Posts Tagged ‘natural capital’

Why economic growth can and inevitably will be green

October 1, 2018

So, approaching matters once again from yet another point of view, we have Jason Hickel explaining a couple of weeks ago “Why Growth Can’t Be Green.” This article provides yet another example of how the problem is the problem. That is, the way we define problems sets up particular kinds of solutions in advance, and sometimes, as Einstein famously pointed out, problems cannot be solved from within the same conceptual framework that gave rise to them. I’ve expanded on this theme in a number of previous posts, for instance, here.

Hickel takes up the apparent impossibility of aligning economic growth with environmental values. He speaks directly to what he calls the rebound effect, the way that “improvements in resource efficiency drive down prices and cause demand to rise—thus canceling out some of the gains.” But that rebound can happen only as long as the economy remains defined and limited by the alignment of manufactured capital and finance, ignoring the largely unexamined and unconsidered possibility that human, social, and natural capital could be measured well enough to be also aligned with finance.

Hence, as I say, the problem is the problem. Broadening one’s conceptualization of the problem opens up new opportunities that otherwise never come into view.

The Hickel article’s entire focus is then on top-down policy impositions like taxes or a Genuine Progress Index. These presume human, social, and natural capital can only ever exist in dead formations that have to be micromanaged and concretely manipulated, and that efficient markets bringing them to life are inherently and literally unthinkable. (See a short article here for an explanation of the difference between dead and living capital. There’s a lot more where that came from, as is apparent in the previous posts here in this blog.)

The situation could be vastly different than what Hickel imagines. If we could own, buy, and sell products in efficient markets we could reward the production of human, social, and environmental value. In that scenario, when improvements in environmental resource efficiency are obtained, demand for that new environmental value will rise and its price will go down, not the resource’s price.

We ought to be creative enough to figure out how to configure markets so that prices for environmental resources (oil, farmland, metals, etc.) can stay constant or fall without increasing demand for them, as could happen if that demand is counterbalanced and absorbed by rising human, social, and environmental quality capital values.

The question is how to absorb the rebound effect in other forms of capital that grow in demand while holding demand for the natural resource base in check. The vital conceptual distinction is between socialistic centralized planning and control of actual physical entities (people, communities, the environment, and manufactured items), on the one hand, and capitalistic decentralized distributed network effects on abstract transferable representations, on the other. Everyone defaults to the socialist scenario without ever considering there might be a whole other arena in which fruitful possibilities might be imagined.

What if, for instance, we could harness the profit motive to promote growth in genuine human, social, and environmental value? What if we were able to achieve qualitatively meaningful increases in authentic wealth that were economically contingent on reduced natural resource consumption? What if the financial and substantive value profits that could be had meant that resource consumption could be reduced by the same kinds of factors as have been realized in the context of Moore’s Law? What if a human economics of genuine value could actually result in humanity being able to adjust the global thermostat up or down in small increments by efficiently rewarding just the right combinations of policies and practices at the right times and places in the right volumes?

The only way that could ever happen is if people are motivated to do the right thing for the earth and for humanity because it is the right thing for them and their families. They have to be able to own their personal shares of their personal stocks of human, social, and natural capital. They have to be able to profit from investments in their own and others’ shares. They will not act on behalf of the earth and humanity only because it is the right thing to do. There has to be evidence and explanations of how everyone is fairly held accountable to the same standards, and has the same opportunities for profit and loss as anyone else. Then, and only then, it seems, will human, social, and environmental value become communicable in a viral contagion of good will.

Socialism has been conclusively proven unworkable, for people, communities, and the environment, as well as financially. But a human, social, and natural capitalism has hardly even been articulated, much less tried out. How do we make human, social, and natural capital fungible? How might the economy transcend its traditional boundaries and expand itself beyond the existing alignment of manufactured capital and finance?

It’s an incredibly complex proposal, but also seems like such a simple thing. The manufactured capital economy uses the common language of good measurement to improve quality, to simplify management communications, and to lower transaction costs in efficient markets. So what should we do if we want to correct the imbalanced negative impacts on people, communities, and the environment created by the misplaced emphasis on aligning only manufactured capital and financial capital?

As has been repeatedly proposed for years in this blog, maybe we should use the manufactured capital markets as a model and use good measurement to improve the quality of human, social, and environmental capital, to simplify communications and management, to lower transaction costs, and to align the genuine human, social, and environmental value created with financial value in efficient markets.

Of course, grasping that as viable, feasible, and desirable requires understanding that substantively meaningful precision measurement is something quite different from what usually passes for quantification. And that is an entirely different story, though one taken up repeatedly in previous entries in this blog, of course….

 

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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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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.

Revisiting Hayek’s Relevance to Measurement

May 31, 2018

As so often happens, I’m finding new opportunities for restating what seems obvious to me but does not impact others in the way it ought to. The work of the Austrian economist Friedrich Hayek speaks to me in a particular way that has always, to me, self-evidently expressed ideas of fundamental value and interest. Reviewing his work again lately has opened it up to a new level of detail that is worth sharing here.

Hayek (1948, p. 54) is onto a key point about measurement and its role in economics when he says:

…the spontaneous actions of individuals will, under conditions which we can define, bring about a distribution of resources which can be understood as if it were made according to a single plan, although nobody has planned it…?

Decades of measurement research shows that individuals’ spontaneous responses to assessment and survey questions conform to one another in ways that might appear to have been centrally organized according to a single plan. But over and over again the same patterns are produced with no efforts made to guide or coerce responses that conform in that way.

