If you’ve helped drive revenue in your company the last few years, you've probably discussed how to make revenue more predictable.
Maybe you've even had a few conversations about this...🙃
Or maybe you're already part of a RevOps team and you've helped contribute to the recent 55% increase in RevOps adoption.
Then again, you could still be weighing the pros and cons of RevOps. Either way, it’s important to ask where this movement is headed and the impact it might have on your business.
Here it is. In a nutshell. 🌰
The goal is to make revenue more predictable.
So, it's the creation and use of a process.
The process aligns sales, marketing, and customer success.
And the outcome should be a repeatable revenue process.
Seems simple enough.
Most of us have likely witnessed some level of misalignment between Sales, Marketing, and Customer Success teams. Maybe we've even seen them operating on their own islands...I mean, it is possible. 😉
But what are the results of siloed efforts and fragmented GTM activities? How about:
Given the potential downside to fragmented GTM efforts, it’s clear why this model is being adopted so quickly. It's also one reason for the rise in the Chief Revenue Officer (CRO) role.
Yet, it’s very early days for RevOps. There are still open questions about where RevOps is headed and how it will impact business.
Beyond the common nomenclature, DevOps and RevOps have key similarities that should provide helpful signposts to indicate where RevOps is headed.
DevOps is often described as a set of practices, a set of methods, and a culture. It has been revolutionary in its efforts to change the way code is developed and deployed.
RevOps is similar. It too is a set of practices and a culture. It is working to change the way teams work together to generate revenue.
In both cases, they should be considered a movement rather than a technology or a role.
DevOps seeks to align Developer teams with IT Operations. Whereas, as stated above, RevOps works to align the Sales teams, Marketing teams, CS teams, and Operations teams.
Obviously, these are all very different functions. They each have their own history, set of best practices, reporting structure, and goals.
As a result, creating a “one team” outcome is extremely challenging.
It didn't take a lot of analysis for DevOps to know that large, bloated releases were an issue. They caused projects to be slow. And they created more failure points. To fix this, Devs turned to both Agile and Lean frameworks.
The Agile/Lean approach broke large projects into smaller pieces that could be iterated upon. It also helped Dev teams to process these smaller pieces faster and pass them along to the next team. So, it created more integration points between teams. It helped them to further align.
RevOps is working through a similar process with GTM teams. It too is breaking apart GTM projects into smaller, iterative activities. And it's helping those teams to execute faster and find more alignment points across the customer journey.
DevOps made one key change to their development process. They introduced testing earlier into the code development process (e.g. CI/CD or “Shift Left”).
This helped in two ways: 1) it ensure different teams were aligned and 2) it reduced disruptions further downstream.
Similarly, RevOps is making one key change to how work gets done.
It is standardizing data pipelines (aka Gen 2 of Business Data). This creates a clean and centralized view of business data. And it means all teams can use the same source of truth.
This helps RevOps in two ways: 1) alignment and 2) faster time to market. Both of these create a notable improvement in customer acquisition.
So, what do all these similarities mean for RevOps? First, most of the revenue operations initiatives that were started in the last few years will serve as your foundation.
It's likely they will be ongoing. They could be multi-year efforts.
Given that, expect more investment in:
These were common first steps for teams who successfully implemented DevOps. So, they seem like reasonable expectations for RevOps in the near-term.
Beyond that, there have been three natural progressions for DevOps that I think we’ll also see in RevOps:
Automation can be defined as setting up one task to run on its own. Sure, Revenue Operations already uses a fair bit of automation. So, this one isn’t too far into the future.
And it makes sense to turn automation to help create some consistency. It can reduce the toil of manual tasks. It helps teams scale. In some ways, this is operations management 101.
Orchestration is next. It's the natural progression. It relies on automation to set up multiple tasks to run on their own as part of a process or workflow. So, orchestration will be critical to fully align Sales, Marketing, CS, and Operations.
Unfortunately, this is something we’re not yet seeing in the marketplace. But we will soon!
Once tools are in place, teams are aligned, and orchestration is a reality, the next natural question is, “is this working?”.
To answer this question, we should see an increase in tools that observe and measure both the process and the outcomes.
Finally, investment in these tools, process, and teams will lead to some natural sprawl. The observation and measurement tools noted above will show some of the inefficiencies. But the natural path will lead to a consolidation of tools into a single platform.
A single platform will enable GTM teams to:
Think GitLab for RevOps.
This likely means there will no longer be a sales operations team, a marketing operations team, and a CS operations team. There will just be a RevOps team.
Getting to the future of RevOps will depend on the maturation of an entire industry. There are many milestones between now and then. But that doesn’t mean we can’t enjoy measurable gains in the meantime.
The main goal of this movement is to drive predictable revenue, right? Undoubtedly, as the vision of RevOps comes to fruition, we’ll see some amazing results. But we don’t need to wait for that future to drive predictable revenue.
As we’ve shared, Tingono makes it easy to retain and grow customer accounts.
We help predict customer churn risk and account growth opportunities. And we do this by building machine learning models based on your business data.
We then turn that insight into action. With AI, we help you and your team focus on what really matters. And with automation, we help you drive the right customer activity at the right time.
This approach helps your revenue teams scale. It gives them the tools they need to focus on activities that drive predictable revenue.
So maybe while you’re waiting for the future of RevOps, you can get a head start on driving predictable revenue by working with Tingono.
If the future inevitably includes AI and automation, you might as well get started asap. And Tingono can get you there sooner rather than later. Interested? Let’s talk!