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02 — Build the engine

Rebuild the finance function so it can run without heroes.

Modernize the operating model and the systems that carry it — process, ERP, EPM, data, automation, and AI. We work at every layer, from selection through go-live and steady state. We build; we don't just recommend.

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The problem

Effort scales with revenue when the engine is manual.

Every doubling of revenue means twice the workload — because the process is fundamentally manual. Growing companies hire analysts to fill in for architecture. That works until it doesn't.

Outgrown QuickBooks or Sage, stuck on a hard migration

QuickBooks and Sage carried you through the early years. Now consolidations, multi-entity accounting, real-time reporting, and audit demands are past what they can serve — but the migration to a modern ERP feels like a year of risk.

Data lives in silos

Sales in Salesforce, financial data in the ERP, ops data in five other tools. No one system tells the whole story, and stitching the answer together takes days.

Automation started, never finished

You bought a bot license or workflow tool. It automated three processes and stalled — because no one owned the roadmap or the data cleanup that would have made the fourth work.

AI in the pitch, not in the workflow

Every finance vendor's demo talks about AI. Almost none of it is deployed in your close, forecast, or reconciliations — because turning demo-AI into workflow-AI is real engineering.

What we do — operating model

The rebuild starts with the design that makes everything else possible.

Systems don't fix a broken operating model. We start with process, role, organization, and data — then bring the systems to match.

A

Operating Model & Process Redesign

Rebuild the target-state finance function from the ground up — what each role owns, how work flows, where the handoffs happen.

  • Target-state operating model and org design
  • End-to-end process maps (record-to-report, procure-to-pay, order-to-cash)
  • RACI and control framework
  • Change management and rollout plan
B

Data Governance & Master Data Management

Fix the foundation your ERP, reporting, and AI depend on — vendor master, customer master, chart of accounts, item master. The discipline that lets every downstream system tell the truth.

  • Master data assessment across vendor, customer, GL, and item domains
  • Data stewardship model, ownership, and approval workflows
  • Standards, taxonomies, and quality controls
  • Duplicate cleanup, retirement, and ongoing hygiene cadence
C

BPM & Shared Services / GCC

Design and stand up (or fix) a shared services or Global Capability Center function that delivers savings without dropping quality.

  • Process assessment and business case
  • Location, legal structure, and workforce design
  • Migration playbook and knowledge transfer
  • Steady-state SLAs and quality controls
What we do — technology stack

Four layers of the finance technology stack.

We work across all four. Most engagements start at one layer and expand as the foundation gets solid.

L1

Systems & Data Foundation

The foundation. ERP, FP&A/EPM, master data, and the data warehouse that connects them. Get this right and every layer above it works.

  • ERP selection, implementation, and migration — SAP (S/4HANA, ECC), Oracle (Cloud ERP, Fusion, NetSuite), Microsoft D365
  • Legacy-to-cloud ERP migrations and platform consolidations post-M&A
  • QuickBooks & Sage migrations to NetSuite, D365, or larger enterprise ERPs
  • EPM / FP&A platform build (Anaplan, Pigment, Vena, Workday Adaptive)
  • Master data management tools and data quality platforms
  • Finance data warehouse, integration architecture, and single source of truth
  • Chart-of-accounts and finance data model redesign
L2

Automation

Where the FTE savings and speed gains actually come from — RPA, workflow, and rule-based automation woven into the close, P2P, and R2R cycles.

  • Intelligent close and reconciliation automation
  • P2P and O2C workflow automation
  • Journal entry, accrual, and consolidation automation
  • Controls that run themselves
L3

Intelligence & AI

Done right, transformative — driver-based forecasts, anomaly detection, AI copilots for close and reporting.

  • Forecast copilots and driver-based planning
  • Anomaly and variance detection
  • Document intel: extract from contracts, invoices, statements
  • Natural-language Q&A over the finance data layer
L4

Finance Analytics & BI

Real-time dashboards, board and investor reporting, self-service analytics — the layer leadership actually uses.

  • Executive and board dashboards
  • Real-time KPI reporting
  • Self-service analytics for business partners (Power BI, Tableau, Looker)
  • Investor-facing reporting packs
How we deliver

Diagnostic, build, and ownership through steady state.

Engagements run in three phases. The first is fast. The last one lasts as long as it takes for the new cadence to hold.

Weeks 1–4

Diagnostic & target state

Read the current state — process, systems, data. Design the target operating model, technology stack, and roadmap. Get leadership aligned.

