatility: Quick market shifts can quickly vanish all the predictions that were made.
- New Product Launches: Demand forecasting for new products is relatively tricky, primarily because of the nature of demand data.
Shocking Fact: ToolsGroup’s research revealed that 41% of companies consider the absence of quality data as their primary issue regarding forecasting.
Example of Demand Forecasting
Let’s better understand demand forecasting with a real existing and successful example:
Procter & Gamble (P&G) implements complex demand forecasting to control its extensive range of products. In the wake of COVID-19, P&G had to change its forecasting to accommodate the ballooning sales of sanitizer and other cleaning goods.
Their secret weapon? It entailed using both, analyzing past market data trends and monitoring current market trends. This approach ensured that, during the crisis, P&G achieved a near-perfect on-shelf availability of 95%, as Supply Chain Dive indicated.
The Bottom Line
To sum up, of all the business operational tools, demand analysis is the compass that leads through the market storms. Many people believe that it is a combination of art and science that relies on numbers along with the seller’s feelings. Get the hang of this, and you’ll sail through a business magnate like a pro.
Remember, even though the world of demand forecasting has no crystal ball, it is more like assembling pieces of a puzzle to gain insight into the future.