Databricks Apps Adoption Playbook - Panel Presentation

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PARTITION: INTRODUCTION

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Slide 1: About Me

So What: Proven track record of building processes that scale, with deep Apps conviction.

Why I’m a Good Fit:

• Data-driven: Built hypothesis validation into my leadership practice
• Process builder: Created Practice Lead motion that outlasts people
• Apps champion: Launched Month of Apps, closed Peet’s Coffee with Apps-led GTM
• Product partner: Deep-dived DBSQL issues with PM (Shant)

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PARTITION: THE OPPORTUNITY

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Slide 2: Problem + Why Now

So What: 14x organic growth proves demand, but we’re leaving wins on the table.

┌─────────────────────────────────────────────────────────────────┐
│                    CURRENT STATE: ORGANIC CHAOS                 │
├─────────────────────────────────────────────────────────────────┤
│   REVENUE:  $5M ──────────────────────────► $70M  (14x growth)  │
│                                                                 │
│   BUT:      ❌ No ICP definition   ❌ FE not enabled            │
│             ❌ No attach tracking  ❌ Signal to PM is ad-hoc    │
│                                                                 │
│   RISK:     Organic growth will plateau without deliberate GTM │
└─────────────────────────────────────────────────────────────────┘

Why Now:

• Market validated (14x growth = demand exists)
• Platform synergies maturing (Lakebase + Unity Catalog + Model Serving)
• Competitive window open (hyperscalers lack integration, ISVs lack compute)

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PARTITION: MY APPROACH

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Slide 3: What Good Looks Like

So What: Shift from “hope it works” to deliberate, measurable, honest GTM.

Four Principles:

1. Hypothesis-driven — Test beliefs explicitly, pivot when invalidated
2. Motion-matched — Quality (Enterprise + PS) vs. Quantity (Digital Native + self-serve)
3. Honest positioning — Know when NOT to sell; build trust, not hype
4. Measured + instrumented — Attach rate, influenced ACV, retention—signal to PM

Slide 4: 3 Core Bets

So What: 3 testable bets with clear decision points—not 8 hypotheses to track.

┌─────────────────────────────────────────────────────────────────┐
│                         3 CORE BETS                             │
├─────────────────────────────────────────────────────────────────┤
│   WHY APPS?              WHERE TO PLAY?        HOW TO WIN?      │
│   ───────────            ──────────────        ───────────      │
│   Apps drive platform    Archetype-matched,    Full-funnel      │
│   expansion via          net-new, motion-      enablement +     │
│   ecosystem moat         aware targeting       SI + metrics     │
│                                                                 │
│   Tests:                 Tests:                Tests:           │
│   • Attach rate          • 80% fit archetypes  • FE confidence  │
│   • Competitive wins     • Motion-retention    • SI time-value  │
│                                                                 │
│   Decision: M6           Decision: M6          Decision: M3, M9 │
└─────────────────────────────────────────────────────────────────┘

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PARTITION: THE PLAYS

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Slide 5: Sales Play - Target + Trigger

So What: FE needs simple triggers to spot Apps opportunities—3 archetypes cover 80%.

flowchart LR
    subgraph Archetypes["APP ARCHETYPES"]
        BC["🎯 BUSINESS COCKPIT<br/>Analytics for execs"]
        DV["🔬 DEEPLY VERTICAL<br/>Industry AI apps"]
        HZ["🛠️ HORIZONTAL<br/>Platform tools"]
    end
    
    BC --> BusBuyer["Business Exec"]
    DV --> DomainBuyer["Domain Specialist"]
    HZ --> PlatformBuyer["Platform Team"]

Trigger Signals:

• “We need a dashboard for executives” → Cockpit
• “We have ML models but can’t operationalize them” → Vertical
• “Data team is bottleneck for business requests” → Horizontal
• “We need infinite scalability” → Defer (not ready)

Slide 6: Sales Play - Position + Qualify

So What: Lead with moat (UC + Lakebase + AI), qualify with 5 questions.

