Data is constantly generated, reviewed, and updated in today’s digital environment. It also aids software engineers in their work by providing accurate, actionable feedback that enables them to better understand where and how to enhance a product or process.

Data also aids IT leaders in visualizing how work is completed, the quality and amount of production, and how they may better the lives of their employees. It’s also an important component of any digital transformation.

Many businesses are introducing metrics-based key performance indicators (KPIs) or goals and key results (OKRs) to encourage employees to consider the corporate value and strategic outcomes in their daily work.

KPIs and OKRs are useful tools for data-driven software engineering when utilized correctly. The correct measurements provide visibility into how successful (or unsuccessful) the firm is, and each employee can see how their work contributes.

When it comes to data-driven software engineering, though, there’s still a lot to learn. The major components, obstacles, and best practices for getting it right are outlined below.

People are key

The ability of your teams to work together, rather than focusing on numbers and charts, is frequently the key to successfully implementing a metrics-based program. Individuals must interact with the data, and they should ideally be the ones asking for more data in order to enhance their work.

This is more likely to occur when the human side of engineering is considered at the start of a KPI or OKR program. With this in mind, a successful data-driven software engineering company will discover what motivates its employees to succeed and what they require to perform their duties more effectively.

There is a drawback to a metrics-driven strategy. When KPIs aren’t correctly implemented, problems arise, especially when:

  1. The development and implementation are clumsy, and they prioritize management over listening to engineers, understanding what they need or desire, and addressing their concerns. Teams will be fearful of a data-driven organization; therefore, leadership must address this concern or risk the resulting disengagement.
  2. The company, department, or team is having a slow year, quarter, or month. It’s difficult to keep team members interested and prevent KPIs or data-based management from becoming oppressive in this environment.
  3. The proportion of team and individual contributions is out of whack. Organizations must strike a good balance between team metrics that assess (and reward) team achievement and individual contribution measurements.

Many of these issues can be avoided by carefully developing metrics or OKR/KPI systems. To get started, your team has to understand the four pillars that make data-driven software possible, as well as how to put them into practice.

Anatomy of a data-driven engineering organization

The key features of data-enabled software engineering are as follows.

Enabling data-driven software engineering requires five essential components in total:

Company vision

Although having a clear company vision is not exactly one of the pillars, it is essential—and it must come from the top. Each pillar is highly influenced by the vision, which should specify what those pillars are (particularly in the case of KPIs and OKRs). The company vision is the organization’s “why,” and it should be represented firmly in your KPIs and OKRs.


These assess your company’s long-term business performance, such as profitability and how well it accomplishes its goals. If one of these KPIs is not met, your employees may get disengaged from the company’s vision.


These are measurable objectives that are less permanent than KPIs. To accomplish and improve results, your OKRs should measure what is happening right now (this month, this quarter, this year). KPIs improve when OKRs are strong. They best demonstrate that you chose the proper work and completed it well.

Engineering metrics

These can be difficult to come by. What constitutes good software development? What criteria do you use to evaluate a great developer? Good engineering metrics should result in software engineers agreeing on standards, a high bar for job quality, and the creation of additional and better features to support more useful work.

Positive behavioral metrics

To better understand why these indicators are significant and how they work, additional explanation beyond this bulleted list is required. What gives your workers enthusiasm and boosts them up so they deliver anyway whether they’re having a bad quarter or a bad team? What motivates them to keep going? What convinces them that it is worthwhile to do so? Positive behavioral measures drive each of these.

How to get it done

While this paradigm might help you overcome some of the challenges of data-driven software creation, keeping up with these pillars may seem difficult.

It’s easy to see why: Extra paper-pushing doesn’t benefit anyone, and a leader’s time and energy are valuable assets. So, here’s a low-cost method to get started on this task and develop it as you figure out which parts are most important to you:

Most KPIs should be an accounting function

Those who aren’t should either be or should be incorporated into the software as a major management function. Be wary of exceptional situations and subdivisions that complicate KPI reporting. Everyone should be measured at the same time. Subdividing large corporations with actual business units is possible.

Experiment with OKRs and scale as necessary

The week did, for example, is a free tool that you may use to get started. Another option is to set some basic OKRs for teams each quarter and track them in a spreadsheet. The spreadsheet results should then be reviewed and discussed on a regular basis.

Get an engineering metrics tool

To keep track of effective engineering metrics, you’ll need one, and there are various options. It’s critical to involve your development staff in order to gain a better understanding of their job. They will be able to better understand their work and how to get more done with the help of an excellent tool. What are the stumbling blocks? What works nicely for you? What makes anything difficult?

Encourage your team to interact with the statistics and come up with new ways to use them. The way to go is to create your own metrics that your team sees as beneficial to them or their fellow engineers. You are free to make suggestions, but the more ownership this has with the folks who are developing your program, the better.

For positive behavioral metrics, using a tool is helpful, but not 100% necessary

By sending automatic emails, texts, or messages, the proper instrument can help transmit positive energy to more people. These provide a boost to managers, demonstrate to employees and bosses that managers transmit that energy, and provide a lift to everyone.

It’s not the same as sending a single email to one individual and keeping track of the data in a spreadsheet. I’ve created tools with this functionality, and the main concepts of this approach include multi-person recognition, up-chain recognition, positive energy flow in general, and principle-based recognition. (I’m working on an open-source utility that I hope to offer soon.) Other employee recognition options exist, and you can locate them by completing a fast online search.

If a tool isn’t available, simply find ways to disseminate as much positive energy as possible and practice up-reporting (e.g., sending praises to the person’s boss or boss’s boss). “One of the finest parts of my job is going around recognizing individuals for all the fantastic things they accomplish,” a CEO I previously worked for said. So, sending her letters regarding my team’s accomplishments was not difficult for me. It made her happy, it made my employees happy, and it made me happy. That’s a lot of good vibes.

Go beyond the numbers

If you have an effective process or methodology that lowers pain points and drives success, data-driven software engineering delivers benefits that go far beyond the numbers. You’ll need to put a larger emphasis on delivering value as your company progresses toward digital transformation. With these measurements in place, the value you provide will be quantifiable, and your staff will be motivated to contribute to the company’s success.

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