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Aigorithmics

Forecasting

Technology that uses historical data, operational data, and business-influencing factors to predict future values, trends, and phenomena

Our solution is based on designing advanced demand and sales forecasting models tailored to the needs of retail and logistics. This enables organizations to prepare for changes in advance, better align available resources with actual needs, and reduce decisions made purely reactively.

When is it worth investing in forecasting technology?

Forecasting technology is particularly useful where decisions must be made in advance and available historical data allows for building reliable models of future events. It enables proactive action and faster response to market and operational changes.

The team wants to predict future results based on historical data and trends,

The organization needs to forecast sales more accurately, taking into account seasonality, market variables, and customer behavior,

When there is a need for better production planning and optimization of inventory and supply chain,

Management needs reliable forecasts for budget planning and strategic decision-making,

The company wants to optimize marketing activities by predicting their effectiveness,

When the organization needs to manage the sales team more efficiently and set realistic goals.

Business Benefits

Production and Logistics Optimization

Demand forecasting supports efficient production planning, better inventory level management, and supply chain optimization. This allows the organization to reduce costs resulting from both shortages and overproduction.

Precise Sales Forecasting

More accurate forecasts help prepare production, logistics, and resources in advance for changing needs.

Effective Marketing Strategy

Forecasting models help analyze the effectiveness of marketing activities, optimize campaigns, and support data-driven planning, which translates into better decisions and higher efficiency of promotional activities.

Effective Sales Team Management

Forecasts enable more accurate determination of sales targets.

CATEGORY:

Machine Learning Solutions, Business Intelligence Solutions, Sales Forecasting

INDUSTRY:

pharmaceutical

PROBLEM:

Estimating sales volume and making management decisions based solely on intuition and assumptions.

SOLUTION:

Structuring collected data for algorithmic analysis and obtaining information of real business value for the Client.

GŁÓWNE EFEKTY PROJEKTU:

  1. More accurate forecasting of sales volume from pharmacies to retail customers (sell-out) using artificial intelligence algorithms.
  2. Comprehensive analysis of available sales data.
  3. Internal training and development of the client toward becoming a fully data-driven company.

CATEGORY:

Machine Learning Solutions, Sales Forecasting

INDUSTRY:

pharmaceutical

PROBLEM:

Difficulties in precisely forecasting sales volume taking into account regional fragmentation.

SOLUTION:

Development of machine learning models for sales forecasting and analysis of factors influencing sales volume. Execution of What-If analysis allowing simulation of sales volume depending on the values of certain variables.

GŁÓWNE EFEKTY PROJEKTU:

  1. More accurate sales volume forecasting and more favorable resource allocation, including funds allocated to advertising.
  2. Ability to test different business scenarios based on What-If analysis, which allows better preparation for changes within the company and its environment.
  3. Identification of the most important factors influencing sales value. Ability to more effectively assess potential opportunities and risks.

CATEGORY:

Deep Learning Solutions, Machine Learning Solutions, Econometric Solutions, Electricity Forecasting

INDUSTRY:

energy (Smart Energy)

PROBLEM:

Inefficient analysis of enormous amounts of collected data.

SOLUTION:

Change of approach and beginning to use existing datasets in artificial intelligence models, which enabled making optimal business decisions regarding current needs and market predictions.

GŁÓWNE EFEKTY PROJEKTU:

  1. Customized service deployed on a cloud environment allowing generation of predictive models using both historical data and external information (including weather data).
  2. Two predictive models in the area of electricity demand and consumption exceeding the project assumption.

CATEGORY:

Machine Learning Solutions, Sales Forecasting

INDUSTRY:

pharmaceutical

PROBLEM:

Difficulties in optimal warehouse management in sales regions. Lack of an effective method for predicting demand for a newly introduced product.

SOLUTION:

Design and implementation of custom machine learning models for sales forecasting taking into account regional fragmentation, also for new products on the market.

GŁÓWNE EFEKTY PROJEKTU:

  1. Improvement of marketing strategies through accurate prediction.
  2. Actual increase in company turnover through appropriate sales strategy.
  3. Visualization of predictions using intuitive reports in the context of external data.

Contact

A conversation is the first step to identifying the organization’s needs and assessing the project’s viability

Schedule a consultation