How Automation in Portfolio Companies Boosts EBITDA—Examples with Impact

Operational excellence has become one of the strongest differentiators in value creation in private equity. Leading PE-owned companies skillfully leverage automation and technology to directly boost EBITDA. Either by lowering costs, accelerating revenue, scaling operations, or unlocking cash, they shift a company’s financial profile faster than most traditional initiatives. Yet for many companies it’s still challenging to figure out where and how to focus efforts so the impact shows up in the P&L. Without a clear framework, automation projects risk becoming misaligned with value-creation priorities. In this post, we show real examples of projects delivered to PE-backed companies. These automations helped release working capital, reduced manual hours, and ultimately lifted EBITDA.

Four automations driving EBITDA growth across portcos

$55,000 annual savings and full tax compliance with automated document matching For many European manufacturing companies, value-added tax (VAT) recovery requires every sales invoice to have a corresponding Proof of Delivery (POD). In practice, this means that missing CMRs or Bills of Lading can delay payments, freeze working capital, and even put VAT claims at risk. Yet despite the financial stakes, most companies still manage this process manually. Traditionally, the workflow looks like this:

1. Logistics teams deliver goods, collect signed PODs, and later bring documents back to headquarters (manual process handling physical documents).
2. Finance teams manually verify each invoice against its corresponding delivery document.
3. Teams chase each other for missing information, leading to errors, delays in VAT retrieval.
4. In the worst cases, tax authorities can reject claims altogether.

The consequences pile up quickly—frozen capital, blocked payments, lost documents, clunky archiving, slow reporting cycles, and dozens of hours spent on scanning and data entry each month.

To fix this, we deployed a combined OCR + RPA automation that replaces the manual back-and-forth with a digital flow. Here’s how it works now:

1. The delivery staff simply scans the POD on the spot.
2. OCR extracts key information directly from the document.
3. An RPA bot matches the POD with the invoice number inside the ERP system.
4. A complete, audit-ready report is generated automatically.
5. Finance teams access a dashboard showing document status, exceptions, and upcoming tax recovery deadlines.

The impact has been immediate:

• 90% reduction in process time—monthly workload dropped from 83 hours to just 8.
• $55,000 saved per year, thanks to reduced manual effort and fewer errors.
• Faster tax retrieval—with complete documentation and automated reporting, no issues have been raised by tax authorities.

$4.1-5.2 million in required working capital released across the group

Late payments can drain an organization’s liquidity. When capital is tied up in overdue invoices, companies struggle to fund innovation, delay strategic projects, and place unnecessary strain on finance teams who spend hours manually chasing payments. There is also an increased risk of writeoffs and financial costs related to factoring. For one of our portfolio clients, overdue invoices in one market averaged $1.2 million, yet there was no single owner for the reminder process. The workflow depended on manual effort and looked as follows:

1. A finance specialist pulls unpaid invoices from the ERP system.
2. Each customer receives a manually written reminder email.
3. Aging reports (30/60/90 days) are generated irregularly.

Hours were lost on repetitive emailing, reporting was inconsistent, and the team lacked real-time visibility into upcoming risks. The process lacked structure, resulting in inconsistent efforts to collect payments on time. As a consequence, DSO, average days to be paid, and past-due balances were significantly off—and at risk of increasing year over year. The absence of a defined process also made it impossible to monitor payment terms and credit risk effectively. As a result, clients with longer payment delays often received the most favorable terms and were inadvertently extended credit for entire quarters.

To fix this, GGS team introduced an RPA agent that fully automated the end-to-end collections process:

• The bot pulls all unpaid invoices directly from the ERP system.
• It generates personalized reminders and sends a structured sequence of emails on behalf of the finance team.
• It continuously collects real-time data, updating dashboards and giving leadership immediate insight into exposure, DSO, and overdue customers.

