Every SaaS company I've worked inside has had the same instinct.

Pipeline is soft? Buy a tool. Forecasting is off? Buy a tool. Reps aren't following up fast enough? Buy a tool.

The result, almost without exception, is a GTM tech stack that looks like it was assembled by committee during a fire drill.

Fifteen platforms. Half of which overlap. None of which talk to each other cleanly. And nobody in the building who can explain how data flows from first touch to closed-won to invoice.

I call it the Frankenstein stack.

It's one of the most expensive problems in B2B SaaS that nobody puts on a P&L.

Data Silos and the Death of Forecasting

Here's what happens when you bolt on tools without an architecture plan.

Outreach tracks sequences. Salesforce tracks opportunities. Clari overlays a forecast model. LeanData routes leads. Gong records calls.

Each tool generates its own version of the truth. And none of them agree.

The CRM should be the single source of truth.

In practice, it becomes a dumping ground.

Reps update it because they have to, not because they trust it. Managers pull reports from three systems and triangulate. Finance runs their own model in a spreadsheet because the numbers from Sales never reconcile.

When nobody trusts the data, forecasting becomes a confidence game.

The loudest voice in the room wins the commit number.

Pipeline coverage ratios are fiction because the pipeline itself is fiction. Stage definitions mean different things to different reps, and nobody enforces them because the system wasn't designed to.

I've seen companies with £30M ARR whose forecast accuracy was worse than a coin flip.

Not because they lacked tooling. Because they had too much of it, and none of it was connected by anything resembling a coherent data architecture.

The Hidden "Bloat Tax"

The software licensing cost is the number that shows up on the finance review.

It's usually eye-watering on its own. But it's the smaller part of the real cost.

The bloat tax is everything else.

It's the two full-time admins maintaining integrations that break every quarter.

It's the onboarding time for new reps who need training on four different platforms before they can start selling.

It's the RevOps analyst spending 60% of their week reconciling data between systems instead of analysing anything useful.

And then there's the friction cost.

When a rep has to update Salesforce, log an activity in Outreach, tag a contact in a separate enrichment tool, and check a dashboard in Clari before moving to the next deal, they're spending more time feeding the machine than selling.

I've audited teams where reps were losing 8–10 hours per week to system administration disguised as "process."

And it's the opportunity cost. Every hour your senior RevOps people spend troubleshooting a Zapier connection or rebuilding a broken sync is an hour they're not spending on architecture, governance, and the strategic work that actually moves the revenue needle.

The bloat tax compounds silently.

It doesn't show up as a line item. It shows up as slower sales cycles, lower win rates, higher ramp times, and a general sense that things are harder than they should be.

Architecture Over Apps

The fix is not another tool.

It's never another tool.

The fix is operational architecture. Designing the workflow first, then applying the absolute minimum amount of technology required to execute that workflow reliably.

That means starting with questions most companies skip entirely.

What does the data model need to look like for forecasting to be trustworthy? Who owns stage definitions, and how are they enforced? What's the contract between Sales and Finance on revenue recognition? Where does a lead become an opportunity, and who decides?

Once those structural questions have clear answers, the technology choices become obvious.

And more importantly, the list gets shorter.

You don't need six tools when the workflow is clean. You might need two. Or you might need a purpose-built system that does exactly what your commercial model requires and nothing else.

I've eliminated over £500k in annual SaaS spend across the companies I've worked with.

Not by finding cheaper alternatives. By removing tools that existed only because the underlying workflow was never properly designed.

When you fix the architecture, the redundancy becomes visible overnight.

The hardest part isn't the technical work. It's the organisational conversation.

Teams become attached to their tools. Vendors have champions internally. Nobody wants to admit that the platform they fought to buy eighteen months ago is now creating more problems than it solves.

But that honesty is exactly what's required.

Revenue operations should be designing systems, not administering a patchwork of disconnected software.

The companies that get this right don't have the fanciest tech stack. They have the most intentional one.