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Forecasting

Forecasting based on Machine learning algorithms

OUR CAPABILITIES IN MACHINE LEARNING

Data science
Data science

Data processing and analysis to find common patterns, dependencies and areas for optimization: preventing out of stock, analyzing the effectiveness of promotional activities, demand drivers’ decomposition, anomaly detection, etc.

Forecasting
Forecasting

Forecasting models based on machine learning algorithms: forecasting of demand, promotional sales, level of assortment cannibalisation, etc.

Optimization
Optimization

Models maximize profits, revenue or reduce costs: optimizing promotional investments, optimizing stock in the warehouse or shop, smart pricing, etc.

ADVANTAGES OF ML FOR FORECASTING

01
MORE ADVANCED
Modern ML approaches can find and learn from implicit patterns between a target variable, such as a demand curve, and various influencing factors that cannot be identified using traditional models or expert opinion.
02
MORE FAST
With ML algorithms, huge amounts of statistical and variable forecast data are processed in minutes, freeing up experts’ time for more important strategic and analytical tasks.
03
MORE ACCURATE
Traditional forecasting methods are based on historical sales data, whereas ML forecasting supplements this data with other critical factors that influence demand: promotion costs, product inventory, weather, etc. ML forecasting enables you to explain changes in the numbers and identify new factors that were not previously evident.
04
MORE COST-EFFECTIVE
Improved forecast accuracy helps in reducing costs, improving profitability and efficiency across the supply chain, making better-informed decisions in the face of rapid change.

TANGIABLE BUSINESS VALUE

Up to 20% increase in forecast accuracy
Up to 20% increase in forecast accuracy
Up to a 50% reduction in the time spent by specialists on forecasting
Up to a 50% reduction in the time spent by specialists on forecasting
Simplification and acceleration of the entire forecasting and planning process
Simplification and acceleration of the entire forecasting and planning process

OUR FORECASTING SOLUTIONS

Even within the same industry, each project will be unique. Therefore, when creating a new customized ML model, we first help to analyze and, if necessary, improve business processes so that any obstacles to the launch and effective use of the new technology solution are eliminated.

BUSINESS PROCESS SETUP
BUSINESS PROCESS SETUP

Audit, analysis and setup of the target business process taking into account the specifics of the ML solution’s capabilities.

ML-MODEL DEVELOPMENT
ML-MODEL DEVELOPMENT

Development, integration and launch of ML forecasting models.

BUSINESS AS USUAL SUPPORT
BUSINESS AS USUAL SUPPORT

ML-model support after launch: technical support for ML-models and functional support for business teams.

KEY FUNCTIONAL AREAS AND USE CASES

Data science techniques and Machine Learning algorithms can more effectively resolve a number of key business problems - from demand forecasting to optimizing multi-million price promotion budgets.

Demand planning
Baseline sales
Total demand
History cleansing
Demand drivers’ decomposition
Trend and seasonality analysis
Outlier detection
Promo planning
Promo uplift evaluation
Regular sales cannibalization
Promotional sales
Non-price promotion effectiveness
Analysis of competitors’ promo strategies
Sales planning
Off-the-shelf sales forecast
Portfolio cannibalization analysis
Seasonal sales
Sales forecast driven by retailers’ co-investments
New product sales
Actuals decomposition and analysis
Supply planning
Inventory level projection
In store out-of-stock analysis and projection
Stock target calculation based on probabilistic forecast
Probabilistic demand forecast

MACHINE LEARNING METHODS USED

Based on the task, availability and quality of incoming data, our data scientists create a model with a unique set of features and algorithms. The goal can be solved by regression methods, decision tree algorithms, ensembles or a combination of the above.

REGRESSION MODELS
A simple yet powerful tool for time series forecasting, offering clear interpretations, ease of application, robustness and reliability, especially in situations with limited data.
DECISION TREES
A versatile and powerful machine learning algorithm, especially in scenarios where interpretability, non-linear relationships and feature selection are important factors.
ENSEMBLES
This technique simultaneously uses multiple learning algorithms, such as decision trees, linear models or neural networks, where a more accurate prediction can be obtained from an ensemble rather than from each algorithm individually. Flexibility in model architecture and hyperparameter tuning ensures fine-tuning for a specific problem.
HEURISTICS
The method accumulates the combined experience of a developers team in a particular industry, taking into account specific cases, and works to improve the efficiency of all the technologies used.

SEAMLESS INTEGRATION WITH ANAPLAN

It is possible to integrate models for forecasting based on machine learning algorithms with the Anaplan platform as well as with any integrated business planning solutions (IBP).

Input data
Data in any format: flat format, DWH, cloud apps etc
ML model
Deployed on a company’s server or virtual machine (VM)
Forecast visualization
Review
Correction
Aprroval
INTEGRATION INTEGRATION
Run a recalculation of the forecast when necessary.
Save a version of the approved forecast to assess its accuracy.
INTEGRATION INTEGRATION
Run a recalculation of the forecast when necessary.
Save a version of the approved forecast to assess its accuracy.

OUR CUSTOMERS USE ML FOR BUSINESS PROCESS TRANSFORMATION

Our forecasting and optimization solutions are used by major companies around the world.

Unilever - baseline and total sales forecast for sales team
Unilever - baseline and total sales forecast for sales team
Greenfields - daily operational forecast by day for 12 weeks
Greenfields - daily operational forecast by day for 12 weeks
Dairy products manufacturer – promo sales forecast
Dairy products manufacturer – promo sales forecast
Greenfields - monthly long-term rolling forecast for 12 months
Greenfields - monthly long-term rolling forecast for 12 months
Dairy manufacturer - regular service support for ML models
Dairy manufacturer - regular service support for ML models
Unilever - total demand forecast for Demand Planning team
Unilever - total demand forecast for Demand Planning team
Unilever - sales forecast for e-commerce customers
Unilever - sales forecast for e-commerce customers
Dairy manufacturer - regular data science service
Dairy manufacturer - regular data science service
Unilever - customized sales forecasting models at Walmart, Amazon and Target
Unilever - customized sales forecasting models at Walmart, Amazon and Target
Unilever - regular service support for ML-models
Unilever - regular service support for ML-models

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