1. The SMEanalyst uses artificial intelligence to screen entrepreneurs through a 10 minute online questionnaire. 2. Predictive analytics then identify each entrepreneur's probability of business growth and survival. 3. Entrepreneurs and screeners are given access to a report with this information.

1. SMEANALYST
Using artificial intelligence to screen and identifying high potential entrepreneurs

2. Most studies done by traditional psychometric companies
1 have limited value due to poor or research methodology
Psychometrics and screening entrepreneurs

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 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. 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 power
Psychometrics and screening entrepreneurs

6. “There appears to be no discoverable pattern of personality characteristics that
distinguish 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 small
business.
• L. W. Busenitz and J. B. Barney, Differences Between Entrepreneurs and Managers in Large
Organizations, Journal of Business Venturing 12
• Johnston, K., Andersen, B., Davidge-Pitts, Ostensen-Saunders. (2009), Identifying Student Potential
for ICT Entrepreneurship using Myers-Briggs Personality Type indictors. Journal of Information
Technology Education.
• Lau, T. (1992), „The Incident Method - An Alternative Way of Studying Entrepreneurial
Behaviour‟, 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 of
Entrepreneurship, 1986

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 report
What is the SMEanalyst?

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. 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. 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. 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. Market Business
=
Opportunity Model
Probability of
Growth &
Entrepreneurial Survival
Relevant experience
Mindset &
& track record
Attitudes
How is probability of growth & survival assessed?

13. What does the free screening report look like?

14. What does the new screening report look like?

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. 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. 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 applicants
Benefits of using the SMEanalyst?

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 request
Pricing & Plans SMEanalyst QuickScreen

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 LoanScreen
Products in development

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 entrepreneurs
Long term objectives

21. SMEANALYST
Using artificial intelligence to screen and identifying high potential entrepreneurs