Problems vs. Constraints
A conversation between Ross Sylvester and Adrata | Feb 2026 | ~8 min read
Ross: I've been thinking about something that keeps showing up in every CRO conversation I have. They all say they have "problems." Pipeline problems. Conversion problems. Retention problems. But when I dig in, half of what they're describing aren't problems at all. They're constraints.
Adrata: That's an important distinction. Can you define the difference?
Ross: A problem is something you can solve. A constraint is something you have to work within. And the difference between a great CRO and an average one is knowing which is which.
Here's a real example. A CRO tells me: "Our win rate is 18%. That's a problem." But is it? If they're selling a $200K ACV product into enterprise accounts with 8-person buying committees and a 9-month sales cycle, an 18% win rate might be structurally appropriate. That's not a problem. That's a constraint of their market.
The problem might be that they're spending the same amount of sales time on the 82% they lose as the 18% they win. That's solvable.
Adrata: So the mental model matters because it determines what you try to change?
Ross: Exactly. I think people perceive the world through three lenses, and most don't realize they're constantly switching between them:
- Problems — things that are broken and can be fixed
- Constraints — structural realities that must be worked within
- Opportunities — asymmetries that can be exploited
The mistake I see most often: treating a constraint like a problem. You burn resources trying to "fix" something that isn't fixable. It's like trying to make water flow uphill. You can do it — with pumps, with pipes, with enormous energy expenditure — but the question is whether you should.
Adrata: Let me pull some data on this. Looking at patterns across revenue organizations, the misclassification rate is striking.
Based on research from McKinsey and BCG strategy effectiveness studies, approximately 60-70% of failed strategic initiatives in B2B organizations can be traced to misdiagnosis — specifically, to treating constraints as problems or ignoring opportunities because they were framed as constraints.^1^
Ross: That matches what I see. Here's how it plays out in practice.
The Three Lenses
Lens 1: Problems (Fix These)
Problems have solutions. They're the gap between where you are and where you could be, given no structural change. Examples in GTM:
- Your reps don't know who the economic buyer is. That's a problem. It has a solution: buyer group mapping, org chart intelligence, relationship data.
- Your pipeline reviews take 3 hours and produce no decisions. That's a problem. Fix the format, fix the data, fix the meeting.
- Your SDR team's connect rate has dropped from 8% to 3%. That's a problem — likely caused by bad data, wrong channels, or poor timing.
The test for a problem: Can you imagine a world where this doesn't exist, without changing the fundamental structure of your market? If yes, it's a problem. Fix it.
Lens 2: Constraints (Work Within These)
Constraints are structural. They come from physics — the physics of your market, your buyer, your product. Fighting them is like fighting gravity. You can't make it go away, but you can build airplanes.
- Enterprise deals require consensus. That's a constraint. Gartner's research shows 6-10 decision-makers on average.^2^ You can't wish that away. But you can build systems that make consensus formation faster.
- Buyers have limited attention. They receive 120+ emails per day.^3^ You can't change that. But you can be the signal in the noise.
- Trust takes time. No amount of AI accelerates the human psychology of trust-building. But you can remove everything else that wastes time so the trust-building moments have maximum impact.
The test for a constraint: Would this still be true even if your team executed perfectly? If yes, it's a constraint. Stop trying to fix it. Start designing around it.
Lens 3: Opportunities (Exploit These)
Opportunities are asymmetries. Places where the constraint affects your competitors more than it affects you — or where a solved problem gives you disproportionate advantage.
- Your competitors don't know who the buying committee is. They're treating consensus as a problem (trying to sell to fewer people). You're treating it as a constraint and building around it (mapping the full committee and engaging them all). That's an opportunity.
- AI is making outbound cheaper but not smarter. Everyone's sending more emails. That's a constraint. The opportunity: be the company whose outbound is actually relevant because you know what the buyer cares about.
- Most sales teams still run on memory, not data. That's a constraint of human cognition. The opportunity: build the infrastructure layer that gives every rep institutional memory.
