A Language to Foster Innovation

What to think of accelerating creative destruction, how a missing shared language for innovation hinders a discussion about that, and why sense-making frameworks help us remedy that. (Talk at SXSW, March 2019)

Transcript

1. A Language to Foster Innovation KP Frahm & Wolfgang Wopperer-Beholz March 8th | SXSW 2019
2. Klaus-Peter
 Head of Innovation Management,
 dpa Wolfgang
 Sense-maker 
 and facilitator,
 self-employed
3. So, innovation.
4. So, innovation. So, innovation. So, disruption
5. So, innovation. So, innovation. So, disruption So, disruption creative destruction
6. Average company lifespan on S&P 500 Index (in years) Year (each data point represents a rolling 7 year average of average lifespan) DATA: INNOSIGHT/Richard N. Foster/Standard & Poor’s Projec�ons based on current data Average company lifespan on S&P 500 Index (in years) Year (each data point represents a rolling 7 year average of average lifespan) DATA: INNOSIGHT/Richard N. Foster/Standard & Poor’s Projec�ons based on current data Average company lifespan on S&P 500 Index (in years) Year (each data point represents a rolling 7 year average of average lifespan) DATA: INNOSIGHT/Richard N. Foster/Standard & Poor’s Projec�ons based on current data Innosight Executive Brie!ng Winter 2012
7. So, innovation. So, disruption So, creative destruction
8. Data: Innosight analysis based on public S&P 500 data sources. See endnote on methodology. www.innosight.com Chart 1: Average Company Li fespan on S&P 500 Index Years, rolling 7-year average 0 5 10 15 20 25 30 35 40 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 Innosight 2018 Corporate Longevity Forecast
9. Data: Innosight analysis based on public S&P 500 data sources. See endnote on methodology. www.innosight.com Chart 1: Average Company Li fespan on S&P 500 Index Years, rolling 7-year average 0 5 10 15 20 25 30 35 40 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 Innosight 2018 Corporate Longevity Forecast
10. Data: Innosight analysis based on public S&P 500 data sources. See endnote on methodology. www.innosight.com Chart 1: Average Company Li fespan on S&P 500 Index Years, rolling 7-year average 0 5 10 15 20 25 30 35 40 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 Innosight 2018 Corporate Longevity Forecast
11. Exhibit 2: Turnover in the S&P 500 Index, 1958-2016 Source: 1958-1990: Jeremy Siegel, “Long-Term Returns on the Original S&P 500 Companies,” Financial Analysts Journal, Vol. 62, No. 1, January/February 2006, 18-31; 1991-2016: FactSet, S&P Dow Jones Indices, Credit Suisse. 0 10 20 30 40 50 60 0% 2% 4% 6% 8% 10% 12% 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Number of Changes Turnover Trend line Michael J. Mauboussin, Dan Callahan, Darius Majd: “Corporate Longevity. Index Turnover and Corporate Performance”
12. Exhibit 2: Turnover in the S&P 500 Index, 1958-2016 Source: 1958-1990: Jeremy Siegel, “Long-Term Returns on the Original S&P 500 Companies,” Financial Analysts Journal, Vol. 62, No. 1, January/February 2006, 18-31; 1991-2016: FactSet, S&P Dow Jones Indices, Credit Suisse. 0 10 20 30 40 50 60 0% 2% 4% 6% 8% 10% 12% 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Number of Changes Turnover Trend line Michael J. Mauboussin, Dan Callahan, Darius Majd: “Corporate Longevity. Index Turnover and Corporate Performance”
13. !
14. Exhibit 2: Turnover in the S&P 500 Index, 1958-2016 Source: 1958-1990: Jeremy Siegel, “Long-Term Returns on the Original S&P 500 Companies,” Financial Analysts Journal, Vol. 62, No. 1, January/February 2006, 18-31; 1991-2016: FactSet, S&P Dow Jones Indices, Credit Suisse. 0 10 20 30 40 50 60 0% 2% 4% 6% 8% 10% 12% 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Number of Changes Turnover Trend line Michael J. Mauboussin, Dan Callahan, Darius Majd: “Corporate Longevity. Index Turnover and Corporate Performance”