The results of testing and assessment produced in educational measurement can be expressed in economic terms fitting quite well with Hayek’s observation. Student abilities, economically speaking, are human capital resources. Each student has some amount of ability that can be considered a supply of resources available for application to the demands of the challenges posed by the assessment questions. When assessment data fit a Rasch model, the supply of student abilities have spontaneously organized themselves in relation to challenging demands for that supply of abilities posed by the test questions. The invariant consistency of the data and resulting model fit has not been produced by coercing or guiding the students to respond in a particular way. Although questions can be written to vary in difficulty according to a construct theory, and though educational curricula traditionally vary in difficulty across grade levels, the patterns of growth and change that are observed are plainly not taking place as a result of anyone’s intentions or plans.

This kind of complex adaptive, self-organizing process (Fisher, 2017) describes not just the relations of student abilities and task difficulties, but also the relations of customer preferences to product features, patient health and functionality relative to disease and disability, etc. It also, of course, applies to supply and demand relative to a price (Fisher, 2015). For students, the price to be paid follows from the probability of a supply of ability meeting the demand for it posed by the challenges encountered in assessment items.

Getting back to Hayek (1948, p. 54), here we meet the relevance of the

…central question of all social sciences: How can the combination of fragments of knowledge existing in different minds bring about results which, if they were to be brought about deliberately, would require a knowledge on the part of the directing mind which no single person can possess?

Per Hayek’s point, no one student will know the answers to all of the questions posed in a test, and yet all of the students’ fragments of knowledge combine in a way that bring about results seemingly defined by a single intelligence. It is this bottom up and self-organized emergence of knowledge structures that we capture in measurement and bring into our culture, our sciences, and our economies by bringing things into words and the common languages of standardized metrics.

This spontaneous emergence of structure does not lead directly of its own accord to the creation of markets. Rather, it is vitally important to recognize, along with Miller and O’Leary (2007, p. 710) that:

Markets are not spontaneously generated by the exchange activity of buyers and sellers. Rather, skilled actors produce institutional arrangements, the rules, roles and relationships that make market exchange possible. The institutions define the market, rather than the reverse.

The institutional arrangements we need to make to create efficient markets for human, social, and natural capital will be staggeringly difficult to realize. But a point in time will come when the costs of remaining in our current cultural, political, and economic ruts will be greater, and the benefits will be lower, than the costs and benefits of investing in a new future. That time may be sooner than anyone thinks it will be.

References

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. (2017). A practical approach to modeling complex adaptive flows in psychology and social science. Procedia Computer Science, 114, 165-174. Retrieved from https://doi.org/10.1016/j.procs.2017.09.027

Hayek, F. A. (1948). Individualism and economic order. Chicago: University of Chicago Press.

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.

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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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Excerpts and Notes from Goldberg’s “Billions of Drops…”

December 23, 2015

Goldberg, S. H. (2009). Billions of drops in millions of buckets: Why philanthropy doesn’t advance social progress. New York: Wiley.

p. 8:
Transaction costs: “…nonprofit financial markets are highly disorganized, with considerable duplication of effort, resource diversion, and processes that ‘take a fair amount of time to review grant applications and to make funding decisions’ [citing Harvard Business School Case No. 9-391-096, p. 7, Note on Starting a Nonprofit Venture, 11 Sept 1992]. It would be a major understatement to describe the resulting capital market as inefficient.”

A McKinsey study found that nonprofits spend 2.5 to 12 times more raising capital than for-profits do. When administrative costs are factored in, nonprofits spend 5.5 to 21.5 times more.

For-profit and nonprofit funding efforts contrasted on pages 8 and 9.

p. 10:
Balanced scorecard rating criteria

p. 11:
“Even at double-digit annual growth rates, it will take many years for social entrepreneurs and their funders to address even 10% of the populations in need.”

p. 12:
Exhibit 1.5 shows that the percentages of various needs served by leading social enterprises are barely drops in the respective buckets; they range from 0.07% to 3.30%.

pp. 14-16:
Nonprofit funding is not tied to performance. Even when a nonprofit makes the effort to show measured improvement in impact, it does little or nothing to change their funding picture. It appears that there is some kind of funding ceiling implicitly imposed by funders, since nonprofit growth and success seems to persuade capital sources that their work there is done. Mediocre and low performing nonprofits seem to be able to continue drawing funds indefinitely from sympathetic donors who don’t require evidence of effective use of their money.

p. 34:
“…meaningful reductions in poverty, illiteracy, violence, and hopelessness will require a fundamental restructuring of nonprofit capital markets. Such a restructuring would need to make it much easier for philanthropists of all stripes–large and small, public and private, institutional and individual–to fund nonprofit organizations that maximize social impact.”

p. 54:
Exhibit 2.3 is a chart showing that fewer people rose from poverty, and more remained in it or fell deeper into it, in the period of 1988-98 compared with 1969-1979.

pp. 70-71:
Kotter’s (1996) change cycle.

p. 75:
McKinsey’s seven elements of nonprofit capacity and capacity assessment grid.

pp. 94-95:
Exhibits 3.1 and 3.2 contrast the way financial markets reward for-profit performance with the way nonprofit markets reward fund raising efforts.

