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Case Study 5 – How a manager used Analytics to get insights from the data to assign resources to her customers.

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Case Study 5 – How a manager used Analytics to get insights from the data to assign resources to
her customers.

Industry – Banking and Financial Services
We follow DCOVA and I methodology to solve the problem. To Understand this methodology, check this whitepaper – https://pexitics.com/Includes/DCOVA%20&%20I%20Whitepaper.pdf


Business Problem – The manager has the details of Earnings across different industries. It wants to
look at the current details of performance and conclude which segments can be clustered together
so that he can then assign Relationship Managers accordingly.
The manager approaches the analytics team with the problem and shares the data with the team.
The analytics team explores the data to treat the data for missing values and outliers. The team
comes out with many visualizations which would help to get insights. The visualization is shown
below –


This graph, the elbow chart, informs the optimum number of cluster to be created for k-means
clustering. Based on this the analytics team uses the k-means cluster algorithm to cluster the data. It them also use the Hierarchical Clustering method to cluster the data. Using the indices for goodness to fit for clustering, then team them suggests the right grouping to the manager.


Based on these insights by the analytics team, the manager then updates the resource list for the customers for optimum utilization.

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