In a Future of Work paradigm, driving a high-performance software delivery lifecycle team looks a bit different — which is really the latest manifestation in a never-ending but unspoken “contract negotiation” between workers and employers. Because of changes in society as well as the marketplace, the business landscape of today looks greatly different than it did even a few short years ago. For example: in the SDLC world — where IT gets done — we’ve seen the space transformed as software teams, as part of their continually evolving priorities, continue to …
Shift away from waterfall and invest in Agile development
Drive DevOps-driven continuous release and delivery of code
Prioritize near-real-time feedback loops and analytics
Move from on-premises to cloud
Direct focus towards continual data extraction to make intelligent decisions
This drives a business environment and paradigm that is all but unrecognizable as a descendant of the “office” environment that dominated work for the latter half of the 20th century.
In navigating an ever-shifting macro environment, what it means to be high-performing continues to change. Some core ingredients emerging out of the Agile revolution continue to hold true: speed to production, continuous everything, focus on velocity, etc. But to position your team to compete in an ever-crowded space, it’s also about raising your “business influence,” e.g. your relevance and contribution to the bottom line to a new high.
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Here are 5 areas that should be top of mind as you eye your team’s next era of performance and impact:
- Continuous Product Lifecycle Velocity: Consider your product lifecycle today. Does progress flow end-to-end via a technology-enabled pipeline, or is the process siloed, rife with manual activities, and prone to rework? Peak performance is supported by embracing a “continuous everything” methodology, with a focus on things like being first to market through exploratory implementation; leveraging predictive data and futuristic tech to fuel velocity; and building robust development, test, build, and release feedback loops supported by quantifiable metrics. If you can’t put the word “continuous” in front of everything you do to get product in the hands of end users, there is room for improvement.
- Predictive Quality of Product & Process: We know the cost of rework is steep — costing a medium-sized business upwards of $4.7 million a year (Source: DevOps Research & Assessment). That’s why being able to predict the quality, performance, and user experience before your product is released is paramount. When we can predict potential quality issues early on, it enables our software development teams to take corrective actions and ensure the highest level of customer satisfaction and experience.
- Emerging Tech Prioritization: The era of emerging tech is nothing new for us as tech leaders, but the pressure mounts to prioritize and re-prioritize daily. Virtualization, cloud, IoT, AI/ML… all these innovations mean we have a wealth of options to consider as means to increase product quality and speed to market. The industry pacesetters (e.g., the best, most high-performing SDLC teams) need to know exactly where to go — and where not to go — when it comes to incorporating accelerators like RPA, AI/ML, IoT, automation, etc., into the SDLC. It boils down to making the right decisions about the right innovations at the right time and at the right place.
- Data-Driven & Intelligence-Centered: There’s little debate that data is everyone’s responsibility today—no exception for leaders of the SDLC. So what does that mean? It is imperative that we start thinking about being data-driven and intelligence-centered. One of the first things that means is standing up new KPIs to uncover truly effective utilization of IT. From leveraging VoC (Voice of the Customer) data to revolutionize software solutions to standing up robust data governance and data integrity to make data reliable and trustworthy, high performance becomes elusive if we remain gut-based rather than ushering in the new era of insight-rich data-centeredness.
- A Seat with Influence: To be high-performing in this workplace era means being able to clearly connect SDLC priorities to overall business objectives. This means going far beyond building software based on technical requirements and, instead, actively contributing to the success and growth of the business by understanding its needs and strategically using technology to drive value. One tip to get started: Have regular meetings with your business unit peers. Yes, that means folks in Product Marketing, the Help Desk, and Sales to name a few! Get closer to VoC and see how you can also build bridges to strengthen your overall organizational influence. Be the village that it takes to be pacesetting!
When thinking about how to inject next-level performance into your SDLC immediately (more on that here), I always like to think of a couple of core questions to round out the tips above:
- Start by asking, “What does high performance mean to us as an SDLC team?” Pay particular attention to how the definition might have shifted from where it was even a few months ago.
- Where does performance feel strong right now? Got it? What is one action/tactic you can enact to go from good to great?
- Where does performance feel wobbly right now? And WHY? Why does this area feel a bit off balance and what can you do to right the ship?
Where effective KPIs come into play is when these “gut-level” feelings — accurate or inaccurate — can be “tested” by measuring and monitoring quantifiable metrics. This brings objectivity to subjective feelings.
“High performance” unquestionably can mean different things to different teams, but some things — like a few I shared above — are going to be mainstays no matter where you find yourself. It’s an exciting time in the SDLC and there are so many ways we can inject next-level performance immediately into our teams!
Interested in speaking with our Solutions Architect team on specific ways to drive high performance into your SDLC? Click here to book your time directly with our team.