Why Teams Call Us
Every engagement starts with an event. Below are the nine that bring people to this page, what each one actually looks like from the inside, what usually caused it, and where we start. If one of these is your quarter, the first call is worth thirty minutes.
Trigger 01
"I inherited a stack I can't audit and a forecast I can't defend."
You are six weeks in. The board wants a number by the end of the quarter and the number you have came out of a CRM you did not build, maintained by people who have left. Two dashboards disagree. Nobody can tell you which pipeline definition the last forecast used, and the person who could has moved teams.
The stack grew one urgent decision at a time. Each tool solved a real problem the week it was bought. Nobody owned the object model across all of them, so definitions drifted, fields multiplied, and the reporting layer got patched instead of rebuilt. That is normal. It is also why the numbers stopped agreeing.
A two-week written diagnostic before you commit to a rebuild. We trace the data from source to board deck, audit the pipeline definitions against what the records actually contain, and hand you prioritised findings you can take to your own leadership. You get a document, not a proposal disguised as one.
Your first forecast miss will be attributed to you, not to the system you inherited. The diagnostic is cheap insurance against defending a number you cannot trace.
Trigger 02
"We have budget and 18 months. The ops debt will eat both."
The plan says double the sales team and triple pipeline. The hiring requisitions are open. Meanwhile the routing rules are a spreadsheet, lifecycle stages mean different things in two systems, and onboarding a rep involves someone explaining the CRM verbally. Every new hire will inherit that.
Nothing went wrong. The company got to this round on a motion that worked at ten people and does not work at fifty. Process debt is not a failure state, it is the normal residue of moving fast. It only becomes expensive at the moment you add headcount on top of it.
Target-state architecture ahead of the hiring wave. We design the data model, lifecycle, routing and reporting the larger team will run on, sequence the build against your hiring plan, and tell you which parts genuinely need to exist before the first cohort starts and which can wait two quarters.
Rebuilding a process while thirty people are using it costs more than building it for thirty people. The window between the round closing and the team arriving is the cheapest this work will ever be.
Trigger 03
"It stalled. Everyone's afraid of the data."
The new platform is provisioned. Some objects are mapped. A test import produced duplicates nobody wants to talk about, so the project quietly moved to next quarter and both systems are now running in parallel. Reps enter data in one, leadership reports from the other, and neither is complete.
The migration was scoped as a data transfer when it is actually a data model decision. Deduplication rules, ownership logic, historical activity, custom field mapping and lifecycle history all need a call made on them. When no one is empowered to make those calls, the project stops moving rather than moving badly.
Unblock, dedupe, ship inside the quarter. We audit what actually transferred, rebuild the mapping where it broke, resolve the duplicate logic, and run cutover with lifecycle stages and routing live on day one. Stalled migrations are among the most common starting states we see.
Every month in parallel adds a month of divergent records to reconcile later. Cleaning up mid-flight is dramatically cheaper than re-platforming a year of bad data afterwards.
Trigger 04
"Volume is fine. Conversion isn't. Nobody can tell me why."
Top of funnel is holding. Marketing hit its number. Sales did not. The theories in the room are channel mix, rep ramp, pricing, and competitor pressure, and there is no data that settles the argument because stage conversion is measured off a dashboard nobody has reconciled against the underlying records.
Stage definitions drifted. Reps advance opportunities on different criteria, some stages are skipped entirely, and a meaningful share of the funnel never gets a first touch inside the window where it converts. The dashboard reports what was entered, which is not the same as what happened.
A funnel diagnostic against the actual data, not the dashboard. We rebuild stage conversion from raw records, measure time-in-stage and speed-to-first-touch, and isolate where the drop is real rather than an artefact of how the funnel is recorded. Then you know which problem you have.
A quarter spent optimising the wrong stage is a quarter gone. Most flat-conversion problems turn out to be measurement problems first and motion problems second.
Trigger 05
"We ran the pilot. Nothing showed up in revenue."
The demo was genuinely impressive. The agent enriched records, drafted outreach, summarised calls. Six months later there is no line in the revenue review that traces back to it, security has questions nobody has answered in writing, and the renewal conversation is coming.
