Archive for the ‘Business’ Category

Metrics, Stocks, Shares, and Secure Ledger Accounts for Living Capital: Getting the Information into the Hands of Individual Decision Makers

August 30, 2018

Individual investments in, and returns from, shares of various kinds of human, social, and natural capital stocks will be tracked in secure online accounting ledgers, often referred to generically using the Blockchain brand name. A largely unasked and unanswered question is just what kind of data would best be tracked in secure ledgers. To be meaningful, entries in such accounts will have to stand for something real in the world that is represented in a common language interpretable to anyone capable of reading the relevant signs and symbols. Since we are talking about amounts of things that vary, measurement will unavoidably be a factor.

High quality measurement is essential to the manageability and profitability of investments of all kinds, whether in manufactured capital and property, or in literacy, numeracy, mental and physical health, sociability, and environmental quality (human, social, and natural capital). The measurability and manageability of these intangible factors has achieved significant levels of scientific precision and rigor over the last 90 and more years.

This development is of increasing interest to economists and accountants who have long envisioned ways of reinventing capitalism that do not assume the only alternative is some form of socialism or communism (see references listed below). Many of today’s economic problems may follow from capitalism’s incompleteness. More specifically, we may be suffering from the way in which manufactured capital alone has been been brought to life, economically speaking, while human, social, and natural capital have not (Fisher, 2002, 2007, 2009a/b, 2010a/b, 2011a/b, 2012ab, 2014, etc.).

One in particular who speaks directly to an essential issue that must be addressed in creating an economy of authentic wealth and genuine productivity is Paul Hawken (2007, pp. 21-22), who says that Friedrich Hayek foresaw

“a remedy for the basic expression of the totalitarian impulse: ensuring that information and the right to make decisions are co-located. To achieve this, one can either move the information to the decision makers, or move decision making rights to the information. The movement strives to do both. The earth’s problems are everyone’s problems, and what modern technology and the movement can achieve together is to distribute problem solving tools.”

Hayek (1945, 1948, 1988; Frantz & Leeson, 2013) is well known for his focus on a distinction between a mechanical definition of individuals as uniform and homogenous, and a more vital sense of economic “true individuals” as complex and interdependent. To create efficient markets for the production of authentic wealth, we need to figure out how to extend the “true individuals” of manufactured capital markets into new markets for human, social, and natural capital (Fisher, 2014).

The distributed problem solving tools we need to support the decision making of “true” individuals are secure online ledgers accounting for investments in measured amounts of authentic wealth. Efficient markets are functions of individual processes that create wholes greater than their sums. The multiplier effect that makes this possible depends on transparent communication. Words, including number words, have to mean something specific and distinct. This is where the value of systematic measurement and metrology comes to bear. This is why we need an Intangible Assets Metric System.

For as long as economists have been concerned with markets, philosophers have been pointing out that society is an effect of shared symbol systems. In both cases, economists and philosophers are focused on the fact that it is only when people have a common language that an idea, a meme, can go viral, that a market can seem to have a mind of its own, and science can maintain an ever-increasing pace of technical innovation.

Our aim is to create the information that will populate the entries in the secure ledger accounts people use to track and manage their investments in literacy, numeracy, health, social, and natural capital. These entries will be posted right alongside their existing entries for investments in manufactured capital and property, which includes everything from groceries to autos to electronics to homes.

But the new ledger accounts will be different from today’s in important ways. Many current accounting entries are ultimately written off as costs producing untracked and unaccountable returns. We simply spend the money on groceries or school tuition or a doctor visit. The income is logged, and so are the expenses. We can see that, yes, buying groceries is an investment of a kind, since we profit from it by enjoying the processes of cooking, sharing, and eating tasty food, by avoiding hunger, and by sustaining good health.

Investments are tracked in a different way, though. Money is not just spent and kissed goodbye. Instead, investment funds are loaned to or leased by someone else who is expected to be able to increase the value of those funds. There are often no guarantees of an increase, but the invested value is associated with a proportionate share in the total value of the business. As the business grows or fails, so does the investment.

In much the same way, if we had the information available to us, we could track the returns on the investments we make in food, education, or health care. If we track the impacts of our dietary choices, we would be able to see if and when the investments we make result in healthy outcomes. The information brought to bear will have to include systematic advice relevant to one’s age, sex, pre-existing conditions, genetic propensities, etc. Additional information on the returns on one’s investments in a healthy diet should also be made available, as might be found in the expected income or expenses associated with the consequences of what is eaten, and how much of it. Sometimes there will be room for improvement, for example, if the foods we eat are too sugary or fatty, or if we eat too much. Other times, maintaining a healthy, varied diet may be all that is needed to see a consistent positive return on investment.

Public reports will allow us all to learn from one another. The ability to communicate in a common language and to see what has worked for others will enable everyone to experiment with new ways of doing things. People with common food interests or problems, for instance, will be able quickly evaluate the relevance and benefits of other people’s approaches or solutions. Because of the ways in which communication and community go together, it may be reasonable to hope that new levels of innovation, diversity, tolerance, and respect will follow.

Many aspects of work, education and health care are already undergoing transformations that move their processes out of the usual office, school and hospital environments. These changes will be accelerated as distributed network effects take hold in each of these various markets.

It is easy to see how the Internet of things may evolve to be the medium in which we manage relationships of all kinds, from education and school to health and safety to work and career. Secure ledgers immune from hacking will be essential. And an important health factor will be to know how much relationship management is enough, and when it’s time to get out into the world. That balancing factor will be a key aspect of a successful approach to connecting information on authentic wealth with the individual decision makers growing it and living it.

References

Andriessen, D. (2003). Making sense of intellectual capital: Designing a method for the valuation of intangibles. Oxford, England: Butterworth-Heinemann.

Anielski, M. (2007). The economics of happiness: Building genuine wealth. Gabriola, British Columbia: New Society Publishers.

Cadman, D. (1986). Money as if people mattered. In P. Ekins &  Staff of The Other Economic Summit (Eds.), The living economy: A new economics in the making (pp. 204-210). London: Routledge & Kegan Paul.

Eisler, R. (2007). The real wealth of nations: Creating a caring economics. San Francisco, California: Berrett-Koehler Publishers, Inc.

Ekins, P. (1992). A four-capital model of wealth creation. In P. Ekins & M. Max-Neef (Eds.), Real-life economics: Understanding wealth creation (pp. 147-155). London: Routledge.

Ekins, P. (1999). Economic growth and environmental sustainability: The prospects for green growth. New York: Routledge.

Ekins, P., Dresner, S., & Dahlstrom, K. (2008, March/April). The four-capital method of sustainable development evaluation. European Environment, 18(2), 63-80.

Ekins, P., Hillman, M., & Hutchison, R. (1992). The Gaia atlas of green economics (Foreword by Robert Heilbroner). New York: Anchor Books.

Ekins, P., & Max-Neef, M. A. (Eds.). (1992). Real-life economics: Understanding wealth creation. London: Routledge.

Ekins, P., & Voituriez, T. (2009). Trade, globalization and sustainability impact assessment: A critical look at methods and outcomes. London, England: Earthscan Publications Ltd.

Fisher, W. P., Jr. (2002, Spring). “The Mystery of Capital” and the human sciences. Rasch Measurement Transactions, 15(4), 854 [http://www.rasch.org/rmt/rmt154j.htm].

Fisher, W. P., Jr. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-1093 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009a, November). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287.

Fisher, W. P., Jr. (2009b). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (Tech. Rep., http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P., Jr. (2010a). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital., Bridge to Business Postdoctoral Certification, Freeman School of Business, Tulane University (p. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2340674).

Fisher, W. P., Jr. (2010b, 13 January). Reinventing capitalism: Diagramming living capital flows in a green, sustainable, and responsible economy. Retrieved from LivingCapitalMetrics.com: https://livingcapitalmetrics.wordpress.com/2010/01/13/reinventing-capitalism/.

Fisher, W. P., Jr. (2011a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), 49-66.

Fisher, W. P., Jr. (2011b). Measuring genuine progress by scaling economic indicators to think global & act local: An example from the UN Millennium Development Goals project. LivingCapitalMetrics.com. Retrieved 18 January 2011, from Social Science Research Network: http://ssrn.com/abstract=1739386.

Fisher, W. P., Jr. (2012a). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012b, May/June). What the world needs now: A bold plan for new standards [Third place, 2011 NIST/SES World Standards Day paper competition]. Standards Engineering, 64(3), 1 & 3-5 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr. (2014, Autumn). The central theoretical problem of the social sciences. Rasch Measurement Transactions, 28(2), 1464-1466.

Frantz, R., & Leeson, R. (Eds.). (2013). Hayek and behavioral economics. (Archival Insights Into the Evolution of Economics). New York: Palgrave Macmillan.

Gleeson-White, J. (2015). Six capitals, or can accountants save the planet? Rethinking capitalism for the 21st century. New York: Norton.

Greider, W. (2003). The soul of capitalism: Opening paths to a moral economy. New York: Simon & Schuster.

Griliches, Z. (1994, March). Productivity, R&D, and the data constraint. American Economic Review, 84(1), 1-23.

Grootaert, C. (1998). Social capital: The missing link? (Vol. 3). Social Capital Intiative Working Paper). Washington, D.C.: The World Bank.

Hand, J. R. M., & Lev, B. (Eds.). (2003). Intangible assets: Values, measures, and risks. Oxford Management Readers). Oxford, England: Oxford University Press.

Hart, S. L. (2005). (2007). Capitalism at the crossroads: Aligning business, earth, and humanity (Foreword by Al Gore) (2nd ed.). Wharton School Publishing.

Hawken, P. (1993). The ecology of commerce: A declaration of sustainability. New York: HarperCollins Publishers.

Hawken, P. (2007). Blessed unrest: How the largest movement in the world came into being and why no one saw it coming. New York: Viking Penguin.

Hayek, F. A. (1945, September). The use of knowledge in society. American Economic Review, 35, 519-530. (Rpt. in Individualism and economic order (pp. 77-91). Chicago: University of Chicago Press.)

