1Demonstration 1 of 4
Experience cannot be left behind
When people leave a band, what happens to the average experience of the people who remain?
In the pack, leavers take the band's own average with them, so the ratio moves only by aging. If experience is a separate stock that ignores departures, attrition shrinks the people and not the years, and the average rises every time someone quits.
The junior band holds 20 people and 40 person-years, so 2.0 years each. Attrition is the fraction leaving per period; dt is the step length. Aging adds dt years for everyone present.
Predict first. With attrition 0.5 and dt 0.01, does the average experience in the junior band stay close to 2.0 when experience is carried?
Choose an example
Constructed example: the chapter's starting band of 20 people and 40 person-years, advanced with the pack's advance function.
Calculated values
- People in the band after
- 19.90
- Total experience after (person-years)
- 40.00
- Average experience after (years)
- 2.010
- Change in the average (years)
- 0.010
- Aging alone would add (years)
- 0.01
Leavers = 0.01 x 0.5 x 20 = 0.10, so people = 20 - 0.10 = 19.90. Experience = 40.0 + 0.20 - 0.10 x 2.0 = 40.00. Average = 40.00/19.90 = 2.010, a change of 0.010 years against 0.01 from aging. Leavers took their own share, so the average moved by about the aging alone.
Use the idea
Plot the ratio of experience to people, not only the totals; the parallel-stock bug hides in the totals.
Where the conclusion applies
One band, no hires and no maturation, short steps. The parallel version is the bug the chapter describes, computed here by plain arithmetic and not by the pack. At a long step the pack's own credit for the leavers' aging also shows, which is why the chapter's test uses a short step.
Check your understanding: With dt = 0.1 and attrition 0.2, how many people leave the junior band in one step?
Chapter 17 source: section "Experience cannot be left behind". Demonstration C17-D01.
2Demonstration 2 of 4
What the surge does
If headcount nearly doubles, how much does capacity rise?
Hires add heads at once and capability slowly, because they arrive with none. With enough hires the junior band also gets greener, since newcomers arrive faster than the juniors mature; with few hires it does not.
Three bands start with 20, 30 and 50 people holding 40, 150 and 500 person-years. Hires enter the junior band with no experience. Effective capacity counts each person in proportion to their experience up to the ramp, and fully after it.
Predict first. With 40 hires per step and a ramp of 4, does capacity rise by more or less than headcount after 3 steps?
Choose an example
Constructed example: the chapter's three-band workforce and its 40 hires per step, with other hire sizes and a ramp of 2 defined for this reader.
Calculated values
- Headcount
- 100 to 193.4
- Headcount rise (percent)
- 93
- Effective capacity
- 90.0 to 135.1
- Capacity rise (percent)
- 50
- Junior average experience (years)
- 2.00 to 1.45
40 hires x 3 steps = 120 people entered; headcount rose by 193.4 - 100 = 93.4, so 120 - 93.4 = 26.6 left. Headcount rise = 93.4/100 = 0.934. Capacity on a ramp of 4 rose by 135.1 - 90.0 = 45.1, which is 45.1/90.0 = 0.501. The gap between the two rises is the dilution a headcount model reports as zero.
Use the idea
Report capacity beside headcount whenever the workforce is changing fast.
Where the conclusion applies
Three bands, the chapter's maturation and attrition rates and no training cost. The pack steps one period at a time and ages everyone by one unit per step, so the ramp is in those units.
Check your understanding: If 120 people entered over three steps and headcount rose by 93.4, how many left?
Chapter 17 source: section "What the surge does". Demonstration C17-D02.
3Demonstration 3 of 4
Read headcount and average experience together
What does it tell you when headcount and average experience move in different directions?
Each pairing of directions is a different story: growing and diluting, aging in place, or the experienced people leaving. Aging pushes the average up over time, so the dilution shows most clearly early in a surge.
Headcount is people across all bands. Average experience is total person-years divided by headcount. The three scenarios differ only in hiring and attrition.
Predict first. Under the senior band leaving, do headcount and average experience both fall after one step?
Choose an example
Constructed example: the chapter's three-band workforce under three scenarios defined for this reader, advanced with the pack's advance function.
Calculated values
- Scenario
- Hiring surge
- Headcount
- 100 to 193.4 (rising)
- Average experience (years)
- 6.90 to 5.06 (falling)
- Reading
- growing and diluting at once
Start: 690 person-years / 100 people = 6.90 years. After 3 step(s): 978.1 / 193.4 = 5.06 years, a change of (-1.84). Headcount changed by 93.4. Headcount rising with average experience falling reads as growing and diluting at once.
Use the idea
Plot both curves and read them as a pair, not one at a time.
Where the conclusion applies
Constructed scenarios in which the senior band loses 0.8 of its people per period in the third; real attrition is rarely uniform across bands, which a single rate cannot show.
Check your understanding: Start with 690 person-years among 100 people. What is the average experience?
Chapter 17 source: section "Three curves, read together". Demonstration C17-D03.
4Demonstration 4 of 4
The recommendation that reverses
Inside a short horizon, how much capability does each person hired actually deliver?
Hires arrive with no experience, so within a short horizon with a long ramp they add heads and little capability. The ratio climbs toward one as the hires mature.
Heads added is headcount with the surge minus headcount without it after the same number of steps. Capacity per head is the capacity gained divided by heads added. A headcount model assumes 1.00.
Predict first. After 1 step with a ramp of 4, how much capacity does a head added by hiring deliver?
Choose an example
Constructed example: the chapter's surge of 40 hires per step against a no-hiring run, compared with the pack's effective_capacity.
Calculated values
- Heads added by hiring
- 76.0
- Capacity gained
- 22.28
- Capacity per head added
- 0.29
- Shortfall against 1.00 per head
- 0.71
With 40 hires per step against none, 76.0 more people remain after 2 step(s). On a ramp of 4 they add 22.28 of capacity. Capacity per head = 22.28/76.0 = 0.29, so the shortfall against a headcount model is 1.00 - 0.29 = 0.71. Each added head delivers a fraction of a head inside this horizon, and the training cost, which this model omits, would lower it further.
Use the idea
State the horizon next to a hiring recommendation; the case for hiring has to be made on the capability curve.
Where the conclusion applies
No training cost, which the chapter says its model omits and which would lower the ratio. Beyond the horizon where hires mature the headcount and chain models agree.
Check your understanding: If 100 heads are added and they deliver 29 units of capacity, what is the capacity per head?
Chapter 17 source: section "The recommendation that reverses". Demonstration C17-D04.