🔦 Continuous Problem Definition

From Symptoms to Signals: observability, evaluation, rollouts, forecasting.

One of my favourite leaders to to learn from is Dave McJannet. He is one of those unicorn leaders, who has vastly diverse experience across complementary areas, like economics, product, and marketing¹. Today I want to talk about how tackling Problems² evolves in a world where the company systems are very dynamic. (yes, thanks AI). And who better to serve as inspiration than Dave!

In a talk once he summarised companies as entities that comprise of 4 big systems: the systems of GTM, Product, Finance and HR. In large orgs each of these systems will have a seasoned leader. Each owns a broad scope: GTM = Marketing, Sales, CS. Product = Product, Design, Engineering. You get the gist.

In large organisations, like the one Dave led, each system has a seasoned owner: CRO, CPO, CHRO, CFO. And the COO triangulates across them. Every C-level has two jobs: spot when there might be a Problem in their system, then solve it or escalate to the COO and broader leadership team. With four strong points of view on the table, the COO’s task is to integrate, judge and decide.

Startups are flatter, but also messier. You don’t have four owners; you have ten: Marketing, Sales, CS, Product, Eng, HR, BizOps, Finance, Legal + the founders! They also need to spot and resolve problems. But… Ask a Marketing VP and you’ll hear symptoms: “MQLs are down; CAC is up.” The temptation is to toss the hot potato downstream: “MQLs aren’t down, therefore Sales isn’t working them.” That’s how finger-pointing starts.

Here’s the trap: most of what start up leaders see are symptoms, not capital-P Problems. Metrics don’t live in isolation. A GTM symptom might be rooted in pricing, activation, or data debt. What looks like Marketing’s Problem is often a cross-system cause hiding in plain sight.

This is where Strategy & BizOps (and strategic COOs) earn their keep. They look at a symptom and know it is just one Signal in all the noise. They work on a portfolio of Signals across silos, map them to shared causes, and drive the initiatives that fix the root Problem, rather than applying band-aids to each metric.

In this post, I’ll show how BizOps manages that portfolio of Signals and leads cross-functional fixes that actually move the revenue machine. And how thanks to new expectations, and demands, call for Continuous Problem Definition and how to get there. Supporters of the SBO Hub also get a full list of things to tweak across the Big Four systems to get to Continuous Problem Discovery, at the end of this article.

So let’s dig in…

Defining Problems, not Symptoms

Scenario 1: ICP drift

For the sake of clarity I will group the following symptoms into the 4 big systems, but if you have a separate leader for each area of these, you can imagine the breakdown. So, each leader will be looking at their own dashboards and spreadsheets. And here is what they might see:

• GTM: CAC up, win-rate vs “no decision” is weak, need to discount heavily to close.

• Finance: Payback period stretching; NRR on new cohorts is lower; sales cycle is up and higher than granular industry benchmarks.

• HR: SDR/AE burnout, and attrition; hiring spec keeps changing.

• Product & Eng: Activation low for new cohorts; roadmap thrash from fragmented asks.

When I took on a situation like this, what mattered to me was that we got to the root cause of the problem. It wouldn’t be enough for the GTM org to slash down spending to reduce CAC; or go into a cheaper channel. This solves CAC. But it would open a ton of issues: NRR could plummet, because the people coming through the new channel are not suitable. The Sales cycle could go drastically up for the same reason. In stead of playing whack ‘em all, all of the above Signals pointed to one culprit: we’re attracting the wrong customers. That’s it. The solution isn’t more hiring, or cleaning up the roadmap. It is defining the ICP and sticking to it.³

Level of difficulty: low.

Scenario 2: Pricing misaligned with value metric

• GTM: Interest is unchanged, but win-rates going drastically down, low expansion, most new deals are custom deals.

• Finance: margin leakage via overage waivers or refunds.

• HR: Comp plan disputes; AE’s frustration and attrition.

• Product & Eng: Metering is non existent; no way to invoice correctly.

This was the situation after a botched pricing change. In stead of taking 4-6 months to do this properly⁴, the company had done this in a week. “As long as it is on the marketing site, we are ready to go.” No. They weren’t. Using creative accounting to ‘massage the sheets’ can help only thus far. (this is why Pricing belongs to the COO, not marketing). With this one, if you are gentle you can put the root cause of the problem to be “pricing didn’t match the value metric” but you can also point to big management and ego problems. Those are very difficult to fix, and I am going to leave them out of scope for this post, and in scope for the next BizOps meet up 😉.

Level of difficulty: high.

Scenario 3: Data/measurement debt

• GTM: Attribution fights; MQL/SQL definitions drift.

• Finance: Forecast vs actual whiplash; CAC/payback re-stated.

• HR: RevOps burnout.

• Product & Eng: Event/schema drift; analytics gaps block decisions; analytics requests pile on.

For anyone experienced, this is a tale you have seen 100 times over. It is the lack of a single source of truth. This is first order of business for any BizOps leader or COO. You simply can’t have that. And again, the solution to the above Signals wouldn’t be for Finance to simply ‘get on top of reporting’, or to hire more RevOps folk. It is to solve for all these symptoms with one initiative. It is not an easy one, and takes time. But it is doable.

Level of difficulty: medium.

To stop patching symptoms, first know they are just Signals. Always trace the shared root and fix it once. Ask “Why” many times, and form a holistic understanding. Integrate the signals, name the real Problem, and sponsor the one initiative that collapses the noise.

Continuous Problem Definition across company Systems

Insight used to take months, now surfaces in days. MBRs and QBRs are too slow. With today’s data appetite and tooling, teams expect near-instant feedback from the big four systems. BizOps’ job is to make those signals continuous and actionable. Let’s look at how to do this reliably.

Here’s the steps to take: