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- How to Measure Developer Productivity?
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Measure developer productivity has always occupied a precarious and oftentimes controversial spot in software project management.
Some business owners swear that there are some metrics that truly help to measure how productive a developer is, others disagree, while others question whether productivity can ever really be measured based on a set of predetermined criteria.
This guide provides clarity on such a complex issue, proving that developer productivity can be measured: the key is to know which metrics to use and, consequently, which ones you ought to avoid.
Breaking Down the Concept of Measuring Developer Productivity
Measuring developer productivity is a facet of software project management that has been the source of immense scrutiny throughout organizations for the last several decades. In fact, some managers consider it to be such a complex task that they would rather leave it as the elephant in the room: a topic that one would rather avoid since there are differing schools of thought on how to approach it.
That said, most project managers and CEOs agree that while defining ideal metrics to evaluate a software developer’s efficiency is a complex process, there is no doubt that the information obtained is beneficial across multiple. The stats speak for themselves.
According to stats shared by Hubspot, low productivity among employers across the U.S collectively contribute to roughly $1.8T in lost income every single year. Needless to say, low productivity implies that a company is not adequately utilizing its existing resources and, consequently, needs to invest more than it should in those types of costs.
In software project management, based on information shared by the Project Management Institute (PMI), roughly 50% of project implementations fail, a statement that implies, in part, that productivity plays a determining role in any software product rollout’s success rate.
For that reason along with so many others, in an effort to assess the progress (or lack thereof) of a given software project, managers rely on a series of metrics that permit them to gauge how productive a developer is.
Largely speaking, whenever a manager thinks of metrics for project management, they immediately they think of metrics related to input and output. While there is some value to looking at those metrics, software development is not like any other type of project, meaning that there is a danger to applying the same principle metrics used for input and output in other projects.
Why do Traditional Input Metrics Don’t Work To Measure Developer Productivity?
Input metrics are a unit of measurement which describes all of the tangible and intangible elements which one puts into a project to achieve a certain output. In essence, they describe a series of actions or behaviors needed that impact the resulting overall goal established by your business.
Usually, they are calculable or easy to quantify numerically, and can also be easily controlled internally.
Bearing this in mind, for general projects, an input metric may refer to a particular number of click-through rates on a landing page or paid ad or even calculate the number of outbound calls made to prospective customers, depending on the business model and type of project.
However, for software projects, and namely software developers, input metrics tend to take on a slightly different character not only in terms of their nature but mainly in terms of their effectiveness as a measuring tool.
Let’s take a closer look at some of the more common ones used in software development as well as why they are a trap that managers shouldn’t fall into:
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As the name suggests, hours worked simply refers to a quantifiable number of hours or amount of time that a developer has dedicated to your project. To many managers, this is a default input metric which, to them, is a clear indicator of employee productivity and, unbeknownst to them, the beginning of a sly trap that they find themselves falling into.
The number of hours one spends on a given task does not necessarily imply that one has been productive during that time. The notion that all work is positive work is a fallacy that cripples the very concept of productivity.
On one hand, the numerical value associated with the amount of work done does not take into account whether the developer worked while sick, distracted, or exhausted.
Consequently, the metric in and of itself does not factor in the time needed to correct tasks that were done poorly nor does it speak to any financial compensation invested to fix any mistakes committed by the developer.
On the other hand (and especially relevant to in-house developers), being present at work and working long hours, does not necessarily mean that the developer is being productive. In the same way that the ‘last to leave the gym’ culture does not necessarily equate to productivity, similarly, the frequently raised eyebrows directed to developers who leave the office before others expect does more harm than good.
In a nutshell, indirectly, this culture encourages developers to spend more time at work trying to convince others that they are being productive, a side effect that has a negative impact on employee engagement and, in turn (and ironically) productivity.
This does not necessarily mean that the metric is outright bad: what it means is that it shouldn’t be taken at face value.
Gauging productivity based on the number of lines of code that a software developer churns out gets you no further to determining true productivity than calculating hours worked.
The best way to understand this is to compare writing code to writing a book.
More words in a sentence do not automatically mean that your writing is better: in fact, it might end up being worse!
More lines in a codebase do not equate to better code quality or productivity. Sometimes, the most complex coding solutions only require a couple of lines of coding from the engineering team.
