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demand planning and forecasting

Demand Forecasting is a technique for estimating future product demand. But the reliability of the forecasting is heavily reliant on the Demand Forecasting Software you are employing. Multiple sales forecasts, derived from a variety of demand forecasting techniques, are often used by supply chain managers to provide a more precise demand prediction. 

The accuracy of a forecast is proportional to the clarity of the data used for demand planning and forecasting. Demand Forecasting Software enhances your forecasting accuracy, just like one by TransImpact, which promises 99% accuracy. 

The first thing for demand planning and forecasting is to figure out your most pressing questions. At this stage, you will realize the types of demand forecasting most beneficial for your business and how to use them most effectively. 

Forecasting in Supply Chain Management  

Foreseeing future product demand by analysis of historical data is the essence of supply chain forecasting, which informs strategic choices in areas like resource allocation, purchasing, and stock levels. Integrating Demand Planning Software makes Supply Chain Operations smoother. 

Ecommerce relies heavily on accurate supply chain forecasting, a crucial part of supply chain management. Without the capacity to foresee future demand, price patterns, and supplier availability, it is difficult to maintain a seamless commerce supply chain. 

What Are Quantitative and Qualitative Forecasting Methods? 

Brands may use demand forecasting systems to improve their data- and research-driven decision-making across the board, from analyzing the market competition to future demand forecasting using past order data, trends, and patterns.

Quantitative and qualitative data are considered in the various forecasting methodologies for the supply chain. 

TransImpact Demand Forecasting Software considers both quantitative and qualitative factors while forecasting Demand. So, what exactly do these terms mean? Take a look: 

  • Quantitative Forecasting: 

Sales forecasts are only one example of future predictions made using quantitative forecasting. It relies on mathematics to produce a pre-set forecasting assessment based on the premise that the future would mainly mirror the past. 

  • Qualitative Forecasting: 

Since no previous data is available, qualitative forecasting is often utilized for new product lines or when a firm initially debuts. Qualitative information is often gathered via interviews and surveys, but it may also be gleaned through industry benchmarking and competitive assessments, among other methods. 

Types of Quantitative Forecasting Methods 

Quantitative approaches, including the utilization of past data, time series, or correlational analysis, are what most businesses check out when they consider forecasting. 

Better choices may be made for both short-term and long-term planning using data-driven insights. 

In ecommerce supply chain management, you may use a few quantitative strategies for foresight. The most popular approaches, when to use them, and how are outlined below: 

Exponential Smoothing Method 

Supply chain forecasting is complex, but exponential smoothing makes it easier. A Demand Planning System helps with exponential smoothening. 

Data-driven predictions may be made more quickly and with less effort than other quantitative approaches, which sometimes require combing several data sets. 

The exponential smoothing approach is simple to implement and works well for making short-term predictions when the correct instruments are used. This is easily achievable with TransImpact Demand Forecasting Software. 

Adaptive Smoothing Method 

The adaptive smoothing technique considers several factors when making a forecast. It delves more deeply into variations throughout time to reveal distinct patterns. 

The automated technologies needed to capture, gather, and aggregate data in real time are essential to this approach, since it enables firms to zero in on certain factors to make better choices. 

A company can reliably forecast outcomes across a wide range of products by using adaptive smoothing and automating the process. 

Moving Average Method 

When it comes to supply chain forecasting, the moving average is one of the easiest ways. It takes whole datasets and averages out subsets to investigate individual data points. Every month, quarter, or year, the average is computed and utilized to produce a forecast for the next period of time. TransImpact Demand Forecasting Software helps you efficiently with this phase. 

Suppose you launched your company in the first quarter and are trying to anticipate sales for the fourth quarter. In that case, you may do so by averaging the sales from the three preceding quarters (though you should also consider seasonal sales spikes like Black Friday and Cyber Monday). 

Recent data may be a stronger indication of the future, but the moving average approach doesn’t account for it. No consideration is given to seasonality or tendencies. That’s why this approach of demand planning in the supply chain excels only at managing stock levels for infrequent purchases. 

Regression Analysis Method 

When doing a regression analysis, it is necessary to consider the connection between two or more independent factors. All regression analyses, regardless of methodology, look at how one or more independent variables affect the dependent variable. 

This basic supply chain forecasting approach considers pre-existing assumptions like seasonality to quantify a few key findings. It provides a simple and quick forecasting approach, especially compared to other methodologies. You can use TransImpact Demand Forecasting System for better analysis. 

