There are a lot of opinions about the best possible way of measuring productivity, but that can bring us to another question entirely: why measure it at all? In this second part of our interview with Adolfo Cruz, we dig into the reasons why measuring productivity is important for any organization.
By Scio Team
If you are adding value for a client during a product’s development, creating something they can use to attract more users or increase their profits, you may say the time invested in the process was productive, but how do you measure that? Can it be done?
Productivity can be witnessed, it happens right in front of you when a team is making progress, but translating that into data is not an easy task; it takes a lot of time and effort to get right, and it might take focus away from the resulting product, ironically affecting your productivity.
It’s similar to that quantum physics phenomenon where you could change the outcome of something by observing it; all the effort invested in getting exact numbers to measure productivity could make you neglect stuff that has value for the product developed, so you need to be very careful in how you implement measurements to not interfere.
So this begs a very important question: why measure productivity at all? You can see people in the software industry questioning that, going as far as suggesting it’s unnecessary, but we disagree. At Scio, we want to know if our engineers are offering real value to our clients, which is very important to us even if sometimes we use subjective, case-by-case measures to do so.
Measurements impact the way products are being developed
Reaching a standard that applies to everyone is complicated, and if you add the fact that some people may be working on different projects and products at the same time, with different challenges and rhythms, you get variables that complicate things further, so we guide ourselves by the idea of “We are productive if we add value to a business”. It’s a given that achieving working software is delivering promises, so it’s more about how a client feels about the products you are making.
The problem is trying to approach this with objectivity, but doling out numbers can have unintentional consequences; developers can over-focus on raising their numbers because the important metric seems to be proving your value with high stats, so it ceases to be a team and instead is just a collection of people making their figures go up. Metrics can bring improvements, but you also need to consider their context to make them helpful, which is why it’s difficult to find a universal solution to measure productivity in software development.
When we are in charge of managing a project, productivity is more focused on avoiding red flags instead of checking who is less productive in any given team, measuring it to avoid deviating too much from our goals; it’s easy to fall from a cliff if you aren’t careful with that. We are not interested in using metrics to know if everyone is achieving some arbitrary standard, but rather steering a ship, looking at the productivity of the team as a whole.
To this end, it’s useful to register the progress of every project and map them out to find general trends rather than trying to get exact figures. Robert D. Austin, the author of the book Measuring and Managing Performance in Organizations, said that unless you can measure 100% of something, there’s no point to measure anything at all, but in most cases, you don’t need to have every single data point, just an educated guess about where the project is heading, helped with some metrics that give a clear perspective.
This can be seen in the sprints. With information about how many story points (the metric used to estimate the difficulty of implementing a given improvement) are completed, how many issues surface, how many are solved, and comparing it with past efforts, the red flags are obvious. If the team completed between 5 and 10 story points in a sprint, but only 1 or 2 the next one, you need to dig into the process; you might find some challenges nobody saw coming and had to be solved to move forward, and you didn’t need more than knowing past productivity to compare.
And often, if you are using Agile Methodologies, the team is the one that realizes when someone is struggling or is free to help and correct the issues themselves. A good team can manage itself, keeping productivity up without needing someone to check their progress daily. This also results in the quality of the product being directly embedded into the productivity of the process, as the team should already know at this point what needs to be measured to plan with the amount of flexibility necessary to succeed.
We help your team deliver more value to the business.
In software development, we could measure how many Final Users are aware of a specific feature, how many support tickets are being sent, how many things are misunderstood, or which things are not working as intended, converting it into data to know if there are issues during development, but you still need to take some subjective measurements, like conversations with the clients to know how they feel about the product, to give context to this information.
That’s the impact we want to have on our clients, and more often than not, they start seeing the benefits of these processes. They take the time to plan their sprints, properly assess the project, and address issues, especially with not very experienced clients, whom we show what a good software development cycle looks like.
After all, developing software is closer to creating art than manufacturing an object, so the question of productivity is similar. Just like writing a novel, it’s hard to estimate exactly how long each step is going to take because human beings are bad at estimating time and effort in the long run.
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As we know how quickly things can change in a short amount of time, Scio typically plans short-term goals (between 1 – 3 months) and mid-term goals (between 6 – 12 months) at most when we work with our clients during the evolution of the product, in order to ensure it has enough room to grow naturally, focusing on the steps we need to reach a desirable outcome, and even then it’s a challenge to keep every detail under control. There have been occasions where we have to overhaul plans to finish a project in the timeframe we set, and in those situations, the final product is different from how we first envisioned it because of the natural evolution that a project goes through.
So planning way too into the future is highly risky, shorter steps with a clear idea of every milestone is a method that has shown us the best results to develop a product, which is one of the principles of the Scrum methodology; working with iterations that have defined starting and ending points, and progress is registered at every step.
And even then you can get slightly different results every time. Sometimes a team is very well attuned and can build things faster than a team mostly composed of new developers, or engineers who had never worked together before, so obviously they took a little longer, which is why Scio evolved to focus more on the value we are delivering to our clients, involving them more in the process, deciding together which features were more valuable, and the priorities to establish.
After all, always having the option to say “Okay, let’s stop for a bit, reorganize, plan better retrospectives, and find areas of improvement” depends on knowing your process back and forth, and that’s why measuring productivity is important.
Measuring productivity is hard, but it’s not impossible. It takes some general metrics and subjective questions dictated by human behavior that are never objective. That’s where Scio comes in – we design teams that fit with the culture and practices of our clients, ensuring that no matter what, we always have the necessary perspective to achieve a successful engagement. If you want help measuring your engineering team’s productivity or just need someone to bounce ideas off of, send us a message. We love talking about this stuff!