Coverage of WeWork's $11 billion collapse focused on a charismatic founder and questionable business model, but it was fundamentally a data integrity failure that destroyed deal integrity.

Here's what should keep you up at night: if a company with WeWork's resources, sophisticated investors, and armies of analysts could hide reality behind bad data for so long, what's lurking in your company's spreadsheets? The uncomfortable truth is that data problems affect companies of all sizes, but smaller businesses face even greater risk because they lack the infrastructure and redundancies that should have caught WeWork's issues.

Today, we're diving into why data integrity equals deal integrity, what this means for your valuation, and most importantly, what opportunities you're missing when your data isn't telling you the truth.

Let's unpack this $11 billion lesson.

The $11 Billion Data Disaster

When WeWork filed for IPO in 2019, its S-1 revealed a masterclass in creative metrics. "Community-adjusted EBITDA" became the poster child for financial engineering, but the real damage went deeper. Inconsistent lease accounting, undisclosed related-party transactions, and conflicting operational metrics created a house of cards that collapsed spectacularly when exposed to sunlight.

However, what most people overlook is that WeWork's data not only concealed problems, but also opportunities. Buried in their chaotic metrics were patterns about which locations actually worked, which customer segments were profitable, and which services drove real value. With clean data, they might have pivoted to a sustainable model years earlier.

3 Ways Bad Data Destroys Your Exit Multiple

1. The Credibility Crater

When buyers find one inconsistency in your data during diligence, they assume there are ten more hiding. I've seen this firsthand. Data quality issues can knock 0.5 to a full turn off your EBITDA multiple. On a $10M EBITDA business, that's $5-10 million in lost value. Why? Because buyers price in the risk of unknown unknowns.

2. The Integration Tax

Messy data creates post-acquisition friction. When your systems don't communicate, your metrics don't align, and your reporting requires manual adjustments, buyers experience months of integration headaches. They'll either walk away or demand a lower price to compensate for the cleanup costs.

3. The Missed Opportunity Cost

This is the hidden killer. Bad data doesn't just hide problems; it blinds you to opportunities. You can't optimize what you can't measure accurately. You can't spot emerging trends in noisy data. You can't make confident bets when you don't trust your numbers. Every day you operate with poor data quality is a day you're leaving money on the table.

The Data Integrity Checklist

Here's the thing: you don't need WeWork-level problems to face WeWork-level consequences (scaled to your size, of course). Start here:

Stop Looking at Vanity Metrics: Rather than running for the comfort of the measures you've always seen or the ones that are easy to produce, think about what truly measures the quality of your business. What genuinely speaks to the future of the business? What could be the canary in the coal mine that you're ignoring?

Create Your Source of Truth: If your sales team, finance team, and ops team all report different numbers for the same metric, you have a WeWork problem brewing. Pick one system of record for each critical metric.

Document Your Definitions: "Customer" means different things to different departments. So does "churn," "pipeline," and even "revenue." Write it down. Make it gospel.