Demand forecast as a profitable business tool

Running a business today is not easy. Challenges, thrown at us by the reality one after another, significantly complicate this process, and it is sometimes extremely difficult to foresee the impact of unfavorable external factors on the market and consumer behavior. One of the most painful points for companies in recent years has been the shift in demand. A growing number of factors, from influencer posts to unexpected circumstances, are causing shoppers to change their buying behavior more frequently.

The problem is that these changes happen quite unexpectedly, and there is no magic tool that could foresee global situations that create risks for companies. But are there other methods to look ahead and adjust your business processes? In this article, we talk about demand forecasting, find out the importance of the process, and look at modern solutions that, based on machine learning algorithms and artificial intelligence, can improve your operational planning in a changing environment.

What is the demand forecast?

It is the process of estimating future demand through the analysis of historical data, information and the influence of additional factors. Effective demand forecasting provides companies with valuable information about opportunities in current and potential markets and helps managers make informed decisions about volume to order, product promotion and overall business strategy.

On the flip side, by ignoring this process, companies risk making wrong decisions in terms of product strategy and target markets. This in turn can create a lot of problems, such as increased storage costs, decreased customer satisfaction, and gaps in supply chain management. In short, the company either loses funds or does not receive them in full.

Historical remark

In general, the trend towards creating separate departments for forecasting demand in companies appeared in the late 80s of the last century. At first, in most cases, forecasts were based on simple statistical models and methods such as moving averages, exponential smoothing, or even instinctive judgment (colloquially called ‘gut feeling’). And then, with the development of technologies in the field of data storage and processing (Big Data), the demand forecasting process has undergone significant changes and has become an indispensable tool for businesses of different industries and sizes.

And if the demand forecasting software market in 2019 was estimated at $3 billion, by 2030 this amount is expected to be more than $14.5 billion (transparency market research). So, further on we’ll outline why you should pay attention to this topic and how demand forecasting can become part of your business processes.

Importance of demand forecast for businesses

Demand is the driver of all business. Not surprisingly, its analysis affects the efficiency of many company processes. Demand forecasting is never 100% accurate (only if it is a coincidence or fraudulent calculation), but it is necessary, because it affects the following:

Budget planning
The data obtained from the forecast helps to make effective financial decisions on operating, production and marketing costs. In addition, a clear picture of expected demand will help plan staff costs and reallocate resources during peak periods of activity.

Developing a pricing strategy
Determining the right price, given the current market activity and demand for your product, is key. Thanks to the demand forecast, you will be able to adjust your pricing policy depending on the situation, as well as set up tools for its implementation in advance, such as discounts, promotions, etc. By understanding the market and potential opportunities, you can set competitive prices and use appropriate value-for-money marketing strategies.

Stock level control
By predicting future demand, you can calculate the optimal amount of goods in stock without creating an overstock. This way you avoid overpaying for excess storage, or, conversely, you can prepare in advance for the hype during a period of increased sales.

It is advisable to use demand forecasting regardless of the business area: be it retail, FMCG, a pharmaceutical company or construction, etc.

Demand forecasting and planning. What’s the difference?

Many people use the concepts of demand forecasting and demand planning interchangeably. However, there is a fundamental difference between the two. And while forecasting is a strategic prediction based on historical data and analysis of related factors, planning is a more tactical process that involves building a plan based on forecast data and developing steps for its implementation.

More about the difference:

Factors affecting demand forecast

There are a number of factors that significantly affect the demand and are taken into account while forecasting. Here are the key ones:

Seasonality  

Demand changes with the seasons. A seasonal brand or cyclical business may have increased activity during peak periods followed by stable or below average sales during the off-season.

Seasonal forecasts take into account products that are more popular during specific periods, holidays or events. And since such products need flexible management of working capacities, resources and storage, effective forecasting will be one of the key tools.

Competitors 

The emergence of new players in direct and related product categories creates more and more alternatives for your customers, which affects demand. The launch of new competitive products or, conversely, the exit of someone from the market can take you by surprise. And a flexible forecast model will allow you to respond faster to changing events.

Type of goods 

The forecasting process will differ for different types of products and services, from perishable goods to subscription services billed on a monthly basis. It is important to know the lifetime value of your customers (total number of purchases per person during a certain period), the size of the average check and the combinations of products purchased. Using the data, you can improve the quality of the forecast and monitor how one SKU is influencing or driving demand for another.

Geography 

The places where your customers are concentrated, the location of production and points of products’ dispatch all affect the forecasting of stocks and the speed of fulfillment of customer orders. And the availability of storage space and fast delivery methods can have a positive impact on the demand forecast.

Types of demand forecast

Depending on the industry, customer base and product specifics, different types of demand forecast are used. Here are the main ones:

Macro-level forecasting
In this case, the general economic situation, external and other large-scale factors that may affect the business are predicted. The analysis of these components provides business with information about local and global risks, opportunities, and also allows you to stay in the context of cultural and market changes.

Micro-level forecasting
The demand forecast at the micro level can be specific to a particular product, region or segment. Usually it refers to one-time or spontaneous changes that can lead to a jump or drop in demand. For example, if you are a local beer producer, and your local team unexpectedly reached the final of the football championship, then you should take care of the availability of goods on the shelves in advance and conduct additional marketing activities.

Short-term demand forecasting
Can be used on macro and micro levels. Usually spans the period of less than 12 months to obtain information about daily tasks. The short-term forecast provides for consultations with sales and marketing departments to better understand their activities, which can increase demand.

Long-term planning
Like the previous one, it can be used for macro and micro levels and is made for a period of more than one year. This type of forecasting helps companies make informed global decisions about expansion, investment, or long-term partnerships. By factoring in a year or more into the forecasting process, a company sees a reliable picture of demand trends that may emerge, for example, after launching a new store or expanding business in other countries.

Demand forecast automation

In the conditions of the modern market, manual methods of interpreting data for forecasting do not cover the needs of companies. A truly flexible and up-to-date approach that takes into account the variability of the environment and the rapid change in customer behavior involves real-time data analysis, that is, the use of technological programs. It also reduces the impact of the human factor and the workload of teams, as well as changes their focus from operational tasks to strategic ones.

An example of such software is SMART Demand Forecast.

The system is based on machine learning and artificial intelligence algorithms. This allows you to take into account all the necessary factors that affect forecast accuracy, including your experience with a particular SKU and product groups.

In addition, Power BI analytics is built into the Demand Forecast system, which allows you to quickly make management decisions based on up-to-date data. And the presence of a universal data structure allows you to store disparate information in a single format and environment.

To learn more about the solution and order a personal demonstration, contact us at sales@smart-it.com.

Summing up

Demand forecasting helps companies make informed decisions that affect everything from inventory planning to supply chain optimization. Today, when customer expectations and behaviors are changing more than ever, having flexible and accurate forecasting software empowers companies to respond quickly to change. And the dilemma of whether to implement systems based on artificial intelligence and machine learning to optimize the demand forecast is turning into a matter of time.