For humans, time is truly precious. This holds even truer in the demanding world of business. And when it comes to Jira time tracking, its importance skyrockets. To truly boost your team's productivity, gain valuable insights into project profitability, and optimize resource allocation across every initiative, a robust Jira time tracking tool isn't just an option – it's essential.

Jira can be used to track all kinds of processes from software development to any kind of service management of business processes. And Atlassian Marketplace knows it very well. That is why in Jira, “Time Tracking” can be done in two ways:

• Worklog based time tracking
• History based time tracking
  
  

These two ways do not conflict, they rather complete each other. One cannot be used in place of the other.  Worklog-based reporting focuses on the total effort put into a task. If many people work on something even briefly but with high effort, this method shows high costs because of the combined effort, but it doesn't show how long the task took.

On the other hand, history-based reporting focuses on how long a task takes. It doesn't show how many people worked on it or their effort levels. Instead, it tracks the time spent on each stage and the total time to finish the task.

Let’s dive in to understand these two and cover all aspects related to time tracking and time in status in Jira.

Worklog Based Time Tracking

Ever wonder exactly how much time is truly spent on each task? Worklog time tracking answers that question, and then some. At its core, it is all about understanding where every minute of your team's effort actually goes. It is a goldmine to know precise cost calculations and to give you the real-world data you need to estimate future projects accurately.

To implement worklog based time tracking, you will be asking your users to enter worklogs onto Jira work items. Your users will declare how much time they’ve spent while working on each work item.

Then you can get high-level reports showing the overall effort distribution.

With Jira’s out-of-the-box features, users can enter worklogs onto Jira work items. These entered worklogs are visible directly on the Jira work items and can also be added as a column in your search results. Furthermore, some Jira dashboard gadgets and reports (like burndown charts) can utilize this data.

These are all great but there is an elephant in the room. Since the data is entered manually by your users, it should never be used for performance monitoring. If your users even suspect that worklog data will affect their performance scores, they will unavoidably (and sometimes unintentionally) start to shape worklog data in a way that will make their performance looks good. This will effectively corrupt your data and there is no way you can cross-check the health of it. You are simply dependent on what your users enter into the system. And yes, this is not good. 

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Advantages and Disadvantages of Worklog Based Time Tracking

When considering worklog based time tracking, it's clear there are significant advantages: it's very effective at tracking costs and capacity and generates reliable data for future estimations. However, this method isn't without its challenges. A primary concern is that users often resist manual worklog entry, perceiving it as excessive extra work, which necessitates periodic checks for managers or project owners to ensure worklogs are completed. Furthermore, you must ensure every piece of work your team does is accurately represented on Jira for the data to be truly useful. Despite these considerations, if you have any kind of cost concerns with your team, whether they're working with internal or external customers, this type of data is critically important for cost and capacity calculation, making worklog based time tracking a definite must.

Given these inherent limitations of manual worklog entry, especially when aiming for deeper process insights or automated data collection, many organizations look for alternative approaches. This brings us to the second method: History based time tracking.

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What is History Based Time Tracking?

The other powerful method for tracking time in Jira utilizes history based tools, sometimes referred to as Workflow Based Time Tracking. This approach leverages the detailed history already stored by Jira for each work item. By analyzing this historical data, you can generate comprehensive reports showing precisely how much time was spent in each status, by each assignee, and much more.

History based time tracking doesn't require any manual data entry; Jira automatically maintains detailed work item histories. This inherent feature means you can begin generating reports anytime, even accessing data on past issues. By keeping your Jira work items up to date, you can collect data from Jira’s history logs without a hitch. This way, their histories accurately reflect the true status of the work being done.

To turn these logs and data into meaningful reports, you need an app, such as Timepiece - Time in Status for Jira by OBSS.

Timepiece - Time in Status isn't just another tool; it's like turning on a bright light in your team's workflow. It gives you a crystal-clear view of everything happening.

Here's how: It shows you exactly how long tasks sit in each step (like "To Do," "In Progress," or "Waiting for Approval"). You'll also see who had an item for how long. This isn't just raw data. It's a powerful insight that helps you spot exactly where things are slowing down.

Think of it as getting a full, top-down view of every project, big or small. The history based time tracking allows you to identify bottlenecks in your process, get measurements for various types of metrics (we’ll cover these soon), and even see the trend over time.

The best part? The app calculates its reports using already existing Jira issue histories. So, when you install the app, you don't need to add anything to your issue workflows and you can get reports on your past issues as well. Simplicity at its finest! So, let’s dive in and see what can be done with Timepiece.

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How to Detect Bottlenecks with Timepiece?

‍One effective way to pinpoint bottlenecks is through the analysis of key metrics such as Cycle Time, Lead Time, Response Time and Resolution Time.

