Field notes
Lessons from the work.
What we’ve learned designing and fixing real operations — across sales, service, delivery and the systems underneath them.
This isn’t a blog.
These are notes from real work — moments where an operation didn’t behave as expected, assumptions broke down, and better design was required.
The goal isn’t to promote tools or tactics. It’s to share what actually works — and why.
- LOG-020
7 Signs Your Sales and Support Teams Are Misaligned
Observation“None of these show up as one broken system. Each shows up as one annoying incident — until you notice they're the same incident, happening again.”
RealisationSeven signs, and what they all point back to: not a communication problem, a shared-data problem. Read the full list.
- LOG-019
Sales and Customer Service Alignment: Shared Data, Not a Meeting
Observation“Sales measures deals closed. Support measures tickets closed. Neither measures the thing real sales and customer service alignment depends on: whether the account is healthy.”
RealisationAlignment isn't a recurring meeting — it's a shared source of truth both teams actually look at. Read the full breakdown.
- LOG-018
Sales-to-Support Handoff: A Process B2B Teams Can Actually Follow
Observation“The most common handoff process in B2B isn't a process. It's a Slack message, sent whenever the rep remembers to send it.”
RealisationA real handoff is four steps, with a defined field set and an explicit acknowledgment — not a ping and a hope. Read the full walkthrough.
- LOG-017
RevOps Agency vs In-House Hire: Which Fits Your Stage
Observation“This isn't a question with a universally right answer. It's a question with a right answer for where your business actually is right now.”
RealisationThe signals that point toward hiring in-house are almost the exact opposite of the signals that point toward bringing in outside help. Read the full breakdown.
- LOG-016
Fractional RevOps vs Full-Time Hire vs Agency: What It Actually Costs
Observation“Comparing sticker prices across a fractional consultant, a full-time hire and an agency is comparing three different things that happen to be priced in the same currency.”
RealisationEach model's cost is driven by something different — and the honest comparison starts with what you're actually buying, not the number on the invoice. Read the full breakdown.
- LOG-015
How to Choose a RevOps Agency: A B2B Buyer's Checklist
Observation“Most evaluation checklists ask what an agency says about itself. The useful ones ask what happens after you sign.”
RealisationA real checklist starts with the problem you're actually trying to fix — not a comparison of vendor logos. Read the full checklist.
- LOG-014
15 Signs Your Company Needs a RevOps Readiness Assessment
Observation“Most companies don't book a RevOps assessment because revenue stopped. They book one because they've started noticing the same handful of signals — usually more than one at once.”
RealisationFifteen signals, grouped by where they actually show up — data, process, people and growth. Read the full list.
- LOG-013
The RevOps Maturity Model: 5 Stages Explained
Observation“Most RevOps maturity models plot the same five stages, and most of them quietly reward the same thing at the top: more automation. That assumption is worth questioning before you use one to judge your own operation.”
RealisationThe five stages are a genuinely useful map. Where they put "mature" at the top is the part worth arguing with. Read the full breakdown.
- LOG-012
HubSpot Lead Scoring Models & Best Practices
Observation“Most lead scoring models don't fail because the math is wrong. They fail because nobody trusts them enough to actually use them.”
RealisationThe best practice that matters most isn't a scoring technique — it's making the model simple enough that a rep could explain it in one sentence. Read the full breakdown.
- LOG-011
How to Set Up Lead Scoring in HubSpot
Observation“HubSpot will let you build a lead score in an afternoon. Building one a rep actually trusts takes longer — and starts with a decision most teams skip.”
RealisationA real lead scoring setup is five decisions, made in order, before a single point value gets assigned. Read the full walkthrough.
- LOG-010
HubSpot SLA Escalation: Catching a Breach Before It Happens
Observation“Most "SLA automation" is just a louder alarm after the deadline's already gone. The useful version fires before it, while someone can still act.”
RealisationEscalation isn't one rule — it's a ladder that gets steeper the closer a ticket gets to breach. Read the full breakdown.
- LOG-009
How to Set Up SLAs in HubSpot Service Hub
Observation“Turning on HubSpot's native SLA feature takes five minutes. Deciding what it should actually enforce takes the work most teams skip.”
RealisationA real SLA setup is four decisions, made in order, before a single workflow gets built. Read the full walkthrough.
- LOG-008
RevOps for B2B: How the Whole System Actually Works
Observation“Ask five people to define RevOps and you'll get five different job descriptions. Almost none of them explain when a B2B business actually needs it — or what breaks first if it doesn't have it.”
RealisationRevOps isn't sales ops with a rebrand. It's whoever owns the handoffs between marketing, sales, delivery and customer success — using one framework, not six disconnected fixes. Read the full guide.
- LOG-007
What SLA management actually means in HubSpot
Observation“HubSpot ships a native SLA feature — pick a target time, watch a countdown start. That's not SLA management. It's a clock nobody's told what to count.”
RealisationReal SLA management needs computed priority, two separate clocks, and a warning before the breach — not after. Read the full breakdown.
- LOG-006
Fluent, not certified
Observation“Buyers evaluating a HubSpot RevOps agency assume the partner badge on the footer measures operational depth. Often it measures something else — spend sold, not fluency built.”
RealisationFluency shows up in the work, not the logo. What matters is what's actually been built inside HubSpot — real lifecycle logic, real automation, real governance — not which tier an agency has been assigned. Read the full breakdown.
- LOG-005
Your best leads are the ones you forgot
Observation“A prospect takes a demo, loves it — then has no budget for two quarters. That's ~180 days of silence no salesperson ever tracks. In most CRMs, that lead quietly dies.”
RealisationThe fix isn't discipline, it's a living score. When engagement and fit are quantified into one number that decays as a lead goes cold and climbs again the moment it re-engages, a six-month-dead lead can resurface as a hot one — automatically. Let the system do the remembering. Read the full breakdown.
- LOG-004
SLA design: accountability over timers
Observation“A client had SLAs defined on paper, but breaches were inconsistent and escalations depended on human follow-up rather than the system.”
RealisationSLAs fail when they're designed around timers instead of accountability flow. By separating the source of truth from the execution layer, responsibility survived even when work left the CRM. Read the full study.
- LOG-001Note
The forecasting fallacy
Observation“A growth-stage company had perfectly configured deal stages, yet its pipeline value ran consistently 40% over-inflated.”
RealisationTooling precision doesn't solve for human pressure. The system failed because a 'manager-approval' stage had quietly become a safe harbour for dead deals. Design for incentives, not just stages.
- LOG-002Note
Automation as a mask
Observation“A support team received daily automated 'at-risk account' alerts, yet churn didn't move.”
RealisationAutomation without ownership creates noise, not action. The alerts fired on tool-logic that ignored the actual relationship data. Slow the automation down; speed the governance up.
- LOG-003Note
The ghost system
Observation“A complex setup where leadership had spent heavily on customisation — but the notes that actually mattered lived in personal spreadsheets.”
RealisationIf a system is too rigid to fit the reality of the work, it gets bypassed. High-integrity operations have intentional friction for data entry but high utility for the person doing it.
We add to these notes periodically, as complex operations reveal new patterns.