The Pitfalls of Prematurely Sharing Data with Investors
- Why founders should be careful about responding to requests from investors for data
- What circumstances make sharing data appropriate
When an investor expresses interest in your company, they will at some point ask you to provide raw data related to your business performance—items like general ledger/P&L outputs, revenue by customer by month details, a detailed projection model , etc.
Their request feels fair—they eventually need to know how your business is doing before they can give you a pulse on valuation or their interest in pursuing a deal.
But when this request comes, tread lightly to avoid putting yourself in an awkward position.
Inaccurate data can get you in trouble
The most important reason why you should be careful about sharing data is that what you share may not be accurate or tell the true story of the underlying business.
Accurate metrics rely on accurate source data. Consider your CRM or other system of record: what percent of your data would you say is correct? Has it been correct historically?
If you haven’t taken time to clean up data, any calculated metrics will be wrong or misleading, which can sow distrust further into a process when the truth comes out.
Even if your source data is perfectly clean, the way in which you calculate a given metric likely varies from how an investor would do so. If you share a metric and it ends up being different from what an investor calculates, that puts you in a suboptimal position.
Investors are taking notes
Once a number (i.e. metric or data point) is out there, you can’t walk it back, whether it’s accurate or not. The investor has it on record, and the number will live throughout the relationship.
If the number is incorrectly pessimistic, it could keep you from attracting interest from the best buyers. If incorrectly optimistic, it could attract a lot of interest, only to be discovered to be wrong during deep diligence and result in a change of the deal terms.
In either case, your ability to close a deal is significantly diminished when you share data prematurely without verifying accuracy first.
Data should be shared in the context of the business
Even in cases where source data is clean and all calculations match an investor’s, you could still shoot yourself in the foot if you don’t take time to position the metrics in the context of the business.
Consider as an example an analysis of SaaS logo retention. If one of your customer segments churned at a high rate, then a logo retention analysis of the full 100% of customers would indicate sub-par performance even if that segment only represented 5% of revenue.
Alternatively, if you provided context (e.g. 95% of revenue comes from customers who churn at a much lower rate), you would put yourself in a better negotiating position with investors.
Guard against specific data requests
Investors will often ask for three types of data:
- Historical data, such as P&Ls and retention calculations (Net, Gross, Logo)
- Raw data, such as general ledgers and revenue by customer by month
- Projections/Forecasts, such as a bottom-up P&L model, win probabilities for deals currently in the pipeline, hiring plans, etc.
With historical data, you need to be concerned with the accuracy of source data and how you calculate the metric. To use gross margin as an example, founders often fail to fully classify as COGS expenses like:
- Support & labor
- Third-party licenses needed for the platform to run
- Payment processing fees
- Hosting costs (e.g. AWS, Azure etc.)
- Implementation/onboarding, consulting & data migration
If you’re not careful, you could report to investors an inflated gross margin, only to later on have them discover that you didn’t fully burden this P&L line item as you should have.
With raw data, you need to be concerned about data accuracy and context. A data export from a given system of record (such as a payments processor) will likely be an incomplete data set and not designed in accordance with GAAP principles, which can create a fragmented picture of your business.
In addition, raw data completely ignores the context of the business, which could be a critical piece for interpreting true performance.
With projections/forecasts, your main concern should be that, by sharing that data, you set a benchmark for yourself that the investor is going to track you against. If for whatever reason you don’t hit your projections or reach certain milestones, you’ll have some awkward conversations that could have been avoided altogether.
For example, if a business grows 85% YoY with 25% EBITDA margins, that’s a stellar year! However, if the investor is expecting 98% growth and 28% EBITDA margins, then they can rightly ask "What went wrong?" No one wants to have that conversation, so avoid prematurely sharing data so you can instead talk about the wonderful year your company just had.
When is the right time to share data?
At some point, an investor will tell you that, in order to underwrite a deal, they’ll need access to data, both structured and unstructured. And they’re right—no one is going to close a deal without digging in to see the business in its raw, unmanicured form.
But as a founder, you need to control the narrative as long as possible while you prepare yourself for a transaction. The best way to do so is to hire an investment bank to help you:
- Clean up your financials
- Frame your data in the context of the business
- Take your business to market as part of a competitive process