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Cycle Time

‍Cycle Time is the duration from the moment actual work on a work item begins until all work is completed. Essentially, it reflects the time spent on the actual work itself. Shorter cycle times typically indicate a more efficient process. Monitoring cycle times, or their constituents, can help identify tasks that may cause delays or impede workflow progression.

Lead Time

‍Lead Time captures the total duration from the moment the task enters your workflow pipeline until its complete delivery. Think of it this way: the clock starts ticking as soon as the work item is created (or lands in your team's work queue) and only stops when all the work is 'fully' completed.

Here is the critical distinction between Lead Time and Cycle Time: Lead Time specifically includes the wait time a task spends in the work queue. This means Lead Time will always be longer than Cycle Time. So, Lead Time is your best indicator of how long it takes to deliver results from start to finish.

Response Time

‍Response Time measures the crucial period from the moment a task is created (or an issue is reported) until the very first action is taken. This could be when actual work begins on the task, or when a response is first communicated back to the customer. Essentially, it's the duration until a hand-off or initial acknowledgment occurs.

By monitoring your response times, you can proactively identify areas where immediate attention is needed, thereby preventing minor delays from escalating into major bottlenecks and impacting your overall efficiency.

Resolution Time

‍Resolution Time tracks the full journey it takes to finally squash an issue or incident, starting the moment a problem pops up and running until it's completely and truly gone. Unlike Response Time, which just clocks the time until the first action, Resolution Time covers the entire adventure until the problem is solved. On the other hand, compared to Lead Time, which usually kicks off when a task is pulled into an active workflow, Resolution Time often stretches back even further to include any time an issue spends waiting in a general backlog before anyone even picks it up.

A final note: Cycle Time and Lead Time are metrics generally monitored internally within the organization. However, Response Time and Resolution Time reflect direct interactions with the customer and are key indicators of the overall customer experience.

How to analyze these metrics with Timepiece - Time in Status for Jira?

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‍Establish Clear Baselines

‍Before diving into metrics analysis, it's essential to establish baseline values for Cycle Time, Lead Time, Resolution Time, or any other metric. This provides a benchmark against which you can measure future performance.

Regular Reporting

‍Implementing regular reporting mechanisms allows teams to stay informed about their performance. Consistent reporting helps in identifying trends and patterns over time, making it easier to pinpoint bottlenecks.

Comparative Analysis

‍Comparative analysis involves assessing current metrics against historical data or industry benchmarks. This helps in understanding whether current performance aligns with expectations and where improvements may be needed.

What Are The Report Types You Can Get with Timepiece?

Timepiece provides different types of reports for tracking the above metrics:

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Status Duration

‍The first and most commonly used report is the Status Duration report. It shows how much time each issue has spent in each status.

Status Duration report can show the time for each status individually but you can also create Consolidated Columns to show the total duration for more than one status as a single column. Very useful for getting the above metrics.

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Duration Between Statuses

‍Another report type is Duration Between Statuses. This report enables user to define metrics that show the duration between two specific statuses.

Using this report, you can get SLA-like metrics where the counter starts at a status, stops at another status, and ignores some predefined statuses in between.

‍Assignee Duration

‍Timepiece also has Assignee Duration report, which shows how much time each issue spent on each assignee. This is an especially great report to analyze the performance of your team.

It is useful to identify cases where some people are overloaded and cannot keep up with the work piling up before them or work items waiting for approval from managers but the managers are always out-of-office and approvals are not done in time.

Group Duration

‍Another similar report is the Group Duration. This report works just like Assignee Duration report but instead of reporting each Assignee individually, it will consolidate them into columns representing user groups.

This type of reporting is very useful where you have separate groups of people working on work items. For example, Level 1 Support, Level 2 Support, etc. ; or Analysts, Developers, Testers, Customers ; or Software Team, Infrastructure Team, External Vendor, etc.

Aggregation and Trend Analysis

‍For all numeric report types, you can calculate averages and sums of those durations grouped by the issue fields you select. For example total in-progress time per team or average resolution time per sprint, week, month, issue type, request type, and so on.

When you group the average reports by date fields such as created year or month, you can observe changes in these averages over time and perform a trend analysis.

Timepiece reports can be accessed through its own reporting page, dashboard gadgets, and issue view screen tabs, providing both calculated data tables and charts.

All Timepiece - Time in Status report data can also be accessed via REST API for integration with external reporting systems.

To learn more or try it free for yourself, click here. Timepiece - Time in Status for Jira. Also, you can explore how Timepiece’s JIRA add-on can revolutionize your metrics measurement process. Enjoy a 30-day free trial to experience the full range of features. Plus, the app is free for up to 10 users.

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