July 11, 2023
A 2022 WhitePaper by the Consortium for Information & Software Quality estimated that the cost of poor quality software in the US had grown to $2.41 trillion with software technical debt amounting to approximately $1.52 trillion of that amount. Given that the total GDP for the US in 2022 was approx $25 trillion, the cost of poor quality is at nearly 10% of total GDP. It’s a shocking figure. Technical debt is a huge problem for technology companies.
For tech leaders in industry the issue of quality is obvious. Good leaders have processes around quality. Good teams measure and address quality in bugs, change requests, or technical debt tickets. They assign percentages of sprint time to address these bugs and tickets. But is this really the full picture of addressing the cost of poor quality?
We don’t think so.
In our work with clients, and with better data and metrics, we are able to see how quality issues don’t just surface in discrete bugs and technical debt tickets. Rather, in the data we are able to see how each and every ticket, story, feature, and epic is impacted by quality. Our benchmark data aligns with many other studies that suggest that, depending on the industry, the size of the business, and the severity of the code defects, the cost of poor quality code can range from 10% to 30% of a company’s annual revenue.
But let’s be clear, quality is about the bottom line and not just limited to engineering tickets. When teams, projects or organizations suffer from quality issues, the result is constant rework, delays, and increased development and maintenance costs. And all of this has follow-on negative impact across the sales, marketing and operations functions. Time is wasted. Customer satisfaction is impacted. Brand reputation is eroded. Bad quality is bad for business.
Could 10 to 30% of your technology delivery output be being lost to quality issues? The survey data would suggest so. Of course, many organizations will struggle to get accurate and insightful data around the true picture and cost of quality in their technology delivery. The data is there but connecting the data to reveal how each team or function impacts quality is difficult to do with project tools like Jira and DevOps. You need to invest to get more joined-up insight. But it’s worth it because getting the actual data and putting a concrete objective figure on the cost of poor quality in your teams, projects and organization can be revelatory for organizations and the leadership. And when you can put an actual price on quality, it changes the discussion around budget and investment.
It’s also a common failing to focus too much attention around quality on technology teams and their efforts. One of the most striking things we see when we benchmark technology delivery performance, is just how much poor product requirements and design reduce quality. We all complain about technical debt because it is tracked. But we don’t talk about experience debt. And design debt. From our data, these are hugely costly. In addition, operational inefficiency in support teams impacts quality. Poor data and metrics in marketing impact quality. It’s not all about engineering. Identifying the root causes of quality issues requires a holistic approach.
It will come as no surprise that we at Implement Partners believe that to truly understand and improve quality, it’s imperative to have better data and metrics. You need data and metrics that offer real-time visibility and granularity of technology quality. But you also need data and metrics that provide insight on quality across your wider org and how that impacts technology delivery.
Sadly, much in-market quality optimization offerings too often come from off-the-shelf play books. Experts in DevOps will usually find a heap of dev ops quality issues. Experts in Agile will find a gaggle of agile issues. A lean consultant will find… lean issues. But we believe that getting better data and insight allows you to get to the root causes of quality issues and address those. And, importantly, armed with accurate data and metrics, you can make data-driven decisions, allocating resources strategically to optimize quality, and applying those resources tactically in teams, projects or across the organization for greatest impact and value.
Focussing on data-driven quality optimization allows for better quality outcomes. With this approach and the data, we’ve seen teams improve code quality metrics by 78% in a matter of weeks. Throughput is increased. And time to market accelerated. And, what’s most satisfying is that these changes that are made are very often small tactical ones made by the teams themselves. Engineers, by their nature, strive for efficiency. Give them the data and they’ll find it.
In conclusion, the cost of poor quality in technology delivery is extensive and can significantly impact an organization’s success. However, overcoming the challenges in improving quality is achievable through data-driven approaches like those offered by Implement Partners. By leveraging better data and metrics, tech leaders can gain valuable insights into team performance, identify opportunities for optimization, and ultimately achieve better business outcomes. And, of course, the efficiency gains allows tech leaders to free development teams to focus on innovation and new feature development. For the business this means getting more value to customers. Improving revenue. Increasing margin. Quality matters! And data is critical.
We specialize in helping technology leaders use data and metrics to improve technology delivery performance and achieve better outcomes.
Want to learn more? Drop us a message and we’ll get back to you.
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