Case Study: Step vs Linear vs Anavai Smart Scale
Same threshold. Same target. Same stretch. Same budget. Only the path between them changes.
500-rep salesforce · ₹1,000 Cr quota · ₹20 Cr target incentive pool · same targets, same people, three plan shapes
- Near-miss band (90–100%) shrinks 2.9pp; over-target grows 3.3pp
- Revenue delivered by quota-clearing reps: 41% → 45%
- The mean barely moves. The shape of the distribution does.
- ₹0.87 Cr released from near-miss funds a ₹0.69 Cr accelerator
- On identical performance, Smart Scale costs ₹0.18 Cr less than Linear
- Step under-spends the pool by 24% — ₹4.7 Cr dead provision
- Stretch performers earn 182% of target vs 176% under Linear
- No cliffs: biggest one-point swing is 7.6pp vs 40–50pp under Step
- Trade-off: bottom 20% see a 21% flatter gradient — by design
- Step parks two-thirds of the force just above a slab line
- One continuous formula, one published parameter k — fully auditable
- Cost-neutral at all three anchors, so provisioning is unchanged
The setup
Same plan anchors across all three curve shapes — Threshold 80% pays 20%, Target 100% pays 100%, Stretch 120% pays 200% — modeled on a 500-rep sales force against a ₹1,000 Cr quota and a ₹20 Cr target incentive pool. The only variable is the shape of the curve between those anchors: a Step (slab) plan, a two-segment Linear plan, and Anavai’s Smart Scale (sigmoid) curve, calibrated with k = 1.2 so 90% attainment pays 48%.
Payout vs. Attainment
Payout (% of target incentive) vs. Attainment (% of quota)
Smart Scale curvature k = 1.2, calibrated so 90% attainment pays 48%.
| Attainment | 85% | 90% | 95% | 105% | 110% | 115% |
|---|---|---|---|---|---|---|
| Step (slab) | 20 | 60 | 60 | 100 | 150 | 150 |
| Linear | 40 | 60 | 80 | 125 | 150 | 175 |
| Smart Scale | 32 | 48 | 70 | 137 | 165 | 185 |
| vs Linear | -8 | -12 | -10 | +12 | +15 | +10 |
Payout as % of target incentive. Green = capital released. Blue = capital redeployed.
Measured in the 90–108% band, where 45% of the salesforce sits. Implied elasticity 0.68. Below 90% the gradient is deliberately flatter — that is where the capital comes from.
A Step plan pays 99% attainment the same as 90%. A Linear plan pays the point before target the same as the point after threshold. Smart Scale is the only one of the three where the reward for the next point depends on which point it is.
Where the Salesforce Lands
% of reps by attainment band
How the simulation works
Every rep has a latent capability and the same discretionary effort ceiling. How much of that ceiling they actually spend responds to the payout gradient ahead of them. No plan is given a head start — the model only reads the slope each plan offers.
Sensitivity: across response assumptions from half to double the base case, reps clearing quota gain +3.0pp to +4.8pp and net incentive spend moves ₹0.03–0.36 Cr. The direction does not flip.
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Disclaimer: This case study is based on an actual pilot diagnosis. All figures presented are anonymized and modeled — they represent a simulated illustration of the underlying plan structure and do not disclose the client’s identity, real financial results, or confidential data.