Deck 18 · Company Research (Briefing Room) + QBR Process

OMX Innovation · Deck 18 · Company Research (Briefing Room) + QBR Process

One Company Research engine, two surfaces — the Briefing Room (5 modes for any company we care about) and the QBR Process (pre-filled quarterly customer reviews for every account that matters).

Build the engine once; use everywhere; never ask the same research question twice.

01 / 06

Why now

The wedge.

QBR (Quarterly Business Review) prep currently takes days per account — manually pulling sales, margin, DIFOT, contract terms, news, sector intelligence
Briefing Room covers the same shape for ANY company we research (prospects, competitors, suppliers, partners)
The 5 modes are already informally in use; codifying turns it from "one analyst knows" to "every commercial conversation grounded"
Anthropic + Snowflake + Plex-CI makes the automated pre-fill feasible today

02 / 06

What this covers

What's in scope.

01

The 5-mode codification

the engine that powers both surfaces

02

The Briefing Room

analyst's research workspace; ask a question, get a 5-mode brief

03

The QBR Pack pre-fill

Tier 1-2 accounts get auto-generated quarterly review packs; rep adds the relationship colour and ships

04

Customer health score

derived from Mode 1+2+4: financial health, ops change signals, news risk

05

Architecture

Anthropic semantic layer + Snowflake + Plex-CI + external feeds (IBISWorld, news, LinkedIn)

06

Integration with Deck 17

AI Semantic Conversations lets users ask "show me [account]'s last 6 months" → triggers a mode-1+4 fetch

03 / 06

The problem

What's broken.

01

QBR prep = days per account

manual data pull, no template, no consistency

02

Research not reused

analyst writes a brief, it's used once, then lost

03

Inconsistent depth

some QBR packs are deep; others are slides with logos

04

No customer health signal

by the time a customer's churning, the news + ops signals were there but unsynthesised

05

Briefing Room is artisan

one analyst running 5-mode in their head; doesn't scale

04 / 06

The benefits

The value story.

Lever

Mechanism

Sizing

QBR prep time

Pre-filled vs manual

Days → <1hr per pack; reps reclaim sales hours

Customer retention

Better QBRs = better customer conversations = retention

Industry: well-run QBRs lift retention 5-15%

Win rate

Pre-prospect briefing = sharper pitch

Strategic; harder to quantify

Customer health early warning

Mode 1+2+4 signals = pre-churn intervention

Reduces churn months

Analyst capacity

Codified engine vs artisan work

Strategic

05 / 06

The ask + roadmap

What we need.

Now

Cover

AM at desk with the Briefing Room screen + customer pack on one monitor; clock visible. Empty inbox in background.

P2

Problem vector grid (4)

: QBR-prep-cost / Inconsistent-depth / No-reuse / No-health-signal

P3

The 5 modes wheel

visual; each mode → what it answers → what sources

P4

Two-surface diagram

Briefing Room + QBR Pack from the same engine

P5

QBR walkthrough demo

top account, pre-filled pack, rep adds colour, ships

Audience

Primary: Chief Commercial Officer + Sales Director + Head of Strategy. Secondary: Account Managers (users), Analysts (engine maintainers). Tertiary: ExCo — uses Briefing Room for any company-of-interest.

References

Memory: OMX project umbrellas — Briefing Room owns Company Research (reference_omx_project_umbrellas) — 5 modes = one brief, not five
Memory: Deck 17 AI Semantic Conversations — same engine; QBR pre-fill is one of its top use cases
Memory: Plex-CI for competitor + supplier mode-3 input
Memory: N3 buying group (reference_omx_n3_definition) — 5,498 SF accounts $18.8M closed-12 = Tier-1 candidate set
Memory: OMX Freshservice API pattern — possible integration for customer-side tickets in mode-2

06 / 06