The key is to work smarter, not harder. Naturally, the smarter you work, the more you will accomplish in a shorter period of time, something which in theory, implies that you will be more productive.
This metric is in and of itself contradictory to measuring productivity.
While it is understood that any software developer will make mistakes when building software, measuring their productivity by their ability to correct the number of errors just doesn’t seem right no matter how you look at it.
Similarly (and on a side note), it is equally illogical to reward a software developer either financially or otherwise for the number of bugs that they’ve spotted and corrected.
Number of Tasks Completed
In the world of software development, it is common for individual developers and teams alike to gauge productivity based on the number of tasks that are completed within a given timeframe.
Sounds logical, right?
On the surface, it does seem like an acceptable metric.
However, similar to the previous ones, it is shallow in its ability to truly shed light on how productive a developer can be.
To put things into perspective, let’s do a side-by-side comparison between the two developers. One accomplishes 100 tasks in a day while the other does 10. On paper, one would automatically assume that the one who does more tasks is more productive.
The problem, however, is that the above scenario does not take into account the level of difficulty of a given task. It is unfair to compare the productivity level of a developer who does 100 simple tasks to that of one who does 10 highly complex tasks in the same time period.
Why do Traditional Output Metrics Don’t Work To Measure Developer Productivity?
Output metrics are the resulting product achieved from your input metrics. They describe what happens when an action associated with an input metric is executed.
Generally, within a software project, output metrics can come in different shapes and sizes. They tend to include financial output metrics that describe revenue gains and profit margins, among others.
However, in the case of measuring developer productivity, they usually relate directly to the input metrics which may or may not include the ones mentioned previously.
One doesn’t need to be a rocket scientist to understand that if the input metrics used in each measure of productivity are skewed then the output metrics will obviously be wrong.
Let’s take a closer look at what this means:
Calculating Lines of Code Written
As has been discussed previously, if code review measurements as an input metric are baseless, then by default, calculating the total number of code lines churned out over a set time period cannot be deemed an acceptable output metric.
In fact, as an output measuring tool, it has even worse impacts on gauging individual performance (or team productivity) than it would have as an input metric. To be frank, a line of code that has no value or constitutes an error is a waste and, consequently, worse than no code at all.
As much as it may seem logical, sadly, there are still engineering managers and product owners who are automatically impressed by the number of lines of code produced by a developer.
In fact, some employers are even willing to pay software developers on a per-line code-produced basis. In case the danger of this isn’t clear, this type of payment method can allow a developer (if they want to) to earn an entire year’s salary in just one day preparing code that doesn’t impact your business value in any way, shape, or form.
Number of Bugs Fixed
Similarly, if a flawed input metric centers around correcting bugs and faults that appear in software development processes, then its resulting output metric would also be inadequate.
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If you reward bug fixing as a measuring tool for developer productivity, then the recruitee may be encouraged to purposefully produce bug-infested software only to correct it later on to give the impression that they are doing the right thing.
In such cases, an employer may feel it fit to manually monitor the software developer’s progress on a project. This is usually done with some type of spyware that is installed on the software developer’s device in order to record screenshots of screen activity, mouse activity, keyboard usage, and more (similar to pull requests in Github but more intrusive). Some of the most popular freelance platforms are notorious for including this feature.
No employee, software engineer or not, can ever feel comfortable with someone breathing down their neck and keeping track of their every move. It creates a highly tense environment, causes discomfort, and actually stifles an employee’s creativity since they feel pressured to perform since they are being watched.
In fact, instead of measuring productivity, you might end up measuring how quickly your hired developer is willing to quit the project from such stress.
Why Measuring Developer Productivity In Teams Is No-Easier?
Even if there were a magical formula to determine the best metrics to measure developer productivity, they would all have to be modified or replaced completely when applying the same principle to software development teams.
As logic will indicate, due to their numbers, a development team will produce results faster than a single developer can.
However, while a team may sound like a productivity machine, this doesn’t necessarily always pan out in reality. A four-member DevOps team of low-performing, poorly-coordinated, unqualified software developers will probably produce worse results than if the individual team members worked separately on the project.
By contrast, you assemble an average-yet-well-coordinated four-member development team and equip them with the right project and they ought to provide solid results.