This was a case of automation paying for itself from day one. Collections improved immediately after launch, and overdue receivables dropped consistently. Designed to scale, the agent has now been deployed in 11 markets, streamlining processes across the entire group and unlocking $4.1–5.2 million in working capital through faster collections. Results across the portfolio:

• $0.7 million released with the first bot
• 68% reduction in overdue receivables
• 60% faster receivables collection
• 11 markets live, ready to scale further
• $4.1–5.2 million in required working capital released

13,400 hours saved each year by reducing manual work

In many manufacturing companies, the order-to-shipment process is still manual. After a customer places an order, someone has to enter the data into the system, confirm the order, monitor production dates, update shipment status, notify the customer, and finally send the invoice. Each step takes time—and when thousands of orders are processed every month, the cumulative workload becomes enormous. For one of our clients, 76,000 orders were being handled manually every year. A team of 30 people was responsible for checking production dates, updating the ERP system, verifying which orders were ready for shipment, and sending individual emails to customers. This daily flow of manual tasks consumed thousands of hours and created unnecessary delays.

To solve this, we introduced two dedicated automation bots, each focused on a different part of the workflow. Bot 1 — Production date notifications

• Logs into the ERP system
• Selects all orders with assigned production dates
• Prepares and sends automated confirmation emails to clients
• Flags orders without production dates to the Customer Service team

Result: 5,400 hours saved annually. Bot 2 — Shipment notifications

• Logs into the ERP system
• Selects all orders ready for shipment
• Generates and sends automated shipment emails
• Alerts Customer Service about orders missing data

Result: 7,000 hours saved annually.

Combined, the automations delivered 13,400 hours saved every year, eliminated two manual processes entirely, and ensured that 76,000 orders are now verified automatically with greater accuracy and consistency. By removing repetitive work, a 30-person team was freed up to focus on customer service, problem-solving, and higher-value activities instead of routine admin tasks. The company now operates with faster turnaround times, fewer errors, and a more resilient order-management process.

97% faster sanctions screening and full audit trail with a single bot

Across industries, there’s a recurring pattern of low-value manual work: fill the form, check the result, archive the proof. Sanctions screening is a textbook example: an employee enters customer or vendor data into an online form, waits for the result, takes a screenshot, and saves it for audit purposes. When the scale grows to thousands of entities, the cost and risk increase rapidly. And with individual sanctions penalties exceeding $1 million, the risk is very real. For one portfolio company, verifying 20,000 customers and vendors against EU, US, and UK sanctions lists took around seven weeks of team time. Employees copied names into a form, waited for responses, captured screenshots, and stored them across multiple folders.

In many companies, this step is outsourced to external attorneys who validate the list and return updated results—only for the company to re-update the ERP afterward. In both setups, verification was slow, fragmented, and heavily dependent on manual work.

We replaced this with a single sanctions-screening bot that works as follows:

• The ERP generates a list of customers and vendors.
• The bot retrieves the latest EU, US, and UK sanctions lists and places them in a designated folder.
• The bot automatically begins processing:

-- Downloads or reads the sanctions lists and standardizes them -- Compares all 20,000+ records against the lists -- Generates a final report plus an exemptions list -- Stores the output in a folder for the legal team to review

Additionally, the company now has a self-service form: any new customer or vendor can be checked individually or in bulk. Within 2–3 minutes, the requester receives an email with the result, and a copy is automatically sent to the legal team—ensuring complete documentation for every check. The impact:

• 97% process time reduction—from 560+ hours down to <16 hours
• From 7 weeks to 2 hours to verify 20,000 contacts
• ~$15,000 saved annually from labor cost reduction with a single bot
• Full audit trail—centralized reports, no missing screenshots, no scattered folders
• Near-zero error risk—the bot processes every record consistently, every time

These are just a few of the many automation examples delivering measurable impact across PE-owned companies. With each project, we go deeper and broader—introducing new initiatives that gradually automate the entire operational landscape. Beyond automation, we also build a deliberate reporting layer for executives and management, driving accountability across teams and connecting previously dispersed systems and data. The savings are clear, immediate, and directly tied to EBITDA. If you want to explore how similar automations could work in your portfolio companies, feel free to drop us a message.