Optimizing Team Performance with AI Predictions


new clients within 3 months


workload and cost reduction


customers and beat your competition


Accenture is a service company and so people are basically irreplaceable for them, plus their consulting business is having to handle increasingly dynamic and complex tasks.

Those who are open to high-tech data-science solutions have a clear advantage and, with the help of our paretos AI, the international consulting agency can now automate important analysis processes and thus scale lucrative services for its clients.


These individual survey results generated a large number of data points that Accenture used to analyze manually. However, this approach was difficult to scale for other clients so by assigning employees who were responsible for the analyses, Accenture had to invest in high fixed costs and was, at the same time, highly dependent on the availability of suitable talent. As a result, the manual data analysis took longer to process and was not efficient enough from a business perspective.

Secondly, this approach was not future-oriented – the results did not indicate how the team performance would develop if there were no changes to the course. The lack of predictive capabilities of the manual assessment was particularly problematic because the teams could not be surveyed often enough so that only a limited number of data points were available for the analysis. As a consequence, it was difficult for Accenture to identify clear patterns and derive valid conclusions from them.

To close this gap, Accenture was looking for an automated analysis option that could fundamentally improve the company’s own recommendation tool.

The goal was to implement team performance forecasts and to integrate a powerful tool into their existing software.


With the help of paretos’ AI-based platform, Accenture was able to integrate reliable forecasting models and a self-learning recommendation engine into its own software solution within a very short time. By automatically analyzing past performances it is now possible for them to dynamically make predictions about how the performance of individual teams will be expected to develop over time. For this purpose, paretos collects historical data and automatically correlates it.

The recommendations of the forecasting model using the reinforcement learning algorithm are also many times more precise, even when only a few data points are initially available. The consultants then receive predictions concerning the future development of their customers and can take a proactive approach.

The easy-to-use paretos dashboard provides project managers and consultants with an overview of all relevant data at all times. The paretos interfaces (APIs) are triggered automatically from the Accenture solution so that the latest analyses and forecasts are visualized in real time – a crucial prerequisite for making Accenture’s services scalable.


With the help of paretos, the use of automated dynamic data analysis was an important milestone for Accenture and enabled the company to offer Team Performance Consulting as an elementary service component for many other clients. As a result, Accenture was able to gain twice as many new clients within just three months. Thanks to the high scalability, immediate savings could be made on personnel costs and workload as compared to the manual evaluation and allowed customer projects to be conducted more efficiently and, therefore, more profitably.

In addition, Accenture was able to qualitatively raise the optimization recommendations for its clients by integrating forecasts, enabling them to react more quickly and flexibly to the development of their teams and to take pre-emptive measures. The result is an innovative and sustainable consulting model that also gives Accenture a significant advantage over strong consulting competitors.


new clients within 3 months


workload and cost reduction


customers and beat your competition

To connect our recommendation and prediction engine to the paretos API was super smooth and was completed within a few weeks without using a single data scientist. Now our model is constantly improving with an AI-based algorithm – this is a game changer for us and, especially, for our clients.

Ilhan Scheer

Global Lead Product, Talent & Organization / Human Potential


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