Financial markets
1. Market aggregates and disseminates standardized data
2. Analysts publish rigorous research reports
3. Investors proactively search for strong performers
4. Investors penalize weak performers
5. Market promotes performance
6. Strong performers grow

Nonprofit markets
1. Social performance is difficult to measure
2. NPOs don’t have resources or expertise to report results
3. Investors can’t get reliable or standardized results data
4. Strong and weak NPOs spend 40 to 60% of time fundraising
5. Market promotes fundraising
6. Investors can’t fund performance; NPOs can’t scale

p. 95:
“…nonprofits can’t possibly raise enough money to achieve transformative social impact within the constraints of the existing fundraising system. I submit that significant social progress cannot be achieved without what I’m going to call ‘third-stage funding,’ that is, funding that doesn’t suffer from disabling fragmentation. The existing nonprofit capital market is not capable of [p. 97] providing third-stage funding. Such funding can arise only when investors are sufficiently well informed to make big bets at understandable and manageable levels of risk. Existing nonprofit capital markets neither provide investors with the kinds of information needed–actionable information about nonprofit performance–nor provide the kinds of intermediation–active oversight by knowledgeable professionals–needed to mitigate risk. Absent third-stage funding, nonprofit capital will remain irreducibly fragmented, preventing the marshaling of resources that nonprofit organizations need to make meaningful and enduring progress against $100 million problems.”

pp. 99-114:
Text and diagrams on innovation, market adoption, transformative impact.

p. 140:
Exhibit 4.2: Capital distribution of nonprofits, highlighting mid-caps

pages 192-3 make the case for the difference between a regular market and the current state of philanthropic, social capital markets.

p. 192:
“So financial markets provide information investors can use to compare alternative investment opportunities based on their performance, and they provide a dynamic mechanism for moving money away from weak performers and toward strong performers. Just as water seeks its own level, markets continuously recalibrate prices until they achieve a roughly optimal equilibrium at which most companies receive the ‘right’ amount of investment. In this way, good companies thrive and bad ones improve or die.
“The social sector should work the same way. .. But philanthropic capital doesn’t flow toward effective nonprofits and away from ineffective nonprofits for a simple reason: contributors can’t tell the difference between the two. That is, philanthropists just don’t [p. 193] know what various nonprofits actually accomplish. Instead, they only know what nonprofits are trying to accomplish, and they only know that based on what the nonprofits themselves tell them.”

p. 193:
“The signs that the lack of social progress is linked to capital market dysfunctions are unmistakable: fundraising remains the number-one [p. 194] challenge of the sector despite the fact that nonprofit leaders divert some 40 to 60% of their time from productive work to chasing after money; donations raised are almost always too small, too short, and too restricted to enhance productive capacity; most mid-caps are ensnared in the ‘social entrepreneur’s trap’ of focusing on today and neglecting tomorrow; and so on. So any meaningful progress we could make in the direction of helping the nonprofit capital market allocate funds as effectively as the private capital market does could translate into tremendous advances in extending social and economic opportunity.
“Indeed, enhancing nonprofit capital allocation is likely to improve people’s lives much more than, say, further increasing the total amount of donations. Why? Because capital allocation has a multiplier effect.”

“If we want to materially improve the performance and increase the impact of the nonprofit sector, we need to understand what’s preventing [p. 195] it from doing a better job of allocating philanthropic capital. And figuring out why nonprofit capital markets don’t work very well requires us to understand why the financial markets do such a better job.”

p. 197:
“When all is said and done, securities prices are nothing more than convenient approximations that market participants accept as a way of simplifying their economic interactions, with a full understanding that market prices are useful even when they are way off the mark, as they so often are. In fact, that’s the whole point of markets: to aggregate the imperfect and incomplete knowledge held by vast numbers of traders about much various securities are worth and still make allocation choices that are better than we could without markets.
“Philanthropists face precisely the same problem: how to make better use of limited information to maximize output, in this case, social impact. Considering the dearth of useful tools available to donors today, the solution doesn’t have to be perfect or even all that good, at least at first. It just needs to improve the status quo and get better over time.
“Much of the solution, I believe, lies in finding useful adaptations of market mechanisms that will mitigate the effects of the same lack of reliable and comprehensive information about social sector performance. I would even go so far as to say that social enterprises can’t hope to realize their ‘one day, all children’ visions without a funding allociation system that acts more like a market.
“We can, and indeed do, make incremental improvements in nonprofit funding without market mechanisms. But without markets, I don’t see how we can fix the fragmentation problem or produce transformative social impact, such as ensuring that every child in America has a good education. The problems we face are too big and have too many moving parts to ignore the self-organizing dynamics of market economics. As Thomas Friedman said about the need to impose a carbon tax at a time of falling oil prices, ‘I’ve wracked my brain trying to think of ways to retool America around clean-power technologies without a price signal–i.e., a tax–and there are no effective ones.”

p. 199:
“Prices enable financial markets to work the way nonprofit capital markets should–by sending informative signals about the most effective organizations so that money will flow to them naturally..”

p. 200:
[Quotes Kurtzman citing De Soto on the mystery of capital. Also see p. 209, below.]
“‘Solve the mystery of capital and you solve many seemingly intractable problems along with it.'”
[That’s from page 69 in Kurtzman, 2002.]

p. 201:
[Goldberg says he’s quoting Daniel Yankelovich here, but the footnote does not appear to have anything to do with this quote:]
“‘The first step is to measure what can easily be measured. The second is to disregard what can’t be measured, or give it an arbitrary quantitative value. This is artificial and misleading. The third step is to presume that what can’t be measured easily isn’t very important. This is blindness. The fourth step is to say that what can’t be easily measured really doesn’t exist. This is suicide.'”

