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Economics November 7, 2017

What information do startups provide to their venture capital investors?

By Katja Kisseleva and Malte Lorenz
What information do startups provide to their venture capital investors?
Venture capital funds have risen as a primary form to finance entrepreneurial activities. These early-stage companies would otherwise have difficulties to obtain financing from other sources, such as traditional bank loans or capital market financing.

This is usually due to high levels of risk and uncertainty and a lack of validation of their businesses over time. Due to the high level of uncertainty, a substantial percentage of investments fail and have to be liquidated. The remaining part of investments is generally sold off privately or merged with other firms.

In any investor-startup relationship, the startup usually has private information, for example, private information regarding the firm’s operational state, which the investor cannot access free of cost. These information asymmetries not only shape the process before the venture capitalist invests in the startup, they also affect the relationship after the investment. Therefore, the venture capitalist will try to ensure the reliable data flow of all the relevant information to mitigate against the risk of the not-fully-supervised entrepreneur. Consequently, the investment agreement (term sheet) would typically include regulations with regards to data transfer. However, prior research has shown that two-thirds of the venture capitalists in the UK did not impose such contractual agreements on their portfolio companies. This leaves room for startups to select the data they want to include in their entrepreneurial reporting to investors.

Our study examined what kind of post-investment information (financial and managerial) early-stage startups select to deliver to their VCs when the VC does not impose standardized requirements. We analyzed a dataset of 30 startups’ reportings, which was provided to us by one Berlin-based venture capital fund, regarding data type, format, consistency, and frequency. This investor did not impose communication or reporting standards on its portfolio companies for a certain period of time, apart from demanding reporting in general. We found that the portfolio companies’ reporting is quite similar on a meta-level. For instance, all firms reported financial or operational performance measures, and 80 percent of the dataset’s startups shared both financial and operational performance data with its investors. When diving deeper into the data, however, the level of heterogeneity increases. We explain these findings by best practices and networking effects, which are utilized by the entrepreneurs to shape the general structures of their reporting, but note that individual preferences would lead to conceptual differences of the entrepreneurial reporting on a detailed level, caused by the absence of regulation.

Detailed Results

Regarding the reported key performance indicators (KPIs), we could observe that very commonly used metrics were chosen: burn rate, net income, revenues, costs, costs of goods sold (COGS), and earnings before interest and taxes (EBIT) — all on a monthly basis. Although these variables are generally acknowledged as standard metrics, not all of the sample’s firms included those indicators in their reporting. Therefore, the availability of the aforementioned figures ranges from nine observations for burn rate, to 19 observations for revenues.

Regarding the reporting itself, we differentiated on several dimensions: data type (quantitative/qualitative, financial/operational), format (spreadsheet, continuous text, bullet points, graph), structure (consistency and frequency). Regarding the data type, all but two firms (28 in total) engaged in quantitative reporting, 23 in qualitative reporting, and 21 used both types of data. On the performance level, 87 percent (26 out of 30) of the firms shared financial performance information, 93 percent (28 out of 30) operational performance information, and 80 percent (24 out of 30) provided insights regarding both performance categories to their VCs. For the 28 firms, which provided operational information, the split between quantitative-operational and qualitative-operational data was equal, totaling 23 firms each. Sixty-four percent of the firms providing operational data (18 out of 28) communicated both quantitatively and qualitatively. Thus, early-stage companies find quantitative and qualitative means of reporting similarly useful in order to display operational information.

On the financial side, however, there are considerable differences between the disclosure of quantitative and qualitative data. While almost all firms (96 percent) passed those data on to explain the firms’ financial state quantitatively, only roughly 35 percent (9 out of 26) also used qualitative data enrichments for the financial status. Consequently, there appears to be a strong preference for using quantitative data to disclose financial matters while no preference whether to communicate operational performance information quantitatively or qualitatively seems to exist.

