This article describes the successful implementation of a Six Sigma Green Belt project in information technology (IT) in which a software development team applied Six Sigma to reduce the resolution time of software defects and minimize rework, thereby increasing customer satisfaction.
A software development team in a leading environmental services company wanted to reduce the resolution time of software defects and change requests that were submitted by the company’s internal customers. The IT team used a defect-tracking application to track the submitted requests and defects. Work items were assigned to the team members for development and testing; updated code was released to the production environment in build cycles of once a month.
The aim of this project was to reduce the development and testing time of work items and to minimize expensive rework using DMAIC (Define, Measure, Analyze, Improve, Control). In the context of this article, rework is defined as revisiting a work item after it is considered resolved and has been deployed to the production environment.
The software development team, business analyst and customers defined the current problem by the following three parameters:
Historical data from the defect-tracking application as well as up-to-date information was used to estimate the average resolution time of a work item. Using variable data derived by analyzing the submitted tickets, it was found that the average resolution time for a work item was one build cycle (34 days), as shown in the figure below. (As a side note, many projects were taking far too long. A business analyst joined the company and quickly cleaned up the backlog and helped close outstanding issues.)
Process mapping was used to characterize the existing process. Table 1 depicts the current assignment of work items in the team. The priority list of work items for the build cycle is comprised of four items:
|Table 1: Work Item Fragmentation – Before|
|Work Item||Build Cycle||Developer|
|Admin tool 1||4||Developer 1|
|Finance-related tool 1||4||Developer 1|
|Admin tool 2||8||Developer 2|
|Finance-related tool 2||8||Developer 2|
The development team manager recognized that software development is a creative process and can quickly get monotonous. Thus, the work was structured so that Developer 1 was assigned two work items: admin tool 1 and finance-related 1 while Developer 2 was assigned the other two work items: admin tool 2 and finance-related tool 2. The mix-and-match assignment of tasks was set to ensure that all developers would get the chance to work on all areas of the application and gain domain knowledge (both functional and technical) of the application.
In the current scenario, similar work items were assigned to different developers, causing work item fragmentation. Both developers would research the same areas of the application independently; they had to understand requirements, trace issues through the modules of code, develop new code and test code for both work items. Since the work items for the developers were distinct, the development and testing times when taken together were significant.
The team realized that if similar work items within the software application were assigned to the same developer, there would be less context switching required, and the development and testing times would reduce significantly (i.e., to a single build cycle). If Developer 1 was assigned both work items related to administrative tools and if Developer 2 was assigned both work items related to finance, the overall development and testing times would likely be reduced.
An input-process-output analysis was used on a sampling of change requests to determine the inputs (x) that affected the resolution time of customer requests. Customer requirements, prioritization of tasks, technical knowledge and communication all had significant effects on the speed of resolution and the quality of the resolved work items. A cause-and-effect matrix was then used to narrow down the factors that would have maximum impact on the resolution time of work items and the amount of rework involved. Unclear requirements and unplanned assignments of work items to developers emerged as the most important points of focus.
Several tools were applied during the Analyze phase of this project. Pareto charts were used to quantitatively analyze the customer requests and determine which areas in the application generated maximum customer requests. It was decided to document the code in these areas and provide user training where needed. The 5 Whys tool was used to analyze reasons for rework across build cycles.
Brainstorming by the development team, a business analyst and the internal customers led to the following discoveries:
Each of these instances required rework.
The software development team documented a process to improve software development efficiency and to reduce rework. The new strategy included the following steps.
|Table 2: Work Item Fragmentation – After|
|Work Item||Build Cycle||Developer|
|Admin tool 1||4||Developer 1|
|Admin tool 2||4||Developer 1|
|Finance-related tool 1||4||Developer 2|
|Finance-related tool 2||4||Developer 2|
Related work items were combined and assigned to one software developer in one build cycle. As shown in Table 2, Developer 1 works on the admin tools, while Developer 2 works on the finance-related tools; this continuity in work improved work item resolution time.
The developers now get customer requirement clarification at the start of a work item, write the necessary code and test a work item in a single software development cycle. Since knowledge and context switching are now minimal, development and testing time decreased and resolution time of work items improved as shown in Table 3.
|Table 3: Project Savings|
|Category||Before (Weeks)||After (Weeks)||Overall Savings (Weeks)|
The list of work items that was used to assign tasks per month was revised to combine related tasks. Resolution time for work items was monitored. It was found that by gathering detailed requirements, carefully prioritizing work items and assigning similar tasks to the same developer, more development and testing could be accomplished in a single build cycle. The defects submitted to the defect-tracking application were monitored and the number of requests for rework decreased significantly.
As a result of this project, the resolution time of related work items was reduced by an average of two weeks (depending on the number of work items combined) with significant savings in man-hours for the development team. The time saved is now used to proactively identify and resolve issues, design robust unit tests, plan new development and improve existing code.
Resolution time of work items was reduced, communication between the developers and customers improved, and customer satisfaction increased. Most importantly, this Green Belt project brought in a culture of continuous improvement within the software development team and similar projects are planned for other areas of the software application.
In this project, the team used tools from Lean, Six Sigma and agile software development as outlined by David Howell in Software Development Convergence: Six Sigma-Lean-Agile.
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