Private Equity / Portfolio Operations practice

One proven workflow. Repeated across the portfolio. Measured in every company.

Operating teams need value creation they can measure, and portfolio companies carry the same back-office friction in different systems. We prove a workflow in one company, turn it into a playbook with its controls and measures, and repeat it across the portfolio.

Built for: Operating Partner · Head of Portfolio Operations · PortCo CEO · PortCo COO · PortCo CFO

Assess a Workflow Book an AI Operating Leverage Audit call

The operating reality

Hold periods are longer, multiple expansion cannot be counted on, and value creation has to come from operations. Most portfolio companies run finance, AP and AR and customer operations with the same manual patterns, each on its own ERP, CRM and spreadsheets, and portfolio reporting depends on someone collecting it all by hand.

Most boards now ask about AI, and most portfolio companies have started something on their own. The question is which workflows are worth doing, how to do them once and repeat them, and how the operating partner will see the effect on cost, cash and capacity in each company.

Workflows

Where the leverage hides

For each workflow: how it runs today, what agents and plain automation take over, and where people keep the judgment.

Portfolio KPI reporting

Today: Portfolio company finance teams fill in templates from their own systems each month, and the operating team chases, checks and reformats them.
Agents and automation: Agents pull agreed KPIs from each company’s systems, check them against definitions and prior periods, and flag gaps and outliers before anyone reads them.
People keep: Company CFOs own their numbers. The operating team decides what the variances mean.

Measured by: Days from month end to portfolio pack · KPI submissions returned for correction · Hours spent collecting data

Cross-company AI opportunity assessment

Today: Each portfolio company runs its own AI experiments, and nobody can compare which workflows paid back or why.
Agents and automation: We baseline the same workflow families in each company with a common method, so cost per outcome and readiness can be compared across the portfolio.
People keep: The operating partner and company leaders decide where to invest and in what order.

Measured by: Workflows baselined per company · Time from assessment to first deployment · Opportunities with a measured baseline

Shared-services workflows: AP, AR and finance operations

Today: AP clerks key invoices, AR teams chase payments and controllers reconcile by hand, slightly differently in every company.
Agents and automation: Agents extract and match invoices, prepare collection follow-ups and propose reconciliations within each company’s approval rules.
People keep: Company finance approves payments, credit decisions, write-offs and journals.

Measured by: Cost per invoice processed · Days sales outstanding · Days to close

Customer operations

Today: Support and order teams answer routine requests by checking several systems and writing each reply by hand.
Agents and automation: Agents classify requests, answer routine ones from live system data and prepare the rest with context for the team.
People keep: Customer teams own escalations, commercial decisions and key accounts.

Measured by: Cost per ticket or order handled · First-response time · Requests resolved without a person

Operating dashboards

Today: Each company builds its own dashboards from exports and spreadsheets, so the same metric means different things in different places.
Agents and automation: Integrations feed agreed definitions into the data warehouse, and agents flag data quality issues and summarize what changed.
People keep: Management teams own the targets and act on what the dashboards show.

Measured by: Metrics on shared definitions · Hours spent building reports by hand · Data quality issues open

Operational and AI-readiness diligence

Today: Deal teams review operations and technology from data room documents and management calls under deadline, with little time to test claims.
Agents and automation: Agents index the data room, map documents to the diligence request list and summarize process, system and AI-readiness evidence with sources.
People keep: The deal team and operating partner judge what the evidence means. Investment decisions stay with the investment committee.

Measured by: Time to first draft of operational findings · Request list items mapped to evidence · Open questions found before management meetings

Repeatable workflow playbooks

Today: A workflow that works in one company stays there, because nobody has written down how it was built, controlled and measured.
Agents and automation: We package each proven workflow with its design, controls, measures and system patterns, so it can be adapted to the next company’s systems.
People keep: The operating team chooses where each playbook goes next. Company management owns the rollout.

Measured by: Companies running each playbook · Time to deploy in the next company · Measured result per company

What we measure

Every workflow gets a baseline before anything changes.

Cost per outcome by company
Days from month end to portfolio pack
Time to deploy a playbook in a new company
Finance and customer operations hours recovered
Working capital measures such as DSO

Risks and controls

Risks and the controls that address them
Risk	Control
Agent output reaches a board or LPs without review.	Agents prepare and flag. Anything for a board, lender or LP is reviewed and approved by a named person in the company or the fund.
Data from one portfolio company reaches another.	Each deployment runs in its own company’s environment with its own access. Playbooks carry designs, never data.
A playbook fails because the next company’s systems or process differ.	Each rollout starts with a baseline and a fit check, and the workflow goes live in stages with fallback to the manual process.
The fund pushes a change that management does not own.	Company leaders approve each deployment and own its results, so accountability stays with management.

How we would approach it

An example workflow design

This is illustrative. It shows how responsibilities split between systems, automation, agents and people. It is not a client result.

Portfolio KPI reporting pipeline

Trigger: A month or quarter closes in a portfolio company.

Reference architecture

An illustrative design showing how we would approach the workflow. Not a client result.

1SystemEach company’s ERP, CRM and data warehouse hold the period data.
2AutomationIntegrations extract the agreed KPIs and map them to shared definitions.
3AgentChecks each figure against definitions and prior periods, flags gaps and outliers, and drafts variance commentary.
4HumanThe company CFO reviews, corrects and approves the submission.
5AgentAssembles the portfolio pack and highlights the companies that need a conversation.
6HumanThe operating team reviews the pack. Anything for a board or LPs is approved before it goes out.
7SystemPortfolio monitoring is updated and each step is logged for measurement.

Controls

Each company’s data stays in its own environment and access
Company CFO approval before any figure leaves the company
Outliers and missing data route to a person
Full log of extraction, check, approval and release

What we would measure

Days from period end to portfolio pack
Submissions returned for correction
Hours spent collecting and checking data
Companies reporting on shared definitions

Related use cases

Assess a PE / Portfolio Ops workflow

Bring us one workflow that is slow, repetitive, error-prone or expensive. We'll help determine whether AI is actually the right lever.