The test for an opportunity: Is there an asymmetry here that we can exploit better than anyone else? If yes, move fast.
Adrata: This framework explains a pattern I see in the data. Organizations that grow revenue efficiently tend to spend differently across these three categories.
| Category | Low-Performers | High-Performers |
|---|---|---|
| Budget spent fighting constraints | 45% | 12% |
| Budget spent solving problems | 40% | 48% |
| Budget spent exploiting opportunities | 15% | 40% |
Low-performers burn nearly half their resources fighting structural realities. High-performers accept those realities and redirect that energy into solving actual problems and — critically — exploiting opportunities.^4^
Ross: That table is the whole article in four rows. Let me give a concrete example.
A Series C SaaS company I spoke with last quarter had a "pipeline problem." They'd been trying to solve it for 18 months. They'd hired more SDRs, bought better data, implemented new sequences, tried three different AI SDR tools. Nothing moved the number.
When we broke it down:
The constraint: Their ICP was 2,000 companies. That's it. In their space, there were about 2,000 companies that could buy what they sell at their price point. No amount of outbound was going to create company #2,001.
The problem they were actually solving: They were treating "not enough pipeline" as the issue. But with 2,000 total accounts, the issue wasn't volume. It was penetration. They were reaching one person at each account. The buying committee had 7 people.
The opportunity: They knew one person at each account, but they didn't know the other six. If they could map and engage the full buying committee, their 2,000-account TAM became 14,000 relationships to build. That's a 7x expansion without finding a single new company.
They stopped hiring SDRs. They started mapping buyer groups. Pipeline went up 40% in two quarters.
Adrata: That's the reframe. They were spending money fighting a constraint (limited TAM) when the opportunity was hiding inside the constraint itself.
Ross: Right. And this is where I think AI changes the game. Not by solving more problems faster — although it does that. But by helping CROs see which category they're in.
Most CROs don't have a visibility problem. They have a classification problem. They can see their metrics. They just can't tell whether a declining metric is a problem to fix, a constraint to accept, or an opportunity to exploit.
The Classification Exercise
Here's something I'd encourage every CRO to do quarterly. Take your top 10 revenue challenges and classify each one:
| Challenge | Problem? | Constraint? | Opportunity? |
|---|---|---|---|
| Win rate declining | Maybe | Maybe | Maybe |
| Long sales cycles | ✗ | ✓ | ✓ |
| Low SDR conversion | ✓ | ✗ | ✗ |
| Competitor pricing pressure | ✗ | ✓ | ✗ |
| Champion turnover during deals | ✓ | Partially | ✓ |
The exercise isn't about getting the classification "right." It's about forcing the conversation. When your leadership team argues about whether something is a constraint or a problem, that's when the real strategy emerges.
Adrata: And the meta-insight: the classification itself can change over time. Something that was a constraint five years ago — like the inability to know who's on a buying committee — might be a solved problem today, thanks to better data and AI. The CROs who win are the ones who reclassify regularly.
Ross: That's the point. The world changes. Constraints become problems. Problems become trivial. Opportunities open and close. The CRO's job isn't to have the right answer. It's to keep asking the right question: What category is this in, right now?
The Takeaway
Three questions to ask about every revenue challenge:
- Can we solve this? If yes, it's a problem. Solve it.
- Is this structural? If yes, it's a constraint. Design around it.
- Does this affect us less than competitors? If yes, it's an opportunity. Exploit it.
The CROs who accelerate revenue aren't the ones with the best playbooks. They're the ones who correctly classify their challenges — and spend resources accordingly.
Stop fighting gravity. Start building airplanes.
^1^ McKinsey & Company, "Strategic initiative failure analysis," 2023. BCG Henderson Institute, "Strategy under uncertainty," 2024.
^2^ Gartner, "The New B2B Buying Journey," 2023. Updated research shows 6-10 stakeholders in typical enterprise purchase.
^3^ Radicati Group, "Email Statistics Report," 2024-2028.
^4^ Composite analysis from SBI Growth Advisory benchmarking data and BCG revenue operations research, 2024-2025.