Identify and Quantify Value Creation Levers for PE Portfolio Companies

Find what moves productivity and EBITDA, and what each lever is worth

We build an econometric model of the company's own data to measure how much each lever, from price, customer mix and retention to staffing, technology and cost to serve, moves productivity and EBITDA. Management can then rank the levers by return and build the value creation plan around the evidence.

From work we have done

We built an econometric model for a PE-backed health care tech company, on nearly two years of operating data from more than 100 sites. Management set its plan from the results, and with our work alongside operators the company became 20% more productive within a year.

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Separate what management controls from what it doesn't

Productivity and EBITDA move with price, staffing and technology, and also with demand, the season and the site. The econometric model holds the second group constant so each lever is measured on its own. It is not the same model for every company: each is built around that company's levers and the data it keeps.

Levers management controls

Price

List price, discounts and fee structure

Customer and service mix

Which customers and services to grow

Retention

Which customers to keep, and at what cost

Cost to serve

Vendor, input and delivery costs per customer

Staffing level and hours

Headcount and hours at each site

Staffing mix

Who handles which work: site staff, floating staff, remote teams

Technology and automation

Including AI, and how work is processed

Channels

How work and customers arrive

Factors held constant

Demand

Market conditions and volume swings

Job size

Large jobs take longer

Season

Month-to-month patterns

Site

Fixed differences between locations

Measured effect

Outcome Each lever's effect on productivity and EBITDA, sized so it can be set against its cost

Figure 1. Levers commonly assessed in PE-backed companies. Which ones matter, and by how much, differs by company.

What the readout gives management

The readout is a table of levers. Each row shows the measured effect, what a realistic change would mean for productivity, and a plain statement of the implication. Set against its cost, each row becomes an EBITDA estimate: a new hire, more hours, a price change, a change in who handles which work, or moving customers onto an electronic channel.

Some results are conditional. At one company, an upload tool raised throughput on large jobs and lowered it on small ones, which pointed to rolling it out by job size.

From an anonymized readout

One more employee at a siteAbout 5% more completed work

One more billable hour per employeeAbout 2% more

Work shifted to floating staffMore output

Work shifted to implementation staffLess output

Intake by batch import or portal instead of manual entryMore output

Upload toolDepends on job size