This is also reflected when examining the format of disclosure. The most frequently used way of disclosing information was the inclusion of some sort of spreadsheet, which 23 firms did, roughly three-quarters of the sample. The number of startups opting to present the information by continuous texts, graphs, and bullet points is quite similar (14, 14, and 17, respectively). Moreover, 21 firms used more than one means of transmitting the information. An explanation for the dominance of the spreadsheet as the format of disclosure might be the overall preferences of startups to convey their financial and operational performance using quantitative data. One could argue that purely numerical data is both easier to prepare and to comprehend when presented by quantitative means. While it seems to be difficult to work through a written segment to extract important metrics, such as numerical performance indicators, spreadsheet-style setups enable the reader to comprehend the data at a glance. However, it remains unclear why graphs, which have a similar or arguably better informative value, are used much less. Further, 27 percent of the sample (eight out of 30) specifically used a comparable quantitative spreadsheet format. The reason for this uniformity appears to be the use of the same reports generated by their tax advisors’ accounting software (BWA: betriebswirtschaftliche Auswertung). Three firms additionally utilized cash on hand and revenues in current and previous periods, which are available through the BWA into graphs and adding some of their most important operational performance indicators.

In addition to inconsistencies concerning format, discrepancies concerning consistency in reporting or its frequency exist. Whereas several firms use quantitative as well as qualitative data to give insights into both financial and operational performance, some firms only send a software-generated spreadsheet without any additional information or explanations. Eleven firms provided just one report over eight months; eleven other firms communicated with their investor twice over the eight months. Seven out of 30 sent three entrepreneurial reports to the investor. One firm stands out by having reported seven times.

We suggest that more frequent reporting appears to be associated with higher homogeneity, even on deeper levels of data, as well as the provision of more insightful information. A practical implication for the venture capitalist is, therefore, to increase the mandated frequency of reporting for its portfolio companies. Although this would not lead to totally identical reporting for all firms, judging by the study’s findings it seems plausible that mandating the startups’ to report in bi-monthly intervals, for instance, would lead to greater depth, on the one hand, and more homogenous reporting, on the other. The VC would be able to implement this improvement at little cost for both itself and the portfolio company.

Case-study: Start-up-VC interaction

Firm X’s communication with its VC exemplifies how an investor may react in order to counter its portfolio company taking advantage of the information asymmetry. The firm provides reports for June and August. Similar to its reporting in June, the firm provides a spreadsheet containing some of its most important metrics along with a continuous text in August. The text superficially explains the startup’s operational status in a generally positive tone and gives numbers to underpin its performance assessment.

However, the VC realizes that there is a significant difference between the planned sales and net income numbers and those which actually occurred. Consequently, the VC demands the further flow of information. It interferes and asks its investee to explain the deviation from performance indicators and to clarify whether the firm’s overarching goals are still realistic. The startup responds by providing a very detailed explanation for the discrepancies in performance, its future strategy to foster growth, and measures on the cost side to attenuate the net income difficulties.

Considering that only a mere three days passed in between the VC’s request and the portfolio company’s reply, it is highly doubtful that the startup had to develop new metrics or twist its internal performance measurement to provide these data. It seems much more likely, that it deliberately chose not to provide them — to act opportunistically. Trying to make its performance appear more advantageous, Firm X omits to communicate important information to put it into context. Possibly, none of its investors would have asked for further information and the startup could have avoided having to elaborate on these unpleasant developments.


The first conclusion from our paper is that even in the absence of standardization there is some content similarity among portfolio companies. Assuming that VCs prefer their investees to communicate financial and operational performance similarly, depending on the desired degree of homogeneity, these similarities may be sufficient. Furthermore, our data suggests that the information of firms that report more frequently has a greater depth, is more homogenous, and tends to be more insightful.

Therefore, the second conclusion is that VCs need to manifest and increase the mandated frequency of reporting for its investees. Although this would not lead to identical reporting for all firms, it seems plausible that mandating the investees to report every two months, for instance, would lead to greater depth, on the one hand, and more homogenous reporting, on the other hand.

All of the above findings are indicative but not conclusive. Therefore, further research is necessary to explore a longitudinal study of startups’ entrepreneurial reporting frequency, informational value, and their long-term performance, as well as a linguistic analysis of the entrepreneurial reports with the purpose of identifying correlations between the entrepreneurs’ tone in reporting and their firms’ performance in the given reporting period.

We would like to thank the Berlin-based venture capital fund, which remains anonymous, for providing us with insights and data.

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