Incites Ventures Announces a Statistically Based, Qualitative Approach to Making Investment Decisions
After more than five years of research, a core team including Incites Ventures LLC and Professor Al Bruno of Santa Clara University has developed a methodology that is a powerful indicator of investment desirability and viability.
Rancho Mirage, CA, November 25, 2008 --(PR.com)-- A Second Opinionäã.
A Statistically Based, Qualitative Approach to Making Investment Decisions.
After more than five years of research, a core team including Incites Ventures LLC and Professor Al Bruno of Santa Clara University has developed a methodology that is a powerful indicator of investment desirability and viability. The methodology addresses the question: “Can a statistical technique be used as a valid method to evaluate a set of fundamental business characteristics as predictors of the invest / do not invest decision and further, as predictors of investment success?”
During deployment of the original Incites Processäã (www.incites.com) to well over 200 business cases it was concluded that the allocation of R&D funds within corporations and the decision process of making venture capital investments lacked real objectivity. When interviewed, corporate decision makers and venture capitalists alike believed that they used some “rule-of-thumb” methods to aid their “gut feel”, but they knew of no truly objective methodology that could be used.
The research team’s results to date strongly reject the hypothesis that simple metrics such as market size, management team quality or even more complex estimates such as those used in the GE matrix, the BCG matrix or the original Incites Process are sufficient to give statistically significant results in identifying investment viability. Used individually or in simple combinations, these commonly used metrics fail to give statistically meaningful results.
This supports a widely held belief that the allocation of corporate R&D funds is one of the areas of corporate governance that needs the greatest attention in this rapidly moving economic environment. Given their performance over the beginning of this decade, many VC’s, when privately polled, believe that their current processes are badly compromised and in need of serious revision. This suggests that the right business analytics software could significantly improve investment performance in both of these key areas.
Using a rich data set of both corporate and venture investments a new, objective data-driven methodology has been developed. A Second Opinionäã involves the use of two independent models, the first one suggests a “would invest” or a “would not invest” decision based on the characteristics of a business, and the second one ranks the probable success of a completed investment. Both models use the statistical technique of predictive and descriptive qualitative discriminant analysis. The methodology was developed using a knowledge base of more than 100, carefully screened, business cases evaluated for investment purposes by Incites Ventures LLC and then evaluated after five years. Reliable third parties, not aware of the model construct or the input questions, but well informed about the performance outcome, performed an assessment and actual classification of the business cases in the knowledge base.
The input data for the first model consists of qualitative answers to 62 questions about the investment candidate in the form of ratings on a discrete scale of only 1, 2 or 3 (1=below average, 2=average, 3=above average). The model then classifies a given business case into either a “would not invest” or “would invest” (0/1) category using discriminant analysis techniques based on the contents of the knowledge base.
A second model further processes the input data and again using the knowledge base predicts the viability of an investment. Internally this module ranks the potential investments into 5 categories, “1” being a poor investment outcome, “2” below average, “3” average, ”4” above average and “5” being excellent and then outputs a summary of these rankings on a 0/1 scale with 0 scoring the 1 and 2 rankings and 1 scoring the 3, 4 and 5 rankings.
Early test cases of this model were drawn from a tier-one venture capital firm having over $1 billion under management and a manufacturing firm with sales in excess of $500 million. The models very accurately classified the potential of investments regardless of individual investor bias. In addition, the analysis provided descriptive information that aided in the understanding of why the specific classification was made. Accuracies of greater than 80% can be demonstrated.
Al Bruno, the William T. Cleary Professor at Santa Clara University, was quoted to say: “ This methodology is ground-breaking in that it allows corporations to rapidly assess R&D and investment proposals to aid in the ever-shortening decision making process now required for the 21st century company to be successful. We like to look at this as a crucial ‘Second Opinion’ for today’s executive.” Gunnar Hurtig, Managing General Partner of Incites Ventures, previously an institutional venture capitalist, said: “In today’s confused investment environment the savvy VC can use the tool to validate investment decisions as part of the due-diligence process. The tool is equally effective in assessing either first round or follow-on round investments.”
-More-
About Incites Ventures
Formed in 1990, the Company has provided strategic direction and interim management for a wide variety of high technology companies. Using its proprietary Incites Process over 200 times the Principals have developed a methodology that can be used by large and small companies as well as by venture capitalists in evaluating their investments.
