Governance…. Yes, I admit, excitement probably wasn’t the emotion you felt after reading that word.  If you’re in SaaS, you probably want to stop reading right now, but I’m challenging you: Give one more minute of your time and then make the decision to continue reading or move on. 

Do any of these phrases resonate with you?

• I want to make data-driven decisions. 
• I want my team to interact seamlessly with downstream and upstream orgs.
• I am growing this company to IPO. 

If you answered yes to any of those, it’s time to take your vitamins and learn about what governance means in a modern SaaS context. If you continue to ignore the concept, it will come back to haunt you at the most critical time (think right before that S-1 filing, when the auditors start really digging). 

Governance in the context of RevOps, one word - TRUST

Ultimately, why focus on governance at all? The end goal of governance is trust. 

If I’m looking at this report or analysis, can I actually trust it? As a leader, you shouldn’t be concerned with the fifteen steps and transformations that happened in the background that led to the chart in front of you. But you absolutely don’t want that devil on your shoulder constantly telling you the numbers are just wrong.  

One of my favorite questions to ask executives is, “Ask each of your teams, how many customers do your systems say we have?” I’m not talking about the number finance throws on a quarterly report; I’m talking about the number each team is operating on. I’d bet, each of your C-suite executives would come back with a different number. If you can’t answer that basic question, how are you trusting your decisions based on other data? 

That’s where RevOps comes in. These are the experts who do care about the fifteen steps that happened before to get you that chart. We care about where the data originated, how it has been aggregated, and whether it is accurate.  

What does governance look like in the modern RevOps team?

If you are thinking governance is another monthly call you need to sit on, that’s not what I’m talking about. I’m speaking about leaders who can drive consistency and alignment across the organizations – in particular, across the operations teams that are powering go-to-market functions and the product teams.  

This should be instinctively how your operational leaders function. They should be training their teams to operate with an alignment mindset on a daily basis. This needs to get embedded into the DNA of the organization, not be a one-off process that triggers at specific cadences.  

I break governance into five key steps: 

• Start with definitions and continual discussions
• Once you define it, document it
• Ensure alignment across the GTM tech ecosystem 
• Ensure alignment with product teams
• Identify sources of truth for analysis - knitting together the data on the backend

1. Start with definitions and continual discussions  

The root of everything: What does XX actually mean? Writing this out and agreeing to key definitions is the critical first step.

Back to the example I mentioned earlier: What is a customer? While the question may sound straightforward, the answer can be extremely complex. At what level of a company hierarchy are we measuring the count? Parent hierarchy, department, region, holding company? That is going to be dependent on your business. It’s a conversation you need to have, especially with FP&A. If each of your platforms are measuring that customer count at different levels, the insights that come from them will all be at different levels, creating a compound issue as you compare signals across the GTM funnel.  

It sounds so simple, but this exercise is often overlooked and the customer count is just assumed. RevOps, in conjunction with other leads, need to define and manage the core data points for the business. This process starts with each portion of the GTM funnel (lead, MQL, SAL, SQL, Qualified Opp, Opp Stages, Bookings), renewal rates, and account classifications (e.g., TAM, SAM, annual revenue, industry).  

Governance needs to be embedded into the operational culture of the organization. Any data point people rely on or can transition across a team needs a level of governance. Governance needs to be defined and discussed. Changes will occur and those changes need to be communicated to audiences that leverage a particular data point.  

2. Once you define it, document it

If you had a conversation, but don’t have a record or resource you can share… it doesn’t count.  Think of a new analyst joining the team. It’s a waste of time if you have to convey everything by word of mouth. Plus, you’re increasing your chance for errors moving forward.  

I’d always recommend documenting these core business elements in conjunction with the data dictionary. The goal is for analysts to pull and treat data the right way. So put those definitions right next to where your team looks to grab data from. 

This is another area where you need to work alongside your data engineering teams and CTO org. Hopefully, the engineering department has a data dictionary platform up and running. Try and get on board with what they’re using and build out an instance for revenue teams.  

The critical part of this: the process isn’t just about having a data dictionary. The tool has to have two parts: business definition AND data dictionary. That business definition has to lead to where you can find the data, which aligns with how to think about the data. 

Platforms like Alation and Collibra are great at this. They can be pricey for a RevOps budget, which is why pairing this with the CTO org is critical. They bridge that gap between business definition and the data.

3. Ensure alignment across the GTM tech ecosystem 

This is critical for RevOps. There is no one-stop-shop for all your platform needs. As you bring in new platforms to your GTM ecosystem, you have to align them. Do not let the platforms align you!

Don’t trust that data is flowing the right way just because the word matches on the platform. You have to be insistent with your vendors on what data is coming into the platform and what data is flowing out of the platform. Just because they have a native SFDC or Hubspot connector, does not mean that it magically works. Test this during the sales process with the vendor and make sure that a platform you bring into your ecosystem can integrate into how you are operating your GTM funnel. 

4. Ensure alignment with product teams

Too often there is a bifurcation when it comes to the data between revenue teams and the actual product. The identifiers that exist on the product don’t necessarily line up with what’s in your CRM, unless you’re looking at the actual naming conventions. This disconnect makes it incredibly difficult to analyze deal performance and what actually occurred once the client was implemented. This can be due to the infancy of the product since it was being built prior to or in tandem to sales systems.  

Aligning your sales data with your product data is going to be key in the future. Product metrics and how those tie to sales motions, pricing, and marketing will be critical to understand performance in the new world. Aligning the data among all these teams is cumbersome and intense, but it’s the broccoli your parents forced you to eat as a child. It will be worth every moment you spend on it. 

5. Sources of truth for analysis - knitting together the data on the backend

If you look in your data warehouse, you’ll be able to find plenty of fields that are titled the exact same word, but they all may be pulling from different sources or mean different things. That makes it really  difficult for an analyst to get data and know it’s the accurate field. 

RevOps should make data pulls as easy as possible. The majority of requests operations teams will get can be answered by a collection of base fields. It’s about slicing and dicing the numbers based on those fields (think industry, company size, or region, to name a few).  RevOps should create and maintain master tables that do the majority of the knitting for the analyst community. A base set of core master tables includes campaigns, opportunities, and accounts. These should each include all the most relevant data points people will traditionally query. 

By doing this you can: 

• Minimize the errors or misinterpretations that result from every analyst starting at ground zero for every query
• Increase speed to results 
• Manage changes to the data centrally vs. having to track down every analyst and have them change each of their queries

Wrapping up

Governance should be baked into how RevOps operates on a daily basis. It doesn’t need to be a separate team or function; it needs to be a commitment to get the best available data in the hands of the people who need it every day.  

When RevOps operates with governance guiding decisions in the background, it enables:

• Data and reporting you can trust
• Analysis that can speak to the entire revenue spectrum, not just one team 
• An ability to pivot faster and bring people along for the journey 
• Increased collaboration among teams 

When platforms like Clari are fed governed, trusted data, the magic starts to happen. Clari’s analysis tools give executives, ops teams, and front-line teams the insights they need to make data-driven decisions. Your forecast is only as powerful and accurate as the data that you feed it. When that data is governed, Clari will give you the best possible insights. You’ll make smarter decisions, which in turn will make revenue teams more efficient and enable the business to scale.

Governance is not a dirty word. It’s a commitment that processes are getting done the right way, which will enable the business to scale in the future.  

Clari is the leader in Revenue Collaboration and Governance, providing the only enterprise platform to run the most important business process: Revenue. More than 1,500 organizations run revenue on Clari to improve win rates, prevent slipped deals, forecast with accuracy, and boost the productivity of all revenue-critical employees. Book a demo today.