Problem

Jira is the acknowledged market leader among project management tools and is a great tool for managing tasks, their requirements, and life cycle. In a regular Jira workflow, project manager’s tool set for ensuring speed and quality of the delivery are limited to task description (i.e well-designed input, requirements, and quality criteria), as well as intelligent assignments.

Different project management methodologies put the responsibility for assignments into different hands, but at the end of the day this remains a human decision.

This demands in-depth knowledge of strength and weaknesses of the team and each of its members, consideration of human factors, manual effort, coordination, and time investment. This approach doesn’t scale well is severely affected by team composition changes, remaining limited to small teams.

Maintaining the kind of knowledge needed to make efficient and unbiased assignments, leveraging team potential efficiently becomes a significant challenge under the conditions of rapid growth, fast-paced projects, and evolving technologies .

Solution

Adding “skills” as an abstraction between your tasks and your workers allows you to significantly simplify management for both:

• Project managers gain the missing piece of the puzzle to, enabling them to guarantee quality of the delivery through a single mechanism of task definition, embedding worker requirements into the task along with the implementation requirements and quality criteria.

• Team managers gain visibility into current, future, or past demand for their team members skills. Knowledge scarcity/density and bottlenecks become visible, facilitating measures like training, hiring, talent distribution between teams.

What benefits do skill-based assignments provide?

Well, a few examples:

• You can share work queues between teams and reduce or avoid idle resources by having workers from multiple teams process other team’s tasks that don’t require project-specific expertise

• You can easily scale your team without work orchestration becoming a bottleneck by eliminating manual effort

• You get higher speed/quality ratio by guaranteeing that every task is implemented by an expert who already has all it takes to deliver the task efficiently.

  • Skill-based assignments paradigm naturally separates work concerns from training concerns. You get clear view into skill gaps (team or individual) and can make conscious decisions about how to address them. Be it training, hiring, or conscious compromise by assigning to an insufficiently qualified worker and letting him learn on the job.

• You can restrict self-assignment to experts only

• You always see who has the skills/knowledge the task or set of tasks require

• You can implement fully-automated push- or pull-style work assignments (e.g. based on expertise and availability)

  • Also relevant in cases of mergers and acquisitions

• Naturally maintained product knowledge map

• Risk mitigation by deciding what knowledge needs to be documented or transferred based on skill/knowledge scarcity in order to avoid knowledge loss.

• Team can be is incentivised into learning (e.g. by calculating bonuses based on completed tasks expertise requirements)

How it works

“Skills for Jira” adds a new custom field type - “Skillset”. These fields match the specified skill requirements with users, exposing this mapping for you to query via JQL or use Jira workflow conditions.

“Skillset” can be merely a convenience helper (show me who has the required skills/knowledge so that I can make a better assignment decision) or an enabler for fully automated assignments (e.g. people get their personal work queue in the form of a JQL filter sorted by priority and filtered by their expertise, which can be used for pulling or pushing next assignments).