Hayek, F. A. (1955). The counter revolution of science. Glencoe, Illinois: Free Press.

Hayek, F. A. (1988). The fatal conceit: The errors of socialism (W. W. Bartley, III, Ed.) (Vol. I). The Collected Works of F. A. Hayek. Chicago: University of Chicago Press.

Korten, D. (2009). Agenda for a new economy: From phantom wealth to real wealth. San Francisco: Berret-Koehler Publishing.

Krueger, A. B. (Ed.). (2009). Measuring the subjective well-being of nations: National accounts of time use and well-being. National Bureau of Economic Research Conference Reports). Chicago, Illinois: University of Chicago Press.

Swann, G. M. P. (2001). “No Wealth But Life”: When does conventional wealth create Ruskinian wealth. European Research Studies, 4(3-4), 5-18.

Vemuri, A. W., & Costanza, R. (2006, 10 June). The role of human, social, built, and natural capital in explaining life satisfaction at the country level: Toward a National Well-Being Index. Ecological Economics, 58(1), 119-133.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

Self-Sustaining Sustainability, Once Again, Already

August 12, 2018

The urgent need for massive global implementations of sustainability policies and practices oddly and counterproductively has not yet led to systematic investments in state of the art sustainability metric standards. My personal mission is to contribute to meeting this need. Longstanding, proven resources in the art and science of precision instrumentation calibration and explanatory theory are available to address these problems. In the same way technical standards for measuring length, mass, volume, time, energy, light, etc. enable the coordination of science and commerce for manufactured capital and property, so, too, will a new class of standards for measuring human, social, and natural capital.

This new art and science contradicts common assumptions in three ways. First, contrary to popular opinion that measuring these things is impossible, over 90 years of research and practice support a growing consensus among weights and measures standards engineers (metrologists) and social and psychological measurement experts that relevant unit standards are viable, feasible, and desirable.

Common perceptions are contradicted in a second way in that measurement of this kind does not require reducing human individuality to homogenized uniform sameness. Instead of a mechanical metaphor of cogs in a machine, the relevant perspective is an organic or musical one. The goal is to ensure that local uniqueness and creative improvisations are freely expressed in a context informed by shared standards (like DNA, or a musical instrument tuning system).

The third way in which much of what we think we know is mistaken concerns how to motivate adoption of sustainability policies and practices. Many among us are fearful that neither the general population nor its leaders in government and business care enough about sustainability to focus on implementing solutions. But finding the will to act is not the issue. The problem is how to create environments in which new sustainable forms of life multiply and proliferate of their own accord. To do this, people need means for satisfying their own interests in life, liberty, and the pursuit of happiness. The goal, therefore, is to organize knowledge infrastructures capable of informing and channeling the power of individual self-interest. The only way mass scale self-sustaining sustainable economies will ever happen is by tapping the entrepreneurial energy of the profit motive, where profit is defined not just in financial terms but in the quality of life and health terms of authentic wealth and genuine productivity.

We manage what we measure. If we are to collectively, fluidly, efficiently, and innovatively manage the living value of our human, social, and natural capital, we need, first, high quality information expressed in shared languages communicating that value. Second, we need, to begin with, new scientific, legal, economic, financial, and governmental institutions establishing individual rights to ownership of that value, metric units expressing amounts of that value, conformity audits for ascertaining the accuracy and precision of those units, financial alignments of the real value measured with bankable dollar amounts, and investment markets to support entrepreneurial innovations in creating that value.

The end result of these efforts will be a capacity for all of humanity to pull together in common cause to create a sustainable future. We will each be able to maximize our own personal potential at the same time we contribute to the greater good. We will not only be able to fulfill the potential of our species as stewards of the earth, we will have fun doing it! For technical information resources, see below. PDFs are available on request, and can often be found freely available online.

Self-Sustaining Sustainability

Relevant Information Resources

William P. Fisher, Jr., Ph.D.

Barney, M., & Fisher, W. P., Jr. (2016). Adaptive measurement and assessment. Annual Review of Organizational Psychology and Organizational Behavior, 3, 469-490.

Fisher, W. P., Jr. (1997). Physical disability construct convergence across instruments: Towards a universal metric. Journal of Outcome Measurement, 1(2), 87-113.

Fisher, W. P., Jr. (1999). Foundations for health status metrology: The stability of MOS SF-36 PF-10 calibrations across samples. Journal of the Louisiana State Medical Society, 151(11), 566-578.

Fisher, W. P., Jr. (2000). Objectivity in psychosocial measurement: What, why, how. Journal of Outcome Measurement, 4(2), 527-563.

Fisher, W. P., Jr. (2002). “The Mystery of Capital” and the human sciences. Rasch Measurement Transactions, 15(4), 854 [http://www.rasch.org/rmt/rmt154j.htm].

Fisher, W. P., Jr. (2003). The mathematical metaphysics of measurement and metrology: Towards meaningful quantification in the human sciences. In A. Morales (Ed.), Renascent pragmatism: Studies in law and social science (pp. 118-153). Brookfield, VT: Ashgate Publishing Co.

Fisher, W. P., Jr. (2004). Meaning and method in the social sciences. Human Studies: A Journal for Philosophy & Social Sciences, 27(4), 429-454.

Fisher, W. P., Jr. (2007). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-1093 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009, November 19). Draft legislation on development and adoption of an intangible assets metric system. Living Capital Metrics blog: https://livingcapitalmetrics.wordpress.com/2009/11/19/draft-legislation/.

Fisher, W. P., Jr. (2009). Invariance and traceability for measures of human, social, and natural capital. Measurement, 42(9), 1278-1287.

Fisher, W. P., Jr. (2009). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P., Jr. (2010, 22 November). Meaningfulness, measurement, value seeking, and the corporate objective function: An introduction to new possibilities. LivingCapitalMetrics.com, Sausalito, California.

Fisher, W. P., Jr. (2010). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital. Bridge to Business Postdoctoral Certification, Freeman School of Business, Tulane University (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2340674).

Fisher, W. P., Jr. (2010). The standard model in the history of the natural sciences, econometrics, and the social sciences. Journal of Physics Conference Series, 238(1), 012016.

Fisher, W. P., Jr. (2011). Bringing human, social, and natural capital to life: Practical consequences and opportunities. In N. Brown, B. Duckor, K. Draney & M. Wilson (Eds.), Advances in Rasch Measurement, Vol. 2 (pp. 1-27). Maple Grove, MN: JAM Press.

Fisher, W. P., Jr. (2012). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012). What the world needs now: A bold plan for new standards [Third place, 2011 NIST/SES World Standards Day paper competition]. Standards Engineering, 64(3), 1 & 3-5 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr. (2015). A probabilistic model of the law of supply and demand. Rasch Measurement Transactions, 29(1), 1508-1511 [http://www.rasch.org/rmt/rmt291.pdf].

Fisher, W. P., Jr. (2015). Rasch measurement as a basis for metrologically traceable standards. Rasch Measurement Transactions, 28(4), 1492-1493 [http://www.rasch.org/rmt/rmt284.pdf].

Fisher, W. P., Jr. (2015). Rasch metrology: How to expand measurement locally everywhere. Rasch Measurement Transactions, 29(2), 1521-1523.

Fisher, W. P., Jr. (2017, September). Metrology, psychometrics, and new horizons for innovation. 18th International Congress of Metrology, Paris, 10.1051/metrology/201709007.

Fisher, W. P., Jr. (2017). A practical approach to modeling complex adaptive flows in psychology and social science. Procedia Computer Science, 114, 165-174.

Fisher, W. P., Jr. (2018). How beauty teaches us to understand meaning. Educational Philosophy and Theory, in review.

Fisher, W. P., Jr. (2018). Separation theorems in econometrics and psychometrics: Rasch, Frisch, two Fishers, and implications for measurement. Scandinavian Economic History Review, in review.

Fisher, W. P., Jr., Harvey, R. F., & Kilgore, K. M. (1995). New developments in functional assessment: Probabilistic models for gold standards. NeuroRehabilitation, 5(1), 3-25.

Fisher, W. P., Jr., Harvey, R. F., Taylor, P., Kilgore, K. M., & Kelly, C. K. (1995). Rehabits: A common language of functional assessment. Archives of Physical Medicine and Rehabilitation, 76(2), 113-122.

Fisher, W. P., Jr., & Stenner, A. J. (2011, January). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series).National Science Foundation: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011, August 31 to September 2). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

Fisher, W. P., Jr., & Stenner, A. J. (2016). Theory-based metrological traceability in education: A reading measurement network. Measurement, 92, 489-496.

Fisher, W. P., Jr., & Wilson, M. (2015). Building a productive trading zone in educational assessment research and practice. Pensamiento Educativo: Revista de Investigacion Educacional Latinoamericana, 52(2), 55-78.

Pendrill, L., & Fisher, W. P., Jr. (2013). Quantifying human response: Linking metrological and psychometric characterisations of man as a measurement instrument. Journal of Physics Conference Series, 459, 012057.

Pendrill, L., & Fisher, W. P., Jr. (2015). Counting and quantification: Comparing psychometric and metrological perspectives on visual perceptions of number. Measurement, 71, 46-55.

 

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

Self-Sustaining Sustainability

August 6, 2018

After decades of efforts and massive resources expended in trying to create a self-sustaining sustainable economy, perhaps it is time to wonder if we are going about it the wrong way. There seems to be truly significant and widespread desire for change, but the often inspiring volumes of investments and ingenuity applied to the problem persistently prove insufficient to the task. Why?

I’ve previously and repeatedly explained how finding the will to change is not the issue. This time I’ll approach my proposed solution in a different way.

Q: How do we create a self-sustaining sustainable economy?

A: By making sustainability profitable in monetary terms as well as in the substantive real terms of the relationships we live out with each other and the earth. Current efforts in this regard focus solely on reducing energy costs enough to compensate for investments in advancing the organizational mission. We need far more comprehensively designed solutions than that.

Q: How do we do that?

A: By financially rewarding improved sustainability at every level of innovation, from the individual to the community to the firm.

