Smeanalyst 2012 - 05 - 12 - venture-lab


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Smeanalyst 2012 - 05 - 12 - venture-lab

  1. 1. SMEANALYSTUsing artificial intelligence to screen and identifying high potential entrepreneurs
  2. 2. Most studies done by traditional psychometric companies 1 have limited value due to poor or research methodologyPsychometrics and screening entrepreneurs
  3. 3. 1 Cross sectional studies: They usually do not predict, but rather retrospectively fit the data to perform “prediction”. 2 Only test the individual: Hence, they leave out many external and important predictors that have shown to be linked to business failure and success. 3 Poor sampling methodology: They often use small samples, few industries, a single geographic locations and few business sizes: Yet generalize the results across many industries, many locations and many different business sizes.Psychometrics and screening entrepreneurs
  4. 4. 4 Survival selection bias: They only assess operating businesses and hence miss the businesses that have failed therefore creating biased results. 5 Lack of convergent validity with performance measures: The only test a single performance measure and hence do not capture how different businesses are really performing. In some causes they do not use a valid performance measure. 6 Do not include control variables: That is they do not control factors that have shown to impact new firm performance and hence results are muddied and often meaningless.Psychometrics and screening entrepreneurs
  5. 5. Most studies done by traditional psychometric companies 1 have limited value due to poor or research methodology 2 Well designed studies have shown traditional psychometrics tests used alone have weak predictive powerPsychometrics and screening entrepreneurs
  6. 6. “There appears to be no discoverable pattern of personality characteristics thatdistinguish between successful entrepreneurs and non-entrepreneurs”(W. Guth, Directors Corner: Research in Entrepreneurship, The Entrepreneurship Forum, winter 1991)Many other researchers have found similar findings:• Gartner, W. (1988). Who is an entrepreneur is the wrong question. American Journal of smallbusiness.• L. W. Busenitz and J. B. Barney, Differences Between Entrepreneurs and Managers in LargeOrganizations, Journal of Business Venturing 12• Johnston, K., Andersen, B., Davidge-Pitts, Ostensen-Saunders. (2009), Identifying Student Potentialfor ICT Entrepreneurship using Myers-Briggs Personality Type indictors. Journal of InformationTechnology Education.• Lau, T. (1992), „The Incident Method - An Alternative Way of Studying EntrepreneurialBehaviour‟, paper read at Internationalizing Entrepreneurship Conference, Dortmund, 22-24 June• Brockhaus and P. S. Horwitz, The Psychology of the Entrepreneur in The Art and Science ofEntrepreneurship, 1986
  7. 7. 1 Entrepreneurs fill in a 10 minute online questionnaire 2 Predictive analytics identify entrepreneurs probability of growth & survival 3 Entrepreneurs/screeners are given access to a reportWhat is the SMEanalyst?
  8. 8. SMEanalyst predictive variables have been shown to significantly related to growth or survival in more than 38 countries around the world including South Africa Botswana Kenya South Africa Chile Malawi Spain China Netherlands Swaziland Croatia Niger Sweden England Norway United States Germany Russia Zimbabwe India Scotland And many more…What data was the SMEanalyst developed from?
  9. 9. Two of the largest properly design studies on new firm performance ever conducted (6,800 + firms). Random sample firms took the test and followed over a three year period. A hold out sample was used to test the predictive power of the developed model. South African growth model based on research done on 5000 firms.What data was the SMEanalyst developed from?
  10. 10. How accurate are the failure scores? Failure % Grouping of entrepreneurs categorized according to probability of failure Venture defined as failed if it is no longer operational (3 year period)How accurate are the growth scores?
  11. 11. Growth % Grouping of entrepreneurs categorized according to probability of growth Growth defined as adding at least 2 employee or grew more than 50% in relative employment (3 year period)How accurate are the growth scores?
  12. 12. Market Business = Opportunity Model Probability of Growth & Entrepreneurial Survival Relevant experience Mindset & & track record AttitudesHow is probability of growth & survival assessed?
  13. 13. What does the free screening report look like?
  14. 14. What does the new screening report look like?
  15. 15. Professor John Luiz, UCT Business School Specialist in Economics in Emerging Markets 53 Published Papers, 11 Books and book chapters, 31 Conference papers Greg Fisher, GIBS & University of Washington Specialist in Technology Entrepreneurship Greg is currently pursuing his PhD in Strategy and Technology at University of Washington and is a visiting lecturer at Gordon Institute of Business Science. In July 2012 he will be Assistant Professor of Management & Entrepreneurship at the Kelly School of Business at Indiana University.Research partners and Advisors
  16. 16. Daniel Saksenberg Actuary and specialist in predictive analytics Daniel Saksenberg specializes in machine learning and artificial intelligence. He has developed models for life insurance, forensics, anti-money laundering, offshore financial centers and transfer pricing. His models are use by corporations around the world. Paul Smith PhD Candidate in Entrepreneurship Paul Smith specializes in new firm performance predictive models. He completed his Masters in Entrepreneurship and is currently pursuing his PhD at the University of Pretoria. He has taught and worked with entrepreneurs at all levels from MBA students at WBS to micro-entrepreneurs in Alexandra township. He has founded 4 businesses in a diverse range of industries from Rowing Boat Manufacturing to Predictive Analytics. Akiva Beebe Technology Entrepreneur Akiva Beebee in a serial entrepreneur having founded 2 companies. Mediacor solutions an online e-learning platform. He is also a co-founder of WhyGuess, a company that drastically increases call center sales through an integrated cloud-computing tool that applies predictive analysis and artificial intelligence.Company Founders
  17. 17. 1 Lower your selection costs . 2 Improve your selection process 3 Adopt entrepreneurial assessment best practices 4 Benefit from 4 decades worth of research 5 Receive reports on the latest entrepreneurship research 6 Compare your entrepreneurs to the rest of the country 7 Keep track of all your programmes applicantsBenefits of using the SMEanalyst?
  18. 18. BASIC SELECT GOLD PLATINUM Free R5,000 per year R15,000 per year R50,000 per year Unlimited 500 screenings 1,500 screenings 5,000 screenings Easy-to-use web survey Easy-to-use web survey Easy-to-use web survey Easy-to-use web survey Instant score report Instant reports Instant reports Instant reports Only scores VC advisor reports VC adviser reports VC adviser reports No support Own Company Branding Own Company Branding Own Company Branding No branding Customer support Customer support Add own questions Annual research report Annual tracking report Customer support NPO and custom rates available on requestPricing & Plans SMEanalyst QuickScreen
  19. 19. 1 FutureScreen 2 SMEanalyst FullScreen with VCadvisor report 3 SMEanalyst screener training 4 Business Plan Competition Platform 5 SA largest longitudinal study on firm performance 6 LoanScreenProducts in development
  20. 20. 1 Largest research report on firm performance 2 Improve our understanding of the reasons entrepreneurs succeed 3 Help develop better training programs 4 Further improve our predictive ability 80% -> 90% 5 Help entrepreneur enablers be more impactful 6 Improve credit to high-growth entrepreneursLong term objectives
  21. 21. SMEANALYSTUsing artificial intelligence to screen and identifying high potential entrepreneurs