Services
Surgical sprints. Compounding retainers.
Every engagement is fixed-scope, fixed-price, and produces a root cause finding your team didn't have before. Start with a sprint. Stay for the architecture.
Bowtie Diagnostic Sprint_
Expose the exact point in your revenue system where growth is leaking — with systems dynamics math, not opinion.
Most SaaS revenue leaders diagnose funnel performance using stage-level conversion rates — a static, flow-only view that masks the structural root cause. This sprint builds the stock-and-flow model of your actual revenue system, identifies the dominant feedback loop, and locates the highest-leverage intervention point.
What you get
- Pre-engagement data intake: CRM export, revenue waterfall, cohort NRR data
- Bowtie mapping session (3 hours) with GTM leadership team
- Systems dynamics model: stock-and-flow diagram parameterized with your conversion rates, ACV, expansion velocity, and churn
- Sensitivity analysis: the 2–3 variables with highest leverage on ARR trajectory
- Capability Trap assessment: where heroics mask structural design failures
- Written diagnostic report (15–20 pages) with intervention map
- Live readout session (2 hours) with revenue leadership
Frameworks: Winning by Design Bowtie, Systems Dynamics, Dynamic Work Design, SPICED
Ideal for: CRO, VP Revenue, or CEO at a $10M–$50M ARR company where pipeline looks healthy but NRR is flat, expansion isn't compounding, or forecast accuracy is below 75%.
Capability Trap Audit_
Find where your revenue team is working harder to stay in place — and design the escape route before AI makes the trap permanent.
The Capability Trap (Repenning, 2001) predicts why revenue organizations fail to improve despite increased investment. This audit maps the specific trap mechanisms inside your revenue motion: where firefighting has displaced process design, where heroic individual performance masks systemic failure, and where AI investment is being applied to a process that shouldn't exist.
What you get
- Structured intake interviews (4–6 people): reps, managers, RevOps, enablement
- Process archaeology: current playbooks, stage definitions, CRM workflows
- DWD work design analysis: work that works vs. work about work vs. work that doesn't work
- Trap mechanism identification and compounding effects
- AI readiness assessment: automate now vs. redesign first vs. don't automate
- Priority matrix with leverage scores
- Written audit report (10–15 pages) + 90-minute debrief
Frameworks: Dynamic Work Design, Systems Dynamics, AI Readiness Framework
Ideal for: VP Sales, CRO, or RevOps leader at a $15M–$75M ARR company that has added headcount, tools, or process layers without corresponding improvement.
Dynamic Work Redesign Sprint_
Redesign the two or three revenue processes that are costing you the most — with enough precision that the fix holds without heroics.
Dynamic Work Design (Repenning) redesigns work at the level of individual tasks — cognitive demands, information requirements, and feedback loop design. This sprint applies DWD to 2–3 revenue processes, produces task-level redesigns, and builds the measurement system to detect whether the new design is being executed.
What you get
- Process selection workshop (2 hours): prioritization by leverage and feasibility
- Current-state work mapping using DWD notation
- Root cause analysis per process
- Future-state work design with cognitive demand reduction and embedded feedback loops
- Implementation runbooks for each redesigned process
- Change adoption framework: leading indicators, 30/60/90 checkpoints, manager coaching cues
Frameworks: Dynamic Work Design, Systems Dynamics, SPICED
Ideal for: RevOps or Enablement leader at a $20M–$80M ARR company with clear evidence of broken process and authority to implement changes.
NRR Acceleration Build_
Engineer the post-sale revenue motion from first contract through expansion — so NRR compounds instead of decaying.
NRR below 115% in a SaaS business with healthy GRR is almost always a post-sale motion design failure. The right side of the Bowtie — Adopt, Expand, Advocate — is typically undefined, unmeasured, and unmanaged as a system. This engagement builds the complete post-sale revenue architecture.