Q: How do we do that?

A: By instituting rights to the ownership of human, social, and natural capital properties, and by matching the demand for sustainability with the supply of it in a way that will inform arbitrage and pricing.

Q: How do we do that?

A: By lowering the cost of the information needed to be able to know how many shares of human, social, and natural capital stocks are owned, and to match demand with supply.

Q: How could that be done?

A: By investing as a society in improving the quality and distribution of the available information.

Q: What does that take?

A: Creating dependable and meaningful tools for ascertaining the quantity, quality, and type of sustainability impacts on human, social, and natural capital being offered.

Q: Can that be done?

A: The technical art and science of measurement needed for creating these tools is well established, having been in development for almost 100 years.

Q: How do we start?

A: An important lesson of history is that building the infrastructure and its array of applications follows in the wake of, and cannot precede, the institution of the constitutional ideals. We must know what the infrastructure and applications will look like in their general features, but nothing will ever be done if we think we have to have them in place before instantiating the general frame of reference. The most general right to own legal title to human, social, and natural capital can be instituted, and the legal status of new metric system units can be established, before efforts are put into unit standards, traceability processes, protocols for intralaboratory ruggedness tests and interlaboratory round robin trials, conformity assessments, etc.

Q: It sounds like an iterative process.

A: Yes, one that must attend from the start to the fundamental issues of information coherence and complexity, as is laid out in my recent work with Emily Oon, Spencer Benson, Jack Stenner, and others.

Q: This sounds highly technical, utilitarian, and efficient. But all the talk of infrastructure, standards, science, and laboratories sounds excessively technological. Is there any place in this scheme for ecological values, ethics, and aesthetics? And how are risk and uncertainty dealt with?

A: We can take up each of these in turn.

Ecological values: To use an organic metaphor, we know the DNA of the various human, social, and natural capital forms of life, or species, and we know their reproductive and life cycles, and their ecosystem requirements. What we have not done is to partner with each of these species in relationships that focus on maximizing the quality of their habitats, their maturation, and the growth of their populations. Social, psychological, and environmental relationships are best conceived as ecosystems of mutual interdependencies. Being able to separate and balance within-individual, between-individual, and collective levels of complexity in these interdependencies will be essential to the kinds of steward leadership needed for creating and maintaining new sociocognitive ecosystems. Our goal here is to become the change we want to institute, since caterpillar to butterfly metamorphoses come about only via transformations from within.

Ethics: The motivating intention is to care simultaneously and equally effectively for both individual uniqueness and global humanity. In accord with the most fundamental ethical decision, we choose discourse over violence, and we do so by taking language as the model for how things come into words. Language is itself alive in the sense of the collective processes by which new meanings come into it. Language moreover has the remarkable capacity of supporting local concrete improvisations and creativity at the same time that it provides navigable continuity and formal ideals. Care for the unity and sameness of meaning demands a combination of rigorous conceptual determinations embodied in well-defined words with practical applications of those words in local improvisations. That is how we support the need to make decisions with inevitably incomplete and inconsistent information while not committing the violence of the premature conclusion. The challenge is one of finding a balance between openness and boundaries that allows language and our organizational cultures to be stable while also evolving. Our technical grasp of complex adaptive systems, autopoiesis, and stochastic measurement information models is advanced enough to meet these ethical requirements of caring for ourselves, each other, and the earth.

Aesthetics: An aesthetic desire for and love of beauty roots the various forms of life inhabiting diverse niches in the proposed knowledge ecosystem and information infrastructure, and does so in the ground of the ethical choice of discourse and meaning over violence. The experience of beauty teaches us how to understand meaning. The attraction to beauty is a unique human phenomenon because it combines apparent opposites into a single complex feeling. Even when the object of desire is possessed as fully as possible, desire is not eliminated, and even when one feels the object of desire to be lost or completely out of touch, its presence and reality is still felt. So, too, with meaning: no actual instance of anything in the world ever embodies the fullness of an abstract conceptual ideal. This lesson of beauty is perhaps most plainly conveyed in music, where artists deliberately violate the standards of instrument tuning to create fascinating and absorbing combinations of harmony and dissonance from endlessly diverse ensembles. Some tunings persist beyond specific compositions to become immediately identifiable trademark sounds. In taking language as a model, the aesthetic combination of desire and possession informs the ethics of care for the unity and sameness of meaning, and vice versa. And ecological values, ethics, and aesthetics stand on par with the technical concerns of calibration and measurement.

Risk and uncertainty: Calibrating a tool relative to a unit standard is by itself already a big step toward reducing uncertainty and risk. Instead of the chaos of dozens of disconnected sustainability indicators, or the cacophony of hundreds or thousands of different tests, assessments, or surveys measuring the same things, we will have data and theory supporting interpretation of reproducible patterns. These patterns will be, and in many cases already are, embodied in instruments that further reduce risk by defining an invariant unit of comparison, simplifying interpretation, reducing opportunities for mistakes, by quantifying uncertainty, and by qualifying it in terms of the anomalous exceptions that depart from expectations. Each of these is a special feature of rigorously defined measurement that will eventually become the expected norm for information on sustainability.

For more on these themes, see my other blog posts here, my various publications, and my SSRN page.

 

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

Differences between today’s sustainability metrics and the ones needed for low cost social value transactions and efficient markets for intangible assets

November 16, 2017

Measurement is such a confusing topic! Everyone proclaims how important it is, but almost no one ever seeks out and implements the state of the art, despite the enormous advantages to be gained from doing so.

A key metric quality issue concerns the cumbersome and uninterpretable masses of data that well-intentioned people can hobble themselves with when they are interested in improving their business processes and outcomes. They focus on what they can easily count, and then they wrongly (at great but unrecognized cost) misinterpret the counts and percentages as measures.

For instance, today’s sustainability and social value indicators are each expressed in a different unit (dollars, hours, tons, joules, kilowatt hours, survey ratings, category percentages, etc.; see below for a sample list). Some of them may indeed be scientific measures of that individual aspect of the business. The problem is they are all being interpreted in an undefined and chaotic aggregate as a measure of something else (social value, sustainability, etc.). Technically speaking, if we want a scientific measure of that higher order construct, we need to model it, estimate it, calibrate it, and deploy it as a common language in a network of instruments all traceable to a common unit standard.

All of this is strictly parallel with what we do to make markets in bushels of corn, barrels of oil, and kilowatts of electricity. We don’t buy produce by count in the grocery store because unscrupulous merchants would charge the same amount for small fruits as for large. All of the scales in grocery store produce markets measure in the same unit, and all of the packages of food are similarly marked in standard units of weight and volume so we can compare prices and value.

There are a lot of advantages to taking the trouble to extend this system to social value. I suppose every one of these points could be a chapter in a book:

  • First, investing in scientific measurement reduces data volume to a tiny fraction of what we start with, not only with no loss of information but with the introduction of additional information telling us how confident we can be in the data and exactly what the data specifically mean (see below). That is, all the original information is recoverable from the calibrated measure, which is also qualified with an uncertainty range and a consistency statistic. Inconsistencies can be readily identified and acted on at individual levels.
  • Now the numbers represent something that adds up the way they do, instead of standing for the unknown, differing, and uncontrolled units used in the original counts and percentages.
  • We can take missing data into account, which means we can adapt the indicators used in different situations to specific circumstances without compromising comparability.
  • We know how to gauge the dependability of the data better, meaning that we will not be over-confident about unreliable data, and we won’t waste our time and resources obtaining data of greater precision than we actually need.
  • Furthermore, the indicators themselves are now scaled into a hierarchy that maps the continuum from low to high performance. This map points the way to improvement. The order of things on the scale shows what comes first and how more complex and difficult goals build on simpler and easier ones. The position of a measure on the scale shows what’s been accomplished, what remains to be done, and what to do next.
  • Finally, we have a single metric we can use to price value across the local particulars of individual providers. This is where it becomes possible to see who gives the most bang for the buck, to reward them, to scale up an expanded market for the product, and to monetize returns on investment.

The revolutionary network effects of efficient markets are produced by the common currencies for the exchange of value that emerge out of this context. Improvements rebalancing cost and quality foster deflationary economies that drive more profit from lower costs (think Moore’s law). We gain the efficiency of dramatic reductions in data volume, and the meaningfulness of numbers that stand for something substantively real in the world that we can act on. These combine to lower the cost of transactions, as it now becomes vastly less expensive to find out how much of the social good is available, and what quality it is. Instead of dozens or hundreds of indicators repeated for each company in an industry, and repeated for each division in each company, and all of these repeated for each year or quarter, we have access to all of that information properly contextualized in a succinct, meaningful, and interpretable format for different applications at individual, organizational, industry-wide, national, regional, or global levels of complexity.

That’s likely way too much to digest at once! But it seemed worth saying it all at once in one place, in case anyone might be motivated to get in touch or start efforts in this direction on their own.

Examples of the variety of units in a handy sustainability metrics spreadsheet can be found at the Hess web site (http://www.hess.com/sustainability/performance-data/key-sustainability-metrics): freshwater use in millions or thousands of cubic meters, solid waste and carbon emissions in thousands of tons, natural gas consumption in thousands of gigajoules, electricity consumption in thousands of kilowatt hours; employee union members, layoffs, and turnover as percentages; employee lost time incident rates in hundreds of thousands of hours worked, percentages of female or minority board members, dollars for business performance.

These indicators are chosen with good reasons for use within each specific area of interest. They comprise an intuitive observation model that has face validity. But this is only the start of the work that needs to be done to create the metrics we need if we are to radically multiply the efficiency of social value markets. For an example of how to work from today’s diverse arrays of social value indicators (where each one is presented in its own spreadsheet) toward more meaningful, adaptable, and precise measures, see:

Fisher, W. P., Jr. (2011). Measuring genuine progress by scaling economic indicators to think global & act local: An example from the UN Millennium Development Goals project. LivingCapitalMetrics.com. Social Science Research Network: http://ssrn.com/abstract=1739386 .