Life Cycle Modelling Method 

Life cycle modelling is a technique used in supply chain forecasting that simulates the evolution of a product across its lifetime. It calls for information from various market segments, including innovators, early and late adopters, and established and emerging consumers. 

Brands may use this information to anticipate better how and where to distribute and sell their goods and how long those items will remain popular. 

Types of Qualitative Forecasting Methods 

Supply chain forecasting relies heavily on quantitative data for its accuracy, although qualitative data has also been valuable. 

Most ecommerce companies employ a mix of quantitative and qualitative techniques to make the most accurate forecasts they can. 

However, qualitative forecasting techniques are helpful when there is a shortage of data. New enterprises and novel items often use qualitative methods of forecasting. 

Most qualitative forecasting techniques utilized in the ecommerce supply chain are outlined here: 

Market Research Method 

Market research is an excellent practice for all businesses, regardless of whether they provide products or services. 

Online retailers may use market research to forecast inventory levels and establish if a product will sell well enough to generate a profit. 

Businesses may use in-house marketing for market research, or they can contact an outside firm. 

Strategies might vary from creating surveys for critical stakeholders to analyzing the market to talking to professionals in the subject. Market Research is convenient with demand planning tools. 

Delphi Method 

Market perspectives and assessments from a select panel of experts or advisers are compiled and examined by a separate panel of experts using the Delphi technique. 

A third party is tasked with collecting views and analyzing the data gleaned from doing so. 

The data is examined meticulously, summarized to identify recurring patterns or trends, and then sent to the company for further inspection. 

This technique is successful and reliable for future projections. 

Historical Analysis Method 

One method of forecasting future sales is looking at similar products’ past performance. 

The results may gauge how customers will react to a brand-new offering. Our Demand Planning Software uses advanced algorithms to analyze this historical data. 

Suppose you can get your hands on sales records. In that case, you may also obtain information about future demand by analyzing the items that have performed well for competitors in the past and comparing them to comparable products in your own range. 

Panel Consensus Method 

To arrive at an accurate prediction, the panel consensus approach polls employees at various levels of an organization. Everyone involved may freely share their thoughts and make educated guesses. 

Collaborating with your ecommerce customer care department, for instance, may help you learn which goods are being returned most often and why, and can also provide you with information about what your consumers are asking for. 

Difficulties in Supply Chain 

Inaccurate supply chain forecasting may impact on a company’s bottom line, reducing profits for a whole quarter or half a year if not addressed quickly. Many popular businesses run out of stock during their annual clearance periods while investing much in advertising to drive demand. 

On the other hand, having stock arrive ahead of schedule might raise storage fees or result in lost sales if the item in question has a limited shelf life. It also prevents money from being spent in ways that might help your firm grow or thrive. This is where TransImpact Demand Forecasting System comes in to help you with accurate demand planning and forecasting. 

How Does Accuracy in Demand Planning Impact the Supply Chain? 

  • Managing the flow of goods from point A to point B involves more than merely tracking supplies and organizing shipping. It affects every area of today’s running of a firm. The value that Supply Chain Managers provide for their companies depends on their ability to predict future demand accurately. 
  • With the help of accurate Demand Forecasting Software, the supply chain management may establish a reorder point to avoid backorders of items or components while still maintaining a minimum inventory level. 
  • The accuracy of demand projections has a bearing on almost every facet of supply chain strategy. Instead of relying on past sales numbers or guesswork, supply chain workers may use demand projections to inform their decision-making in the future. 
  • The Demand Planning Tools help the supply chain management outline the activities required to have enough inventory on hand and satisfy customer demand. They include all relevant parties in the demand planning process. 
  • Rapid changes in customer demand are no match for demand forecasting. As one concrete example, recent studies have shown how a hybrid demand forecasting model may provide reliable predictions despite substantial market volatility and inherent uncertainty. 
  • A vital component of a well-thought-out supply chain is the demand planning phase. The ultimate goal of end-to-end planning is to provide a seamless and satisfying experience for the consumer from the first concept to the final delivery. 
  • Demand Forecasting tools enable you to use the insights gleaned from market research analytics and put them into practice via the demand planning process, enhancing the efficiency of the supply chain’s operations at every stage. 

TransImpact offers Demand Forecasting Software that uses more than 250 advanced sales forecasting algorithms. It forecasts for up to 5 years with 99% accuracy. 

To know more, schedule a free demo with us! 

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