What you get
- Post-sale Bowtie mapping with explicit Adopt/Expand/Advocate stage definitions
- SPICED post-sale adaptation for expansion conversations
- Handoff architecture: AE to CSM protocol with data transfer and cadence design
- Expansion trigger library: 8–12 signals with response protocols
- NRR systems dynamics model: current vs. redesigned motion at 6 and 12 months
- CS playbook for commercial motion (not account management)
- Measurement framework with NRR leading indicators and cohort tracking
Frameworks: Winning by Design Bowtie (right-side), SPICED, Systems Dynamics, DWD
Ideal for: CRO or VP CS at a $15M–$60M ARR company where GRR is above 85% but NRR is below 110%.
RevOps Intelligence Layer_
Build the data architecture and agentic infrastructure your revenue system needs to run on signal, not spreadsheets.
Revenue intelligence failures are architecture failures, not tool failures. This engagement designs and builds the underlying infrastructure: CRM schema aligned to Bowtie stages, automated data validation via MCP-connected agents, and a live reporting layer that surfaces metrics without manual prep.
What you get
- CRM audit: schema review against Bowtie stage definitions, data quality scoring
- Schema redesign specification aligned to Bowtie stages and SPICED
- MCP server configuration: 1–2 Claude MCP servers connected to CRM
- Agentic reporting: automated Bowtie stage reporting, expansion signal alerts, NRR cohort reports
- Claude Skills library: 3–5 custom skills for the revenue team
- Data governance spec: ownership model, hygiene SLAs, admin runbook
- Handoff + training: 2-hour live walkthrough with RevOps team
Frameworks: Winning by Design Bowtie, Claude Code + MCP, Claude Skills, Systems Dynamics
Ideal for: RevOps leader or CTO at a $20M–$100M ARR company spending 30%+ of capacity on data reconciliation.
ICP Sharpening Session_
Rebuild your Ideal Customer Profile from revenue data — so every growth motion is aimed at the customers who actually compound.
Most ICP definitions are built from founder intuition and early logos, never rebuilt from data. This session rebuilds ICP from three sources: revenue cohort analysis, systems dynamics LTV modeling, and SPICED retrospective analysis. The output is an operationalized ICP — not a persona card, but a qualification instrument.
What you get
- Revenue cohort analysis: segmentation by NRR, ACV, ramp time, expansion velocity, churn
- SPICED retrospective: won/lost analysis through qualification lens
- Systems dynamics ICP model: LTV trajectory by segment with sensitivity analysis
- ICP definition: 3–5 tiers with firmographic, technographic, and behavioral criteria
- Qualification upgrade: SPICED-aligned criteria and disqualification triggers
- Operationalization: CRM scoring logic, SDR/AE qualification card, marketing brief
Frameworks: SPICED, Systems Dynamics, Winning by Design Bowtie
Ideal for: CMO or CRO at a $10M–$50M ARR company where pipeline volume is healthy but quality is inconsistent.
AI GTM Readiness Assessment_
Determine exactly which AI investments will compound your revenue system — and which ones will automate the wrong motion.
AI GTM investment decisions are being made with two failure modes: tool-first selection (buying from vendor demos) and initiative-first (launching AI transformation without process diagnostic). This assessment scores every GTM process on three dimensions: process quality, data availability, and ARR leverage.
What you get
- GTM process inventory: structured audit of every recurring revenue process
- AI leverage scoring: process quality × data availability × ARR impact
- Capability trap risk assessment per process
- Vendor evaluation matrix (if active proposals exist)
- Investment sequencing: automate now vs. redesign first vs. don't automate
- Executive briefing document (8–12 pages), board-ready
Frameworks: Dynamic Work Design, Systems Dynamics, Bowtie, Claude Code / MCP
Ideal for: CRO or CEO at a $15M–$80M ARR company being pressured to adopt AI without a framework to evaluate proposals.
Forecast Architecture Sprint_
Build a revenue forecast derived from your Bowtie system dynamics — not from rep optimism and stage probability defaults.
Stage-weighted pipeline forecasts are structurally incapable of accuracy above a certain threshold because they model revenue as static. This sprint replaces stage-weighting with a systems dynamics forecast model parameterized from your actual data — producing probabilistic forecasts with confidence intervals.