Living Capital Metrics for Financial and Sustainability Accounting Standards

May 1, 2015

I was very happy a few days ago to come across Jane Gleeson-White’s new book, Six Capitals, or Can Accountants Save the Planet? Rethinking Capitalism for the 21st Century. The special value for me in this book comes in the form of an accessible update on what’s been going on in the world of financial accounting standards. Happily, there’s been a lot of activity (check out, for instance, Amato & White, 2013; Rogers & White, 2015). Less fortunately, the activity seems to be continuing to occur in the same measurement vacuum it always has, despite my efforts in this blog to broaden the conversation to include rigorous measurement theory and practice.

But to back up a bit, recent events around sustainability metric standards don’t seem to be connected to previous controversies around financial standards and economic modeling, which were more academically oriented to problems of defining and expressing value. Gleeson-White doesn’t cite any of the extensive literature in those areas (for instance, Anielski, 2007; Baxter, 1979; Economist, 2010; Ekins, 1992, 1999; Ekins, Dresner, & Dahlstrom, 2008; Ekins, Hillman, & Hutchins, 1992; Ekins & Voituriez, 2009; Fisher, 2009b, 2009c, 2011; Young & Williams, 2010). Valuation is still a problem, of course, as is the analogy between accounting standards and scientific standards (Baxter, 1979). But much of the sensitivity of the older academic debate over accounting standards seems to have been lost in the mad, though well-intentioned, rush to devise metrics for the traditionally externalized nontraditional forms of capital.

Before addressing the thousands of metrics in circulation and the science that needs to be brought to bear on them (the ongoing theme of posts in this blog), some attention to terminology is important. Gleeson-White refers to six capitals (manufactured, liquid, intellectual, human, social, and natural), in contrast with Ekins (1992; Ekins, et al., 2008), who describes four (manufactured, human, social, and natural). Gleeson-White’s liquid capital is cash money, which can be invested in capital (a means of producing value via ongoing services) and which can be extracted as a return on capital, but is not itself capital, as is shown by the repeated historical experience in many countries of printing money without stimulating economic growth and producing value. Of her remaining five forms of capital, intellectual capital is a form of social capital that can satisfactorily be categorized alongside the other forms of organization-level properties and systems involving credibility and trust.

On pages 209-227, Gleeson-White takes up questions relevant to the measurement and information quality topics of this blog. The context here is informed by the International Integrated Reporting Council’s (IIRC) December 2013 framework for accounting reports integrating all forms of capital (Amato & White, 2013), and by related efforts of the Sustainability Accounting Standards Board (SASB) (Rogers & White, 2015). Following the IIRC, Gleeson-White asserts that

“Not all the new capitals can be quantified, yet or perhaps ever–for example, intellectual, human and social capital, much of natural capital–and so integrated reports are not expected to provide quantitative measures of each of the capitals.”

Of course, this opinion flies in the face of established evidence and theory accepted by both metrologists (weights and measures standards engineers and physicists) and psychometricians as to the viability of rigorous measurement standards for the outcomes of education, health care, social services, natural resource management, etc. (Fisher, 2009b, 2011, 2012a, 2012b; Fisher & Stenner, 2011a, 2013, 2015; Fisher & Wilson, 2015; Mari & Wilson, 2013; Pendrill, 2014; Pendrill & Fisher, 2013, 2015; Wilson, 2013; Wilson, Mari, Maul, & Torres Irribarra, 2015). Pendrill (2014, p. 26), an engineer, physicist, and past president of the European Association of National Metrology Institutes, for instance, states that “The Rasch approach…is not simply a mathematical or statistical approach, but instead [is] a specifically metrological approach to human-based measurement.” As is repeatedly shown in this blog, access to scientific measures sets the stage for a dramatic transformation of the potential for succeeding in the goal of rethinking capitalism.

Next, Gleeson-White’s references to several of the six capitals as the “living” capitals (p. 193) is a literal reference to the fact that human, social, and natural capital are all carried by people, organizations/communities, and ecosystems. The distinction between dead and living capital elaborated by De Soto (2000) and Fisher (2002, 2007, 2010b, 2011), which involves making any form of capital fungible by representing it in abstract forms negotiable in banks and courts of law, is not taken into account, though this would seem to be a basic requirement that must be fulfilled before the rethinking of capitalism could said to have been accomplished.

Gleeson-White raises the pointed question as to exactly how integrated reporting is supposed to provoke positive growth in the nontraditional forms of capital. The concept of an economic framework integrating all forms of capital relative to the profit motive, as described in Ekins’ work, for instance, and as is elaborated elsewhere in this blog, seems just over the horizon, though repeated mention is made of natural capitalism (Hawken, Lovins, & Lovins, 1999). The posing of the questions provided by Gleeson-White (pp. 216-217) is priceless, however:

“…given integrated reporting’s purported promise to contribute to sustainable development by encouraging more efficient resource allocation, how might it actually achieve this for natural and social capitals on their own terms? It seems integrated reporting does nothing to address a larger question of resource allocation….”

“To me the fact that integrated reporting cannot address such questions suggests that as with the example of human capital, its promise to foster efficient resource allocation pertains only to financial capital and not to the other capitals. If we accept that the only way to save our societies and planet is to reconceive them in terms of capital, surely the efficient valuing and allocation of all six capitals must lie at the heart of any economics and accounting for the planet’s scarce resources in the twenty-first century.
“There is a logical inconsistency here: integrated reporting might be the beginning of a new accounting paradigm, but for the moment it is being practiced by an old-paradigm corporation: essentially, one obliged to make a return on financial capital at the cost of the other capitals.”

The goal requires all forms of capital to be integrated into the financial bottom line. Where accounting for manufactured capital alone burns living capital resources for profit, a comprehensive capital accounting framework defines profit in terms of reduced waste. This is a powerful basis for economics, as waste is the common root cause of human suffering, social discontent and environmental degradation (Hawken, Lovins, & Lovins, 1999).

Multiple bottom lines are counter-productive, as they allow managers the option of choosing which stakeholder group to satisfy, often at the expense of the financial viability of the firm (Jensen, 2001; Fisher, 2010a). Economic sustainability requires that profits be legally, morally, and scientifically contingent on a balance of powers distributed across all forms of capital. Though the devil will no doubt lurk in the details, there is increasing evidence that such a balance of powers can be negotiated.

A key point here not brought up by Gleeson-White concerns the fact that markets are not created by exchange activity, but rather by institutionalized rules, roles, and responsibilities (Miller & O’Leary, 2007) codified in laws, mores, technologies, and expectations. Translating historical market-making activities as they have played out relative to manufactured capital in the new domains of human, social, and natural capital faces a number of significant challenges, adapting to a new way of thinking about tests, assessments, and surveys foremost among them (Fisher & Stenner, 2011b).

One of the most important contributions advanced measurement theory and practice (Rasch, 1960; Wright, 1977; Andrich, 1988, 2004; Fisher & Wright, 1994; Wright & Stone, 1999; Bond & Fox, 2007; Wilson, 2005; Engelhard, 2012; Stenner, Fisher, Stone, & Burdick, 2013) can make to the process of rethinking capitalism involves the sorting out of the myriad metrics that have erupted in the last several years. Gleeson-White (p. 223) reports, for instance, that the Bloomberg financial information network now has over 750 ESG (Environmental, Social, Governance) data fields, which were extracted from reports provided by over 5,000 companies in 52 countries.  Similarly, Rogers and White (2015) say that

“…today there are more than 100 organizations offering more than 400 corporate sustainability ratings products that assess some 50,000 companies on more than 8,000 metrics of environmental, social and governance (ESG) performance.”

As is also the case with the UN Millennium Development Goals (Fisher, 2011b), the typical use of these metrics as single-item “quantities” is based in counts of relevant events. This procedure misses the basic point that counts of concrete things in the world are not measures. Is it not obvious that I can have ten rocks to your two, and you can still have more rock than I do? The same thing applies to any kind of performance ratings, survey responses, or test scores. We assign the same numeric increase to every addition of one more count, but hardly anyone experimentally tests the hypothesis that the counts all work together to measure the same thing. Those who think there’s no need for precision science in this context are ignoring the decades of successful and widespread technical work in this area, at their own risk.

The repetition of history here is fascinating. As Ashworth (2004, p. 1,314) put it, historically, “The requirements of increased trade and the fiscal demands of the state fuelled the march toward a regular form of metrology.” For instance, in 1875 it was noted that “the existence of quantitative correlations between the various forms of energy, imposes upon men of science the duty of bringing all kinds of physical quantity to one common scale of comparison” (Everett, 1875, p. 9). The moral and economic  value of common scales was recognized during the French revolution, when, Alder (2002, p. 32) documents, it was asked:

“Ought not a single nation have a uniform set of measures, just as a soldier fought for a single patrie? Had not the Revolution promised equality and fraternity, not just for France, but for all the people of the world? By the same token, should not all of the world’s people use a single set of weights and measures to encourage peaceable commerce, mutual understanding, and the exchange of knowledge? That was the purpose of measuring the world.”

The value of rigorously measuring human, social and natural capital includes meaningfully integrating qualitative substance with quantitative convenience, reduced data volume, augmenting measures with uncertainty and consistency indexes, and the capacity to take missing data into account (making possible instrument equating, item banking, etc.)  In contrast with the usual methods, rigorous science demands that experiments determine which indicators cohere to measure the same thing by repeatedly giving the same values across samples, over time and space, and across subsets of indicators. Beyond such data-based results, advanced theory makes it possible to arrive at explanatory, predictive methods that add a whole new layer of efficiency to the generation of indicators (de Boeck & Wilson, 2004; Stenner, et al., 2013).

Finally, Gleeson-White (pp. 220-221) reports that “In July 2011, the SASB [Sustainability Accounting Standards Board] was launched in the United States to create standardized measures for the new capitals.” “Founded by environmental engineer and sustainability expert Jean Rogers in San Francisco, SASB is creating a full set of industry-specific standards for sustainability accounting, with the aim of making this information more consistent and comparable.” As of May 2014, the SASB vice chair is Mary Schapiro, former SEC chair, and the chairman of SASB is Michael Bloomfield, former mayor of NYC and founder of the financial information empire. The “SASB is developing nonfinancial standards for eighty-nine industries grouped in ten different sectors and aims to have completed this grueling task by February 2015. It is releasing each set of metrics as they are completed.”

