Value Creation Diagnostic
Data & KPI Visibility

Turn fragmented systems into trusted operating visibility.

We help PE-backed companies connect their source systems and define the KPIs that matter. Then we build the reporting layer management and sponsors can actually run on.

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The operating reality

When the reports disagree, the plan can't be managed

PE value creation execution depends on trusted operating visibility. If the board report says one thing and the management dashboard another, nobody can manage the plan with confidence. It gets worse when the source systems and the spreadsheet rollups add their own numbers.

  • Board reports lag operating reality. Monthly close-driven reporting hides what changed last week. The plan is current; the data behind it is not.
  • Systems disagree on the same number. Finance keeps its own version of revenue and margin. Operations and sales keep theirs, and sponsor reporting keeps another. Pipeline gets counted a different way in each.
  • KPI definitions drift over time. Bookings and gross margin mean different things to different teams. Utilization and contribution shift by period and by entity, and nobody announces the change.
  • Spreadsheets replace the dashboard. Operators stop trusting dashboards and rebuild a parallel reporting layer in spreadsheets every cycle.
  • Add-on integration makes it worse. New acquisitions multiply the source systems and fragment the chart of accounts. Consolidated visibility arrives later with each one.

What we build

The reporting layer behind PE operating visibility

A data and KPI visibility layer sized for a portfolio company. It runs from source integration and KPI definitions to dashboards and exception reporting, on the operating cadence sponsors and management use.

  • CDC & source-system integration

    Near-real-time change data capture from ERP, CRM, billing, operations and portfolio-company line-of-business systems into a governed analytics foundation.

  • Data lake & warehouse foundations

    Analytics-ready storage and modeling layers tuned to portfolio-company scale, with enough engineering for the reporting load and no more.

  • KPI semantic layer & definition governance

    A single documented definition for every KPI sponsors and management run on. Each definition has an owner and a version history, and every team can audit it.

  • Operational dashboards & board views

    Operating dashboards for management and board-cycle visibility for sponsors, drawn from one trusted reporting layer.

  • Exception reporting & data quality

    Reconciliation and data-quality checks, with exception alerts and freshness signals on top. Together they catch breakage before the board cycle does.

  • Reporting automation tied to operating cadence

    Weekly and monthly reporting automated against the same trusted layer as the board-cycle pack, sized to how the business actually runs.

Why PE cares

Visibility decides whether a plan is run or only reported

With trusted KPIs, management can run the plan week to week. Without them, it can only explain results after the quarter closes.

Value creation progress visibility
Sponsors and operating partners see workstream progress between board cycles instead of waiting for quarter-end.
Faster operating decisions
Management makes pricing and staffing decisions on current data instead of stale rollups. Integration and cost-take-out calls work from the same data.
QofE & diligence readiness
Trusted definitions and reconciled source data reduce diligence friction in a refinancing or recapitalization, and again at exit.
Add-on integration visibility
Consolidate reporting across roll-up acquisitions on one operating cadence instead of one-off bolt-on dashboards.
Exit readiness & management credibility
A reporting layer the buyer can read—and that management can defend—shortens the path from LOI to close.

Implementation path

Six stages from fragmented sources to a trusted reporting cadence

  1. Source-System Inventory

    Map the systems that already hold the data the plan depends on. That means ERP and CRM along with billing and operations. HR and add-on systems belong on the map too.

    Outcome

    A short, decision-ready inventory of where the operating truth currently lives—and where it disagrees.

  2. Critical KPI Definition

    Lock the KPIs that sponsors and management will actually run on. Each one gets a definition and an owner in one place, with its source and cadence recorded beside it.

    Outcome

    A KPI definition layer the board and the operators sign off on with finance, before the build starts.

  3. CDC & Integration Setup

    Stand up the integration layer between source systems and the analytics foundation, prioritized to the KPIs that matter most.

    Outcome

    Trusted, near-real-time data movement into the analytics layer—without re-platforming the operating systems.

  4. Data Quality & Reconciliation

    Reconcile source systems to the analytics layer and add data-quality checks. Exceptions surface before reports go out.

    Outcome

    A reporting layer management trusts—and stops bypassing with parallel spreadsheets.

  5. Dashboard & Reporting Build

    Operational dashboards for management and board-cycle views for sponsors. The operators on point get exception reporting.

    Outcome

    One trusted reporting layer feeding management and sponsors on the board cadence, with no duplicate sources.

  6. Operating Cadence & Support

    Embed the reporting layer into the weekly and monthly operating reviews and the board cycle, with ongoing data-engineering support.

    Outcome

    A reporting cadence the sponsor expects, sized to how the company actually operates.

Where it fits

The services that depend on trusted KPIs

Data and KPI visibility sits between sponsor pressure and operating execution. AI automation builds on it. So do transaction services and modernization.

  • AI Workflow Automation

    Trusted data is the precondition for AI in the loop. Automation built on broken data is rework waiting to happen.

  • Technology Diligence

    Diligence findings on data and integration become the data workstreams the operating plan depends on. Reporting findings do too.

  • Legacy Workflow Modernization

    Many reporting gaps trace back to fragile legacy workflows. Modernization and data capture often need to move together.

  • Cloud & Data Foundations

    Cost-tuned cloud and data architecture that supports the KPI visibility layer without over-engineering the stack.

  • CDC & Data Lake Integration

    The technical layer behind KPI visibility. Change data capture and ingestion pull from fragmented portfolio-company systems, and reconciliation checks the result.

  • Decision Engines & Optimization

    Once KPIs are trusted, decision engines turn them into repeatable pricing, staffing, routing, procurement, cost-to-serve and prioritization decisions.

Bring the KPI gap, and we will name the first reporting workstream worth executing

We strengthen sponsor and management-team execution capacity. We do not replace the judgment of management, the sponsor, or the operating partner.

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