Goldberg gives example here of $10,000 invested witha a 10% increase in value, compared with $10,000 put into a nonprofit. “But if the nonprofit makes good use of the money and, let’s say, brings the reading scores of 10 elementary school students up from below grade level to grade level, we can’t say how much my initial investment is ‘worth’ now. I could make the argument that the value has increased because the students have received a demonstrated educational benefit that is valuable to them. Since that’s the reason I made the donation, the achievement of higher scores must have value to me, as well.”

p. 202:
Goldberg wonders whether donations to nonprofits would be better conceived as purchases than investments.

p. 207:
Goldberg quotes Jon Gertner from the March 9, 2008, issue of the New York Times Magazine devoted to philanthropy:

“‘Why shouldn’t the world’s smartest capitalists be able to figure out more effective ways to give out money now? And why shouldn’t they want to make sure their philanthropy has significant social impact? If they can measure impact, couldn’t they get past the resistance that [Warren] Buffet highlighted and finally separate what works from what doesn’t?'”

p. 208:
“Once we abandon the false notions that financial markets are precision instruments for measuring unambiguous phenomena, and that the business and nonproft sectors are based in mutually exclusive principles of value, we can deconstruct the true nature of the problems we need to address and adapt market-like mechanisms that are suited to the particulars of the social sector.
“All of this is a long way (okay, a very long way) of saying that even ordinal rankings of nonprofit investments can have tremendous value in choosing among competing donation opportunities, especially when the choices are so numerous and varied. If I’m a social investor, I’d really like to know which nonprofits are likely to produce ‘more’ impact and which ones are likely to produce ‘less.'”

“It isn’t necessary to replicate the complex working of the modern stock markets to fashion an intelligent and useful nonprofit capital allocation mechanism. All we’re looking for is some kind of functional indication that would (1) isolate promising nonprofit investments from among the confusing swarm of too many seemingly worthy social-purpose organizations and (2) roughly differentiate among them based on the likelihood of ‘more’ or ‘less’ impact. This is what I meant earlier by increasing [p. 209] signals and decreasing noise.”

p. 209:
Goldberg apparently didn’t read De Soto, as he says that the mystery of capital is posed by Kurtzman and says it is solved via the collective intelligence and wisdom of crowds. This completely misses the point of the crucial value that transparent representations of structural invariance hold in market functionality. Goldberg is apparently offering a loose kind of market for which there is an aggregate index of stocks for nonprofits that are built up from their various ordinal performance measures. I think I find a better way in my work, building more closely from De Soto (Fisher, 2002, 2003, 2005, 2007, 2009a, 2009b).

p. 231:
Goldberg quotes Harvard’s Allen Grossman (1999) on the cost-benefit boundaries of more effective nonprofit capital allocation:

“‘Is there a significant downside risk in restructuring some portion of the philanthropic capital markets to test the effectiveness of performance driven philanthropy? The short answer is, ‘No.’ The current reality is that most broad-based solutions to social problems have eluded the conventional and fragmented approaches to philanthropy. It is hard to imagine that experiments to change the system to a more performance driven and rational market would negatively impact the effectiveness of the current funding flows–and could have dramatic upside potential.'”

p. 232:
Quotes Douglas Hubbard’s How to Measure Anything book that Stenner endorsed, and Linacre and I didn’t.

p. 233:
Cites Stevens on the four levels of measurement and uses it to justify his position concerning ordinal rankings, recognizing that “we can’t add or subtract ordinals.”

pp. 233-5:
Justifies ordinal measures via example of Google’s PageRank algorithm. [I could connect from here using Mary Garner’s (2009) comparison of PageRank with Rasch.]

p. 236:
Goldberg tries to justify the use of ordinal measures by citing their widespread use in social science and health care. He conveniently ignores the fact that virtually all of the same problems and criticisms that apply to philanthropic capital markets also apply in these areas. In not grasping the fundamental value of De Soto’s concept of transferable and transparent representations, and in knowing nothing of Rasch measurement, he was unable to properly evaluate to potential of ordinal data’s role in the formation of philanthropic capital markets. Ordinal measures aren’t just not good enough, they represent a dangerous diversion of resources that will be put into systems that take on lives of their own, creating a new layer of dysfunctional relationships that will be hard to overcome.

p. 261 [Goldberg shows here his complete ignorance about measurement. He is apparently totally unaware of the work that is in fact most relevant to his cause, going back to Thurstone in 1920s, Rasch in the 1950s-1970s, and Wright in the 1960s to 2000. Both of the problems he identifies have long since been solved in theory and in practice in a wide range of domains in education, psychology, health care, etc.]:
“Having first studied performance evaluation some 30 years ago, I feel confident in saying that all the foundational work has been done. There won’t be a ‘eureka!’ breakthrough where someone finally figures out the one true way to guage nonprofit effectiveness.
“Indeed, I would venture to say that we know virtually everything there is to know about measuring the performance of nonprofit organizations with only two exceptions: (1) How can we compare nonprofits with different missions or approaches, and (2) how can we make actionable performance assessments common practice for growth-ready mid-caps and readily available to all prospective donors?”

p. 263:
“Why would a social entrepreneur divert limited resources to impact assessment if there were no prospects it would increase funding? How could an investor who wanted to maximize the impact of her giving possibly put more golden eggs in fewer impact-producing baskets if she had no way to distinguish one basket from another? The result: there’s no performance data to attract growth capital, and there’s no growth capital to induce performance measurement. Until we fix that Catch-22, performance evaluation will not become an integral part of social enterprise.”