Like the SASB and other groups, Gleeson-White (p. 222) reports, Bloomberg

“aims to use its metrics to start ‘standardizing the discourse around sustainability, so we’re all talking about the same things in the same way,’ as Bloomberg’s senior sustainability strategist Andrew Park put it. What companies ‘desperately want,’ he says, is ‘a legitimate voice’ to tell them: ‘This is what you need to do. You exist in this particular sector. Here are the metrics that you need to be reporting out on. So SASB will provide that. And we think that’s important, because that will help clean up the metrics that ultimately the finance community will start using.’
“Bloomberg wants to price environmental, social and governance externalities to legitimize them in the eyes of financial capital.”

Gleeson-White (p. 225) continues, saying

“Bloomberg wants to do more generally what Trucost did for Puma’s natural capital inputs: create standardized measures for the new capitals–such as ecosystem services and social impacts–so that this information can be aggregated and used by investors. Park and Ravenel call the failure to value clean air, water, stable coastlines and other environmental goods ‘as much a failure to measure as it is a market failure per se–one that could be addressed in part by providing these ‘unpriced’ resources with quantitative parameters that would enable their incorporation into market mechanisms. Such mechanisms could then appropriately ‘regulate’ the consumption of those resources.'”

Integrating well-measured living capitals into the context of appropriately configured institutional rules, roles, and responsibilities for efficient markets (Fisher, 2010b) should indeed involve a capacity to price these resources quantitatively, though this capacity alone would likely prove insufficient to the task of creating the markets (Miller & O’Leary, 2007; Williamson, 1981, 1991, 2005). Rasch’s (1960, pp. 110-115) deliberate patterning of his measurement models on the form of Maxwell’s equations for Newton’s Second Law provides a mathematical basis for connecting psychometrics with both geometry and natural laws, as well as with the law of supply and demand (Fisher, 2010c, 2015; Fisher & Stenner, 2013a).

This perspective on measurement is informed by an unmodern or amodern, post-positivist philosophy (Dewey, 2012; Latour, 1990, 1993), as opposed to a modern and positivist, or postmodern and anti-positivist, philosophy (Galison, 1997). The essential difference is that neither a universalist nor a relativist perspective is necessary to the adoption of practices of traceability to metrological standards. Rather, focusing on local, situated, human relationships, as described by Wilson (2004) in education, for instance, offers a way of resolving the false dilemma of that dichotomous contrast. As Golinski (2012, p. 35) puts it, “Practices of translation, replication, and metrology have taken the place of the universality that used to be assumed as an attribute of singular science.” Haraway (1996, pp. 439-440) harmonizes, saying “…embedded relationality is the prophylaxis for both relativism and transcendance.” Latour (2005, pp. 228-229) elaborates, saying:

“Standards and metrology solve practically the question of relativity that seems to intimidate so many people: Can we obtain some sort of universal agreement? Of course we can! Provided you find a way to hook up your local instrument to one of the many metrological chains whose material network can be fully described, and whose cost can be fully determined. Provided there is also no interruption, no break, no gap, and no uncertainty along any point of the transmission. Indeed, traceability is precisely what the whole of metrology is about! No discontinuity allowed, which is just what ANT [Actor Network Theory] needs for tracing social topography. Ours is the social theory that has taken metrology as the paramount example of what it is to expand locally everywhere, all while bypassing the local as well as the universal. The practical conditions for the expansion of universality have been opened to empirical inquiries. It’s not by accident that so much work has been done by historians of science into the situated and material extension of universals. Given how much modernizers have invested into universality, this is no small feat.
“As soon as you take the example of scientific metrology and standardization as your benchmark to follow the circulation of universals, you can do the same operation for other less traceable, less materialized circulations: most coordination among agents is achieved through the dissemination of quasi-standards.”

As Rasch (1980: xx) understood, “this is a huge challenge, but once the problem has been formulated it does seem possible to meet it.” Though some metrologically informed traceability networks have begun to emerge in education and health care (for instance, Fisher & Stenner, 2013, 2015; Stenner & Fisher, 2013), virtually everything remains to be done to make the coordination across stakeholders as fully elaborated as the standards in the natural sciences.

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Pendrill, L., & Fisher, W. P., Jr. (2015). Counting and quantification: Comparing psychometric and metrological perspectives on visual perceptions of number. Measurement, p. in press. doi: http://dx.doi.org/10.1016/j.measurement.2015.04.010.

Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests (Reprint, with Foreword and Afterword by B. D. Wright, Chicago: University of Chicago Press, 1980). Copenhagen, Denmark: Danmarks Paedogogiske Institut.

Rogers, J., & White, A. (2015, April 28). Focusing corporate sustainability ratings on what matters. Huffington Post. Retrieved from http://www.huffingtonpost.com/jean-rogers/focusing-corporate-sustai_b_7156148.html.

Stenner, A. J., & Fisher, W. P., Jr. (2013). Metrological traceability in the social sciences: A model from reading measurement. Journal of Physics: Conference Series, 459(012025), http://iopscience.iop.org/1742-6596/459/1/012025.

Stenner, A. J., Fisher, W. P., Jr., Stone, M. H., & Burdick, D. S. (2013, August). Causal Rasch models. Frontiers in Psychology: Quantitative Psychology and Measurement, 4(536), 1-14 [doi: 10.3389/fpsyg.2013.00536].

Williamson, O. E. (1981, November). The economics of organization: The transaction cost approach. The American Journal of Sociology, 87(3), 548-577.

Williamson, O. E. (1991). Economic institutions: Spontaneous and intentional governance [Special issue]. Journal of Law, Economics, & Organization: Papers from the Conference on the New Science of Organization, 7, 159-187.

Williamson, O. E. (2005). The economics of governance. American Economic Review, 95(2), 1-18.

Wilson, M. (Ed.). (2004). National Society for the Study of Education Yearbooks. Vol. 103, Part II: Towards coherence between classroom assessment and accountability. Chicago, Illinois: University of Chicago Press.

Wilson, M. (2005). Constructing measures: An item response modeling approach. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Wilson, M. R. (2013). Using the concept of a measurement system to characterize measurement models used in psychometrics. Measurement, 46, 3766-3774.

Wilson, M., Mari, L., Maul, A., & Torres Irribarra, D. (2015). A comparison of measurement concepts across physical science and social science domains: Instrument design, calibration, and measurement. Journal of Physics: Conference Series, 588(012034), http://iopscience.iop.org/1742-6596/588/1/012034.

Wright, B. D. (1977). Solving measurement problems with the Rasch model. Journal of Educational Measurement, 14(2), 97-116 [http://www.rasch.org/memo42.htm].

Wright, B. D. (1999). Fundamental measurement for psychology. In S. E. Embretson & S. L. Hershberger (Eds.), The new rules of measurement: What every educator and psychologist should know (pp. 65-104 [http://www.rasch.org/memo64.htm]). Hillsdale, New Jersey: Lawrence Erlbaum Associates.

Wright, B. D., & Stone, M. H. (1999). Measurement essentials. Wilmington, DE: Wide Range, Inc. [http://www.rasch.org/measess/me-all.pdf].

Young, J. J., & Williams, P. F. (2010, August). Sorting and comparing: Standard-setting and “ethical” categories. Critical Perspectives on Accounting, 21(6), 509-521.

An Entrepreneurial Investment Model Alternative to Picketty’s Taxation Approach to Eliminating Wealth Disparities

May 14, 2014

Is taxation the only or the best solution to inequality? The way discussions of wealth disparities inevitably focus on variations in how, whom or what to tax, it is easy to assume there are no viable alternatives to taxation. But if the point is to invest in those with the most potential for making significant gains in productivity, so as to maximize the returns we realize, do we not wrongly constrain the domain of possible solutions when we misconceive an entrepreneurial problem in welfare terms?

Why can’t we require minimum levels of investment in social capital stocks and bonds offered by schools, hospitals, NGOs, etc? In human capital instruments offered by individuals? Why should not we expect those investments to be used to create new value? What supposed law of nature says it is impossible to associate new human, social and environmental value with stable and meaningful prices? And if there is such a law (such as Kenneth Arrow (1963) proposed), how can we break it? Why can’t we reconceive human and social capital stocks and flows in new ways?

There is one very good reason why we cannot now make such requirements, and it is the same reason why liberals (including me) had better become accustomed to accepting the failure of their agenda. That reason is this: social and environmental externalities. Inequality is inevitable only as long as we do not change the ways we deal with externalities. They can no longer be measured and managed in the same ways. They must be put on the books, brought into the models, measured scientifically, and traded in efficient markets. We have to invent accountability and accounting systems that harness the energy of the profit motive for the greater good—that actually grow authentic wealth and not mere money—and we have to do this far more effectively than has ever been done before.

It’s a tall order. But there are resources available to us that have not yet been introduced into the larger conversation. There are options to consider that need close study and creative experimentation. Proceeding toward the twin futilities of premature despair or unrealistic taxation will only set up another round of self-fulfilling prophecies inexorably grinding to yet another unforeseen but fully foretold disaster. Conversations about how to shape the roles, rules and institutions that make markets what they are (Miller and O’Leary, 2007) need to take place for human, social, and natural capital (Fisher and Stenner, 2011b). Indeed, those conversations are already well underway, as can be seen in the prior entries in this blog and in the sources listed below.

Arrow, K. J. (1963). Uncertainty and the welfare economics of medical care. American Economic Review, 53, 941-973.

Fisher, W. P., Jr. (2007). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-1093 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009a). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287.

Fisher, W. P., Jr. (2009b). NIST Critical national need idea White Paper: Metrological infrastructure for human, social, and natural capital (http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology (11 pages).

