Article by Vikas Basra, Global Head, Intelligent Engineering Practice, Ness Digital Engineering
Today, digital experiences are the driving force behind everything—whether it’s boosting employee engagement, making rewards programs sparkle, or delivering customer service that wows.
DevOps is the industry that underpins all of this, bridging the gap between software development and IT. The importance of this market can be seen by current forecasts, with the industry expected to grow by 20% until 2026, reaching a market size of $18 billion.
This is before we even touch on the phenomenal growth of AI, a space which has seen Big Tech investments hit a quarter trillion dollars. Such investments are testament to how future business growth across industries is going to be inextricably linked to digital tools and technologies.
Velocity Without Compromising Quality is Mission-Critical for Competitive Advantage
With that in mind, leaders need to tackle a growing but often overlooked issue: Velocity; or specifically, the speed at which an organization can zoom through its software release cycle to roll out new features and products—without compromising on quality!
Velocity is a critical focus in DevOps, yet many businesses struggle with it. While some teams celebrate releasing features every few months, top performers like Amazon and Netflix achieve release cycles in days. Traditional enterprises often take 3-6 months due to rigid hierarchies, manual QA, and limited CI/CD automation. In contrast, Amazon deploys code every 11.7 seconds using microservices and CI/CD, while Netflix enables daily updates through full-cycle developers.
DevOps varies by perspective—some prioritize IaC, others emphasize automated pipelines or continuous integration. At its core, DevOps integrates the entire lifecycle: Plan, Code, Build, Test, Deploy, and Operate, demanding maturity across Agile practices, CI, automation, security, and more.
Despite tracking engineering metrics, organizations often fail to distinguish high-performing teams from those lagging. True performance requires both speed and quality. Teams excelling in one but not the other risk falling behind, unable to keep up with customer expectations in a fast-paced world.
The ability to release new features or push through code that fixes an important user error is business critical.
Challenges in Achieving Velocity and Quality is multifaceted
- Complexity of Modern Development: Modern software development is now more complex, with trends like cloud computing, security demands, citizen developers, and GenAI transforming workflows. These shifts have made accelerating development speed a greater challenge than ever.
- Cross-Team Dependencies: Releasing a product requires multiple teams working together, but interdependencies can cause delays. Even if one team is efficient, others, like cloud architecture, might slow the process, especially with modern systems’ growing complexity.
- Limited Understanding of Velocity and Quality: Speed alone isn’t enough – quality is crucial. Agile and Kanban boost efficiency but often overlook bottlenecks in modern, interconnected development. Balancing speed and quality become tougher as projects grow more complex.
Intelligent Engineering as the Solution
Have you unlocked the full productivity potential of your organization by using process, automation, and GenAI? By combining these powerful tools, organizations can boost their productivity to the fullest. A data-driven approach, along with a strong focus on process, DevOps, test automation, and automation strategies is crucial for improving speed and efficiency.
When these elements—process, automation, and AI—are applied in a structured way, they form what we call Intelligent Engineering. This approach helps continuously improve performance and productivity, driving consistent progress.
However, it’s important to note that productivity levels can vary widely across different teams, depending on how mature these practices are.
More Resources ≠ (is not equal to) Better Velocity
The pressure to move faster means that often organizations throw more resources, usually in the form of more developers, at the problem. Yet the complexity that we explored means that adding more hands to the keyboard won’t magically fix the underlying issues. Throwing more programmers at the problem will do little to get companies to meet a short deadline for a new feature when bottlenecks and quality control issues are present in the pipeline.
Likewise, falling for the low-quality code trap to reach a deadline more quickly is like using a band aid to stem a leak. It might help the company release a feature, but won’t solve foundational issues. More importantly, pushing out code with quality issues risks major reputational damage.
As we move into 2025, leaders need to understand what questions to ask in order to uncover sources of waste and set KPIs that offer actual improvements to the speed and quality of development work.
With this answer serving as a foundation, decision makers can begin to answer key questions about the software engineering talent they have spent time and money to hire.
These questions include:
- What are the key challenges to getting engineers to work at their optimal level?
- How do we know if developers are spending their time on activities that truly drive value?
- How does the process within organizations affect their ability to produce their best work?
Data is Central to High-Performing Teams
Although velocity presents a challenge, decision-makers need to remember that it can be addressed using a data-driven approach.
While adding more resources won’t solve underlying issues, when organizations leverage tools and technologies with the ability to measure the entire pipeline and pull from productivity management software that teams use, the issues begin to rise to the surface and become transparent. By analyzing all available data sources, leaders can uncover the answers to critical questions that get to the heart of the issue. For example, they can assess how effectively teams are performing in bug testing or identify the average handover time between teams, revealing key insights into process efficiency.
Some of this data will show that there are avoidable sources of waste that, when eliminated, immediately help to improve the overall velocity rates. In other cases, the data can identify where teams are struggling with quality measures so that support such as automation can be applied.
Using such an approach at Ness Digital Engineering, it was found that across 45+ client engagements, 62% of high performing teams achieved high speed without compromising quality. Impact analysis of various KPI drivers demonstrated that Requirements Stability is the single biggest driver of high performing teams. Next, stability of requirements during sprints drives speed and quality by as much as 41% across accounts, highlighting an important finding for the industry. While velocity can be hampered by many factors, the stability of requirements during sprints had a consistently significant impact on the overall speed and quality.
In short, by starting with the data, we can find the areas that are impacting speed and quality and develop relevant KPIs and solutions that address these problem areas. This approach will deliver an immediate ROI and ensure that the productivity measures in place effect change in the ways that matter for the business.
Actionable Questions for Leaders
Leaders must focus on:
- Identifying obstacles that prevent engineers from operating optimally.
- Evaluating whether team activities truly drive value.
- Understanding how internal processes impact performance.
Immediate ROI from Data-Driven Insights
- By addressing bottlenecks and quality issues using data-driven KPIs, businesses can improve velocity and deliver faster ROI.
A Call to Action for 2025
- Digital experiences rule the marketplace in 2025. Every company should aim to excel in the delivery of software products to keep ahead of the competition. Many leaders aren’t aware that the ability to release new features and code updates at a fast pace is both mission-critical and difficult to achieve.
- By tapping into a data-driven approach that digs deep into the heart of complex development challenges and pairing it with cutting-edge coding tools, companies can speed up their release rates while keeping their code quality in top shape—no compromises needed!
- Companies must adopt intelligent process, DevOps, automation, and GenAI strategies, leveraging automation and data to enhance both speed and quality in software delivery.
- Those who excel in these areas will outpace competitors in the digital marketplace.
