SIMAC Problem Management

Project description

Our main research question is as follows:

How can we make the problem management process, visible and highlight its
value in reducing incidents and addressing root causes?

Using certain visualisations in a dashboard for example a boxplot we should be able to highlight stores that are outliers on certain products. Then we can display what stores are exact outliers and pinpoint any root causes from there.

Context

The assignment is focused on improving the visibility and transparency of Simac’s Problem Management process and its Continuous Service Improvement approach for their retail branch, both of which are based on ITIL standards. These processes are already standardized within Simac and are implemented operationally through the Service Management tool, Topdesk. The goal is to integrate these processes for Jumbo making them visible and measurable within Qliksense, Simac’s reporting tool. This will help both Simac and its clients to monitor and evaluate theefficiency, status, and results of the Problem Management and CSI processes.

This project emerged when Simac were willing to improve their service delivery for clients through Continuous Service Improvement (CSI). The need for clear, real-time visibility into these processes has led Simac to prioritize integrating their Problem Management process into reporting tools, which will demonstrate the added value to their clients. This allows clients to see how Simac is actively addressing and preventing issues, reinforcing the value of their solutions and building trust through transparency and accountability. Making the Problem Management and CSI processes visible and measurable, Simac aims to provide clients with greater confidence in their service efficiency while demonstrating the impact of continuous improvement efforts.

Results

Our project resulted in the creation of a functional dashboard within Qliksense, where you can see the average store incidents, using drill down mechanics you can drill down on the exact store and see the percentage increase or decrease compared to the average that was already established. The store outliers per product is also an important mechanic of the dashboard where you can instantly see the outliers of stores based on certain categories we have set based on extensive data analysis.

We also worked on a solution to provide a most common action list, taken on certain incidents. This part shows the most common solution per problem, then with our stakeholders we defined if it was a Major incident or a common incident. For example a common incident is resetting your password. This eventually gave us a list of most common solutions used on particular incidents.