Fisher, W. P., Jr. (2010a, 22 November). Meaningfulness, measurement, value seeking, and the corporate objective function: An introduction to new possibilities. Sausalito, California: LivingCapitalMetrics.com (http://ssrn.com/abstract=1713467).

Fisher, W. P. J. (2010b). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital (http://ssrn.com/abstract=2340674). Bridge to Business Postdoctoral Certification, Freeman School of Business: Tulane University.

Fisher, W. P., Jr. (2010c, June 13-16). Rasch, Maxwell’s method of analogy, and the Chicago tradition. In G. Cooper (Ed.), https://conference.cbs.dk/index.php/rasch/Rasch2010/paper/view/824. Probabilistic models for measurement in education, psychology, social science and health: Celebrating 50 years since the publication of Rasch’s Probabilistic Models. FUHU Conference Centre, Copenhagen, Denmark: University of Copenhagen School of Business.

Fisher, W. P., Jr. (2011a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), 49-66.

Fisher, W. P., Jr. (2011b, Thursday, September 1). Measurement, metrology and the coordination of sociotechnical networks. In S. Bercea (Ed.), New Education and Training Methods. International Measurement Confederation (IMEKO). Jena, Germany: http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24491/ilm1-2011imeko-017.pdf.

Fisher, W. P., Jr. (2012a). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012b, May/June). What the world needs now: A bold plan for new standards [Third place, 2011 NIST/SES World Standards Day paper competition]. Standards Engineering, 64(3), 1 & 3-5 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr., & Stenner, A. J. (2011a, January). Metrology for the social, behavioral, and economic sciences. http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011b, August 31 to September 2). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium. Jena, Germany: http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf.

Fisher, W. P., Jr., & Stenner, A. J. (2013a). On the potential for improved measurement in the human and social sciences. In Q. Zhang & H. Yang (Eds.), Pacific Rim Objective Measurement Symposium 2012 Conference Proceedings (pp. 1-11). Berlin, Germany: Springer-Verlag.

Fisher, W. P., Jr., & Stenner, A. J. (2013b). Overcoming the invisibility of metrology: A reading measurement network for education and the social sciences. Journal of Physics: Conference Series, 459(012024), http://iopscience.iop.org/1742-6596/459/1/012024.

Miller, P., & O’Leary, T. (2007, October/November). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-734.

What the Economy Needs?

September 5, 2012

Expanding on remarks made by Thomas Friedman in the course of an interview with Charlie Rose broadcast on August 31, 2012…

Friedman broke the problem down to three key points. We have to have 1) a plan, 2) a fair tax contribution from the rich, and 3) aspirations for improving the overall quality of life, economically and  democratically.

The plan outlined from various points of view in this blog is to create a scientific and market infrastructure for intangible assets (human, social and natural capital), assets amounting to at least 90%of the capital under management.

The plan is fair in its advancement of equal opportunity to invest in and realize returns from one’s skills, motivations, health and trustworthiness. Everyone will be able to invest in, and receive their share of the profits from, the human, social, and natural capital stocks of individuals, communities, schools, hospitals, social service agencies, firms, etc. The rich will then both contribute to the advancement of the greater good at the same time they are able to profit from the growth in the authentic wealth created by improvements to human, community, and environmental value.

The plan aspires to great accomplishments in the depth and breadth of the innovation it will facilitate, its fulfillment of democratic principles, and the new economic growth it promises.

And so I would now like to raise a couple of sets of questions. What if all the money put into Medicare, Medicaid, education, HUD, food stamps, the EPA, etc. was instead invested in an infrastructure for intangible assets metrology and HSN capital stocks (individual, organizational–school, hospital, nonprofit, NGO, firm–and community)? Usually, talk of letting the market solve social and environmental problems is nothing but a self-serving excuse for allowing greed to rule at the expense of the greater good. Those so-called market solutions do nothing to actually shape the institutions, rules, and roles by which markets are created, and so the end result would be catastrophic. But there is an essential and unnoticed inconsistency in previously proposed approaches that involves the double standards used in defining and actualizing the various forms of capital.

As previous posts (like this one or this one) in this blog, and several of my publications, have argued, manufactured capital and property have long since been brought to life by transferable representations (titles, deeds, precision quantity measures, etc.) and the various legal, financial, educational, and scientific institutions built up around them. Human, social, and natural capital have not been brought to life and so we remain unable to take proper possession of our own properties, the ones that we most value and on which life, liberty, and happiness are most dependent.

But what if we created the needed market institutions, rules, and roles? What if everyone knew how many shares of community capital they owned, and what the current price of those shares in the market was? What if tuition for an advanced degree was denominated in the shares of literacy capital one obtained, as evident in the increased literacy measures achieved? What if taxes were abolished and minimum investments in human, social, and natural capital stocks were required? What if real, efficient, functional markets in intangible assets were created, and the associated governmental programs and departments were abolished? How much would the federal budget decrease? How much would government shrink? How much might the economy grow if that much money was invested in human, social, and natural capital stocks paying even a minimal reasonable profit?

Another round of questions asks whether we have the optimal social safety net in the current institutional context, or if perhaps that safety net could be significantly improved by following through on the concepts of impact investing and outcome-based budgeting to create a truly sustainable and socially responsible economic system? What if everyone held known numbers of tradable shares of their intangible assets (their skills, motivation, health, trust)? What if the value of those shares was common public knowledge? What if the investment paths to increasing the number and value of shares held were all well known? What if monetary profit could be derived–and could only be derived–by increasing the value of human, social, and natural capital shares? What if groups of people joined together in various kinds of organizations (schools, hospitals, businesses) to collectively grow the value of their authentic wealth? What if lean thinking was applied to the 90% of the capital under management (the human, social, and natural capital) that is currently nearly unmanageable because it is not measured in universally uniform scientific units?

The balance scale is a common symbol of justice. We do not usually aspire to take that symbol as seriously as we could. We ought to have a plan for economic justice that does not have to coerce anyone to acknowledge, pay back, and re-invest in the broad support they received en route to becoming successful. And we ought to have a plan that reinvigorates the aspirations for equal opportunity and freedom that have become a model for people all over the world. Friedman got the broad strokes right. Now’s the time to start filling in the details.

Review of “Advancing Social Impact Investments Through Measurement”

August 24, 2012

Over the last few days, I have been reading several of the most recent issues of the Community Development Investment Review, especially volume 7, number 2, edited by David Erickson of the Federal Reserve Bank of San Francisco, reporting the proceedings of the March 21, 2011 conference in Washington, DC on advancing social impact investments through measurement. I am so excited to see this work that I am (truly) fairly trembling with excitement. I feel as though I’ve finally made my way home. There are so many points of contact, it’s hard to know where to start. After several days of concentrated deep breathing and close study of the CDIR, it’s now possible to formulate some coherent thoughts to share.

The CDIR papers start to sort out the complex issues involved in clarifying how measurement might contribute to the integration of impact investing and community development finance. I am heartened by the statement that “The goal of the Review is to bridge the gap between theory and practice and to enlist as many viewpoints as possible—government, nonprofits, financial institutions, and beneficiaries.” On the other hand, the omission of measurement scientists from that list of viewpoints adds another question to my long list of questions as to why measurement science is so routinely ignored by the very people who proclaim its importance. The situation is quite analogous to demanding more frequent conversational interactions from colleagues while ignoring the invention of the telephone and not providing them with the tools and network connections.

The aims shared by the CDIR contributors and myself are evident in the fact that David Erickson opens his summary of the March 21, 2011 conference with the same quote from Robert Kennedy that I placed at the end of my 2009 article in Measurement (see references below; all papers referenced are available by request if they are not already online). In that 2009 paper, in others I’ve published over the last several years, in presentations I’ve made to my measurement colleagues abroad and at home, and in various entries in my blog, I take up virtually all of the major themes that arose in the DC conference: how better measurement can attract capital to needed areas, how the cost of measurement repels many investors, how government can help by means of standard setting and regulation, how diverse and ambiguous investor and stakeholder interests can be reconciled and/or clarified, etc.

The difference, of course, is that I present these issues from the technical perspective of measurement and cannot speak authoritatively or specifically from the perspectives represented by the community development finance and impact investing fields. The bottom line take-away message for these fields from my perspective is this: unexamined assumptions may unnecessarily restrict assessments of problems and their potential solutions. As Salamon put it in his remarks in the CDIR proceedings from the Washington meeting (p. 43), “uncoordinated innovation not guided by a clear strategic concept can do more than lose its way: it can do actual harm.”

A clear strategic concept capable of coordinating innovations in social impact measurement is readily available. Multiple, highly valuable, and eminently practical measurement technologies have proven themselves in real world applications over the last 50 years. These technologies are well documented in the educational, psychological, sociological, and health care research literatures, as well as in the practical experience of high stakes testing for professional licensure and certification, for graduation, and for admissions.

Numerous reports show how to approach problems of quantification and standards with new degrees of rigor, transparency, meaningfulness, and flexibility. When measurement problems are not defined in terms of these technologies, solutions that may offer highly advantageous features are not considered. When the area of application is as far reaching and fundamental as social impact measurement, not taking new technologies into account is nothing short of tragic. I describe some of the new opportunities for you in a Technical Postscript, below.

In his Foreword to the CDIR proceedings issue, John Moon mentions having been at the 2009 SoCap event bringing together stakeholders from across the various social capital markets arenas. I was at the 2008 SoCap, and I came away from it with much the same impression as Moon, feeling that the palpable excitement in the air was more than tempered by the evident fact that people were often speaking at cross purposes, and that there did not seem to be a common object to the conversation. Moon, Erickson, and their colleagues have been in one position to sort out the issues involved, and I have been in another, but we are plainly on converging courses.

Though the science is in place and has been for decades, it will not and cannot amount to anything until the people who can best make use of it do so. The community development finance and impact investing fields are those people. Anyone interested in getting together for an informal conversation on topics of mutual interest should feel free to contact me.

