Why private markets professionals are switching from Excel to purpose-built tools

Excel has been the operating system of private markets for thirty years. Financial models, deal tracking, portfolio monitoring, comparable analysis — if it involves numbers and private companies, there is an Excel spreadsheet for it.

And Excel is genuinely excellent at many things. It is flexible, familiar, offline-capable, and universal. Every analyst in every fund on every continent knows how to use it. This is a real advantage.

So why are an increasing number of private markets professionals moving away from it?

The collaboration problem

Excel was designed for single-user work. Multiple people editing the same spreadsheet — whether over email, SharePoint, or even real-time collaboration tools — is a fundamentally broken experience.

Deal pipelines managed in Excel face a recurring problem: two analysts update the same row on the same day. One version gets lost. The pipeline is wrong. Someone wastes an hour reconciling. This is not a technology failure — it is an architectural limitation. Shared documents were not designed to be the source of truth for a team's operational data.

Purpose-built deal management platforms maintain a single source of truth with concurrent access built in from the start.

The context problem

Private markets deals have context. The last conversation with the management team, the red flag identified in the CIM, the comp analysis that justified the entry multiple — all of this lives in analysts' heads, in email threads, and in folders that are not well organized.

When a junior analyst leaves a firm, a significant portion of the institutional knowledge about active deals leaves with them. A new hire starting on a live mandate has to reconstruct context from old emails and incomplete notes.

Purpose-built platforms capture deal context as it accumulates — documents, notes, contacts, analysis — and make it retrievable for anyone on the team, including people who were not there when the deal started.

The analysis quality problem

This is the subtler issue, and arguably the more important one.

When analysis lives in Excel models, the quality of that analysis is limited by what analysts can build manually. Comparable company analysis takes a full day for a thorough analyst — selecting peers, gathering financial data, calculating multiples, building the output. Given time pressure, corners get cut. The comp set is not as rigorous as it should be. Historical data is thin.

AI-powered analysis platforms change this calculus. A comparable analysis that would take 6 hours to build manually can be done in 20 minutes when the peer selection, data gathering, and multiple calculation are automated. This is not a marginal improvement — it is a structural shift in what is analytically possible given the time available.

When analysis is faster, teams can evaluate more opportunities, maintain more rigorous screening, and spend their analytical energy on the judgment calls that actually differentiate deals — not the mechanical data work.

The data room problem

Managing data room access via email and shared folders is a security and efficiency problem that most firms have lived with because there was no better alternative.

A typical mid-market M&A process involves 15 to 30 buyers receiving access to documentation in waves, with different disclosure for different stages. Managing this manually — tracking who has signed NDAs, who has received which documents, who has asked which questions — creates compliance risk and wasted time.

Purpose-built data room software solves this: granular permissions, audit trails, Q&A management, and automated document access workflows. The data room becomes a managed process, not an email thread.

The switching cost myth

The most common objection to adopting purpose-built tools is the switching cost: "We already have an Excel pipeline. Migrating to a new platform will take months."

This is overstated. Most modern platforms allow CSV import of existing deal data. A well-organized Excel pipeline can be migrated in a day. The more significant investment is workflow change — getting the team to actually use the platform instead of defaulting to the spreadsheet.

Our experience is that teams that successfully make the switch do three things:

1. Start with a single use case — usually deal tracking — and win on that use case before expanding

2. Designate a champion — one analyst who becomes the internal expert and advocates for the tool

3. Accept imperfect data initially — the platform does not need to have perfect historical data on day one; the value comes from forward-looking discipline

What the transition actually looks like

Week 1: Import existing pipeline into the new platform. Set up deal stages that match your existing process.

Month 1: Active deals managed in the platform. Document uploads for deals in due diligence. Team learns the interface.

Month 3: Historical analysis — old comp sets, past deal notes — starts migrating in. Institutional knowledge begins accumulating.

Month 6: The platform is the default. Excel still exists for custom financial modeling (as it should), but pipeline, documents, contacts, and deal communication live in one place.

The value is not immediate — it builds over time as deal context accumulates and the team develops new analytical habits around faster, AI-assisted analysis.

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Excel will remain the best tool for building financial models for the foreseeable future. The argument is not against Excel — it is for recognizing that deal management, document analysis, and comparable company analysis have better tools available now.

The private markets professionals who move first will have an information advantage over those who move last.

Blind Side is the platform we built to accelerate this transition for Italian and European private markets professionals.