pp. 264-5:
Long quotation from Ken Berger at Charity Navigator on their ongoing efforts at developing an outcome measurement system. [wpf, 8 Nov 2009: I read the passage quoted by Goldberg in Berger’s blog when it came out and have been watching and waiting ever since for the new system. wpf, 8 Feb 2012: The new system has been online for some time but still does not include anything on impacts or outcomes. It has expanded from a sole focus on financials to also include accountability and transparency. But it does not yet address Goldberg’s concerns as there still is no way to tell what works from what doesn’t.]

p. 265:
“The failure of the social sector to coordinate independent assets and create a whole that exceeds the sum of its parts results from an absence of.. platform leadership’: ‘the ability of a company to drive innovation around a particular platform technology at the broad industry level.’ The object is to multiply value by working together: ‘the more people who use the platform products, the more incentives there are for complement producers to introduce more complementary products, causing a virtuous cycle.'” [Quotes here from Cusumano & Gawer (2002). The concept of platform leadership speaks directly to the system of issues raised by Miller & O’Leary (2007) that must be addressed to form effective HSN capital markets.]

p. 266:
“…the nonprofit sector has a great deal of both money and innovation, but too little available information about too many organizations. The result is capital fragmentation that squelches growth. None of the stakeholders has enough horsepower on its own to impose order on this chaos, but some kind of realignment could release all of that pent-up potential energy. While command-and-control authority is neither feasible nor desirable, the conditions are ripe for platform leadership.”

“It is doubtful that the IMPEX could amass all of the resources internally needed to build and grow a virtual nonprofit stock market that could connect large numbers of growth-capital investors with large numbers of [p. 267] growth-ready mid-caps. But it might be able to convene a powerful coalition of complementary actors that could achieve a critical mass of support for performance-based philanthropy. The challenge would be to develop an organization focused on filling the gaps rather than encroaching on the turf of established firms whose participation and innovation would be required to build a platform for nurturing growth of social enterprise..”

p. 268-9:
Intermediated nonprofit capital market shifts fundraising burden from grantees to intermediaries.

p. 271:
“The surging growth of national donor-advised funds, which simplify and reduce the transaction costs of methodical giving, exemplifies the kind of financial innovation that is poised to leverage market-based investment guidance.” [President of Schwab Charitable quoted as wanting to make charitable giving information- and results-driven.]

p. 272:
Rating agencies and organizations: Charity Navigator, Guidestar, Wise Giving Alliance.
Online donor rankings: GlobalGiving, GreatNonprofits, SocialMarkets
Evaluation consultants: Mathematica

Google’s mission statement: “to organize the world’s information and make it universally accessible and useful.”

p. 273:
Exhibit 9.4 Impact Index Whole Product
Image of stakeholders circling IMPEX:
Trading engine
Listed nonprofits
Data producers and aggregators
Trading community
Researchers and analysts
Investors and advisors
Government and business supporters

p. 275:
“That’s the starting point for replication [of social innovations that work]: finding and funding; matching money with performance.”

[WPF bottom line: Because Goldberg misses De Soto’s point about transparent representations resolving the mystery of capital, he is unable to see his way toward making the nonprofit capital markets function more like financial capital markets, with the difference being the focus on the growth of human, social, and natural capital. Though Goldberg intuits good points about the wisdom of crowds, he doesn’t know enough about the flaws of ordinal measurement relative to interval measurement, or about the relatively easy access to interval measures that can be had, to do the job.]

References

Cusumano, M. A., & Gawer, A. (2002, Spring). The elements of platform leadership. MIT Sloan Management Review, 43(3), 58.

De Soto, H. (2000). The mystery of capital: Why capitalism triumphs in the West and fails everywhere else. New York: Basic Books.

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. (2003). Measurement and communities of inquiry. Rasch Measurement Transactions, 17(3), 936-8 [http://www.rasch.org/rmt/rmt173.pdf].

Fisher, W. P., Jr. (2005). Daredevil barnstorming to the tipping point: New aspirations for the human sciences. Journal of Applied Measurement, 6(3), 173-9 [http://www.livingcapitalmetrics.com/images/FisherJAM05.pdf].

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. (2009a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. In M. Wilson, K. Draney, N. Brown & B. Duckor (Eds.), Advances in Rasch Measurement, Vol. Two (p. in press [http://www.livingcapitalmetrics.com/images/BringingHSN_FisherARMII.pdf]). Maple Grove, MN: JAM Press.

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

Garner, M. (2009, Autumn). Google’s PageRank algorithm and the Rasch measurement model. Rasch Measurement Transactions, 23(2), 1201-2 [http://www.rasch.org/rmt/rmt232.pdf].

Grossman, A. (1999). Philanthropic social capital markets: Performance driven philanthropy (Social Enterprise Series 12 No. 00-002). Harvard Business School Working Paper.

Kotter, J. (1996). Leading change. Cambridge, Massachusetts: Harvard Business School Press.

Kurtzman, J. (2002). How the markets really work. New York: Crown Business.

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), 701-34.

A truly ambitious plan to tackle climate change 

December 3, 2015

A recent story in the NY Times asks just what a truly ambitious plan to tackle climate change would look like. Pledges of emissions cuts being made in Paris this month are projected to fall short of what is needed to solve the problem of climate change. Calls for mass mobilization on the scale of the U.S.’s entry into WWII are met with skepticism at the same time that leaders are signing on for stronger terms in the Paris agreement than their countries have agreed to.

One crucial assumption is made across the full range of the proposals for more stringent standards and innovative technologies. That assumption is that solving the problem of climate change is a matter of marshaling the will to get the job done. On the face of it, of course, it seems inane to consider something as important as will power to be part of the problem. If people don’t want to do something, how could it possibly ever get done?

