robbie.es Robbie Höll
Tell me what you have in mind
Independent feasibility study · Private-equity use case

Mapped 4,500 bookkeeping firms to test a buy-and-build thesis.

I independently explored whether the fragmented Dutch bookkeeping-firm market could support a credible buy-and-build strategy, with informal input from a private-equity investor assessing whether the opportunity warranted further work.

To test the thesis, I built a market-wide dataset, screening methodology and financial model covering approximately 4,500 firms.

Independent analysis · Market mapping · Candidate screening · Feasibility conclusion

Confidentiality note

This case presents my independent feasibility analysis. The identity of third parties, individual firms, non-public discussions and any confidential input are not disclosed.

Dashboard figures beyond the approximate overall market size are illustrative.

Market mapped ≈ 4,500 firms

Structured coverage of the Dutch bookkeeping-firm market.

Market structure Highly fragmented

A long tail of small, owner-led firms with limited individual scale.

Thesis tested Buy & build

Target availability, platform economics and potential value creation.

Feasibility conclusion No-go

The specific thesis did not justify further work under the assumptions tested.

Bookkeeping firms market scanner
Independent feasibility overview
Amsterdam The Hague Rotterdam Utrecht Eindhoven Maastricht Groningen
Screening overview
Illustrative screening visualisation
Firms mapped
4,527
After basic filters
2,842
Financial data available
1,974
Qualified candidates
272
High-potential targets
78

Candidate scoring

80–100
78
60–80
194
40–60
326
20–40
612
0–20
764

Market structure

Long tail of small owner-led firms

The question

Could fragmentation support an attractive buy-and-build strategy?

The initial thesis looked promising: thousands of firms, many small owner-led businesses and a market that appeared suitable for consolidation.

But fragmentation alone does not create an attractive investment case.

The real questions were whether there were enough suitable acquisition targets, whether a meaningful platform could be assembled and whether the potential value creation justified the complexity, time and risk.

The goal was not to prove the idea. It was to determine whether the idea deserved further investment.
What I built

A market-wide dataset and screening engine.

I created a structured dataset covering approximately 4,500 Dutch bookkeeping firms and translated it into a repeatable feasibility-assessment workflow.

The system combined market mapping, company-level enrichment, target screening and financial modelling in one decision framework.

  • Automated collection and structuring of market data
  • Company-level enrichment and classification
  • Multi-criteria acquisition-candidate scoring
  • Geographic and market-fragmentation analysis
  • Ranking of potentially relevant targets
The model

From market data to platform economics.

The analysis tested what a consolidating platform could realistically look like over time.

It considered acquisition pace, target availability, purchase multiples, financing, integration effort, synergies and potential valuation uplift.

  • Organic growth and bolt-on acquisitions
  • Purchase-multiple and exit-multiple sensitivities
  • Cost synergies and potential revenue cross-sell
  • Financing requirements and integration capacity
  • IRR, cash-on-cash and payback scenarios
What the data showed

Highly fragmented, but not sufficiently attractive at scale.

The market contained a large number of firms, but the strongest candidates were limited in both number and scale.

Once realistic assumptions were applied to acquisition quality, integration effort, payback periods and platform economics, the thesis became less compelling.

There were potentially interesting firms, but not enough evidence that the proposed strategy could create an attractive platform at the required scale.

The feasibility conclusion

A clear answer to whether the thesis warranted further work.

No-go Under the assumptions and investment criteria tested, the opportunity did not justify proceeding to a full investment process.

This conclusion applied to the specific strategy, assumptions and return requirements tested.

A different operating model, investor profile or consolidation strategy could lead to a different outcome.

Why it mattered

The value was the decision, not the dashboard.

Faster conviction

The thesis could be tested systematically without months of fragmented manual research.

Better capital allocation

A well-founded no prevented further time and resources from being committed to a weak version of the opportunity.

Reusable methodology

The same approach can be applied to other fragmented markets, investment themes and commercial hypotheses.

Have a market, investment or commercial thesis worth testing?

I build focused datasets, screening frameworks and decision tools to determine whether an opportunity deserves further work.

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