Similarly, if you can leverage the expertise of a development team that has the right work culture, attitude, skills, and experience needed for your software project, then you have no need to worry.
However, when it comes to truly measure productivity in a team, by and large, it is a highly complex task.
Software development teams, by their very nature, require that two or more persons coordinate their efforts and contribute towards the completion of a given project. For that reason, the work output produced by the team is a by-product of individual efforts which require interaction, planning, and coordination which are all interdependent upon each other.
Within a team, while some members may not be as active as others, that does not diminish the value they contribute to the overall functioning of the unit.
This is because those members may very well be force multipliers without whom the other team members would have significant difficulty carrying out their activities. For that reason, in as much as their productivity may seem low, their impact on the rest of the team is immeasurable.
How To Measure Developer Productivity The Right Way?
Having established the dangers associated with measuring both team and individual productivity, let us now turn our attention to recommendable ways of quantifying or qualifying their performance.
Please note that there isn’t a set of one-size-fits-all metrics that determine productivity. As software projects require different skills and tasks from developers.
Therefore, it is up to the company or business to define the metrics which are best suited for your software programmers based on the type of project you are completing.
Generally speaking, these metrics can be classified under three essential categories:
- Metrics that measure how much work is completed.
- Metrics that gauge the quality of work that was produced.
- Metrics that speak to the manner in which a developer approached their tasks (did they prioritize tasks, do the tasks completed coincide with the overall business goal).
When combined, these guidelines assist you in figuring out the criteria upon which you ought to judge how productive a developer or development team is.
Let’s examine some acceptable metrics that you can consider incorporating in how you measure developer productivity:
Tasks Multiplied by Complexity
You can consider this an improved version of the metric which examines the number of tasks that were completed.
In essence, this metric seeks to qualify the type of tasks that are completed on a level of complexity in an effort to better contextualize the type of contribution that a developer or development team makes to a given software project.
Once tasks have been completed, a numerical value then is assigned to each one in accordance with the level of difficulty of each task, and, in the end, an aggregate score is calculated to determine how productive that developer has been.
Of course, this type of metric is highly subjective as the product owner or relevant managerial personnel on the project would have to first determine the various degrees of complexity for set tasks in order to then monitor the results.
However, it does allow for greater flexibility when determining case-by-case productivity among developers for any software initiative.
This metric can be implemented with a closed ticket implementation tool such as Trello or Asana. These types of applications allow one to upload tasks, assign them to team members, and close each one once they have been completed.
Velocity Multiplied by Task
When done correctly, velocity can be a solid metric to measure progress throughout the product development cycle.
In its purest form, velocity simply determines how quickly a task is finished within a given timeframe. It seeks to answer the question ‘how much can this developer or development team do within X number of working days?’.
Once the result has been obtained, then that becomes the standard measuring tool for output which one can use for future tasks. If the team takes less time than the initial measurement, some businesses then use that new time as the measuring stick.
A way to optimize this metric is to factor in the notion of complexity in the task completed when calculating velocity. As can be expected, a complex task will take a longer period of time to complete than a simpler one.
Therefore, examining only time without complexity will not paint an accurate picture of how productive a developer is. However, once you apply a different weighting to speed based on task complexity, then you can better gauge how well a developer or development team has been performing.
Overall Team Performance
If you have contracted the services of a software development team, then you find that it will be far easier to gauge the performance of the team as a whole as opposed to individual team members.
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The easiest way to do this is to determine whether this team consistently produces useful software solutions within a suitable time period. This falls in line with one of the principles of Agile processes, something which forms the cornerstone of most software engineering operations.
In order to do so, you can rely on raw statistical data obtained through aggregate calculations on complexity and task ratios.
However, you ought to substantiate it with the careful observation that emphasizes organizational management. This can be achieved through honest one-on-one interviews with individual team members where you get anonymous feedback that speaks to internal management within the team and how well they coordinate with each other.
This is also a good opportunity to combine developer productivity with boosting employee motivation by encouraging them to document their own achievements so that they can keep a track record of their successfully completed goals.
Fostering A Healthy Work Culture
Although this doesn’t directly allow you to quantify developer productivity, it does play a significant role in the chances of it increasing or decreasing.
