Our toolbox for analysis and visualisation includes both open source and proprietary software tools. We are not tied to any specific software but some of our preferred tools are:

Large amounts of data not helpful if no one can make sense of them. We use some of the latest analytics approaches to solve complex real world problems.

• Machine learning (Predictive and Prescriptive analytics)
• Simulation (What-if scenario, Monte Carlo, Extreme case)
• Graph analytics (Social and Economical Network analysis) 

We create models of market and employee behaviour. This lets us understand future changes using simulations and make better plans and decisions.

Our solutions have help clients to:

• find unexpected clusters and patterns and develop new strategy
• identify new groups of users and communicate better to them
• predict the impact on cost and behaviour of policy changes
• test multiple scenarios before making decisions
• recommend best alternatives when changes are large and complex 

Sometimes it is not just the general behaviour of a market which is important but rather the unusual, the abnormal, the outliers.

This is why we use also develop rule-based models or anomaly detection algorithms to automatically identify abnormal behaviour or spend.

Automated approaches also allow us to scan through large datasets efficiently