The pilot proved the model works. Nobody built the layer that makes it measurable. There was no baseline captured before deployment, no cost-per-action instrumentation, and no attribution path from the agent's output to a closed deal. AI sits at layer three of the revenue operating system and only produces revenue if the layers underneath it are real and the layer above it can measure the change.
A readiness and governance review, then a rebuild of the measurement. We assess data quality per use case, scope access and approval gates, write the AI policy your security team can sign, and instrument the before state. If we cannot instrument it, we say so before you spend more.
An unmeasured pilot gets cancelled at renewal regardless of whether it worked. The instrumentation is what buys the programme a second year.
Trigger 06
"Marketing, sales and finance report different pipeline."
Three decks go into the same meeting with three pipeline figures. The first twenty minutes are spent reconciling them instead of deciding anything. Everyone privately believes their own number and nobody wants to be the one who concedes, because conceding means their function missed.
Nobody is lying. Everyone is measuring a different object. Marketing counts created pipeline at MQL, sales counts qualified opportunities, finance counts what passed a revenue recognition test. Each definition is defensible in isolation. There is no single agreed definition set that all three roll up to.
One data model, one definition set, one source. We document what each team currently measures, put the differences on one page, run the definition decisions to a conclusion with all three in the room, and rebuild reporting off the agreed model. The hard part is the agreement, not the build.
Every board cycle spent reconciling numbers is a board cycle not spent on decisions. It also quietly erodes trust in whichever function is least able to defend its methodology.
Trigger 07
"Every new rep makes the process problem worse."
Ramp time is getting longer, not shorter. Leads sit unclaimed because routing depends on someone noticing. Two reps work the same account from different angles. The onboarding doc is out of date and the real process lives in the heads of the three people who have been there longest.
The process was tacit and it worked, because a small team can hold shared context in their heads. Tacit process does not survive headcount growth. Each hire dilutes the shared context further, and the symptoms show up as routing failures and inconsistent data long before anyone calls it a process problem.
Routing, SLA and lifecycle before the next cohort starts. We build deterministic assignment rules, define the handoff criteria between functions, set response-time SLAs with enforcement, and document the whole thing so onboarding stops depending on who is free that week.
Longer ramp on a larger cohort compounds. The cost of fixing routing is flat; the cost of not fixing it scales with every rep you add.
Trigger 08
"The board wants efficiency and I can only show spend."
The efficiency mandate arrived. You have total spend by channel and total closed revenue, and a ratio between them that moved in the wrong direction. What you do not have is any view of where in the funnel the cost is concentrated, so every proposed cut is a guess with a budget attached.
Cost is tracked at the channel level and outcomes are tracked at the deal level, with nothing joining them stage by stage. You cannot optimise cost per acquisition when you cannot measure cost per stage. Tool spend compounds the problem: overlapping licences accumulate faster than anyone audits them.
Cost-per-stage instrumentation and stack consolidation. We map tool spend against actual usage, rank consolidation candidates by cost and switching risk, and build the attribution needed to attach cost to funnel stages rather than to channels alone. Then the cuts are informed.
Efficiency cuts made without stage-level cost data usually remove the spend that was working, because that spend is often the most visible.
Trigger 09
"Two CRMs, two taxonomies, one board deck."
The deal closed. Both organisations have a working revenue stack and they disagree about almost everything: what a qualified opportunity is, how territories are defined, which currency the pipeline reports in, whether a renewal is new business. Consolidated reporting is currently a person with a spreadsheet.
Integration planning covered legal, finance and headcount. The GTM data model was assumed to be an IT task and scheduled after the close. The integration plan and the data model are the same document, and most teams write only one of them.
Entity model design and consolidation sequencing. We decide what stays separate and what merges, design the entity and currency model for consolidated reporting, and sequence the migration so the board deck works before the systems are fully merged. Reporting first, platform consolidation second.
Manual consolidation holds for two quarters and then breaks, usually in the quarter you most need clean numbers. This is also work where we take engagements outside the core ICP, because the problem is two of everything rather than one of nothing.
Who This Is For
These decisions get made by a group, and the group does not share a question. Here is what each seat gets out of the first two weeks.