The six ways we attack every Kauzio decision

When a decision goes into Kauzio, it does not get a fresh personality each time. It gets argued on the same six axes, in the same order, with the same evidence requirements. We call them opposition axes because the job of each one is to push back against the case being made.

The six are fixed. Revenue risk, margin impact, demand elasticity, operational friction, reversal cost, uncertainty level. Every Pulse decision is scored on all six before a verdict is written.

Here is what each one does.

1. Revenue risk

The question. If this decision goes the wrong way, how much top-line revenue is exposed over the next quarter.

The evidence it looks for. Historical sales tied to the category, customer or channel the decision touches. Concentration of revenue in the affected segment. The size of the worst plausible swing, not the average swing.

Take a hypothetical case. A retailer considers dropping a slow-moving SKU. Revenue risk pulls the trailing 12-month sales for that SKU, checks whether any of it was attached to baskets that included higher-margin items, and reports a worst-case revenue gap of 1.8 percent of category sales. That number becomes a hard input to the verdict.

2. Margin impact

The question. What does this decision do to gross margin in the period it lands, and in the period after.

The evidence it looks for. Unit economics for the product, service or role being changed. Cost trends in the inputs. Whether the margin move is one-off or compounding.

Take a hypothetical case. A hospitality operator wants to raise prices on a flagship dish by 8 percent. Margin impact models the contribution per cover at the new price, at the old cost base and at a 4 percent cost rise scenario. It reports a 230 basis point margin lift in the base case and a 90 basis point lift in the worst case. Both numbers go on the decision card.

3. Demand elasticity

The question. How will the customer or counterparty actually respond, and how confident are we in that response.

The evidence it looks for. Past responses to similar moves in the same segment. Comparable benchmarks in the sector. The shape of the response curve, not just the midpoint.

Take a hypothetical case. A fintech raises a credit threshold by 30 points. Demand elasticity checks the historical approval-to-application ratio at neighbouring thresholds, models the application drop-off, and quotes a band. Approvals will fall between 6 and 11 percent, with a most-likely value of 8 percent. The band is the honest answer. The midpoint alone would not be.

4. Operational friction

The question. What does this decision cost the people who have to execute it.

The evidence it looks for. Workflow steps changed. Systems touched. Training required. The team's current load.

Take a hypothetical case. A clinic considers moving from two-week to four-week appointment booking windows. Operational friction maps the reception workflow, counts the touchpoints in the booking software, and flags two of them as manual. It quotes a one-off setup load of 14 hours and an ongoing weekly load of 1 hour. Small numbers, but they go on the card so nobody is surprised later.

5. Reversal cost

The question. If this decision turns out wrong in 30 days, how hard is it to undo.

The evidence it looks for. Contracts signed. Stock committed. Public commitments made. Sunk cost. Time to restore the prior state.

Take a hypothetical case. A professional services firm considers signing a 24-month office lease. Reversal cost reads the lease terms, prices the break clause, and reports a reversal cost of 11 months of rent if the call has to be undone in year one. That number is what triggers the sleep lock and pushes the verdict from instant to overnight.

6. Uncertainty level

The question. How much do we actually know, and how much are we guessing.

The evidence it looks for. Volume and recency of relevant data. Variance across sources. The calibration score for this sector. Whether the question sits inside a band Kauzio has seen before or outside one.

Take a hypothetical case. A retailer asks Kauzio about expanding into a new region with no prior sales history. Uncertainty level reports a high score, the calibration page is referenced, and the verdict comes back as a small reversible test rather than a full commitment. The uncertainty score did not block the move. It shaped it.

Why the same six, every time

The most common objection to a fixed frame is that decisions are different. A hire is not a price change. A lease is not a discount.

True, and the inputs are different. But the questions a serious operator asks are not. Every decision, in every business, is helped by knowing the revenue at risk, the margin shape, how the other side will react, what it costs the team, how reversible it is, and how confident the evidence is.

A different framework every time means a different blind spot every time. A fixed framework means the same blind spots are caught the same way, every meeting, with no one person having to remember to ask. That is more useful than a fresh opinion. It is also more honest. The case for the decision has to survive the same six attacks every other decision survived. Nothing gets a free pass because the room liked the idea.

That is the spine of the Pulse decision loop. Six axes, same order, every time, with the evidence written down so the next person can check it.