LexisNexisRisk Solutions Software Engineering Internship

ABOUT MY INTERNSHIP

During Summer 2020, I had an incredible opportunity to work on the FIDO BI team at LexisNexisRisk Solutions.

I was able to provide insight into how hours worked are distributed among projects on many different levels. This was important for project management and helped teams better manage their time, improving efficiency for the company. I communicated efficiently with a diverse team nationwide and presented work to senior management.

CONTEXT

What is Jira?

The Jira ticket is an important tool used by the company and its main purpose is for employees to log their work and report the status of their projects whether it is open, in progress, or closed. From this, we are able to interpret the working hours of people. Management can get a better picture of project status as well as the productivity of teams. Jira is a way to measure productivity so we can understand where our time is going and refine how we allocate our resources. That way we go after the right business outcomes, driving efficiency in the organization which is why we are measuring these hours.

Main Focus

The main focus of the project was to create a report that analyzes and tracks Jira Tickets on multiple levels from a team as a whole to an individual engineer. I measured the performance summary such as hours spent in different time ranges for example, daily, weekly, and monthly. My goal for this project was to provide a clear and accurate picture to depict the task progress on projects through the Jira records. 

Project Demo

Although I’m unable to share the exact demo of my project, I will share some features that were implemented.

• Summary Tab: This provides a general overview of an employee which can be selected in the “View As” tab. We can do a search and choose which employee’s data we are going to look at. This depicts a holistic view meaning including their supervisors and the supervisees.

• Employee Summary Table: Includes key factors like the hours logged, number of worked tickets, and the FTE ratio which stands for the full-time employee ratio: you’re supposed to work 8 hours a day. We take how many hours you logged in the last column and divide that by the total amount of work hours you should have which is “work hours logged”

• Monthly Time Spent Hours Table: Portrays how many hours are worked over a specific time period which can be chosen by the date dropdown. Here we can do a search which I’ve already done, for example, June 2020. I’ve incorporated time spent hours over every week in June, the numbers on the x-axis symbolize each week. We can clearly track not only an individual assignee’s data but everyone related to them in the hierarchy, viewing the whole team as a big picture. This would include how many Jira tickets have a team completed in total. How many members are in the team and how many hours have the team accumulated together.

• Employee Drillthrough:

  • From the employee table on the summary tab we can drill through on a specific employee which takes us into the employee drill through tab. We go from a high general level of understanding to a more detailed view.

  • The employee drill through features key points like the assigned tickets resolved and worked tickets of a specific employee as well as the FTE ratio.

  • We also get a trend analysis of the hours logged by day in a specific time period which like the summary tab before can be filtered as wished by the date.

  • Table of all the tickets worked by that specific employee and relevant details including the issue type, status, and hours worked. And if you click on the numbers on the bottom of the hours logged by day table symbolizing the week of the month you can filter the tickets worked in that specific week.

• List of tickets that the employee worked:

  • Differentiated by their key names, we can further look in detail at a specific ticket by drilling through one, leading us to the ticket drill through.

  • When you drill through a specific ticket, you are immediately taken to an in-depth overview of that ticket including who is the assigned employee, the status, when was it created, the priority.

  • We can also view the hours logged by day of that specific ticket in the table

• Worklog Comments: and the dates they were recorded as well as the hours logged and which assignee wrote it are featured. If you click on the numbers on the bottom of the hours logged by day table which symbolize the week number of June we can actually filter these worklog comments to only those from the second week of June.

• Pi Chart: Filter the employee in the worklog area.

From a broad summary to meticulous analysis, this project provides insight into how are the hours worked distributed among projects on many different levels. This is excellent for project management and helps the team manage their time better, improving efficiency for the company.