No developer will ever thrive in a toxic environment where they are unhappy. According to the book Time, Talent, Energy (Bain & Company Inc), an employee who feels engaged with their work churns out 125% more in productivity than one who isn’t. Needless to say, for startups that value productivity to scale more than any other business, this is important.
There are a number of fun ways in which you can build employee engagement such as through standup meetings to keep the team energetic, among others.
For that reason, you can use work culture and employee engagement metrics as parallels to complement other metrics used in measuring developer productivity.
Why All Companies Should Care About Measuring Developer Productivity?
Despite the extensive discussion on metrics for developer productivity, some companies do not incorporate any steadfast rules when it comes to measuring developer productivity.
This is quite typical in a remote work culture where there is less physical contact with software developers. This also tends to occur in businesses whose primary work culture centers around raw output as opposed to input.
While some companies may be resistant to the need to put in place the types of metrics indicated above, I cannot overstate why they are so important.
Whether you work with a remote team or not, you are still working with people. Humans are not machines who can produce anything at any given time, in the same way, every single time.
Emotions, challenges, problems, and difficulties, among others, affect how we work and these are things that need to be taken into account in the evaluation of a software project’s development cycle, otherwise, you will be doing the management of your project a serious disservice.
How To Simplify Measuring Developer Productivity?
While these metrics mentioned previously are all crucial in successfully measuring developer productivity, it still doesn’t change the fact that you still have to evaluate a developer or team’s performance.
This evaluation may either be satisfactory or not, depending on your standards. You may find that the developer or team does not demonstrate the right levels of productivity needed to continue operating on the project.
The easiest way to drastically reduce the chances of this occurring is to ensure that your software developer(s) align with your project’s specific needs from the get-go. Doing so involves partnering with professionals who have both the experience and skills needed to take on your project and succeed.
Sourcing these types of professionals is not easy. Businesses tend to resort to popular freelance platforms or job boards to scout talent.
However, for such platforms which do not have a vetting or evaluation process, you are the one who has to undertake the entire quality control process when sifting through candidates.
To make matters worse, these platforms are teeming with shady professionals who claim to have the right expertise for your project, yet they often misrepresent their skills, thus making it difficult for you to get in contact with the right talent for your project.
Instead, here’s a way to secure top, reputable, credible talent to get on board your software project and guarantee a successful working collaboration.
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DevTeam.Space is a vetted community of expert software developers who are supported by an agile AI process which makes it easier to assimilate top talent into your software development project and watch it become a success.
All team members who constitute the Devteam.Space software community are carefully selected, being merited for the experience, skill, and drive to deliver excellent results for all of our partnering clients. They also go the extra mile by constantly seeking new ways to increase their knowledge in key software development areas so that they can continue to impact positively on software projects across the globe.
All of our developers are supported by an agile AI algorithm process that has all the functionality you need for successful project management:
- Allows you to easily align the product development cycle with the various software development phases which constitute the project and in turn clearly separate milestones and their corresponding payments.
- Access weekly reports and daily workday overviews which cover updates on the progress of your project.
- Easily pinpoint challenges within a software development workflow that are stunting its completion so it can easily be resolved.
- Provides you with data that will enable you to gauge both a team and an individual software developer’s performance throughout all phases of your software development cycle.
By partnering with developers who are already predisposed to the Kanban principle of Agile methodology, you almost guarantee to measure high productivity output.
Final Thoughts On Measuring Developer Productivity
This guide breaks down the best way to measure software development productivity both on an individual and team level. Be sure to be prudent about the types of metrics you use since not all are made equal. Also, stay clear of freelance platforms when searching for talent. Chances are, you’ll end up collaborating with someone who isn’t the right fit for you.
Read more on how to measure KPIs for developers on our blog here.
Wondering where you can secure top talent? Take a couple of minutes to fill out a DevTeam.Space questionnaire. An account manager from DevTeam.Space will reach out to you as soon as possible.
FAQs on How to Measure Developer Productivity
You do not measure developer productivity by the number of code lines written, hours worked, bugs fixed, and tasks completed.
In scrum development, you can measure developer productivity in terms of the actual delivery of software. If the product owner is satisfied, it is a successful sprint by the development team.
Developer productivity is how productive a developer is in a given time frame. It also depends on the complexity of the task the developer is working on at this time.