The Importance of Engineering Metrics – Why Gut Feeling Isn't Enough
The Journey of Adopting Engineering Metrics
The Journey of Adopting Engineering Metrics
In our fast-paced digital world, it can be tempting to rely on the “gut feelings” of your engineers. After all, many of the most famous examples of brilliant inventions are those that came about almost by accident, driven by a moment of inspiration. And as these ideas whizz around the world and inspire others to copy and improve upon them, it’s natural to assume that the best engineers aren’t the ones who measure everything but rather those with sharp instincts.
In practice — at least in some fields — this may be true. After all, if you’re designing something like a bridge or airplane or skyscraper, there are some things you have to envision first before you look at measurable data. Today, however, much of software engineering has become quantifiable, which is why metrics matter if you want to succeed.
Maintaining the performance of an engineering organization is challenging. There are so many different factors to monitor and manage in order to ensure that projects run smoothly, resources are utilized effectively, budgets are not exceeded, and products are delivered on time and with the right level of quality. That’s why engineers need a toolkit of metrics to help them understand their processes and keep tabs on their progress.
Metrics also give you the insight you need to lead your team more effectively by providing a clear picture of where your team is at and how they’re progressing. They can also alert you to any issues early on so that they are much easier to deal with before they become intractable problems.
Getting started with metrics can be difficult.
This article provides insights and examples of why engineering metrics are more important than gut instinct, and offers some advice on how to build a useful set of metrics for your team.
What Are Engineering Metrics?
Engineering metrics are the best and most effective way to assess the quality and proficiency of an engineering team. Knowing every quantifiable measure for your codebase and product lifecycle is beneficial when it comes to evaluating performance and identifying the various strengths and pitfalls of any given project.
Consider a more basic and less technical metric such as user satisfaction, which can be further subdivided into customer satisfaction and employee feedback. A customer satisfaction metric is used for publicly available products, whereas employee feedback is usually required for internal applications before they are released to the general public.
User satisfaction metrics can provide a wealth of information to a team. If the product receives poor or negative feedback, future implementations will be aimed at improving the product and obtaining positive feedback. On the plus side, if the reviews are average to good, changes will be made to improve the software's state. As a result, there’s value to tracking software metrics.
The following are four key benefits to relying on metrics over gut instinct:
1. Improved development process
What should be measured is just as important as why when it comes to development.
To elaborate, an important process metric such as lead time, which refers to the time it takes for ideas to be created and delivered as fully fledged software, is the foundation of any development process you use. A long lead time may indicate a less effective team, whereas a short lead time may indicate that the team is more responsive to customers.
The time it takes to change a software system and put that change into production is referred to as cycle time, which is sometimes used interchangeably with lead time.
For example, your customers have reported difficulties using the API; how long does it take you to make the necessary changes, improve the API, and put it into production?
This is one reason why engineering metrics trump gut instinct in the development process.
If you are not tracking customer reviews and user satisfaction, you will be caught off guard and have no idea what your devoted customers are going through (more on that in a minute).
But suppose you made the necessary effort to understand their plights, but you lack a critical system that tracks cycle time, leaving you blindsided on the development process or how often you respond on time.
It is easy to assume that a few days to weeks will suffice to resolve a minor issue, but the most important consideration is whether the users of the tools have the luxury of waiting that long or will they turn to another product (perhaps your competitor).
It is important to note that these metrics are simply numbers and do not provide specific solutions or recommendations, but they are the first step in retaining users by accelerating the development and resolution processes.
A better development (and resolution) process has a positive impact on customer retention, which leads to increased sales and revenue.
2. Increased sales and revenue
Jeff Bezos, one of the forefathers of e-commerce, is a big proponent of customer focus. The principle of focusing on customers rather than competitors is what propelled Amazon to a trillion-dollar valuation.
Customer focus, according to Bezos, is not only about listening to or learning about customers, but also about inventing on their behalf because it is impossible for them to do so.
This insight directly relates to accelerating the development process and its impact on revenue and sales.
To see it firsthand, let us go through a customer experience cycle:
For every problem that costs an existing customer, assume that 100 customers will follow suit and that new customers will become averse to your products.
A quick development process is required in a rapidly evolving space to invent and release a large set of necessary tools and technologies.
You can't gamble on speed if you want to secure user/customer loyalty. The evolution of social networks has increased instant gratification by making everything readily available, so people are unlikely to stick around if a piece of software or a product fails miserably. There are always alternatives, namely your competitors.
Consider your project. What are some obvious bottlenecks you can address to increase conversions? What are some examples of things that work now but will not work in the future? Fix them right away.
3. Improved product quality and scalability
Because software crashes and failures are unavoidable, more emphasis should be placed on determining how well a software performs in a production environment.
There are several unique metrics, such as application crash rate, which is a measure of how many times an application fails divided by how many times it has been used.
Let's look at the mean time to recovery (MTTR) metric, a part of the DORA metrics, which measures the time it takes from the discovery of a bug or a breach to the deployment of a viable solution.
Having a consistent set of metrics running through your code is essential for ensuring the state and fragility of a piece of software. A long MTTR could indicate that the teams are not elite performers or that the solutions are not viable.
A building team is expected to solve a particular problem only once. Because MTTR is a powerful indicator of the overall impact of a crash, resources can be channeled to keep the number as low as possible. A low MTTR is achieved by increasing the efficiency of resolution processes.
The concept of scalability refers to how a system's property handles an increasing amount of work as resources are added to the system. Technical leads can gain insight into how a program handles the scaling phase by utilizing metrics such as lead time (the amount of time it takes for ideas to be created and delivered as software), team velocity, Github open and close rates, and MTTR.
4. Saves time and resources
Understanding the project requirements is the most important factor that influences project speed and saves money. This is why design and planning are included in the initial stages of every software development lifecycle.
Misplaced priorities and disproportionate resources are two issues that stifle the growth of many startups. You cannot be successful in the technology industry if your entire thought process is based on haphazard analysis and chance. Data and numbers are essential.
Because the insights gathered during the early stages of your software are untested, they may differ (slightly) from the outcome when run in production. (In other words, expected outcome = actual outcome.) As a piece of software matures, many insights into what works and what doesn't emerge.
Even though most of the core fundamentals of business are similar, the technical understanding varies. Tech leads and builders who make a concerted effort to learn more about how their software is performing through the use of engineering metrics always outperform those who analyze based on their feelings. Further, understanding the needs and trajectory of your project is critical because it saves you a lot of time, manpower, and money.
To learn more about the adoption of engineering metrics, be sure to check out the latest resources and software on the Keypup blog, including information on automating DORA metrics, software delivery, and quality insights.