1
More reps, same revenue
The most common growth decision in software, and the one that most often fails — because revenue per rep is not a constant, it is an output of a system the hiring decision itself changes.
I'm Vijay Kumar. I run operations and revenue in enterprise software — most recently as chief operating officer and chief innovation officer of a technology company in agentic AI, subscriptions, support and services. I spend my time on the gap between what a decision is supposed to do and what it actually sets off.
How I help
Three ways I'm useful
Operating
Twenty-five years running revenue, customer success and delivery. I've managed P&Ls from $50 million all the way to $1.2 billion, and teams ranging from 25 people to over a thousand globally, and learnt a lot along the way. I have a strong bias towards operating models that survive contact with a real quarter.
Sponsor-side work
Diligence support and post-close operating plans, in the language sponsors use: EBITDA bridge, revenue quality, retention mechanics, hold-period risk. I have run the retention side of a $1.2B book, so I know which of those numbers are load-bearing.
Building
I build the tools I argue for — a structured model of how a technology company actually works, and simulations that let a leadership team rehearse a decision before committing to it. The experiment is running at firstdominosym.ai.
The map
Fifty-four things I have watched leaders do, over and over
A field guide for founders, operators and investors. Each column is a part of the company; each row is how often the work happens. Click any card to turn it over, and the panel shows what the activity is, what breaks without it, and where I have done it myself.
Kind of work
The map is wide — scroll it sideways to see every column.
My favourite COO plays
Some activities matter far more in combination than alone. Each one feeds the next. Pick a play to light up its parts on the map.
Recent writing
Five notes on why decisions miss
Short pieces, each one about a decision that looked right in the plan and went wrong in the company.
2
The $15M you save, and the bill that arrives later
Cost is the easiest thing in a company to find, because it sits in a ledger. The capacity it was buying does not, which is why the saving and its consequence land in different years.
3
Your plan is a straight line. Your company is a loop.
Spreadsheets add. Companies feed back. Almost every operating plan assumes effects stop travelling after one step, and almost every surprise comes from the step after that.
4
Nobody is arguing about the decision
Executive disagreements are rarely about the choice on the table. They are about two different unwritten models of how the business works, and nobody in the room can see either one.
5
Every better decision starts with a better question
"Should we hire more salespeople" is a worse question than "what is currently limiting revenue per rep". The quality of a decision is capped by the quality of the question that produced it.
What I'm building
FirstDomino Sym
A model of how a technology company actually works, built so that a leadership team can ask a question, change an input, and watch the consequences arrive — including the ones three steps downstream that a spreadsheet cannot reach.
384metrics mapped
465computed-from dependencies
31metric families
L0–L9levels, headline down to transaction
The question library
Twenty-five questions a leadership team actually argues about. Every one of them is a causal question rather than a reporting question, which is why the usual dashboard cannot settle it.
Growth
Will more salespeople actually create more growth?
Interactive experience
Growth
Should we enter a new market?
On request
Growth
Where should the next growth dollar go?
On request
Growth
Is pricing helping growth, or hiding a problem?
On request
Growth
Can our current business model support the next stage?
On request
Cost & capacity
Can we save $15M without weakening the business?
Interactive experience
Cost & capacity
Which costs protect the capacity we need?
On request
Cost & capacity
Should we automate before we reduce headcount?
On request
Cost & capacity
How much operating capacity can we safely remove?
On request
Cost & capacity
Does the sequence of cost reductions change the outcome?
On request
Customers & delivery
What is causing our delivery backlog?
On request
Customers & delivery
Would faster onboarding unlock more revenue?
On request
Customers & delivery
Where is customer churn really coming from?
On request
Customers & delivery
Are we winning more customers than we can serve?
On request
Customers & delivery
Which service investment would matter most?
On request
Value & capital
Should we reinvest cash or protect the balance sheet?
On request
Value & capital
Which growth strategy earns its cost of capital?
On request
Value & capital
Does better EBITDA also mean better cash flow?
On request
Value & capital
Which business unit deserves the next investment?
On request
Value & capital
What assumptions matter most to our investment case?
On request
Execution & resilience
What if our most important initiative is delayed?
On request
Execution & resilience
Can the company absorb several changes at once?
On request
Execution & resilience
What should happen first in our transformation?
On request
Execution & resilience
Where are we most exposed to a demand shock?
On request
Execution & resilience
Which leading signals should change our decision?
On request
Bring the question and the assumptions behind it. The first session is a working one, not a pitch.