SMART Decision HUB

About Demand Forecast

The system simplifies the forecasting process and increases its accuracy. At the same time, it reduces the operational burden on the supply chain team, which allows it to change its focus from operational tasks to strategic ones.

30 Sep 2025 3 MIN READ

Release 5.0

Not just an update, but a new level of demand control: more accurate forecasts, promo scenarios, multi-country analysis, and a speed the entire business will feel.

Benefits of using
SMART Demand Forecast

Accurate forecasting of regular and promotional sales will allow you to ensure that your business has the right inventory in time, maximize sales and improve service levels at a low cost.

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Increased forecast
accuracy with AI & ML

SMART Demand Forecast is based on machine learning and artificial intelligence algorithms. This will help take into account all the necessary factors that affect forecast accuracy, including your experience with a particular SKU and product group.

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Reduced inventory

Powerful analytics and high forecasting accuracy make it possible to ensure the availability of goods at the right time and in the required quantity, without creating an overstock.

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Optimization of
availability level

Intelligent algorithms provide high forecast accuracy, which has a direct impact on maintaining a high level of product availability. As a result, you not only increase profits, but also improve the level of service and the reputation of the business as a whole.

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Saved labor costs

Optimizing the planning and analytics process in SMART Demand Forecast helps avoid team overload, shifts their focus from operational to strategic tasks, and reduces human error.

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Reduced write-offs

High forecasting accuracy helps ensure the optimal level of goods to meet consumer demand, while avoiding the creation of surpluses in the warehouse. This in turn allows you to reduce the number of write-offs.

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Prompt business
decision making

Powerful Power BI analytics allows you to quickly make management decisions based on up-to-date data. In SMART Demand Forecast, you can conduct sales retrospectives, analyze the quality of input data, the quality of promo sets and compensated sales.

Artificial intelligence in SMART Demand Forecast

Start your supply chain transformation with SMART Demand Forecast ML & AI algorithms.

Average accuracy 68 ,75%

AI can efficiently process and analyze huge amounts of data, thus revealing dependencies and trends that may not be detected by traditional methods.

The use of such technologies in forecasting directly affects its quality. The precision of forecasts for both regular and promotional sales demand significantly impacts inventory management efficiency, stock availability, service levels, promotional outcomes, and company profitability

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Functions of the SMART Demand Forecast system

Work with Analog Products

Forecasting for new products and stores using analogs helps improve strategy and avoid unnecessary costs associated with launching a new product or expanding the network. AI-driven selection of analogs optimizes costs for manual analysis when data is insufficient, enhancing the quality of forecasting.

Modeling

The quick generation of demand forecasts for regular and promotional sales allows for rapid adaptation to changes in factors affecting demand.
The ability to create scenarios with different promotional conditions enables modeling and comparing potential outcomes to avoid unnecessary costs and adjust the marketing strategy.

Processing Anomalies

AI identifies anomalies in the data and automatically smooths them, helping to use accurate data and adapt models to changing conditions.
In cases where automatic smoothing does not apply, the system provides the option for manual adjustments to minimize risks.


SMART Demand Forecast Analytics

Forecast decomposition

Allows for understanding which factors (seasonality, trends, promotions) have the greatest impact on the forecast, helping to better adapt strategies and timely adjust marketing, logistics, and production plans.

Forecast Quality Analysis

Identifies weaknesses in forecasts, analyzes model errors, and improves their efficiency, minimizing the risks of incorrect purchasing or planning.

Historical Sales Analysis

Identifies trends, seasonality, and key sales drivers that form the foundation for strategic planning.

Data Quality Analysis

Detects gaps or errors in input data, minimizing model errors.

ABC-XYZ Analysis

ABC-XYZ classification allows focusing on the most critical products, minimizing surpluses and shortages, thereby reducing storage costs.

Product Stock Analysis

Reduces operational costs and optimizes the procurement process, avoiding excesses or shortages of products.

