The client (a telco provider) was struggling with the problem of turnover of experienced operators in call centers. The aim of the project was to understand the cause of attrition and based on this understanding, predict the attrition of specific employees. The solution was to serve team leaders to work with employees at risk of leaving.

Together with the client, we identified hypotheses related to employee retention and attrition. The project collected the necessary data and trained a model of attrition. In total, we evaluated 466 predictors of voluntary employee attrition. Based on user stories collected from team leaders, we designed a dashboard to help with employee retention (who is at risk of leaving, for what reasons, and how to work with them).

This project showed to the client how to systematically use their own HR data to make effective people management decisions based on data. Using predictive analytics, we helped the client gain insight into their employees at higher risk of leaving and also insights into the factors that are typically associated with employees' decision to leave. The predictive model was able to satisfactorily identify employees with a high probability of leaving in the following periods 1 3 months.

Nowadays, digitization and business transformation change the original perception of business – our clients and their customers reduce the need to attend touchpoints physically. When it comes to the definition of “physical touchpoints”, we can understand it as any way consumers can interact with a business organization person-to-person. But since there is not so much interest, why not start optimizing these physical places, right?

To identify the consumption of (non)customers of branches in a certain area, we help by defining polygons around the located branches to show the reach at a distance chosen by the client. The overlap that may arise will help us identify the density of branches in the context of the area and the possible cannibalism of (non)customers of branches of the same bank.

One way of defining a polygon can be a simple buffer, a distance in the form of a circle around the points, the other way could be an advanced geospatial analysis called isochrones.

Even if your business may already have a robust network of branches, stores or other customer touchpoints, location intelligence may come in handy for its optimization. Sometimes hard decisions like reducing the number of branches must be made, especially if there have been significant changes on the market or if you are planning on merging multiple branch networks.

A real-time dashboard we developed for a major car manufacturer helping their CFO and Plant manager monitor and optimize performance, costs and safety. We developed a special interactive view for each of the end-users (CFO, Plant manager) based on their business objectives to bring them relevant data in context and frequency (for Plant manager in real time).

With real-time management in production, you can achieve informed and efficient management of capacity and resources. Using the Tableau mobile app, the entire operation can be monitored at any time and from anywhere.