8 March 2019

Demand prediction

Demand prediction


Demand forecast estimates about future customer's demand by using historical data, external data sources and any other information that affects directly or indirectly to the company.

An adequate forecasting gives the company valuable information about the potential in its current market and other markets, so that managers can make the right decisions. Without a demand forecast, companies risk making poor decisions about their target markets and products. Forecasting demand means taking into account the level of activity from which we define the other business parameters: fixed and variable costs, investment plans strategy and financing terms, etc. los gerentes puedan tomar decisiones acertadas sobre precios, estrategias de crecimiento empresarial y potencial de mercado. Además permite planificar la producción, con la consecuente reducción de desperdicios y reducción de costes de producción. Sin un pronóstico de la demanda, las empresas se arriesgan a tomar malas decisiones sobre sus productos y mercados objetivo.

There are several reasons why forecasting demand is an important process.

  • It enables companies to optimize inventory more efficiently, increasing turnover rates and reducing warehousing costs.
  • Provides insight into the upcoming cash flow, this means that companies can budget with more accurately.
  • Anticipating demand means knowing when to increase staff and other resources to keep operations running smoothly during peak hours.

Demand forecasting involves not only the indiscriminate collection of data to feed a "black box" but requires, by definition, the processing of that data, its transformation into information.

This involves a constant task of observing the environment (market, economic evolution, competitor movements, regulatory changes, sales system performance, etc.) which, in itself, is a rich source of information for decision making in multiple areas.

The digital revolution is transforming companies and the procedures they use for their management. Advanced data analytics and Artificial Intelligence are becoming key business tools, thanks to which companies increase their productivity, strengthen their markets and position themselves ahead of their competitors. La Analítica Avanzada de datos y la Inteligencia Artificial se están convirtiendo en herramientas clave de negocio, gracias a las cuales las compañías incrementan su productividad, afianzan sus mercados y se sitúan por delante de sus competidores.

It is essential that demand forecasting methods are efficient, inexpensive, accurate and adaptable to market behavior. All these requirements can be covered in analytical models.

Solutions based on predictive analytics models are a key tool for anticipating the future and choosing the best way forward. In this way, greater efficiency is achieved in the different departments and processes, and the company's operational risks are reduced.

The advantages of using demand forecasting methods are

1. Custom supply design based on consumer buying habits.

2. Improve inventory management, increasing turnover rates and lowering warehousing costs.

3. Anticipate the state of the next cash flow. This means that companies can budget more accurately to meet supplier payments and other operational costs.

4. Know when staffing and other assets need to be expanded to maintain operations during production surges.

5. Anticipate possible equipment breakdowns, taking into account data on their activity, so that machinery maintenance can be organized in advance.

6. Detect fraudulent actions or movements and non-payments before they happen in order to put in place procedures to prevent or mitigate them.


Given the uncertainty of current markets, large companies have been forced to use different techniques to reduce this to the lowest possible levels s, among all these techniques we find the use of different predictive algorithms for the realization of statistical models that help the company in achieving the objectives.

By means of demand prediction models the company is able to stop a more precise forecast of the sales levels that it will be able to reach with a certain product and thus be able to adjust the different production processes with what will obtain a significant reduction of costs , another important section that is obtained with this model is the management of the stock which is one of the great objectives of the big companies of sectors as the retail since the existence of a too high stock or too low supposes big costs for the company.

Medium and long term demand predictive models deal with more general aspects since their impact on a company is greater and for its development will be necessary to have a large historical data. On the other hand short-term models tend to be more precise since the factors affecting demand change constantly and by shortening these times it will be easier to anticipate and adapt to them.

Generally these models are carried out quantitatively with historical data and the resulting value is adjusted according to the company's business vision.

Among these models we can emphasize models of prediction of escape of clients, models of prediction of potential clients, models of prediction of satisfaction of the client with the company and models of prediction of demand, this last one is having a great boom in the last years due to its great variety of applications.

If you want to know how demand prediction models can help your business write us and we will advise you personally.