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CBT SCM Demand Forecasting


CBT DF (Demand Forecasting)

CBT Demand Forecasting is a tool for fast compilation and convenient visualization of product demand forecast with the help of mathematical forecasting models set and quick input of necessary adjustments based on available operational data.

Many companies look at future sales through the prism of past sales, for example, based on the previous month or a similar month last year. This statement is true for small companies or top-level strategic planning. But as soon as a company faces expansion: instead of dozens of SKUs and business units – hundreds or even thousands, or when you need to decompose a top-level plan to a detailed level taking into account a dozen factors – companies need software tools that can do it. It turns out that if your company does not have a built-in planning process – you still plan.

And the accuracy of the planning result directly depends on the completeness of information, influencing factors, transparency of the process, the interaction of departments, supply chains, etc.

In nine out of ten cases when implementing business systems for customers, we are faced with a case of launching new products. And the first thing we hear from experts is a request from their management, which reads: “How will these new products be sold?”.

This is literally a request for a sales schedule in the future, in terms of periods and regions. In the future, that means planning. In solving this case on the one hand, we have to face the lack of history of the new products sale, and in this case we can choose similar characteristics of products or group of products, and if not – the dynamics of sales can be seen from competitors. But then, we need to put it all together, divide it by region and by period. On the other hand, we need to understand what result in sales growth we will get if we hold campaigns to support the launch five days before the launch, the day of the launch, five days after the launch, fifteen, etc. .

Прогнозування продажів з урахуванням всіх необхідних факторів, що впливають для великого інформаційного потоку неможливо без автоматизованої системи. А якщо немає системи – немає і відповіді на питання: “Як будуть продаватися ці новинки? “.

Capabilities .

Analyze actual sales;

Clear the fact of sales from bursts of promotional activity and other anomalous values;

Calculate trends based on sales;

Calculate seasonality upon sale;

Look for the dependence of sales to change any factors affecting the market: prices, exchange rate, range, promotions, shares in networks, etc .;

Check autocorrelations and closeness of the relationship between factors;

Calculate regression analysis;

Model sales forecast taking into account the influencing factors;

Compare forecast models;

Provide recommendations for promotional activities;

CBT SCM Demand Forecasting
CBT Demand Forecasting – a tool for fast compilation and convenient visualization of the forecast of demand for products by means of a set of mathematical models of forecasting and fast introduction of necessary adjustments taking into account the available operational data.
Category: FMCG, Manufacturing, Wholesale trade and distribution, Transport, logistics, warehouse, Pharmaceutics, Corporations and holdings, Manufacturing enterprises, Distributors and wholesalers, Trade enterprises, Inventory and supply management, Planning, Production Management (MES, APS)
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CBT Demand Forecasting
in work .

The software product CBT Demand Forecasting includes the concept of fast compilation and convenient visualization of demand forecast using a set of mathematical models of forecasting and rapid introduction of the necessary adjustments, taking into account the available operational data

Product review

CBT Demand Forecasting
is a standalone program
and includes subsystems:

Regulatory information

it is work with all the necessary regulatory and reference information. This is usually a one-time operation when filling the system.

Input management

it is a tool of communication with external information bases in which operational and production accounting is conducted

Demand forecasting

it is the main subsystem of calculation, analysis and visualization of demand forecast

The program has a convenient functionality to download and combine a variety of inputs: primary and secondary sales, marketing activities, strategic and operational plans, deficits, exchange rates, weather, etc., which are downloaded automatically according to previously set regulations or manually.

Input data can be downloaded from various sources:

  • the company’s accounting system;
  • third-party storage systems;
  • excel files.

Input data can be cleaned both manually, point-by-point corrections of peaks or sales failures, and in automatic mode, using the existing mechanisms – cutting peaks in a given range and cleaning from promotional shipments.

Download and clear input data

Formation of demand forecast

CBT Demand Forecasting has a flexible and intuitive system of settings and selections, it allows you to customize the report form individually for each user, depending on: required datasets, sections analyzed, graphical content and data visualization, which greatly facilitates data handling analysis.

