Venture Dashboards were created for each of the firms, covering almost every conceivable stage of funding such as seed, Series A, Series B, Series B-1, C, D, E, EE/F and related convertible bridge notes between rounds. In the case of large angel rounds at an early stage, even more exotic structures were encountered. Naturally, each of these dashboards was kept in the strictest of confidence. What is presented herein are the general founder and venture fund experiences in creating them, along with nuances particular to a given sector or stage of funding, that will allow your team to approach best practice more quickly.
The primary objective was to see just how quickly data could be “extracted, transformed and loaded” into a living venture dashboard that management, investors and others could use in a real life setting immediately. In all, over 1.5 million investor outcomes were modeled as part of this process, across nearly 300 financing event closings and more than 10,000 prospective milestone outcomes, venture leasing alternatives, acquisition scenarios and other projections.
73 Interviews with fund investing partners, fund CFOs, founders, individual angels, angel groups, investment bankers, valuation professionals and key advisors were conducted. In many of these interviews, we had subjects or their representatives attempt to take existing reports and data they already had (spreadsheets, Word documents, PowerPoint Presentations, revenue models, Stock Purchase Agreements, third party valuations, audit reports and so forth) and turn them into superior knowledge and insights as quickly as a Fortune 500 executive could customize and access an analytics dashboard. Then we tested the 5 click benchmark.
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In the course of these interviews, we discovered that a key source for applying manual analytics to mental venture dashboards came from web searches and blogs, so we incorporated that into the analysis.
We then had a similar analysis performed by independent chartered accountants using IPO data from a handful of venture funded companies that went public. One firm attempted the analysis manually and the other tried to use dashboards instead. This paper’s author performed the same analysis independently as a baseline.
In all, over 1.5 million investor outcomes were modeled as part of this process, across nearly 300 financing event closings and more than 10,000 prospective milestone outcomes |
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