How does forecast accuracy affect your business profits?

Calculate how much money your business will receive by increasing the accuracy of forecasting!

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Find out how much you can improve your forecasting accuracy with SMART Demand Forecast

Get a consultation

Why choose SMART Demand Forecast 

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Comprehensive approach 

Possibility of simultaneous forecasting of regular and promo sales. 

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Data security 

The system guarantees GDPR compliance and takes care of the security of your personal data. 

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Expert team 

Interaction with experienced specialists in the implementation of IT solutions, demand forecasting and data management.  

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Integration with Microsoft 

Using a single ecosystem of Microsoft solutions allows you to set up fast and high-quality integrations. 

How does SMART Demand Forecast
affect your business? 

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The system calculates the optimal quantity
of goods to meet demand
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Ensuring proper availability in points
of sale 
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Prevention of overstock
in the warehouse 
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Reducing lost sales 
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Decrease in funds frozen in stocks 
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SMART Decision HUB

Demand forecasting
in retail

Learn more

Increasing competition, the constant impact of promotional campaigns on the assortment, changing buying behavior and context, dependence on changing external factors – all this plays an important role in demand forecasting.

SMART Demand Forecast allows not only to take into account all these factors, but also to improve the accuracy of operational, medium-term and long-term forecasts. And the Power BI block built into the interface makes it possible to analyze the results at any time.

See for yourself in the pilot project!

How is forecast system implemented? 

Step 1

Pilot project 

Drawing up a plan and fixing the goals & KPIs of the project, describing all your business processes, determining the state of your database, organizing secure interaction. Preparation and launch of the model, subsequent analysis of its results. 

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Step 2

Product testing

Coordination of the test plan and schedule, setting up the integration process and deploying the solution infrastructure. Organizing training sessions for users on the use of the system. Testing the product, analyzing the results and making a decision to launch the system. 

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Step 3

System launch 

Scaling the use of the solution. Support of system functionality
in accordance with emerging requests. 

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Our goal is your business result

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With you every step of the way 

We support you at every stage: from proper data structuring to applying algorithms to all SKUs and stores. 

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Effective ML & AI algorithms 

The system is based on ML & AI algorithms that constantly learn from your data and improve the accuracy of forecasting. 

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Guaranteed data security 

We care about ensuring a high level of data security and GDPR compliance. 

    Table View Configuration
    as Needed

    The user can customize the table view according to business needs. The flexible interface of the solution allows adjusting the displayed columns and their sequence, saving and applying pre-defined table display configurations.

    The functionality provides quick access to table views without the need for reconfiguration.

    Import/Export of Analog Products

    The solution allows for bulk uploading or downloading product analog data in a convenient format. This simplifies the process of updating information through the system interface.

    Імпорт Експорт товарів аналогів

    PROCESSING OF ANOMALIES

    Filtering Analog Products
    by Product Levels

    It allows for quickly finding relevant products or store analogs, taking into account the product and business hierarchies.

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    Selection of the Forecasting Period and Time Aggregation

    The ability to select the required time period and data aggregation level (day, week, month, year) provides flexibility in viewing and analyzing data depending on the chosen timeframe.

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    Import / Export of Forecast Results

    Exporting the prepared forecast in a convenient format with the option to select either individual or all scenarios allows for integration with external systems for further use and execution of the forecast.

    Manual Forecast Adjustments

    The ability to manually adjust the system-generated demand forecast based on expert evaluation or additional factors provides flexibility and greater accuracy in forecasting, taking into account specific business circumstances.

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    Selection of Anomaly Aggregation

    The ability to group and summarize detected anomalies according to the selected time aggregation level (day, week, month, etc.) simplifies trend analysis and helps assess the impact of anomalies on overall performance indicators.

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    Making Manual Adjustments after Data Smoothing

    The ability to manually adjust the system-generated demand forecast based on expert evaluation or additional factors provides flexibility and greater accuracy in forecasting, taking into account specific business circumstances.

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