Having access to performance data can help employees gain deeper understanding of their strengths and areas to work on – something especially important for development teams, who are under increasing pressure to innovate faster, create services to keep up with customer demands and fight off their business’ competitors. Awareness of output is crucial to increasing the speed of innovation; having concrete data allows teams to gain this understanding of their work, steps they can take to self-improve and, ultimately, accelerate the innovation process. So why aren’t more companies empowering their IT teams with this kind of data?
Advances in modern technology have enabled us to become masters at measuring our behaviour. We are obsessed with self-analytics, from smartwatches that record how many steps we’ve taken in a day, to our phones monitoring how long we’ve spent on certain apps, we now have constant access to data we can use to improve who we are and the way we live our lives. In fact, we now produce a mind-boggling 2.5 quintillion bytes of data every day. Why is it then that that we’re not able to gain the same level of understanding of our performance in the workplace?
- Pave the way to the future: modernising the mainframe (opens in new tab)
A Fitbit for developers
For large enterprises, where the mainframe is the backbone, an intuitive interface is critical. Newer developers may have never seen a green-screen environment before. They will have different expectations, as will more experienced developers, since they’ve all been exposed to modern, user-friendly operating systems. As such, a modern IDE and analysis tools, can help developers of all backgrounds and experience levels work confidently and speedily on the mainframe. Sometimes it is easier to continue to work with the familiar, with muscle memory likely leading developers to work on autopilot. However, with access to performance data, correlated with developer behaviour, teams will be able make evidence-based decisions that improve the speed and quality of their output. As they become more aware of how the ways they work make a difference, so they are enabled to change and measure the impact of that change – just like when they use a Fitbit to improve physical and mental health.
Armed with this ‘Fitbit for developers’, teams will have a clear idea of how they’re doing at work, the areas they perform well in, what could be improved and how changes in behaviour impact output. The measurements also provide evidence that they are getting better, giving a sense of individual achievement that translates to the successes of the team, inspiring a more creative landscape to drive innovation forward.
Modernising training methods
The way today’s digital-savvy developers prefer to be taught about new methods and concepts has changed and moved on from the old, ‘read the manual’ approach. Developers are now accustomed to hopping onto YouTube for video tutorials in their personal lives, for everything from cooking to DIY, they no longer want desk-based, textbook learning opportunities. As mainframe-reliant companies drive forward millennial recruitment plans, they need to provide this modern, ‘Google/YouTube’ model for training too.
Online training curriculums can offer tailored, role-based modules for developers, while simultaneously providing data on individual tools usage. Having transparency of data allows teams to understand how changes to behaviour or tooling can benefit their performance and inspire them to adapt to be more effective individually and organisationally.
The data gleaned from new, online curriculums doesn’t just benefit development teams. When understanding tool usage, there’s also the added bonus for businesses that they will have access to metrics showing how effective the training has been and if investments in new tooling are paying off. This is hugely beneficial to the wider educational programme, as it enables an organisation to use data to constantly re-assess their teaching methods and measure adoption and usage of new tools that have been implemented.
After developers complete training, IT leaders can consult the data they’ve produced to gain an understanding of the areas developers are thriving in, where they may need extra help, what new products they’ve started using and what the business impact is. These metrics provide IT teams with knowledge on how effective a tool or a training course is, so they can then report back to the wider business to guide future decision-making.
Then, as is the standard expectation when data is collected, businesses are able to carry out further analytics to assess the impact on industry-standard measures such as quality, velocity and efficiency. This can be done both at a team and organisational level to show how the mainframe community is doing as a whole.
Data as the formula for success
Across all industries, it’s no longer a case of “big beats small”; now “fast beats slow”. Businesses need to innovate faster while also improving quality and efficiency to keep up, and empowering development teams to embrace new ways of working and measure the positive impact it has on their output is crucial. Organisations should be considering how data and machine learning can help mainframe software development and delivery teams with this, enabling them to better understand their current performance levels, where this can be enhanced with new tooling or processes and the learning programmes on offer to help them on the road to self-improvement.
- Debunking the three biggest mainframe myths (opens in new tab)
Dr Elizabeth Maxwell, EMEA Mainframe Technical Director, Compuware (opens in new tab)