But as I’ve pointed out in a number of previous posts in this blog, complex problems sometimes cannot be solved from within the conceptual framework that engendered them. We are in this situation in large part because our overall relation to the earth is based on assuming it to be a bottomless well of resources, with the only limitation being the creativity we bring to bear in tapping those resources. Though many of us, perhaps a majority, are seriously committed to reconceiving our relation to the earth in sustainable terms, practical results are nearly impossible to produce within the existing institutional framework. Our economic, legal, accounting, education, etc. systems are all set up to support a consumer ethos that hobbles and undercuts almost all efforts intended to support an alternative sustainability ethos. It is both ironic and counterproductive to formulate solutions to the problem of climate change without first changing the institutional background assumptions informing the rules, roles and responsibilities through which we conceptualize and implement those solutions.

Insight into this problem is provided by recent work on standards for sustainability accounting. It shows that, by definition, efforts targeting change in economic externalities like environmental concerns cannot be scaled up in ways that are needed. This happens simply because balancing mission and margin demands maintenance of the bottom line. Giving away the business in the name of saving the planet might be a noble gesture but it is the opposite of sustainable and more importantly does not provide a viable model for the future.

So how do we model a new kind of bottom line that balances mission and margin in a new way? A way in which institutional rules, roles and responsibilities are themselves configured into the sustainable ecological relations we need? A way in which means and ends are unified? How do we become the change we want to see? How can we mobilize an international mass movement focused on doing what needs to be done to solve the problem of climate change? What possibilities do we have for catalyzing the increasingly saturated solution of global discontent and desire for a new relation to the earth? Can natural social processes of leaderless self organizing systems be seeded and guided to fruition? What would that seeding and guidance look like?

For proposed answers to these questions and more on what a model of a truly ambitious plan to tackle climate change might look like, see other posts in this blog here, here, here, and here.

With Reich in spirit, but with a different sense of the problem and its solution

October 4, 2015

In today’s editorial in the San Francisco Chronicle, Robert Reich seeks some way of defining a solution to the pressing problems of how globalization and technological changes have made American workers less competitive. He rightly says that “reversing the scourge of widening inequality requires reversing the upward distributions [of income] within the rules of the market, and giving average people the bargaining power they need to get a larger share of the gains from growth.”

But Reich then says that the answer to this problem lies in politics, not economics. As I’ve pointed out before in this blog, focusing on marshaling political will is part of the problem, not part of the solution. Historically, politicians do not lead, they follow. As is demonstrated across events as diverse as the Arab Spring and the Preemption Act of 1841, mass movements of people have repeatedly demanded ways of cutting through the Gordian knots of injustice. And just as the political “leadership” across the Middle East and in the early U.S. dragged its feet, obstructed, and violently opposed change until it was already well underway, so, too, will that pattern repeat itself again in the current situation of inequitable income distribution.

The crux of the problem is that no one can give average people anything, not freedom (contra Dylan’s line in Blowin’ in the Wind about “allowing” people to be free) and certainly not a larger share of the gains from growth. As the old saying goes, you can lead a horse to water, but you can’t make it drink. People have to take what’s theirs. They have to want it, they have to struggle for it, and they have to pay for it, or they cannot own it and it will never be worth anything to them.

It is well known that a lack of individual property rights doomed communism and socialism because when everything is owned collectively by everyone, no one takes responsibility for it. The profit motive has the capacity to drive people to change things. The problem is not in profit itself. If birds and bees and trees and grasses did not profit from the sun, soil, and rain, there would be no life. The problem is in finding how to get a functional, self-sustaining economic ecology off the ground, not in unrealistically trying to manipulate and micromanage every detail.

The fundamental relevant characteristic of the profits being made today from intellectual property rights is that our individual rights to our own human and social capital are counter-productively restricted and undeveloped. How can it be that no one has any idea how much literacy or health capital they have, or what it is worth?! We have a metric system that tells us how much real estate and manufactured capital we own, and we can price it. But despite the well-established scientific facts of decades of measurement science research and practice, none of us can say, “I own x number of shares of stock in intellectual, literacy, or community capital, that have a value of x dollars in today’s market.” We desperately need an Intangible Assets Metric System, and the market rules, roles, and responsibilities that will make it impossible to make a profit while destroying human, social, and natural capital.

In this vein, what Reich gets absolutely correct is hidden inside his phrase, “within the rules of the market.” As I’ve so often repeated in this blog, capitalism is not inherently evil; it is, rather, unfinished. The real evil is in prolonging the time it takes to complete it. As was so eloquently stated by Miller and O’Leary (2007, p. 710):

“Markets are not spontaneously generated by the exchange activity of buyers and sellers. Rather, skilled actors produce institutional arrangements, the rules, roles and relationships that make market exchange possible. The institutions define the market, rather than the reverse.”

We have failed to set up the institutional arrangements needed to define human, social, and natural capital markets. The problem is that we cannot properly manage three of the four major forms of capital (human, social, and natural, with the fourth being manufactured/property) because we do not measure them in a common language built into scientifically, economically, legally and financially accountable titles, deeds, and other instruments.

And so, to repeat another one of my ad nauseum broken record nostrums, the problem is the problem. As long as we keep defining problems in the way we always have, as matters of marshalling political will, we will inadvertently find ourselves contributing more to prolonging tragic and needless human suffering, social discontent, and environmental degradation.

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.

