How many hires does a support week really need, in odds rather than averages?
Six agents, 1,400 tickets a week, 180 closed per agent. The sheet says two hires leave 40 to spare. Across 20,000 futures two hires keep up in 51 in 100 runs, and 85% odds of keeping up takes three.
Operations Starter Monte Carlo Pro engine
After you install, this is the model to open.
How many hires keep 85% odds of hitting the support target?
- In your spreadsheet, click the Sortia icon in the strip of icons down the right-hand edge. No strip? Click the arrow at the bottom-right to open it. You can also use Extensions, then Sortia, then Open Sortia.
- Click Start from a template and put that name in the search box.
- Pick the card with that name and click Load this template. It arrives on a new tab with real numbers already in it.
This one runs on a Pro engine, and every free install includes five full-quality runs on your own numbers, shared across all five Pro engines rather than five for each. After that, Pro is $199/year.
What it does
Six agents on a support team, 1,400 tickets arriving a week and 180 closed per agent per week. As typed the team closes 1,080 and the backlog grows by 320 a week. Hire two and the sheet shows 40 tickets to spare, hire three shows 220 and hire four shows 400, so two hires looks like enough. Click Run with tickets arriving and tickets closed per agent as three-point estimates, 1,150, 1,400 and 1,850 for the arrivals and 150, 180 and 205 for the agent.
The seed is set to 7 and the trials to 20,000 so your first run reproduces these figures exactly. Spare capacity with two hires comes back with a mean of -1.1 tickets a week and a median of 4.5, and two hires keep up with the week in 51 in 100 runs. The 40 to spare the sheet showed is a coin toss. Three hires keep up in 86 in 100 runs, with a mean spare of 178.0 and a median of 183.3, so three is the number of hires that keeps at least 85% odds of hitting the target.
Four hires keep up in 98 in 100 with a median spare of 362.2, which is the price of the last twelve points of odds: one more salary. The three candidates share one draw of arrivals and one draw of the agent rate in every trial, so the difference between their readings is the hiring decision alone. The tornado on the three-hire reading puts tickets arriving first at -0.81, carrying 67% of the spread, and tickets closed per agent at 0.56, so the week's volume matters more than how fast anyone works.
Second run: if the last quarter's volume can be trusted, narrow the arrivals draw in the Risk Analysis panel to 1,300, 1,400 and 1,600 and rerun. The odds at two hires rise and the odds at three rise further, and how far they move is what a better forecast of volume is worth against a salary. What the model cannot tell you: each week is drawn on its own with no backlog carried in from the week before, so a run of bad weeks is not in the range; a new hire closes tickets at the full rate from day one, when ramp-up takes months; tickets are counted, not weighed, so a week of hard tickets looks like a week of easy ones; and 85% odds of keeping up in a given week is not 85% odds of keeping up every week of the quarter.
To make it yours, put in your own team size, the weekly arrivals from your ticket system as a low, likely and high, and the rate your agents actually close at, and set the same two ranges on the draws in the Risk Analysis panel.
The model
It arrives on a tab called Template: Hires With 85% Odds, carrying these columns:
- Agents on the team today (people)
- 6
with the model computed beside the data:
| Spare capacity with the team as it is (tickets per week, negative = the backlog grows) | -320 |
| Hire 2 | 8 |
| Hire 3 | 9 |
| Hire 4 | 10 |
Once it is in your sheet
- The model arrives with real numbers in it and runs as it stands, so you can press the button first and understand it second.
- Change the numbers to yours. The sheet marks which cells are inputs and which hold formulas, and most labels carry a note explaining the row.
- Press the run button at the bottom of the panel. It is labeled for the tool you are in, and the result lands on its own tab, with a written reading of it beside the figures.
Never used Google Sheets? Start here goes the whole way, in seven steps, and assumes nothing.
Next question
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- Which tasks actually set your launch date?Launch Plan: Find the Critical Path
- Which risks actually deserve the money?Project Risk Register, Priced
- Which office wins once you price the commute?Where Should the Office Be?
Every model like this one, and the method behind them: Monte Carlo simulation.