Months 1–9

Build & migrate

Redesign core processes, stand up new systems, migrate data and work, integrate automation and AI, and manage change. The heavy lift.

Months 6–12

Steady state

Stabilize the new function, tune the metrics, close remaining gaps, hand back to your leadership with the cadence holding.

How we engage

Common engagement shapes.

Transformation work rarely fits one shape. It depends on where you're starting, what needs rebuilding, and how much of the stack you're touching. These are the shapes we run into most.

Scoped rebuild

Function-level transformation

A single, well-bounded rebuild — the close, the reporting cadence, FP&A, or a specific process — designed, executed, and handed back with the new operating rhythm holding.

Best fit when one part of finance is clearly the constraint and leadership wants results this quarter, not next year.

Cadence
Focused project
Typical length
3–6 months
Team side
Small joint team
Exits when
New process in steady state
Foundation

ERP implementation or migration

Selection through go-live for a modern ERP — SAP (S/4HANA, ECC), Oracle (Cloud ERP, Fusion, NetSuite), or Microsoft D365 — or migration off a legacy platform (QuickBooks, Sage, SAP ECC, Oracle EBS) to a modern cloud ERP. Also covers FP&A/EPM platforms (Anaplan, Pigment, Vena, Workday Adaptive).

Best fit when the current platform can't be extended anymore, or when M&A/carve-outs have left multiple systems that need to consolidate.

Cadence
Program leadership
Typical length
6–12 months
Team side
Joint with implementation partners
Exits when
Steady state post go-live
Automation & intelligence

Close automation, AI & analytics deployment

Targeted automation for the close cycle, reconciliations, or a broken P2P/O2C flow — using your existing ERP plus a chosen automation layer, no platform replacement required. Or the next step up: production-grade AI for forecasting, anomaly detection, or document intelligence.

Best fit when the foundation is stable and the next leverage is speed of insight and reduced manual analyst work.

Cadence
Focused project
Typical length
2–6 months
Team side
Small technical build team
Exits when
Automations / models in production
End-to-end

Full finance transformation

The full rebuild — target operating model, systems, data, organization, automation, and AI — sequenced across nine to fifteen months. Diagnostic first, then build, then a Hold phase where we stay through the change until the new cadence sticks.

Best fit when the finance function is fundamentally the wrong shape for the business and incremental fixes have stopped working.

Cadence
Program leadership
Typical length
9–15 months
Team side
Cross-functional program
Exits when
New model runs without us
Common questions

Common questions about Transformation & Technology.

Which ERP or EPM should we choose? +

That depends on your industry, revenue, entity structure, and complexity. Many of the companies we work with are on QuickBooks or Sage today and need to move up — usually to NetSuite or D365 in the mid-market band, sometimes directly to SAP S/4HANA or Oracle Cloud ERP if the business is larger. We work across the modern ERP landscape (SAP S/4HANA and ECC, Oracle Cloud ERP and Fusion, Oracle NetSuite, Microsoft D365) and the major EPM platforms (Anaplan, Pigment, Vena, Workday Adaptive). The right answer is about your data, your process, and your team's technical comfort — not about which platform has the best marketing.

Do you handle ERP migrations, or only fresh implementations? +

Both. A large share of the mid-market work we scope is migration, not greenfield — moving off an aging SAP ECC to S/4HANA, consolidating ERPs after M&A, upgrading from Oracle EBS to Fusion or NetSuite, or moving from QuickBooks/Sage to a modern cloud ERP. Migration is its own discipline: data cleanup, cutover planning, parallel testing, and change management sit at the center.

How much of the AI hype is real? +

In finance, a lot of it now. Two years ago most vendor AI was demo-only. Today, workflow AI for close, reconciliation, document extraction, and forecasting is production-ready — with real engineering to make it work in your environment. We can walk through what's ready today and what isn't.

Can you just handle a piece — like close automation — without a full rebuild? +

Absolutely. Most engagements start at one layer. Close automation, a reporting rebuild, or an FP&A platform can all be scoped as standalone projects. We only recommend deeper work when there's a real payback.

How do you handle change management? +

Every technology project succeeds or fails on adoption. We plan change management into every engagement — user training, adoption metrics, and a hypercare period where our team stays close after launch. The system nobody uses is the same as no system.

Ready?

Tell us where you're headed. We'll steer the finance.

A 30-minute call to pressure-test where you are and where the gaps are — no deck, no obligation.