15. Exhibit 2: Turnover in the S&P 500 Index, 1958-2016 Source: 1958-1990: Jeremy Siegel, “Long-Term Returns on the Original S&P 500 Companies,” Financial Analysts Journal, Vol. 62, No. 1, January/February 2006, 18-31; 1991-2016: FactSet, S&P Dow Jones Indices, Credit Suisse. 0 10 20 30 40 50 60 0% 2% 4% 6% 8% 10% 12% 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Number of Changes Turnover Trend line Exhibit 3: Hypothetical Turnover in the S&P 500 Index, 1958-2016 Source: Credit Suisse. 0 10 20 30 40 50 60 0% 2% 4% 6% 8% 10% 12% 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Number of Changes Turnover Trend line Michael J. Mauboussin, Dan Callahan, Darius Majd: “Corporate Longevity. Index Turnover and Corporate Performance”
16. Exhibit 2: Turnover in the S&P 500 Index, 1958-2016 Source: 1958-1990: Jeremy Siegel, “Long-Term Returns on the Original S&P 500 Companies,” Financial Analysts Journal, Vol. 62, No. 1, January/February 2006, 18-31; 1991-2016: FactSet, S&P Dow Jones Indices, Credit Suisse. 0 10 20 30 40 50 60 0% 2% 4% 6% 8% 10% 12% 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Number of Changes Turnover Trend line Exhibit 3: Hypothetical Turnover in the S&P 500 Index, 1958-2016 Source: Credit Suisse. 0 10 20 30 40 50 60 0% 2% 4% 6% 8% 10% 12% 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Number of Changes Turnover Trend line Michael J. Mauboussin, Dan Callahan, Darius Majd: “Corporate Longevity. Index Turnover and Corporate Performance”
17. Exhibit 2: Turnover in the S&P 500 Index, 1958-2016 Source: 1958-1990: Jeremy Siegel, “Long-Term Returns on the Original S&P 500 Companies,” Financial Analysts Journal, Vol. 62, No. 1, January/February 2006, 18-31; 1991-2016: FactSet, S&P Dow Jones Indices, Credit Suisse. 0 10 20 30 40 50 60 0% 2% 4% 6% 8% 10% 12% 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Number of Changes Turnover Trend line Michael J. Mauboussin, Dan Callahan, Darius Majd: “Corporate Longevity. Index Turnover and Corporate Performance”
18. Exhibit 6: S&P 500 Turnover, 1990-2016 Source: Thomson Reuters; S&P Dow Jones Indices; Credit Suisse. 0% 2% 4% 6% 8% 10% 12% 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Annual Turnover S&P 500 Turnover Michael J. Mauboussin, Dan Callahan, Darius Majd: “Corporate Longevity. Index Turnover and Corporate Performance”
19. Exhibit 6: S&P 500 Turnover, 1990-2016 Source: Thomson Reuters; S&P Dow Jones Indices; Credit Suisse. 0% 2% 4% 6% 8% 10% 12% 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Annual Turnover S&P 500 Turnover Michael J. Mauboussin, Dan Callahan, Darius Majd: “Corporate Longevity. Index Turnover and Corporate Performance” Exhibit 6: S&P 500 Turnover and U.S. M&A Volume, 1990-2016 Source: Thomson Reuters; S&P Dow Jones Indices; Credit Suisse. 0% 2% 4% 6% 8% 10% 12% 0.0 0.5 1.0 1.5 2.0 2.5 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Annual Turnover Volume (Trillions of 2015 U.S Dollars) U.S. M&A Volume S&P 500 Turnover
20. Will the real problem please stand up?
21. Percentage of Exits 0 % 25 % 50 % 75 % 100 % 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 VC exits via M&A via IPO M&A vs. IPOs Sources: Jay R. Ritter, University of Florida; National Venture Capital Association
22. Photo by Jesse Bowser on Unsplash Long-term Goals
23. Photo by Laura Ockel on Unsplash Different Paradigm
24. The real problem:
25. So, innovation. So, disruption So, creative destruction So, short-termism
26. Creative Destruction Accelerate Short- termism Decelerate /
27. Model 1 
 