The calculation of the demand forecast is performed using a set of mathematical models: regression and multifactor regression model; weighted average model, cleaned of seasonal noise (SRVZ); moving average, etc.

When choosing the optimal formula for calculating the demand forecast, the user can use the built-in function of calculating the Average Absolute Percentage Error Forecast (MARE), adjust the ratio and comparison of some measures with others, visually assess the demand models calculated by different models.

The program has a universal mechanism for creating formulas and calculation measures. This mechanism allows the user to create various formulas, such as: Average absolute error rate – MAPE, Forecast accuracy or Forecast Accuracy, Weighted distribution, numerical distribution and many others.

Set up a variety of calculation measures, as well as create all sorts of relationships and comparisons of some measures with others:

  • the ratio of actual sales to operational sales plans (Δ, Fact / Plan);
  • the ratio of current sales to sales of the previous month (Δ, Fact / Fact-1);
  • the ratio of current sales to sales of the current period of the previous year (Δ, Fact / Fact-12);
  • the difference between operational sales plans and strategic plans (Δ, Plan – Strategy) and others.

Calculations can be performed both in real terms and as a percentage.

Universal mechanism for creating formulas

Multifactor regression model

CBT Demand Forecasting implements a multifactor regression model that takes into account the influence of various additional factors when calculating the demand forecast.

The first example shows how to predict the demand for a novelty (or position with a short sales history) as an additional regression factor using the behavior of a subgroup of goods (APG factor).

The second example shows how the dollar exchange rate (USD factor) is used as an additional regression factor when forecasting demand.

The diagram shows two forecast options – for the regression model with additional factors and the regression model without additional factors.

Thus, when using a multifactor regression model, for a number of positions it is possible to obtain greater accuracy of demand forecasting, due to the use in regression of factors influencing the behavior of these positions.

CBT Demand Forecasting.

Automated creation of demand forecasts

Getting the best forecast based on all introductory, in a few steps and in a short period of time.

Convenient analytical reports

With instant visualization of changes in graphs and reports when making adjustments.

Fast start

You can quickly start working with the program with minimal settings and restrictions with a gradual transition to high detail, more sophisticated forecasting algorithms and dependencies.

Interactive adjustments

Manual changes to the demand forecast taking into account operational information and analysis of the results of changes.

Flexible demand forecasting

Helps to build the processes of operational sales planning in combination with periodic monthly, quarterly, annual.

A solid foundation

Grow the company without increasing the workload to the departments of planning, marketing and sales. Provides opportunities for the development of forecasting algorithms. Open source.

Customers who trust us.

What goals will you be able to achieve?

Reducing the duration of the operational planning cycle

Increasing the speed of response to changes in the environment and operational information (up to 2-3 hours per day, several iterations of adjustments per day instead of 1-2 times a week earlier and partial daily / weekly rescheduling).

Improving the efficiency of capital use

material, human and other resources through centralized inventory management, sales plans, distribution of products and raw materials

The general decrease in the level of stocks in the system

About 30%.

Faster and deeper analysis

stocks, demand, distribution of raw materials and finished products and their dynamics, with the same or less human resources, the creation of several parallel scenarios for sales forecast and distribution of products.

Strengthening the control of the correctness of the tasks of the automated system

automatic calculations, visual inspection of inventory levels and planning accuracy, analysis of changes in plans for sales, supply, production and distribution of products.



Thanks to CBT Demand Forecasting, we have obtained a stable and accurate level of demand forecasting
We have got more jewelry planning, more jewelry forecasting, which give more accurate inventory management.
Bohdan Vasylkivskyi, Supply Chain Management Director, Biosphere Corporation

Thanks to CBT Demand Forecasting, we have obtained a stable and accurate level of demand forecasting, even taking into account the growth of new products over the last year by about 50%. As a result, the average daily balance of goods in the warehouse decreased from a stable 42-45 days to a stable 22-23 days, in fact, it allowed us to pass 3 years of sales growth, which received the corporation, with the previous warehousing capacity. We did not increase the warehouse, we were able to process this turnover without increasing the staff or warehouse space. We have got more jewelry planning, more jewelry forecasting, which give more accurate inventory management.

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