PHARMA · SG&A
Discovery Synthesis · The Core Story
OptiGen Generics · Global BU · 11% → 14% operating margin · $720M SG&A flat
Delta
14% op margin
155 bps
spread — same $720M envelope
0 of 5 teams named the incentive conflict before R3
firm-level signal
OptiGen Generics has $2,000M in net sales and a mandate to move operating margin from 11% to 14% without increasing the $720M SG&A budget. The only lever is reallocation — moving spend from bucket D toward bucket A. Five teams ran the same simulation. Delta delivered 14%. Alpha, Gamma, and Epsilon ranged 11–12%. The 155 bps spread came from the same dataset, same mandate, and same $720M envelope. Every team hit the same three traps: country-first analysis in R1, fairness spread in R2, and shock reversion in R3.
01
Change the first question in every SG&A session
Start every SG&A cycle with: what share is funding bucket D? Not: what does each country need? The first question determines the allocation logic. Change the first slide; the allocation follows.
02
Name the incentive conflict now
Field force KPIs reward coverage, not bucket A contribution. No team named this before Round 3. Fix the metric, not the person.
03
Write one shock rule before the next Board cycle
A shock in a country triggers a bucket review — not a budget increase. Teams that held this rule landed 14%. Those without it landed 11–12%.
PHARMA · SG&A
Overall Combined · All 5 Teams
155 bps spread — same $720M envelope
Delta
14% op margin
11–12%
Alpha & Epsilon range
155 bps
spread — same $720M envelope
0 of 5
0 of 5 teams named the incentive conflict before R3
| Team | Identity | Score | Bucket D End | Key Pattern |
|---|---|---|---|---|
| Alpha | Country-First | 11–12% | 14%+ | Fairness spread + shock reversion |
| Beta | Portfolio-First | 12–13% | 12% | Elegant theory, poor country execution |
| Gamma | Sales-First | 11% | 15% | Over-weighted field force, cut medical |
| Delta | Efficiency-First | 14% | 10% | Across-the-board cuts early — recovered |
| Epsilon | Balanced | 12–13% | 11% | Right language, avoided hard D-exit calls |
Delta performed best. Alpha and Epsilon scored at the bottom. The 155 bps spread came from the same dataset, same mandate, and same constraints. Every team hit the same three traps in the same order.
The simulation selects for a dominant behaviour pattern regardless of team composition. Delta's advantage was not superior skill — it was an identity least attached to the default first instinct. The system design produced the spread.
The offsite design is the intervention. Change the opening frame for the next session. The spread narrows when the first question changes — not when team composition changes.
PHARMA · SG&A
Team Arc · Alpha
Score: 11–12% · Target: 14% op margin · Bucket D share remained above 14% throughout all rounds
11–12%
Alpha final score (target: 14% op margin)
Bucket D share remained above 14% throughout all rounds
Bucket D share remained above 14% throughout all rounds
70% of R1 analysis tokens on country deep-dives
70% of R1 analysis tokens on country deep-dives
R1–R4
Same trap pattern every round — process unchanged
R1
Country-first opening
70% tokens
country
country
R2
Fairness spread
+5% field
−8% marketing
−8% marketing
R3
Shock reversion
3 of 3 shocks
reverted
reverted
R4
Board case
11–12%
vs 14% target
vs 14% target
Alpha opened with country analytics, spread SG&A fairly in R2 (field +5%, marketing −8%), reverted to country budgets under all three Round 3 shocks, and presented 11–12% operating margin to the Board — below the 14% target.
Alpha's arc reveals a team with the right language but the wrong reflexes. They could describe One SG&A. They could not act on it when a named geography was under pressure. Country GM identity governed the choices, not the framework.
One structural fix: remove country ownership of SG&A budgets from the pre-read framing. Replace it with a bucket-first mandate where country GMs advise on execution, not allocation.
PHARMA · SG&A
Round 1 · System
How does the process perform under real time pressure and information constraints?
70%
Alpha analysis tokens on country deep-dives
$108M
SG&A locked in negative-margin franchises
30%
Southern Europe bucket D share — highest
0 of 5
Teams started with bucket mix analysis
All five teams spent Round 1 analysing country-level P&Ls. No team opened with a bucket A vs D lens. Southern Europe — highest bucket D share at 30% — received more analysis time than India, which had the strongest growth. Team Alpha spent 70% of tokens on country deep-dives.
When the first instinct is to protect country budgets, the team is managing the past. Bucket D accounted for 15% of Net Sales but consumed proportionally more SG&A. No one looked there first. The system is rewarding local attachment, not BU value creation.
Start every allocation review at bucket level, not country level. Require the first 15 minutes of any SG&A session to answer: what share of our SG&A is funding negative-margin products? Make bucket exposure visible before country discussions open.
TEAM POLL
In your current SG&A planning process, what is the opening frame?
Arena's view: In the simulation, 0 of 5 teams opened with bucket economics — despite having the data available. Country P&Ls as the default opening frame is the single most powerful driver of country-first allocation behaviour. The opening frame is the intervention.
PHARMA · SG&A
Round 2 · People
How do leaders actually decide under governance and conviction pressure?
4 of 5
Teams spread SG&A evenly across countries
+5%
Alpha field sales vs flat mandate
-8%
Alpha marketing cut despite bucket A need
0 of 5
Teams named incentive conflict before R3
Four of five teams distributed SG&A increases proportionally across all country clusters — the 'fairness spread.' No team reduced headcount in any cluster. Marketing and medical budgets were trimmed instead. No team named the incentive conflict between field force KPIs and bucket A profitability before Round 3.
Even when given the data, leaders defaulted to what felt equitable rather than what creates value. Field force is the most visible SG&A line — cutting it feels like a people decision. The real allocation problem is invisible in the org chart and only visible in the bucket economics.
Name the incentive conflict explicitly in the offsite pre-read. Ask leaders to state, before seeing the data: which function's KPIs are most misaligned with bucket A growth? Build one cross-functional forum with explicit authority to override country budget protections.
INFERENCE CHECK
Why did 4 of 5 teams spread SG&A proportionally ('fairness spread') even when bucket economics pointed to concentration?
PHARMA · SG&A
Round 3 · System × People
What happens when shocks and pressure interact with the system and people inside it?
3 shocks
SE tender, LatAm delay, India competitor
3 of 5
Teams reverted to country-first under pressure
0 of 5
Teams fully exited bucket D in any cluster
11–12%
Op margin for teams who reverted
Three shocks were introduced: a tender loss in Southern Europe, a regulatory delay in Latin America, and a competitor entry in India. Three of five teams immediately re-allocated SG&A back into the affected country rather than holding their bucket-first position. No team had a pre-agreed shock response rule.
Under pressure, systems revert to what people know. Country-first thinking re-emerged the moment a concrete shock hit a named geography. Bucket discipline collapsed because no team had pre-agreed a decision rule for how shocks should change the allocation model.
Before the next planning cycle, establish one rule: a shock in a country triggers a bucket review, not an automatic budget top-up. Write it down. Test it in a 30-minute scenario session before the next Board cycle.
DECISION STAMP
In your organisation, when a commercial shock hits a specific market — what most commonly happens to the SG&A allocation decisions made in the annual planning cycle?
🔒 Stamped. Your response has been recorded.
Arena's view: 3 of 5 teams in the simulation reverted to country-first allocation under all three shocks — despite having articulated a bucket-first strategy. The reversion is the system default, not an exception. A shock protocol converts intention into mechanism.