A scenario
What happens if we cut fifteen percent of the company
The saving is immediate and certain. The second wave of leavers, the ones who were not cut, is the part that gets missed, and it arrives in month three with a bill attached.
Run this on your own numbersAll scenarios
Ships as a scenario: one lever, layoff_pct at 15, landing in month one.
Mechanics
What the model does with it
Four things happen in the month of the cut and none of them is the reason this scenario is interesting. The reason is what the morale shock does over the six months after it.
Headcount, salespeople, severance, shock
Headcount falls by the percentage, spread across the surviving departments in proportion to their size. Salespeople fall by 0.6 times the percentage, so a fifteen percent cut takes nine percent of the sales team. Severance goes into the one off line at the number cut times cost per head times the severance months assumption, which defaults to two. And a morale shock of 0.1 plus the cut fraction is booked, which at fifteen percent is 0.25.
On the invented Harborline twin the arithmetic is quick
Forty six people, fifteen percent, is 6.9 people. At a manufacturing cost per head of 6,400 dollars that is about 88,000 dollars of severance out of cash in month one against a saving of about 44,000 dollars a month. The severance pays for itself in two months on the cost line alone, which is why this decision looks so clean on a page and so different in a run.
The morale shock decays slowly on purpose
The shock is subtracted from morale in the month it lands and then keeps 55 percent of its size each month until it drops below 0.01 and is discarded. From 0.25 that is roughly 0.25, 0.14, 0.08, 0.04, 0.02, 0.01 across six months. Morale is separately pulled back toward its own target at 20 percent a month, so the two fight each other, and the shock wins for the first quarter.
The second wave
Staff attrition is the base assumption multiplied by an exponential in morale, so a morale index falling from 0.68 to 0.43 raises attrition by about half again. Leavers are backfilled at 70 percent by default, at full hiring cost, which means part of the saving is immediately spent replacing people you chose to keep. This is the mechanism the scenario exists to show.
Selling power falls twice
Effective selling power is the ramped rep count over the starting rep count, multiplied by 0.7 plus half the morale index. The cut takes nine percent of reps directly and the morale term takes roughly another twelve percent on top. New business scales with that to the power of 0.7, so pipeline follows about a quarter later without anybody in sales having done anything differently.
Utilisation rises, quality falls, churn follows
Revenue over a smaller headcount is higher utilisation. Above 1.12 the strain counter runs. The quality target carries both a utilisation term and a headcount ratio term, so a cut lowers quality twice. Satisfaction trails quality at 18 percent a month, churn takes the difference, and the revenue line starts moving in the quarter after the saving.
And then management may cut again
If the churn that follows pushes operating profit down and runway with it, the finance lead cuts between 4 and 20 percent of headcount and 30 percent of marketing, with its own morale shock on top of the one still decaying. That path, a cut that causes the conditions for the next cut, shows up in a minority of replications and it is the single most useful thing this scenario produces.
The ecosystem
Which agents move, and why
A layoff is the scenario where the employee class stops being scenery. Every department is an agent with an objective about stability, and the model lets that objective cost you money.
- Departments weight getting the work done without drowning at 0.4 and working somewhere that still looks stable at 0.3. The cut moves both at once
- Salespeople weight avoiding a quarter that ends their year at 0.2, which is the objective a layoff raises hardest, and the ones who can leave are usually the ones you wanted to keep
- Customers never learn there was a layoff. They experience relative quality and service, and they act at renewal
- The finance lead weights protecting cash at 0.4 and is the agent most likely to order the second round
- The operations lead weights keeping people from burning out at 0.2 and will hire back into strain if runway allows, on a four month cooldown, which is how a company ends up rehiring in month seven
- The investor weights no surprises. Two or three negative months reach them, and from there every plan is judged against cash rather than growth
The ledger
What this answer is standing on
| Assumption | What it does here | Why to check it first |
|---|---|---|
| Monthly cost per head | Sets both the saving and the severance | A company average applied to a cut that is not average will be wrong in both directions at once |
| Severance in months of pay | The one off cash cost in the month of the cut | Defaults to two months for everybody. Real schedules vary by tenure and jurisdiction |
| Monthly staff attrition | The base that the morale exponential multiplies | The second wave is entirely a function of this number and the morale shock |
| Morale | The starting point the shock is subtracted from | Usually an estimate. If your starting morale is already low, this scenario is much worse than the default run shows |
| Revenue a head can serve per month | Turns a smaller company into a strained one | The mechanism that converts a cost decision into a quality problem |
| Cost to hire one person | Paid again on every backfill, at 70 percent of leavers | Quietly reverses part of the saving in months three to eight |
| Monthly quota per rep and sales attrition | Turn a nine percent sales cut into a pipeline problem | Worth checking even when sales is not the department being cut |
Run sensitivity after the scenario. On a layoff it usually shows that the answer is standing on staff attrition and morale rather than on the size of the cut, which is not the argument the meeting was having.
Honestly
Where this is weakest
This scenario is built to show the delayed cost of a cut, so it will rarely tell you a cut is a good idea. Read it as a floor on the cost rather than a balanced view, and know what it is leaving out.
- The cut is uniform across departments, spread in proportion to size. A real reduction is selective, and a selective one is usually better than this model assumes
- Nobody is more valuable than anybody else. The model has no idea who left
- No legal process, no consultation period, no notice served before the cost comes out
- One severance figure for everybody, in months of pay
- No productivity gain from removing people who were not contributing, which is the argument the decision is usually made on
- Morale is one number for the whole company, so a cut that hits one site hard and another not at all is modelled as though it hit everybody evenly
The earliest month you could know
Voluntary attrition is the tripwire on this one
What people ask about this one
How big a cut can we make before it goes wrong?
Run a sweep on the lever across the range you would actually consider. The curve is rarely smooth, because the morale shock is the cut percentage plus 0.1, so the attrition feedback grows faster than the cut does. The useful reading is the point where the p10 path stops recovering inside the horizon.
Is cutting one department better than cutting across the company?
They are different levers and they behave differently. The department lever adds a permanent quality drag based on what that department held up, and a smaller morale shock of 0.16. The percentage lever spreads the reduction and books a larger shock. Run both and compare, because the answer depends entirely on what the department in question was doing.
Why does the model make a layoff look so expensive?
Because it prices two things most plans do not: the people who leave afterwards and the service quality that falls when the survivors are busier.
It also leaves out the argument for a cut, which is that some of the removed cost was not producing anything. If that is your case, the honest way to model it is to cut headcount and separately raise capacity per head, and to write down in the brief why you believe the second part.
Does it model a hiring freeze alongside the cut?
There is a freeze flag in the engine that stops backfill and stops replacing salespeople who leave. It makes the saving larger and the capacity problem worse, and it is worth running both ways, because a freeze changes this scenario more than a few percentage points on the cut does.
Next
The questions this one leads to
Put the second wave on the same page as the saving
The saving is in month one and everybody in the room can compute it. The rest arrives between month two and month eight, and a run with a band on it is a better argument than a strong opinion.