If you understand something about technology, you no longer need to explain the value and advantages of agile and DevOps. The era of failed projects, command-and-control timelines, and manual infrastructure operations is long gone for them.
However, most leaders in the tech industry are also aware that agile and DevOps functions take time and investment. And at some point, the company management also asks about the return on investment.
If you’re a software-as-a-service company that develops and sells technology, then agility and DevOps can go hand-in-hand with streamlined products, new customers, and revenue growth.
In many companies, investments can be justified in this way. But many IT departments also have to cut costs these days. IT decision-makers should, therefore, be prepared to be able to answer questions about their “savings share”.
Knowing how Agile and DevOps methodologies can help increase efficiency and reduce costs is reasonable. We have compiled eight options for you.
According to Andrew Davis, senior director at DevOps provider Copado, Agile and DevOps are intended to achieve two fundamental goals: “In his book ‘ How to measure anything ‘, author Douglas Hubbard states that there are only two factors that are suitable for this can make a consistent prediction of ROI based on whether the project was cancelled before going live and how quickly users are adopting the product.”
Davis points out that by getting features to users faster, you can demonstrate ROI via speed to market. The cost savings could be realized through more frequent production releases, the lower overhead per release, and fewer post-release defects or operational problems.
Technology companies are adopting agile methods to make course corrections as priorities shift more easily. This responsiveness should management as a financial benefit, says Roger Valade, senior vice president of engineering at technology consultancy G2, “One of the key benefits of Agile is ensuring we’re always working on what matters most.
It’s difficult to quantify that financial benefit in concrete terms, but focusing on our sometimes shifting priorities and avoiding waste continuously is critical at this point.”
What is the financial impact of delays in planning new features or long cycle times in releasing features to production? One way to calculate cost savings: show how much less time and, therefore, the cost you spend on administrative or non-value-added tasks.
Another way to illustrate the cost reduction is: Calculate how much you save through faster feature release cycles.
Adjusting priorities is also a form of decision-making. Peter Kreslins Jr., CTO and co-founder of iPaaS provider Digibee, believes that smarter and faster decision-making brings a high return on investment: “Agile methods can give teams more autonomy and reduce the hidden costs of centralized decisions.
Agile -Practices can also be used to anticipate decisions about the right products, rather than spending money developing them and only finding out later if they’re useful.”
The key is establishing decision-making authority (who gets to make what decisions) and empowering teams to make more decisions faster.
Then you only have to measure how much time (and money) you save through these measures – for example, because meetings, e-mails or presentations are no longer necessary.
Investing in continuous testing and test-driven development (TDD) can significantly increase quality and result in significant cost savings. Marko Anastasov, a co-founder of CI/CD provider Semaphore, explains: “Introducing TDD may seem like an additional effort at first, but it reduces costs in the long term – at least compared to the waterfall model.
While the costs increase linearly in the latter, the curve slopes in the fall of TDD tend to flatten out, so if the project lasts long enough, test-driven development will always pay off in the end.”
For production applications, analyze the cost of fixing bugs and operational issues. You then calculate to what extent automated testing would reduce these costs.
Automated testing and TDD reduce time and cost compared to manual procedures and help ensure quality as DevOps teams increase release frequency.
Automated testing is just one ingredient to optimize the quality and reliability of more complex applications. After all, tests are only as good as the data they are based on. In the case of applications that collect complex data, have a large user base, and have multi-step workflows, test data is difficult to create and manage.
These problems can be addressed with the help of synthetic datasets, test data management tools and the implementation of service virtualization.
” Implementing effective test data management tools, including virtualization, is an important way to reduce costs in the context of shift-left DevOps and agile frameworks,” said Roman Golod, CTO and co-founder of DataOps provider Accelario.
“Not only does this reduce cloud costs, but it also accelerates DevOps internal test data management because there is no longer a need to wait for the DBA to transfer the production database to the non-production environment.
In addition, automatic masking and synthetic data reduce the need for comprehensive Implement data protection measures in non-production databases.”
High-load applications often have a “needle in a haystack” problem. That said, a few users are having trouble with the functionality, performance or other user experience aspects.
Calculate the customer or end-user support costs of solving complex application problems and show where richer test data or service virtualization can reduce those costs.
As good as an executive has heard that moving to the cloud saves money. However, this can only be realized if the IT department assumes responsibility and manages the “consumption”.
What does it mean in this context Responsibility to adopt, says David Williams, senior vice president of market strategy at self-service infrastructure provider Quali: “Public cloud providers’ billing and usage reports do not provide a context in terms of resource consumption.
Organizations must be able to accurately track environments to identify users, teams and projects. Only this context makes it possible to plan future cloud costs more precisely and to manage, optimize and reduce them.”
To reduce cloud consumption, ways to automate elasticity, shutting down, or restructuring services must be identified. Teams can achieve cost savings by moving to serverless architectures, shutting down off-peak environments, archiving data to less expensive storage options, and adopting other best practices.
“The number one way to reduce labour costs is to hire the right people,” said Stanley Huang, co-founder and CTO of DevOps specialist Moxo.
“In a competitive environment labour market and an ever-evolving landscape of tools and architectures, the best way to reduce costs and get the most out of your people is to automate CI/CD pipelines, manual processes, and other elements of the ecosystem . “
Digibee CTO Kreslins adds, ” DevOps methodologies can automate the entire software release lifecycle, reducing manual effort, errors, and the incidents that ultimately drive costs.”
Savings come from estimating the cost of manual operations, prioritizing areas to focus on, and measuring the impact. Trying to automate everything everywhere is unrealistic for many understaffed IT teams.
Therefore, focus on the areas where most work can be saved and then measure the impact. This is an issue that DevOps leaders need to take charge of – and also work with senior management in the process.
To underscore the importance of agile course corrections, development expert Valade has an anecdote up his sleeve: “One of my first Agile trainers told me that more than 90 per cent of the time pilots fly off course on a flight – they constantly adjust their route to ensure to arrive at the right destination.
I find this example particularly fitting because Agile similarly helps us refine our path based on empirical data and ensure that we achieve our goals and stay on the right course.”
DevOps teams invest time in making applications observable and implementing AI Ops to centralize monitoring and operational data. In addition, the product managers working with the agile teams review usage analytics, survey users, and interview key customers and stakeholders.
The return on investment of intelligent feedback loops should extend beyond the overall business goals and product outcomes.
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