At Split, we sit at an intersection between the two worlds of DevOps and Analytics. From this powerful vantage point, here are the top trends we see unfolding in 2018.
5. DevOps Goes Enterprise-wide
In 2017, enterprises of all sizes started implementing DevOps for some of their newer services. Forrester Research recently estimated that 63% of enterprises have implemented DevOps in some form. Analyst firms, like Gartner and Forrester, and consultancies like McKinsey, recommended strategies for introducing new modern DevOps processes for newer projects in the enterprise. This was particularly true for enterprises with significant legacy waterfall software projects.
In 2018, we expect DevOps to become a more mainstream approach in the enterprise. The early success of initial projects will lead to DevOps growing to more project silos across the enterprise. In many enterprises, a DevOps approach will become the mainstream way of building and delivering software.
4. DevOps Turns to Analytics to Measure Results
As early DevOps success grows, it moves from being a side project to drive innovation towards standard business process that requires regular reporting of progress against KPIs. Enterprises will grapple with the challenges of accelerating deployment speed while maintaining quality. The impact against both of these metrics, along with other customer experience metrics, will need to be regularly measured to evaluate investment levels in new software projects.
3. Modern AppDev to Drive Language Fragmentation
The benefits are numerous of moving from a legacy web app built as a monolith to microservices that have an API backend and Single Page App (“SPA”) or mobile front-end. However, one drawback of giving agile AppDev teams across an enterprise some flexibility in tools and languages they use is that you might get a more heterogeneous environment across all your development projects. Enterprises will look to standardize some aspects of the stack. Likely aspects are container technology and DevOps tools.
2. Analytics Becomes Part of the Dev Toolkit
Data and analytics technology will be increasingly embedded in a broad range of software products. First, analytics products looked to make a better version of Excel. Then, specific use cases for analytics were carved off, with specific products being built to handle specific functional use cases, like sales territory planning or pricing analysis.
In 2018, we are going to see software vendors building analytics modules for their product that provides insight into that specific domain for their customers. Some products will even combine this data with data from external sources.
Split itself is taking this approach, bringing analytics into the world of feature management, and in one place allowing engineers and product managers to see the impact of feature releases on key metrics. It is an example of analytics applied to a specific domain, with analysis automated and optimized for a set of use cases.
1. Growth Product Management Expands to Experimentation Product Management
And, rounding things out, this one is something we are seeing happening directly as we talk to our customers. For several years, hiring a “Product Manager, Growth” has been a hot trend in Silicon Valley, and has spread across all industries building digital products. As we talk to CTOs and VPs of Product, many are looking for that “growth” role to expand past being a silo focused on “growth hacking” to becoming an enabler for the entire product team to conduct experiments. This involves building out infrastructure to support experimentation at scale in the organization.
Looking Forward to 2018
At Split, we’re excited about all that 2018 has in store. We can’t wait to see how all the new technology becoming available is going to be used by enterprises of all types to make their businesses more efficient, decrease risk, and enhance the user experience. Key to this success is being able to make smarter product decisions to guide software development investments. With Split, organizations can do just that, by measuring the impact of feature releases on all the customer experience metrics that matter.
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