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Predictive Business Model Rating

What Websites and LinkedIn Profiles Reveal About Investment Risk

· investment,risk,startups

The importance of market size estimates and financial projections for the investability of startups is often exaggerated. We tend to gravitate towards quantitative information and numbers, particularly if they meet our expectations of size and growth rate.

Yet, it is tacit knowledge, experience and expert opinion that often drive the eventual investment decisions in early stage companies. Indeed, research indicates that quantitative financial information makes up 20-25% of investment risk. The rest is non-financial, unquantified expert know-how.

What if tacit knowledge could be coded and quantified? Every intern could become a Dr. House. The benefit of business risk decision-making accessible to all.

Observation and Experience Yield Tacit Knowledge

Many of us have been subjected to, and love or hate the Myers-Briggs personality typology.  Steeped in the theory of Carl Jung, the test is structured around the two major attitudes or orientations of personality – extroversion and introversion, and four basic functions (thinking, feeling, sensing, and intuiting). 

The test is often dismissed as not being scientific and thus not testable.  That is not its purpose.  It is based on observations of people.  Decades of observations. It really only tells you how you are wired to take in and process data, not your actual skills and abilities.  

We live in a world of information.  The more we accumulate, the more we have to process. All the time. Every day. And in the process we accumulate tacit knowledge.  Knowledge informs opinions, perspectives, and decisions. Experiences influence how we project, 'market', and identify ourselves.

Tacit Knowledge in Business Design and Investment

Entrepreneurial business development is an extension of these experiences. Serial entrepreneurs and investors accumulate new knowledge from failures and successes.   And using this tacit knowledge, they make investment, strategic and operational decisions.  

It is not knowable - until significant market validation - whether an investment has a likelihood of success.  By tracking product development from idea to beta and pilot, and by measuring financial growth and margins, the business evolves, pivots and takes off or languishes.  

The myth of legendary investors and successful VC firms with high exits is sprinkled with insights such as: right timing or team, investors with special 'gut feel', and 'finger on the societal or industrial pulse'. A bet on a founder, a trend or a technology with a 'diverse exit ecosystem'. And above all, a calculated risk on the potential to tap a large market - preferably $1 bn. over time.

Information asymmetry is driven by tacit knowledge.

Public Disclosures of Private Companies have Predictive Risk Value

Importantly, tacit knowledge is reflected in the structure of professional profiles, the design and content of company websites. An aspirational message of capability and strategic intent. It is not scientific and is not testable. But it can be measured.

Big data approaches uncover unique knowledge structures. In fact, your company's public disclosures reveal more about your investment grade than you realize. Websites, LinkedIn profiles, blogs and news releases provide a wealth of data and insights that inform risk. It is the 75% of risk that is non-financial and is forward-looking.

Based on research on over 4,000 companies across the business lifecycle, the KeyStone Compact Group designed and backtested an algorithmic approach to capture business investment risk from 'non-financial information'. By combining binary assessment and powerful back-end analytics, both the value capture position and investment grade of a company can be quantified.

Traditional Equity, Creative Long-Term, Non-Dilutive, or Bootstrap Financing?

Algorithmic data processing of your public information reveals value chain dependencies, leverage of position and assets, connectivity in the industry, upside potential, scalability, and capital efficiency. And all without the benefit of a business plan or financials. It is a snapshot in time. As the business, people and experiences evolve, so does the investment grade and position.

Algorithms do not replace due diligence. Myers-Briggs tests do not replace an employment test period. But both have important signaling value. They uncover trends, proclivities and risk.

KeyStone Compact Algorithms Tracks Value of Business Mentoring

Mentoring has long been upheld as a key driver of tactical and operational success for early startups, in part because it transfers the benefit of tacit knowledge gained from experience to the management of the company. TechStars is one of the most successful incubator models resulting in helping entrepreneurs build great businesses.

A longitudinal study (tracking of companies over time) between 2011 and 2015 compared the success rate of top-30 equity-investable companies selected using KeyStone Compact models from the Global CleanTech Cluster Association (GCCA) with 59 graduating companies from the TechStars program. The figure shows that algorithmic analysis tracks mentoring success in the incubator very closely.

KeyStone Compact. Tacit knowledge codified. Backtested. Constantly updated. Accessible to anyone with basic business knowledge.

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