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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On the Criterion Institute’s Leaders Shaping Markets initiative

November 14, 2013

The Criterion Institute’s Leaders Shaping Markets initiative is an encouraging development in large part because of its focus on systems level change. As the Institute recognizes, the questions being raised and the resources being invested are essential to overcoming recurrent problems of fragmentation and marginalization in efforts being made in more piecemeal fashion across a number of other arenas.

Of particular interest from the Institute’s second roundtable session is Joy Anderson’s list of Strategies for Shaping Market Systems. Anderson presents five strategies:

  1. reframing the issues, problems, and boundaries of the system;
  2. engaging systems of power, elegantly;
  3. continuously identifying leverage points in the system;
  4. building structures and leadership for sustained systems-level disruption; and
  5. attending to change over time and across context.

Reframing is the right place to start. As I’ve said elsewhere in this blog, the problem is the problem. At this level of complexity, problems cannot be solved from within the same paradigm they were born from. Conceiving ways of redefining problems that truly reframe the issues and boundaries of a system is hard enough, but implementing them is even harder.

From my point of view, philosophically, the central problem that makes everything so difficult has to do with our deeply ingrained Western habits of thought around not viewing problems and solutions as of a piece, as wholes in which each implies the other. As long as we keep defining problems and solutions in ways that separate them, as though the solution is in no way involved in perpetuating the problem, we are hopelessly stuck.

So we restrict our options for solving problems by the way we frame the issues. And when we misidentify the problem, as when we fail to properly frame it, then we will likely not only not solve it, we will make it worse. That seems to be exactly what’s been going on in the struggle for economic and social justice for decades and centuries.

So if we reframe the problem of shaping markets around the mutual implication of problems and solutions, how do we move to the next step, to engaging systems of power, elegantly? There are a lot of deep and complex philosophical concepts involved here, but we can cut to the chase and note that our language and tools embody problem-solution unities. Social ecologies of relationships define the meanings and uses of things and ideas.

One way of engaging systems of power elegantly to shape markets might then be to harness the power driving those markets in new, more efficient and meaningful ways. The question that then immediately arises concerns the next of Anderson’s five points: where do we find the leverage in the system that would enable the harnessing of its power?

There is likely no greater concentration of power in markets than the profit motive. How might it become the primary lever for engaging the power of the market? We might, for instance, deploy tools and ideas that co-opt the interests of the systems of power by enhancing the predictability of market forces and sustainability of profits. Concentrating now on dwelling within the problem-solution unity of how to shape markets, we can tap into a key factor that makes markets efficient: we manage what we measure, and management is facilitated when we can measure quality and quantity cheaply and easily.

Common currencies for the exchange of value are essential not just to trade and commerce, but also take shape as the standard metrics employed in science, engineering, music, and as the signs and symbols of basic communication. Money is such an easy to manage measure of value that the problems we are addressing here stem in large part from using it too exclusively as a proxy for the authentic wealth we really want. Engaging with systems of power elegantly also then requires us to think in terms of extending the power of standard units of measurement into the new domains of intangible assets: human, social, and natural capital.

This is where we arrive at the structures for sustained system-level disruption. Current economic models and financial spreadsheets focus on the three classic forms of capital: land, labor, and manufactured tools/commodities. (Money, as liquid capital, is fungible relative to all three.) Of these three, we have a metric system for measuring and managing only property and manufactured tools/commodities.

Green economics offers an alternative four-capitals model that adds social capital and reframes land as natural capital and labor as human capital. Both of the latter are found to be far more complex and valuable than their usual reductions to a piece of ground or “hands” would suggest. Human capital involves health, abilities, and motivations; natural capital includes the earth’s air and water purification systems, and food supplies. The addition of social capital is justified on the grounds that, without it, markets are impossible.

What we do not have is a metric system for three of the four forms of capital. Nor do we have the legal and financial systems needed to bring these forms of capital to life in efficient markets, to make them recognized and accepted in banks and courts of law. We further also do not have leaders aware of the need for these structures, and of the established basis in scientific research that makes them viable.

The science is complex and technical, but it brings to bear practical capacities for meaningful, individual level, qualitatively informative and quantitatively rigorous measurement. There is considerable elegance in this method of approaching engagement with the systems of power. There is mathematical beauty in the symmetry and harmony of instruments tuned to the same scales. There is exquisite grace in the way the program for shaping markets grows organically from the seeds of existing markets. The human value of enabling the realization of heretofore unreachable degrees of individual potentials would be enormous, as would be the social value of being able to make returns on investments in education, health care, social services, and the environment accountable.

Successful new markets harnessing the profit motive in the name of socially responsible and sustainable economies well ought to provoke a new cultural renaissance as the proven relationships between higher rates of educational attainment and health, community relations, and environmental quality are born out. The challenges are huge, but properly framing the problems and their solutions will unify our energies in common purpose like never before, bringing joy to the effort.

For further reading along these lines, see:

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

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). Washington, DC: National Science Foundation, http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36

Fisher, W. P., Jr. (2012, 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://ses-standards.org/associations/3698/files/2011WSDthirdplacepaper.pdf or http://ssrn.com/abstract=2083975

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, http://doi:10.1016/j.measurement.2009.03.014

Fisher, W. P., Jr. (2011). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), 49-66, http://ssrn.com/abstract=1698867

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

https://livingcapitalmetrics.wordpress.com/2010/01/13/reinventing-capitalism/

Dispelling Myths about Measurement in Psychology and the Social Sciences

August 27, 2013

Seven common assumptions about measurement and method in psychology and the social sciences stand as inconsistent anomalies in the experience of those who have taken the trouble to challenge them. As evidence, theory, and instrumentation accumulate, will we see a revolutionary break and disruptive change across multiple social and economic levels and areas as a result? Will there be a slower, more gradual transition to a new paradigm? Or will the status quo simply roll on, oblivious to the potential for new questions and new directions? We shall see.