###
A Statistically Based, Qualitative Approach to Making Investment Decisions.
After more than five years of research, a core team including Incites Ventures LLC and Professor Al Bruno of Santa Clara University has developed a methodology that is a powerful indicator of investment desirability and viability. The methodology addresses the question: “Can a statistical technique be used as a valid method to evaluate a set of fundamental business characteristics as predictors of the invest / do not invest decision and further, as predictors of investment success?”
During deployment of the original Incites Processäã (www.incites.com) to well over 200 business cases it was concluded that the allocation of R&D funds within corporations and the decision process of making venture capital investments lacked real objectivity. When interviewed, corporate decision makers and venture capitalists alike believed that they used some “rule-of-thumb” methods to aid their “gut feel”, but they knew of no truly objective methodology that could be used.
The research team’s results to date strongly reject the hypothesis that simple metrics such as market size, management team quality or even more complex estimates such as those used in the GE matrix, the BCG matrix or the original Incites Process are sufficient to give statistically significant results in identifying investment viability. Used individually or in simple combinations, these commonly used metrics fail to give statistically meaningful results.
This supports a widely held belief that the allocation of corporate R&D funds is one of the areas of corporate governance that needs the greatest attention in this rapidly moving economic environment. Given their performance over the beginning of this decade, many VC’s, when privately polled, believe that their current processes are badly compromised and in need of serious revision. This suggests that the right business analytics software could significantly improve investment performance in both of these key areas.
Using a rich data set of both corporate and venture investments a new, objective data-driven methodology has been developed. A Second Opinionäã involves the use of two independent models, the first one suggests a “would invest” or a “would not invest” decision based on the characteristics of a business, and the second one ranks the probable success of a completed investment. Both models use the statistical technique of predictive and descriptive qualitative discriminant analysis. The methodology was developed using a knowledge base of more than 100, carefully screened, business cases evaluated for investment purposes by Incites Ventures LLC and then evaluated after five years. Reliable third parties, not aware of the model construct or the input questions, but well informed about the performance outcome, performed an assessment and actual classification of the business cases in the knowledge base.
The input data for the first model consists of qualitative answers to 62 questions about the investment candidate in the form of ratings on a discrete scale of only 1, 2 or 3 (1=below average, 2=average, 3=above average). The model then classifies a given business case into either a “would not invest” or “would invest” (0/1) category using discriminant analysis techniques based on the contents of the knowledge base.
A second model further processes the input data and again using the knowledge base predicts the viability of an investment. Internally this module ranks the potential investments into 5 categories, “1” being a poor investment outcome, “2” below average, “3” average, ”4” above average and “5” being excellent and then outputs a summary of these rankings on a 0/1 scale with 0 scoring the 1 and 2 rankings and 1 scoring the 3, 4 and 5 rankings.
Early test cases of this model were drawn from a tier-one venture capital firm having over $1 billion under management and a manufacturing firm with sales in excess of $500 million. The models very accurately classified the potential of investments regardless of individual investor bias. In addition, the analysis provided descriptive information that aided in the understanding of why the specific classification was made. Accuracies of greater than 80% can be demonstrated.
Al Bruno, the William T. Cleary Professor at Santa Clara University, was quoted to say: “ This methodology is ground-breaking in that it allows corporations to rapidly assess R&D and investment proposals to aid in the ever-shortening decision making process now required for the 21st century company to be successful. We like to look at this as a crucial ‘Second Opinion’ for today’s executive.” Gunnar Hurtig, Managing General Partner of Incites Ventures, previously an institutional venture capitalist, said: “In today’s confused investment environment the savvy VC can use the tool to validate investment decisions as part of the due-diligence process. The tool is equally effective in assessing either first round or follow-on round investments.”
-More-
About Incites Ventures
Formed in 1990, the Company has provided strategic direction and interim management for a wide variety of high technology companies. Using its proprietary Incites Process over 200 times the Principals have developed a methodology that can be used by large and small companies as well as by venture capitalists in evaluating their investments.
###
Contact
Incites Ventures, LLC
Gunnar Hurtig, III
7604692941
www.incites.com
Gunnar Hurtig, III
7604692941
www.incites.com
Contact
Categories