What you get
- Historical data analysis: 8–12 quarters of pipeline, conversion, and velocity data by segment
- Systems dynamics forecast model: P50, P75, P90 quarterly and annual forecasts
- Forecast process redesign with leading indicator inputs
- CRM forecast field specifications and calculation logic
- Manager coaching protocol for new methodology
- CFO/board reporting template aligned to model outputs
- 2x working sessions for model calibration with revenue leadership
Frameworks: Systems Dynamics, Winning by Design Bowtie, ICP Sharpening
Ideal for: CRO or CFO at a $20M–$80M ARR company where forecast accuracy is below 85%.
Retainers
Revenue Architecture Retainers
After the diagnostic, the system compounds. Ongoing Bowtie monitoring, systems dynamics model maintenance, AI infrastructure builds, and strategic advisory — four tiers scaled to your complexity.
Signal_
$10M–$30M ARR$8,500/mo
3 months minimum
Monthly Bowtie diagnostics, systems dynamics monitoring, and strategic guidance for revenue leaders who need a thinking partner grounded in math. Typical clients identify 1-2 high-leverage interventions per quarter that the retainer investment pays for within 30 days.
- Monthly Bowtie health report with systems dynamics interpretation
- Single highest-leverage intervention identified each month
- 1–2 page strategic advisory memo per month
- 2x 60-minute live sessions per month
- Unlimited async Q&A (24-hour SLA)
- Up to 4 hours/month AI infrastructure maintenance
Standard_
$25M–$60M ARR$16,500/mo
4 months minimum
Ongoing revenue architecture optimization: Bowtie monitoring, process redesign execution, and agentic infrastructure that compounds month over month. Clients typically recover 3-5x the monthly retainer in addressable revenue within the first quarter of optimization.
- Weekly automated Bowtie reporting + monthly written interpretation
- One DWD process redesign per quarter
- One Claude Skills build or MCP enhancement per month
- Monthly forecast model recalibration
- 4x 60-minute live sessions per month
- Up to 12 hours/month AI infrastructure work
Scale_
$50M–$100M ARR$28,500/mo
6 months minimum
Full-stack revenue architecture for companies scaling through complexity: multi-segment Bowtie management, accelerated AI infrastructure, and systems-based decision-making. Designed for the complexity level where a single missed leverage point costs more per month than the retainer.
- Segment-level Bowtie health reports (weekly, automated)
- Two DWD process redesigns per month
- 6–10 Claude Skills across AE, CSM, RevOps, and management
- Up to 3 MCP servers deployed and maintained
- 6x 60-minute live sessions per month
- Up to 30 hours/month AI infrastructure work
Enterprise_
$75M–$200M ARR$45K–$65K/mo
6 months minimum
Embedded revenue architecture: dynamic.work_ operates as the intelligence and design layer inside the client's GTM org. For organizations where revenue system architecture failure is measured in millions per quarter.
- Complete revenue system audit and systems dynamics model (Month 1)
- Parallel DWD process redesigns (3–4 concurrent)
- Full MCP server suite + unlimited Claude Skills
- Agentic process automation: up to 5 autonomous processes by month 6
- Unlimited live sessions + dedicated Slack channel
- Dedicated team: primary architect + infrastructure specialist
How Engagements Unfold
Start with a sprint. Stay for the architecture.
Diagnostic Sprint (8-15 days)
Start with a Bowtie Diagnostic, Capability Trap Audit, or AI Readiness Assessment. You get a parameterized model and a root cause finding. Most clients know their next step within 48 hours of the readout.
Build Sprint (10-15 days)
Based on the diagnostic finding, run a targeted build: process redesign, NRR architecture, RevOps intelligence layer, or forecast model. Fixed scope, fixed price, clear deliverable.
Retainer (ongoing)
The system compounds. Monthly Bowtie monitoring, systems dynamics model maintenance, AI infrastructure builds, and strategic advisory. The diagnostic creates the trust. The build creates the dependency. The retainer captures the compounding value.
Typical timeline from first sprint to retainer: 6-12 weeks. Total investment before retainer: $30K-$55K.
Not sure which sprint fits?
Tell us the symptom. We'll tell you if it's structural — and which engagement is the right starting point.