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Using a Value Stream approach to go beyond DevOps and Agile

Software application development is a profitable and high-growth industry, with the UK market estimated to reach a value of £32.8bn this year. To compete effectively and remain relevant, organisations have focused on making sure the entire lifecycle, from concept to release, is as short and efficient as possible. By Mike O’Rourke, Chief R&D Officer, Digital.ai

The push to optimise the software development and delivery lifecycle has seen the creation of strategies such as DevOps, where software development and IT operations are integrated, and iterative Agile planning and management methodologies are adopted.

However, as many development teams have discovered, independent efforts to improve DevOps and agile practices can only take them so far. While individual processes might be optimised, many teams still lack a comprehensive view of the entire lifecycle, the insight to make data-driven decisions, and the ability to funnel knowledge learned in the field back into planning, development and delivery processes.

One solution to this challenge is a value stream approach that concentrates on creating better visibility across the teams, tools and processes involved in software development and delivery. A value stream approach uses continuous analytics delivered through an integrated platform to establish a better understanding of the business impact of the software development pipeline, including customer satisfaction, revenue and growth.

It connects the major components that enable the continuous development and delivery of software to provide visibility and insight into not just the end-to-end process, but also into the impact and alignment with business objectives. Essential components to achieve this integrated view include Agile planning and project management, DevOps, application security, quality testing, and AI-powered analytics.

Improving agile planning and project management

At the heart of agile methodologies is a focus on continual improvement through collaboration and iterative planning. Taking a value stream approach to Agile enhances planning and management by providing visibility, tracking and reporting on work across all teams, locations, programs and portfolios. Crucially, this includes bi-directional communication between development teams and the wider enterprise.

A value stream platform approach to Agile ensures that all teams have full context for the release pipeline, including the real value of their activity and how it impacts the rest of the development lifecycle to improve the overall performance of the business. These capabilities are even more critical now, as teams are likely to be working remotely and be scattered across multiple locations.

Enhancing DevOps

DevOps involves a process of continual improvement to the development process, particularly through the application of automation to accelerate complex activities repeatedly executed across distributed teams. However, it is all too easy for this process to become overly focused on managing the technical steps and collating related metrics and lose sight of the wider business needs.

With a value stream approach to DevOps, organisations gain a holistic view of the entire lifecycle and surface new opportunities to leverage the speed and predictability offered by DevOps, ensuring that IT outputs are aligned with business outcomes, and new tools and processes implemented will maximise value for the entire company rather than a single team or process.

Putting security first

In the race to release applications as quickly as possible, security has historically been overlooked in the development lifecycle. While it may shave some time from the development schedule, stinting on security has consistently been found to result in a product that is vulnerable to cyber-attacks and leave the customer, and ultimately the business itself, at risk.

Instead, security measures should be woven into the code of the application itself. This integrated approach ensures security concerns are addressed at all stages of the software lifecycle and allows for the introduction of specific security capabilities, such as encryption and obfuscation to protect data at rest and in transit, as well as defences that can send an alert to the developer or shut the app down if users attempt to open it in a sandbox.

Making security part of the value stream process reduces risk, eliminates rework, and improves customer trust, satisfaction and retention – all key components of driving sustained business value.

Optimising testing

Testing is one of the most important elements of the development process, as a slow, crash-prone app will result in poor customer satisfaction and loss of revenue. All new products and product updates therefore need to go through rigorous testing before they see the light of day.

However, for many organisations testing is also expensive and unpredictable. One of the biggest challenges of software testing is the sheer volume of systems and platforms that must be accounted for. The application must be fully functional on each of the many of different mobile and desktop devices, operating systems and browsers, in any possible combination. Automated testing is essential for analysing the different deployment possibilities without impacting development time.

A continuous approach to testing supported through a value stream approach can also help to dramatically speed up the release and deployment process, allowing iterations to be tested throughout the development process so that issues can be addressed as they emerge. This ultimately ensures that each product delivers greater value to the business by improving the team’s responsiveness to troubleshooting issues, without causing lengthy and costly delays.

Iterating with AI-powered analysis

An essential element of both DevOps and agile software development and delivery is the ability to respond rapidly to feedback and coordinate continual changes to the operating environment. Rather than analysing the outcomes only after product release, continuous analysis throughout the development lifecycle makes it possible to iterate processes and increase value at each stage of development.

Increased understanding of software delivery performance and predictive assessment of areas for improvement can be enhanced with the use of advanced AI-powered analytics. By gathering data from throughout the development process and feeding it through natural language processing and machine learning algorithms, it is possible to continually assess performance across both development and IT operations and identify issues that are damaging efficiency or causing risk.

The resulting insights can be used to inform changes to the value stream and resolve any issues early on. By using AI analytics to process data throughout the lifecycle and beyond, the organisation can unlock a far greater level of value from the development pipeline.

Keeping a laser focus on business outcomes, not outputs

While shortening product development and delivery lifecycles will continue to be a major initiative for organisations, they must not lose sight of the greater goal: driving business value. Each team should look at how they can help the business achieve objectives such as improving efficiencies, reducing customer churn, driving down OpEx and improving the speed of delivery. Rather than cutting corners, this must come through creating more efficient processes, with each development stage contributing as much value to the company as possible.

Keeping the value stream top of mind throughout the development lifecycle by providing end-to-end visibility and insights, enables teams to work together to improve both production efficiency and product quality. With a value stream approach that integrates each stage of development, organisations can build on investment in DevOps and agile management practices to ensure all activity is generating value that will lead to increased customer satisfaction and company growth.

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