Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.
If you think about your day-to-day at work — whether you’re working from your home office, a coffee shop or the actual office — we interact with dozens, if not hundreds, of tools regularly. From task management, document collaboration, finance software, calendar apps or messaging platforms, we are constantly interacting with and sharing information — and this is just to manage our individual day-to-day. At a departmental level, the number of applications teams use has grown exponentially. According to a report from Productiv, most departments use between 40 and 60 different applications. That’s a lot of apps for employees to keep track of – and be proficient at using.
Consider the IT and devops teams that are building the multitude of apps and platforms that keep work running smoothly. Businesses are facing an ever-evolving web of processes and applications, and the tools, technologies and languages to iterate on and deliver software are evolving, expanding and specializing faster than ever. These teams are at the heart of software delivery and innovation, but their jobs are becoming more complicated at the same time it is also getting harder to simply build the software that today’s businesses depend on.
That’s why it’s time for tech leaders (like myself) to take a step back and rethink our approach to optimizing and modernizing our tech stacks — a new approach that focuses on team efficiency, solid partnership with the business and successful ideation. When we do so, we create elite performing teams, which, according to Google, have 208 times more frequent code deployments and are 2,604 times faster to recover from incidents.
Focus on the right metrics, not just adding new software
I recently spoke with a CTO who said that as they moved to remote work, they rolled out more tools to measure their team’s productivity and output. The result? Their entire engineering team revolted. Rather than making the assumption that adding more software will encourage your team to work harder (in this case, adopting a new tech solution that tracks if your employees are actually working), I recommend a different approach.
Event
MetaBeat 2022
MetaBeat will bring together thought leaders to give guidance on how metaverse technology will transform the way all industries communicate and do business on October 4 in San Francisco, CA.
Register Here
At Slack, we measure productivity and output by “time to audience” or “speed plus quality.” By examining questions like, “How long does it take to specify the work?” “How long does it take to edit and iterate?” or “How long does it take to deploy and measure?” I can easily uncover insights that help speed up or shift my team’s development practices — and I can do that all without just jumping at any new technology that comes down the pipeline.
Old isn’t necessarily bad
It’s easy to get distracted by the next new thing, but we often overlook one simple fact when it comes to an optimized tech stack: It’s about how efficiently your engineering teams can work with it, regardless of how old it is. If working with an older tech stack means you can’t make changes quickly, that is not always a tech stack problem, rather it is more of an innovation and devops problem. We need to stop fixating on the use of older tools, like a Java database and SQL server. These are still powerful in their own right. Instead, it’s likely your team can’t make changes quickly, which may be what is actually slowing them down.
For example, say you’re building a new mobile app and it takes three to four minutes to compile, but you want to decrease that time to under a minute. Those few minutes of difference may not sound like they’re that impactful, but imagine you need to compile this app more than 50 times each day. Even if you can save a few mins on each cycle by driving efficiencies in how teams work, that’s a massive impact on ROI to the business.
It’s all about efficiencies in our work, how we can improve ROI through quicker release rates, reduce the time to resolve incidents, or the improvement of change failure rates. It’s not just about how new the tools we’re using, but instead about how we can drive efficiency.
Automate the time-consuming tasks
Automating away the mundane, time-consuming tasks that suck up too much energy and effort can free up valuable resources that lead to more actionable insights – across the enterprise. With low-code and automation tools, your company’s IT, devops and engineering teams can focus on solving more complex problems and iterating, testing and rolling out products quicker and more efficiently. With low-code tools in use, we can give more power to the people — technical or not. In fact, Gartner says 80% of technology products and services will be built by those who aren’t technology professionals by 2024.
It’s time for a new model geared for the future of work
As companies grapple with the rapid transition to new ways of working, we’re under more pressure than ever to keep businesses running smoothly while testing and deploying new technologies that drive businesses — and our customers — forward.
I call on other IT, devops and engineering leaders to prioritize their greatest assets — their people — by focusing on better processes for innovation, new ways to measure team-level success and dialing in on the tools needed to automate away the complexity that prevents progress.
Steve Wood is the senior vice president of product and platform at Slack
DataDecisionMakers
Welcome to the VentureBeat community!
DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own!
Read More From DataDecisionMakers
Source by venturebeat.com
