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Aigorithmics

Solutions

Forecasting
(forecasting)

We use data collected by our Customer as input data for predictive models. The data makes it possible to forecast future values and trends.

Benefits:

  • Accurate sales prediction.
  • Reliable budget planning for the coming years.
  • Accurate production planning, that increases supply chain efficiency.
  • Optimization of the marketing strategy operationalization.
  • Effective sales team management.
  • Cost optimization, e.g. by reducing warehouse space.

CATEGORY:

Machine learning, Business Intelligence, Sales forecasting

INDUSTRY:

pharmaceutical

PROBLEM:

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

SOLUTION:

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

MAIN EFFECTS OF THE PROJECT:

  1. More accurate forecasts of the sales volume from pharmacies to retail customers (sell-out) thanks to artificial intelligence algorithms.
  2. Comprehensive analysis of available sales data.
  3. Internal training and development of the contractor towards a fully data-driven company.

CATEGORY:

Machine learning, Sales forecasting

INDUSTRY:

pharmaceutical

PROBLEM:

Difficulties with precise sales volume forecast considering the regional fragmentation.

SOLUTION:

Development of machine learning models for sales forecast and analysis of factors influencing its size. Performing a what-if analysis which allows to simulate the sales volume depending on the value of particular variables.

MAIN EFFECTS OF THE PROJECT:

  1. More accurate sales volume forecast and better resource allocation, including optimal marketing funds allocation.
  2. Possibility of testing various business scenarios based on what-if analysis, that allows to prepare for changes inside the company as well as its environment.
  3. Root-cause analysis and identification of crucial factors affecting sales value. Possibility of effective potential opportunities and risk evaluation.

CATEGORY:

Deep Learning, Machine Learning, Econometric solutions, Electricity forecast

INDUSTRY:

Smart Energy

PROBLEM:

Inefficient analysis of huge amounts of collected data.

SOLUTION:

Change of the approach, usage of data sets in artificial intelligence models, which made possible to make optimal business decisions regarding the current needs and market predictions.

MAIN EFFECTS OF THE PROJECT:

  1. A customized service embedded in a cloud environment that allows to generate predictive models, using both historical data and external information (including weather data).
  2. Two predictive models overperforming project’s assumptions in the area of electricity demand and consumption.

CATEGORY:

Machine learning, Sales forecasting

INDUSTRY:

pharmaceutical

PROBLEM:

Difficulties with optimal warehouse management in sales regions. Lack of effective ways to predict the demand for a newly introduced product.

SOLUTION:

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

MAIN EFFECTS OF THE PROJECT:

  1. Marketing strategies improvement thanks to accurate prediction.
  2. Actual increase in the company’s sales thanks to the appropriate sales strategy.
  3. Prediction visualization with perspicuous reports in the context of external data.