Making the Unknown Known: The Source of Truth Illusion

For revenue teams, the concept of a “Source of Truth” is like a myth. It’s discussed in pipeline councils, debated in data engineering standups and RevOps all-hands. Everyone agrees on the goal: a single place to get answers, aligned to the business, and checked off by leadership. 

For most organizations, however, this source of truth doesn’t exist. 

Cross-functional teams sit at the intersection of data inputs, throughputs and outputs. Each of these is controlled by a different system and often a different group of subject matter experts. Because each team manages its own tools and processes, clarity is fragmented and confidence in your business data suffers. 

The Illusion of Control

On paper, everything looks fine. Pipeline coverage is decent, the teams are entering forecasts, tools are “working”, and sales activities are happening at a decent clip. 

But below the surface, things are off. Maybe a few key deals are showing signs of slowing down. A few renewals have gone dark or asked for pricing but no meeting. A few large deals that were promising have overstated values. 

And leaders might not know until it’s too late. The biggest risks to your quarter aren’t the ones you can see. They’re the ones hiding in your stack, invisible until it’s too late. 

Enter The Unknown Unknowns

Let’s break the risks to your business down into three categories: 

• Known knowns: Insights readily available in dashboards or reports 
• Known unknowns: Insights you know are important but require RevOps to unearth
• Unknown unknowns: Risks you don’t even know to look for, but can sink your quarter

These are the blind spots where risks quietly compound: 

• Deals slipping without visibility
• Stagnant pipeline aging past average cycle times
• Rep productivity and pacing issues hidden in averages
• Poor deal qualification or single threading

These risks only become visible in hindsight, after the plan is missed and the damage done. 

So how do we address this problem, get to a source of truth, and identify the risks before they become quarter-ending torpedoes?

Get Your Systems Working for You

A source of truth doesn’t start in the reporting layer. It starts at the source. The moment data is entered, changed, removed, or omitted. With the average company using 17+ tools in the GTM stack, it’s easy to anticipate what comes next.

The result for most organizations? Data schizophrenia with every tool telling a different story. 

The solution isn’t an extensive data transformation process or data warehouse full of a scheduled extract from every system. Technology is evolving quickly away from that necessity. 

Organizations that spend the time to get the data correct in systems instead of cobbling together processes to fix it after the fact will find themselves equipped with future facing source data aligned to new AI tech. 

A source of truth encompasses good system data at the source, paired with real-time awareness, AI-driven contextualization and pattern recognition to put insight loops and direct action in the hands of your entire GTM team. 

The Future is Agentic Contextualization

Five years ago, a RevOps team had to manually align schemas, build bridges across tools, and clean data downstream. 

With today’s technology, Model Context Protocols (MCPs) paired with LLMs enable contextual data unification directly at the source. It’s been said that AI is only as good as the data powering it, and that’s true, but it doesn’t mean you have to create good data outside your systems. Focus your effort on aligning system level data and let AI take you the last mile. 

This is what a Revenue Command Layer can do for your business. Interface directly with your systems utilizing AI, asking questions, getting answers, and taking action the moment the need strikes. 

That’s power at your fingertips, the unknowns become known and you make better decisions because you can. No lag time, no slowdown. 

The best AI platforms won’t ask or expect you to get rid of your tools. Build the optimal tech stack for your organization and fully utilize it to guide your business. Just make sure you’re pairing it with AI that unifies, saves time, and prevents data schizophrenia at the source.