Technical Postscript

There are at least six areas in efforts to advance social impact investments via measurement that will be most affected by contemporary methods. The first has to do with scale quality. I won’t go into the technical details, but numbers do not automatically stand for something that adds up the way they do. Mapping a substantive construct onto a number line requires specific technical expertise; there is no evidence of that expertise in any of the literature I’ve seen on social impact investing, or on measuring intangible assets. This is not an arbitrary bit of philosophical esoterica or technical nicety. This is one of those areas where the practical value of scientific rigor and precision comes into its own. It makes all the difference in being able to realize goals for measurement, investment, and redefining profit in terms of social impacts.

A second area in which thinking on social impact measurement will be profoundly altered by current scaling methods concerns the capacity to reduce data volume with no loss of information. In current systems, each indicator has its own separate metric. Data volume quickly multiplies when tracking separate organizations for each of several time periods in various locales. Given sufficient adherence to data quality and meaningfulness requirements, today’s scaling methods allow these indicators to be combined into a single composite measure—from which each individual observation can be inferred.

Elaborating this second point a bit further, I noted that some speakers at the 2011 conference in Washington thought reducing data volume is a matter of limiting the number of indicators that are tracked. This strategy is self-defeating, however, as having fewer independent observations increases uncertainty and risk. It would be far better to set up systems in which the metrics are designed so as to incorporate the amount of uncertainty that can be tolerated in any given decision support application.

The third area I have in mind deals with the diverse spectrum of varying interests and preferences brought to the table by investors, beneficiaries, and other stakeholders. Contemporary approaches in measurement make it possible to adapt the content of the particular indicators (counts or frequencies of events, or responses to survey questions or test items) to the needs of the user, without compromising the comparability of the resulting quantitative measure. This feature makes it possible to mass customize the content of the metrics employed depending on the substantive nature of the needs at that time and place.

Fourth, it is well known that different people judging performances or assigning numbers to observations bring different personal standards to bear as they make their ratings. Contemporary measurement methods enable the evaluation and scaling of raters and judges relative to one another, when data are gathered in a manner facilitating such comparisons. The end result is a basis for fair comparisons, instead of scores that vary depending more on which rater is observing than on the quality of the performance.

Fifth, much of the discussion at the conference in Washington last year emphasized the need for shared data formatting and reporting standards. As might be guessed from the prior four areas I’ve described, significant advances have occurred in standard setting methods. It is suggested in the CDIR proceedings that the Treasury Department should be the home to a new institute for social impact measurement standards. In a series of publications over the last few years, I have suggested a need for an Intangible Assets Metric System to NIST and NSF (see below for references and links; all papers are available on request). That suggestion comes up again in my third-prize winning entry in the 2011 World Standards Day paper competition, sponsored by NIST and SES (the Society for Standards Professionals), entitled “What the World Needs Now: A Bold Plan for New Standards.” (See below for link.)

Sixth, as noted by Salamon (p. 43), “metrics are not neutral. They not only measure impact, they can also shape it.” Though this is not likely exactly what Salamon meant, one of the most exciting areas in measurement applications in education in recent years, one led in many ways by my colleague, Mark Wilson, and his group at UC Berkeley, concerns exactly this feedback loop between measurement and impact. In education, it has become apparent that test scaling reveals the order in which lessons are learned. Difficult problems that require mastery of easier problems are necessarily answered correctly less often than the easier problems. When the difficulty order of test questions in a given subject remains constant over time and across thousands of students, one may infer that the scale reveals the path of least resistance. Individualizing instruction by targeting lessons at the student’s measure has given rise to a concept of formative assessment, distinct from the summative assessment of accountability applications. I suspect this kind of a distinction may also prove of value in social impact applications.

Relevant Publications and Presentations

Fisher, W. P., Jr. (2002, Spring). “The Mystery of Capital” and the human sciences. Rasch Measurement Transactions, 15(4), 854 [http://www.rasch.org/rmt/rmt154j.htm].

Fisher, W. P., Jr. (2004, Thursday, January 22). Bringing capital to life via measurement: A contribution to the new economics. In  R. Smith (Chair), Session 3.3B. Rasch Models in Economics and Marketing. Second International Conference on Measurement in Health, Education, Psychology, and Marketing: Developments with Rasch Models, The International Laboratory for Measurement in the Social Sciences, School of Education, Murdoch University, Perth, Western Australia.

Fisher, W. P., Jr. (2005, August 1-3). Data standards for living human, social, and natural capital. In Session G: Concluding Discussion, Future Plans, Policy, etc. Conference on Entrepreneurship and Human Rights [http://www.fordham.edu/economics/vinod/ehr05.htm], Pope Auditorium, Lowenstein Bldg, Fordham University.

Fisher, W. P., Jr. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2008, 3-5 September). New metrological horizons: Invariant reference standards for instruments measuring human, social, and natural capital. Presented at the 12th International Measurement Confederation (IMEKO) TC1-TC7 Joint Symposium on Man, Science, and Measurement, Annecy, France: University of Savoie.

Fisher, W. P., Jr. (2009, November). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287.

Fisher, W. P.. Jr. (2009). NIST Critical national need idea White Paper: Metrological infrastructure for human, social, and natural capital (Tech. Rep., http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P., Jr. (2010). The standard model in the history of the natural sciences, econometrics, and the social sciences. Journal of Physics: Conference Series, 238(1), http://iopscience.iop.org/1742-6596/238/1/012016/pdf/1742-6596_238_1_012016.pdf.

Fisher, W. P., Jr. (2011). Bringing human, social, and natural capital to life: Practical consequences and opportunities. In N. Brown, B. Duckor, K. Draney & M. Wilson (Eds.), Advances in Rasch Measurement, Vol. 2 (pp. 1-27). Maple Grove, MN: JAM Press.

Fisher, W. P., Jr. (2011). Measuring genuine progress by scaling economic indicators to think global & act local: An example from the UN Millennium Development Goals project. LivingCapitalMetrics.com. Retrieved 18 January 2011, from Social Science Research Network: http://ssrn.com/abstract=1739386.

Fisher, W. P., Jr. (2012). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012, May/June). What the world needs now: A bold plan for new standards. Standards Engineering, 64(3), 1 & 3-5 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr., & Stenner, A. J. (2011, January). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). Retrieved 25 October 2011, from National Science Foundation: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011, August 31 to September 2). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

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Comments on the New ANSI Human Capital Investor Metrics Standard

April 16, 2012

The full text of the proposed standard is available here.

It’s good to see a document emerge in this area, especially one with such a broad base of support from a diverse range of stakeholders. As is stated in the standard, the metrics defined in it are a good place to start and in many instances will likely improve the quality and quantity of the information made available to investors.

There are several issues to keep in mind as the value of standards for human capital metrics becomes more widely appreciated. First, in the context of a comprehensively defined investment framework, human capital is just one of the four major forms of capital, the other three being social, natural, and manufactured (Ekins, 1992; Ekins, Dresden, and Dahlstrom, 2008). To ensure as far as possible the long term stability and sustainability of their profits, and of the economic system as a whole, investors will certainly want to expand the range of the available standards to include social and natural capital along with human capital.

Second, though we manage what we measure, investment management is seriously compromised by having high quality scientific measurement standards only for manufactured capital (length, weight, volume, temperature, energy, time, kilowatts, etc.). Over 80 years of research on ability tests, surveys, rating scales, and assessments has reached a place from which it is prepared to revolutionize the management of intangible forms of capital (Fisher, 2007, 2009a, 2009b, 2010, 2011a, 2011b; Fisher & Stenner, 2011a, 2011b; Wilson, 2011; Wright, 1999). The very large reductions in transaction costs effected by standardized metrics in the economy at large (Barzel, 1982; Benham and Benham, 2000) are likely to have a similarly profound effect on the economics of human, social, and natural capital (Fisher, 2011a, 2012a, 2012b).

The potential for dramatic change in the conceptualization of metrics is most evident in the proposed standard in the sections on leadership quality and employee engagement. For instance, in the section on leadership quality, it is stated that “Investors will be able to directly compare all organizations that are using the same vendor’s methodology.” This kind of dependency should not be allowed to stand as a significant factor in a measurement standard. Properly constructed and validated scientific measures, such as those that have been in wide use in education, psychology and health care for several decades (Andrich, 2010; Bezruzcko, 2005; Bond and Fox, 2007; Fisher and Wright, 1994; Rasch, 1960; Salzberger, 2009; Wright, 1999), are equated to a common unit. Comparability should never depend on which vendor is used. Rather, any instrument that actually measures the construct of interest (leadership quality or employee engagement) should do so in a common unit and within an acceptable range of error. “Normalizing” measures for comparability, as is suggested in the standard, means employing psychometric methods that are 50 years out of date and that are far less rigorous and practical than need be. Transparency in measurement means looking through the instrument to the thing itself. If particular instruments color or reshape what is measured, or merely change the meaning of the numbers reported, then the integrity of the standard as a standard should be re-examined.

Third, for investments in human capital to be effectively managed, each distinct aspect of it (motivations, skills and abilities, health) needs to be measured separately, just as height, weight, and temperature are. New technologies have already transformed measurement practices in ways that make the necessary processes precise and inexpensive. Of special interest are adaptively administered precalibrated instruments supporting mass customized—but globally comparable—measures (for instance, see the examples at http://blog.lexile.com/tag/oasis/ and that were presented at the recent Pearson Global Research Conference in Fremantle, Australia http://www.pearson.com.au/marketing/corporate/pearson_global/default.html; also see Wright and Bell 1984, Lunz, Bergstrom, and Gershon, 1994, Bejar, et al., 2003).

Fourth, the ownership of human capital needs clarification and legal status. If we consider each individual to own their abilities, health, and motivations, and to be solely responsible for decisions made concerning the disposition of those properties, then, in accord with their proven measured amounts of each type of human capital, everyone ought to have legal title to a specific number of shares or credits of each type. This may transform employment away from wage-based job classification compensation to an individualized investment-based continuous quality improvement platform. The same kind of legal titling system will, of course, need to be worked out for social and natural capital, as well.