 
 Model 2 
 
 / Model 1 Language 1 
 
 
 Model 2 Language 2 
 
 Model 1 Language 1 products
 businesses
 5- to 10-year business cycles
 Model 2 Language 2 
 
 Model 1 Language 1 products
 businesses
 5- to 10-year business cycles
 Model 2 Language 2 business models
 paradigms
 50- to 70-year long waves
28. Complexity Photo by Brannon Naito on Unsplash
29. Different interests
30. Model 3 Language 3 
 
 
 Model 4 Language 4 
 
 / Model 3 Language 3 Value for users
 Quality of design
 Focus on retention
 Model 4 Language 4 Value of customers
 Quality of forecasts
 Focus on conversion
31. Help? http://zyzixun.net/image-download/3141703.html
32. Controlled Vocabulary?
33. Photo by JC Gellidon on Unsplash Photo by Olga Guryanova on Unsplash Photo by Roman Mager on Unsplash Photo by Blake Guidry on Unsplash Photo by Cassie Matias on Unsplash
34. The limits of my language are the limits of my world. Ludwig Wittgenstein
35. Photo by Analise Benevides on Unsplash
36. Shared vocabulary Understanding Fixed vocabulary Exclusion /
37. Help? http://zyzixun.net/image-download/3141703.html
38. A shared language to talk about languages.
39. Sense-making frameworks: meta-languages to develop 
 specific models and languages.
40. https://en.wikipedia.org/wiki/Cyne!n_framework http://www.storycoloredglasses.com/p/con#uence-sensemaking-framework.html https://labs.spotify.com/2014/03/27/spotify-engineering-culture-part-1/ http://donellameadows.org/systems-thinking-resources/ https://www.#ickr.com/photos/jurgenappelo/5201864328 http://wulrich.com/csh.html
41. Sense-making frameworks 
 open discussion, pull apart assumptions, and surface problems. Cynthia Kurtz
42. https://www.researchgate.net/publication/220231316_A_concept_geometry_for_conceptual_spaces Conceptual Spaces Black White Green Red Yellow Blue bitter salty sour sweet Depth Length Height
43. https://nma.vc Tools for everyday use
44. A sense-making framework for product innovation:
45. The Product Field.
46. inside outside purpose implementation Introduction Realization
48. purpose on the inside
49. implementation on the inside
50. implementation on the outside
51. purpose on the outside
53. The Product Field
54. Developers Executives Product Managers Designers Make the right decisions Create successful products No shared language The Product Field
55. Developers Executives Product Managers Designers Make the right decisions Create successful products No shared language The Product Field
56. Developers Executives Product Managers Designers Make the right decisions Create successful products No shared language The Product Field Startups Enterprises Busines Model Canvas Trainings Website Sense- making framework Canvas Ignoring complexity Better Products Better world Wolfgang Mark Nick Increasing complexity Digitalations Method Develop- ment Facilitation Conferences Includes all stake- holders
57. Developers Executives Product Managers Designers Make the right decisions Create successful products No shared language The Product Field Startups Enterprises Busines Model Canvas Trainings Website Sense- making framework Canvas Ignoring complexity Better Products Better world Wolfgang Mark Nick Increasing complexity Digitalations Method Develop- ment Facilitation Conferences Includes all stake- holders
58. Rinse and repeat.
59. Some examples:
60. „There seems to be a problem in the upper-left, again.“
65. „Let’s take a look at the context again.“
68. solution
69. problem
70. alternatives
72. „Are we doing idea push 
 or value pull?“
77. A tool to create alignment and buy-in.
78. A tool to think and act autonomously.
79. A language to foster innovation: a meta-language, embodied in a sense-making framework for everyday use.
80. Use it with your team, with your stakeholders, on a regular basis, to think for yourself.
81. (At least not over innovation.) https://knowyourmeme.com/photos/1022354-the-hitchhikers-guide-to-the-galaxy
82. Book signing: 2 pm, SXSW Book Shop Product Thinking Meetup: 3/12, 11 am https://productfield.com @productfield @kpfrahm @wowo101