Which companies deserve a closer look? Change the search scope and priorities, and follow how the selection responds.
A mid-sized medical technology provider wants to complement its clinical monitoring business with digital applications and recurring revenue. It is considering companies in DACH, Benelux and the Nordics. The initial revenue range is €15–100 million.
This standalone portfolio demonstration draws on my experience in company research and developing an Excel analysis tool at Dräger. It does not reproduce that tool and contains no internal data or real transaction.
Eligible profiles: 5 of 8
Sorted by weighted score, highest first. The score prioritises further review; it does not value a business.
Connected patient monitors for mid-sized hospitals. Hardware sales with maintenance contracts and a proprietary data platform.
Service, calibration and remote maintenance of clinical devices. A high share of contract revenue, with a limited proprietary product portfolio.
Wearable sensors for clinical follow-up care. A strong technological complement, currently focused on its domestic market.
Cloud-based analysis of monitoring data. A strong subscription business with substantial investment in product development.
Components and accessories for a range of medical devices. An established business, but limited direct customer access.
Exports all eight demonstration profiles, current scope, weights, scores and exclusion reasons. Semicolon-delimited CSV suitable for Excel.
Choose two or three profiles from the list. Your selection stays in place when you change the search scope.
No profile selected yet.
The two largest weighted contributions come from Strategic fit and EBITDA margin.
Verify these assumptions first; a high score is not a reason to buy on its own.
How long do the three largest customer contracts run, and do they include special termination rights?
Lead over second place: 1.3 points
A close field: less than five points separate the leaders. Small changes in the assessment could change the order.
The three scenarios use the same search scope. Only their weights differ.
First identify the strategic gap to close. Region and size act as exclusion rules here; fit, growth, profitability, revenue quality and integration then determine priority.
All revenues refer to fictional 2025 figures in millions of euros. Growth is revenue growth versus 2024; EBITDA margin is EBITDA divided by revenue. Recurring revenue is the share of contractually recurring revenue in total revenue.
Each criterion is converted to 0–100 points and multiplied by its relative weight. The sum is the overall score. Thresholds are deliberate demonstration assumptions, not industry benchmarks.
A profile with a missing weighted metric receives no overall score and is set aside. If that metric has zero weight, it does not block calculation, but the data gap remains visible. Other missing values are not estimated.
Growth and earnings scenarios show whether the leading profile remains first under different priorities. Risks are discussed separately, rather than hidden in an additional, opaque score deduction.
The output is a prioritised list for research and discussion. Financial statements, customer contracts, regulatory approvals, ownership and integration assumptions would need review before further decisions. Purchase price, financing and synergies are deliberately outside this model.
Overall score = sum of criterion points × relative weight
1 → 0 · 2 → 25 · 3 → 50 · 4 → 75 · 5 → 100
Qualitative demonstration assessment, with a rationale for each profile.
0% → 0 · 25% → 100
Linear between these limits. Negative values = 0; values above 25% = 100.
0% → 0 · 25% → 100
Linear between these limits. Negative values = 0; values above 25% = 100.
0% → 0 · 80% → 100
Linear between these limits. Values above 80% = 100.
1 → 0 · 2 → 25 · 3 → 50 · 4 → 75 · 5 → 100
5 means easier integration, not greater risk. Rationale in each profile.
Calculated using unrounded values; displayed to one decimal place. Equal scores are sorted by profile identifier.
Source: entirely synthetic portfolio dataset; no external company data.
This standalone portfolio demonstration draws on my experience in company research and developing an Excel analysis tool at Dräger. It does not reproduce that tool and contains no internal data or real transaction.