Fifth, given scientific standards for each major form of capital, practical measurement technologies, and legal title to our shares of capital, we will need expanded financial accounting standards and tools for managing our individual and collective investments. Ongoing research and debates concerning these standards and tools (Siegel and Borgia, 2006; Young and Williams, 2010) have yet to connect with the larger scientific, economic, and legal issues raised here, but developments in this direction should be emerging in due course.

Sixth, a number of lingering moral, ethical and political questions are cast in a new light in this context. The significance of individual behaviors and decisions is informed and largely determined by the context of the culture and institutions in which those behaviors and decisions are executed. Many of the morally despicable but not illegal investment decisions leading to the recent economic downturn put individuals in the position of either setting themselves apart and threatening their careers or doing what was best for their portfolios within the limits of the law. Current efforts intended to devise new regulatory constraints are misguided in focusing on ever more microscopically defined particulars. What is needed is instead a system in which profits are contingent on the growth of human, social, and natural capital. In that framework, legal but ultimately unfair practices would drive down social capital stock values, counterbalancing ill-gotten gains and making them unprofitable.

Seventh, the International Vocabulary of Measurement, now in its third edition (VIM3), is a standard recognized by all eight international standards accrediting bodies (BIPM, etc.). The VIM3 (http://www.bipm.org/en/publications/guides/vim.html) and forthcoming VIM4 are intended to provide a uniform set of concepts and terms for all fields that employ measures across the natural and social sciences. A new dialogue on these issues has commenced in the context of the International Measurement Confederation (IMEKO), whose member organizations are the weights and standards measurement institutes from countries around the world (Conference note, 2011). The 2012 President of the Psychometric Society, Mark Wilson, gave an invited address at the September 2011 IMEKO meeting (Wilson, 2011), and a member of the VIM3 editorial board, Luca Mari, is invited to speak at the July, 2012 International Meeting of the Psychometric Society. I encourage all interested parties to become involved in efforts of these kinds in their own fields.

References

Andrich, D. (2010). Sufficiency and conditional estimation of person parameters in the polytomous Rasch model. Psychometrika, 75(2), 292-308.

Barzel, Y. (1982). Measurement costs and the organization of markets. Journal of Law and Economics, 25, 27-48.

Bejar, I., Lawless, R. R., Morley, M. E., Wagner, M. E., Bennett, R. E., & Revuelta, J. (2003, November). A feasibility study of on-the-fly item generation in adaptive testing. The Journal of Technology, Learning, and Assessment, 2(3), 1-29; http://ejournals.bc.edu/ojs/index.php/jtla/article/view/1663.

Benham, A., & Benham, L. (2000). Measuring the costs of exchange. In C. Ménard (Ed.), Institutions, contracts and organizations: Perspectives from new institutional economics (pp. 367-375). Cheltenham, UK: Edward Elgar.

Bezruczko, N. (Ed.). (2005). Rasch measurement in health sciences. Maple Grove, MN: JAM Press.

Bond, T., & Fox, C. (2007). Applying the Rasch model: Fundamental measurement in the human sciences, 2d edition. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Conference note. (2011). IMEKO Symposium: August 31- September 2, 2011, Jena, Germany. Rasch Measurement Transactions, 25(1), 1318.

Ekins, P. (1992). A four-capital model of wealth creation. In P. Ekins & M. Max-Neef (Eds.), Real-life economics: Understanding wealth creation (pp. 147-155). London: Routledge.

Ekins, P., Dresner, S., & Dahlstrom, K. (2008). The four-capital method of sustainable development evaluation. European Environment, 18(2), 63-80.

Fisher, W. P., Jr. (2007). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009a). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287.

Fisher, W. P.. Jr. (2009b). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P.. Jr. (2010). Rasch, Maxwell’s method of analogy, and the Chicago tradition. In G. Cooper (Chair), https://conference.cbs.dk/index.php/rasch/Rasch2010/paper/view/824. Probabilistic models for measurement in education, psychology, social science and health: Celebrating 50 years since the publication of Rasch’s Probabilistic Models.., University of Copenhagen School of Business, FUHU Conference Centre, Copenhagen, Denmark.

Fisher, W. P., Jr. (2011a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. In N. Brown, B. Duckor, K. Draney & M. Wilson (Eds.), Advances in Rasch Measurement, Vol. 2 (pp. 1-27). Maple Grove, MN: JAM Press.

Fisher, W. P., Jr. (2011b). Measurement, metrology and the coordination of sociotechnical networks. In  S. Bercea (Chair), New Education and Training Methods. International Measurement Confederation (IMEKO), http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24491/ilm1-2011imeko-017.pdf, Jena, Germany.

Fisher, W. P., Jr. (2012a). Measure local, manage global: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. in press). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012b). What the world needs now: A bold plan for new standards. Standards Engineering, 64, in press.

Fisher, W. P., Jr., & Stenner, A. J. (2011a). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). Retrieved 25 October 2011, from National Science Foundation: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011b). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

Fisher, W. P., Jr., & Wright, B. D. (Eds.). (1994). Applications of probabilistic conjoint measurement. International Journal of Educational Research, 21(6), 557-664.

Lunz, M. E., Bergstrom, B. A., & Gershon, R. C. (1994). Computer adaptive testing. International Journal of Educational Research, 21(6), 623-634.

Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests (Reprint, with Foreword and Afterword by B. D. Wright, Chicago: University of Chicago Press, 1980). Copenhagen, Denmark: Danmarks Paedogogiske Institut.

Salzberger, T. (2009). Measurement in marketing research: An alternative framework. Northampton, MA: Edward Elgar.

Siegel, P., & Borgia, C. (2006). The measurement and recognition of intangible assets. Journal of Business and Public Affairs, 1(1).

Wilson, M. (2011). The role of mathematical models in measurement: A perspective from psychometrics. In L. Mari (Chair), Plenary lecture. International Measurement Confederation (IMEKO), http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24178/ilm1-2011imeko-005.pdf, Jena, Germany.

Wright, B. D. (1999). Fundamental measurement for psychology. In S. E. Embretson & S. L. Hershberger (Eds.), The new rules of measurement: What every educator and psychologist should know (pp. 65-104 [http://www.rasch.org/memo64.htm]). Hillsdale, New Jersey: Lawrence Erlbaum Associates.

Wright, B. D., & Bell, S. R. (1984, Winter). Item banks: What, why, how. Journal of Educational Measurement, 21(4), 331-345 [http://www.rasch.org/memo43.htm].

Young, J. J., & Williams, P. F. (2010, August). Sorting and comparing: Standard-setting and “ethical” categories. Critical Perspectives on Accounting, 21(6), 509-521.

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Open Letter on New Infrastructure as a Platform for Economic Growth and Scientific Innovation

December 21, 2011

Dear Thought Leaders Everywhere,

As you are no doubt well aware, one issue in particular is being brought to a head by the lingering economic malaise and the continuing situation in Europe: the austerity measures needed for countering debt problems are going to severely limit growth potentials, if they do not lead straight to recession or depression, unless sources of new efficiencies are found. Given the huge existing levels of debt, it is increasingly difficult to justify the capital injections the economy needs, so thinkers from Paul Krugman to Bill Clinton have proposed the possibility that some new technical infrastructure could provide a platform for new growth, much as the Internet has.

Energy might be a productive area to focus on, for instance. Others go straight to immediately available technologies, and speak of investments in existing infrastructure, such as roads and bridges. But even if a program for bringing that kind of concrete engineering up to full capacity was put in place, it would provide only a small fraction of the jobs and growth actually needed.

The basic idea is right on the mark, though no one seems to realize there are types of infrastructure beyond tangible assets like energy, or roads and bridges. Stop a second and think about it. We say we manage what we measure. Standardized weights and measures are widely recognized as an essential core feature of productivity and innovation in science, engineering, and the economy. But existing standardized metrics are exclusively focused on physics and chemistry, machines and tools, and property. And that’s the problem: manufactured capital and property make up only about 10% of all the capital under management.

What’s the other 90%? Human capital: skills, motivations, health. Social capital: trust, commitment, loyalty. Natural capital: water and air purification services, genetic variation, fisheries. Why don’t we have standardized weights and measures for managing these essential core areas of education, health care, human and natural resource management, social services, etc.? After all, if we manage what we measure, and we lack measures for the vast majority of the capital in the economy, we are probably lucky to be doing as well as we are. Our faith in efficient markets is not misplaced as much as we have not yet really made it central to the economics of every form of capital.

There are a lot of reasons why we don’t have standardized metrics for measuring individual amounts of intangible assets like human, social, and natural capital, but the supposed “subjectivity” of those forms of capital is NOT one of them. Decades of research and practice prove the viability of the technology needed for unifying the measurement of everything from literacy capital to health capital, from social capital to natural capital. What stands in our way as a society has much more to do with preconceptions and unexamined assumptions than with the supposed “soft” nature of the social sciences and psychology.

White papers published online by NIST and NSF, and a recent award-winning essay forthcoming in Standards Engineering (full references are listed below), provide rational justifications for a new research agenda focused on developing and implementing an intangible assets metric system. Such a system would enable us to act on the truth that we can accomplish far more working together cooperatively in a common framework than we can as individuals.

Better measurement is essential to better management. In the context of today’s pressing economic and social issues, new questions about the way we manage every form of resource need to be raised. You are in a position from which these questions can be effectively put forward for consideration by thought leaders across a wide array of disciplines and industries. We hope you will see fit to do so. If we can be of any further assistance, please do not hesitate to let us know. Thank you.

Sincerely,

William P. Fisher, Jr., Ph.D.

A. Jackson Stenner, Ph.D.

Fisher, W. P., Jr. (2009). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (Tech. Rep. No. http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P., Jr. (2012). What the world needs now: A bold plan for new standards. Standards Engineering, forthcoming. For the ANSI press release, see http://webstore.ansi.org/NewsDetail.aspx?NewsGuid=590a225c-d779-4f81-804e-4d05ef239c37.)

Fisher, W. P., Jr., & Stenner, A. J. (2011, January). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). Retrieved 25 October 2011, from National Science Foundation: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Creative Commons License
LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.