flowchart TB
    subgraph Moat["DATABRICKS APPS MOAT"]
        UC["UNITY CATALOG<br/>Governance"]
        LB["LAKEBASE<br/>Serverless OLTP"]
        AI["AI/ML PLATFORM<br/>Co-located models"]
        SQL["SQL/JOBS<br/>Compute"]
    end
    
    UC --> Flywheel["ADOPTION FLYWHEEL"]
    LB --> Flywheel
    AI --> Flywheel
    SQL --> Flywheel

5 Qualification Questions:

1. Net-new or migration? → Net-new = fit
2. Data in Lakehouse? → Yes = strong fit
3. AI-powered? → Yes = differentiator
4. Business users? → Yes = expands market
5. Strict governance? → Yes = our moat

Slide 7: Signals + Levers

So What: Systematic signal capture gives PM prioritized feedback, not noise.

flowchart LR
    Capture["1. CAPTURE<br/>Field reports"]
    Enrich["2. ENRICH<br/>Customer + ACV"]
    Escalate["3. ESCALATE<br/>Package for PM"]
    Track["4. TRACK<br/>Status updates"]
    Close["5. CLOSE<br/>Resolved"]
    
    Capture --> Enrich --> Escalate --> Track --> Close

Top 3 Deal Blockers:

1. No public URLs without login → External apps blocked
2. No firewall / ingress-egress → FSI/HLS compliance blocked
3. Vertical scaling only → High-traffic apps blocked

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PARTITION: EXECUTION

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Slide 8: 3-6-12 Action Plan Overview

So What: Phased approach with decision points—prove before scaling.

gantt
    title 12-Month Adoption Roadmap
    dateFormat  YYYY-MM
    axisFormat  %b

    section Phase 1: Prove It
    Lighthouse + Council      :p1a, 2026-01, 4w
    Enablement sprint         :p1b, 2026-02, 6w
    Strategic wins            :milestone, p1m, 2026-03, 1d

    section Phase 2: Scale It
    Attach tracking           :p2a, 2026-04, 4w
    Playbook v1               :p2b, 2026-04, 8w
    Attach improvement        :milestone, p2m, 2026-06, 1d

    section Phase 3: Expand It
    SI pilot + Coverage       :p3a, 2026-07, 20w
    Full coverage             :milestone, p3m, 2026-12, 1d

Slide 9: Phase 1 - Prove It (M1-3)

So What: Land 3-5 strategic wins to prove Apps can drive platform adoption.

M3 Decision (HOW to Win?):

• ✅ If FE confidence +20%: Scale enablement
• ❌ If no improvement: Investigate product blockers

Slide 10: Phase 2 - Scale It (M4-6)

So What: Build attach tracking and scale proven playbooks.

M6 Decision (WHY + WHERE):

• ✅ If attach rate positive & 80% fit archetypes: Scale playbooks
• ❌ If no attach signal: Reposition as standalone

Slide 11: Phase 3 - Expand It (M7-12)

So What: Drive coverage to 50+ accounts with SI leverage.

M9 Decision (WHY + HOW):

• ✅ If competitive win rate improving & SI time-to-value ≤ internal: Scale SI globally
• ❌ If SI underperforms: Build internal FDE capacity

Slide 12: Operating Cadence

So What: Structured rhythm ensures nothing falls through the cracks.

Top 3 Risks + Mitigations:

1. Lighthouse don’t convert → Diversify pipeline, lower bar
2. Enablement not adopted → Exec mandate, measure application
3. Product gaps block wins → Position for right use cases

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PARTITION: CLOSE

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Slide 13: The Ask

So What: Clear asks to enable success.

Success = Phase gates hit:

• P1: 3+ wins, exec sponsorship, enablement delivered
• P2: Attach tracking live, playbooks adopted
• P3: 50+ accounts, SI motion started

Appendix: Timing Summary

Last Updated: January 2026