1. Myth: Qualitative data and methods cannot really be integrated with quantitative data and methods because of opposing philosophical assumptions.

Fact: Qualitative methods incorporate a critique of quantitative methods that leads to a more scientific theory and practice of measurement.

2. Myth: Statistics is the logic of measurement.

Fact: Statistics did not emerge as a discipline until the 19th century, while measurement, of course, has been around for millennia. Measurement is modeled at the individual level within a single variable whereas statistics model at the population level between variables. Data are fit to prescriptive measurement models using the Garbage-In, Garbage-Out (GIGO) Principle, while descriptive statistical models are fit to data.

3. Myth: Linear measurement from ordinal test and survey data is impossible.

Fact: Ordinal data have been used as a basis for invariant linear measures for decades.

4. Myth: Scientific laws like Newton’s laws of motion cannot be successfully formulated, tested, or validated in psychology and the social sciences.

Fact: Mathematical laws of human behavior and cognition in the same form as Newton’s laws are formulated, tested, and validated in numerous Rasch model applications.

5. Myth: Experimental manipulations of psychological and social phenomena are inherently impossible or unethical.

Fact: Decades of research across multiple fields have successfully shown how theory-informed interventions on items/indicators/questions can result in predictable, consistent, and substantively meaningful quantitative changes.

6. Myth: “Real” measurement is impossible in psychology and the social sciences.

Fact: Success in predictive theory, instrument calibration, and in maintaining stable units of comparison over time are all evidence supporting the viability of meaningful uniform units of measurement in psychology and the social sciences.

7. Myth: Efficient economic markets can incorporate only manufactured and liquid capital, and property. Human, social, and natural capital, being intangible, have permanent status as market externalities as they cannot be measured well enough to enable accountability, pricing, or transferable representations (common currency instruments).

Fact: The theory and methods necessary for establishing an Intangible Assets Metric System are in hand. What’s missing is the awareness of the scientific, human, social, and economic value that would be returned from the admittedly very large investments that would be required.

References and examples are available in other posts in this blog, in my publications, or on request.

The New Information Platform No One Sees Coming

December 6, 2012

I’d like to draw your attention to a fundamentally important area of disruptive innovations no one seems to see coming. The biggest thing rising in the world of science today that does not appear to be on anyone’s radar is measurement. Transformative potential beyond that of the Internet itself is available.

Realizing that potential will require an Intangible Assets Metric System. This system will connect together all the different ways any one thing is measured, bringing common languages for representing human, social, and economic value into play everywhere. We need these metrics on the front lines of education, health care, social services, and in human, reputation, and natural resource management, as well as in the economic models and financial spreadsheets informing policy, and in the scientific research conducted in dozens of fields.

All reading ability measures, for instance, should be transparently, inexpensively, and effortlessly expressed in a universally uniform metric, in the same way that standardized measures of weight and volume inform grocery store purchasing decisions. We have made starts at such systems for reading, writing, and math ability measures, and for health status, functionality, and chronic disease management measures. There oddly seems to be, however, little awareness of the full value that stands to be gained from uniform metrics in these areas, despite the overwhelming human, economic, and scientific value derived from standardized units in the existing economy. There has accordingly been virtually no leadership or investment in this area.

Measurement practice in business is woefully out of touch with the true paradigm shift that has been underway in psychometrics for years, even though the mantra “you manage what you measure” is repeated far and wide. In a fascinating twist, practically the only ones who notice the business world’s conceptual shortfall in measurement practice are the contrarians who observe that quantification can often be more of a distraction from management than the medium of its execution—but this is true only when measures are poorly conceived, designed, and implemented.

Demand for better measurement—measurement that reduces data volume not only with no loss of information but with the addition of otherwise unavailable interstitial information; that supports mass customized comparability for informed purchasing and quality improvement decisions; and that enables common product definitions for outcomes-based budgeting—is growing hand in hand with the spread of resilient, nimble, lean, and adaptive business models, and with the ongoing geometrical growth in data volume.

An even bigger source of demand for the features of advanced measurement is the increasing dependence of the economy on intangible assets, those forms of human, social, and natural capital that comprise 90% or more of the total capital under management. We will bring these now economically dead forms of capital to life by systematically standardizing representations of their quality and quantity. The Internet is the planetary nervous system through which basic information travels, and the Intangible Assets Metric System will be the global cerebrum, where higher order thinking takes place.

It will not be possible to realize the full potential of lean thinking in the information- and service-based economy without an Intangible Assets Metric System. Given the long-proven business value of standards and the role of measurement in management, it seems self-evident that our ongoing economic difficulties stem largely from our failure to develop and deploy an Intangible Assets Metric System providing common currencies for the exchange of authentic wealth. The future of sustainable and socially responsible business practices must surely depend extensively on universal access to flexible and practical uniform metrics for intangible assets.

Of course, for global intangible assets standards to be viable, they must be adaptable to local business demands and conditions without compromising their comparability. And that is just what is most powerfully disruptive about contemporary measurement methods: they make mass customization a reality. They’ve been doing so in computerized testing since the 1970s. Isn’t it time we started putting this technology to systematic use in a wide range of applications, from human and environmental resource management to education, health care, and social services?