Archive for the ‘econometrics’ Category

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.

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.

References

Alder, K. (2002). The measure of all things: The seven-year odyssey and hidden error that transformed the world. New York: The Free Press.

Amato, N., & White, S. (2013, December 7). IIRC releases International Integrated Reporting Framework. Journal of Accountancy. Retrieved from http://www.journalofaccountancy.com/news/2013/dec/20139207.html

Andrich, D. (1988). Sage University Paper Series on Quantitative Applications in the Social Sciences. Vol. series no. 07-068: Rasch models for measurement. Beverly Hills, California: Sage Publications.

Andrich, D. (2004, January). Controversy and the Rasch model: A characteristic of incompatible paradigms? Medical Care, 42(1), I-7–I-16.

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

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

Ashworth, W. J. (2004, 19 November). Metrology and the state: Science, revenue, and commerce. Science, 306(5700), 1314-1317.

Baxter, W. T. (1979). Accounting standards: Boon or curse? In The Emmanuel Saxe distinguished lectures in accounting. http://newman.baruch.cuny.edu/digital/saxe/saxe_1978/baxter_79.htm.

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

De Boeck, P., & Wilson, M. (Eds.). (2004). Explanatory item response models: A generalized linear and nonlinear approach. Statistics for Social and Behavioral Sciences). New York: Springer-Verlag.

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

Dewey, J. (2012). Unmodern philosophy and modern philosophy (P. Deen, Ed.). Carbondale, Illinois: Southern Illinois University Press.

Editorial. (2010, 10 June). Accounting standards: To FASB or not to FASB? The Economist, http://www.economist.com/node/16319655.

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

Engelhard, G., Jr. (2012). Invariant measurement: Using Rasch models in the social, behavioral, and health sciences. New York: Routledge Academic.

Everett, J. D. (1875). Illustrations of the C. G. S. system of units. London, England: Taylor & Francis.

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 19). Draft legislation on development and adoption of an intangible assets metric system. Retrieved 6 January 2011, from https://livingcapitalmetrics.wordpress.com/2009/11/19/draft-legislation/

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

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

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

Fisher, W. P., Jr. (2010b). 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 (http://ssrn.com/abstract=2340674).

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

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

Fisher, W. P., Jr. (2011b). 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. (2015). A Rasch perspective on the law of supply and demand. Rasch Measurement Transactions, in press.

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

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

Fisher, W. P., Jr., & Stenner, A. J. (2011a, January). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). Retrieved 12 January 2014, from National Science Foundation: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

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

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

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

Fisher, W. P., Jr., & Stenner, A. J. (2015). The role of metrology in mobilizing and mediating the language and culture of scientific facts. Journal of Physics Conference Series, 588(012043).

Fisher, W. P., Jr., & Stenner, A. J. (2015). Theory-based metrological traceability in education: A reading measurement network. Measurement, in review.

Fisher, W. P., Jr., & Wilson, M. (2015). Building a productive trading zone in educational assessment research and practice. Pensamiento Educativo, in review.

Fisher, W. P., Jr., & Wright, B. D. (1994). Introduction to probabilistic conjoint measurement theory and applications (W. P. Fisher, Jr., & B. D. Wright, Eds.) [Special issue]. International Journal of Educational Research, 21(6), 559-568.

Galison, P. (1997). Image and logic: A material culture of microphysics. Chicago: University of Chicago Press.

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

Golinski, J. (2012). Is it time to forget science? Reflections on singular science and its history. Osiris, 27(1), 19-36.

Haraway, D. J. (1996). Modest witness: Feminist diffractions in science studies. In P. Galison & D. J. Stump (Eds.), The disunity of science: Boundaries, contexts, and power (pp. 428-441). Stanford, California: Stanford University Press.

Hawken, P., Lovins, A., & Lovins, H. L. (1999). Natural capitalism: Creating the next industrial revolution. New York: Little, Brown, and Co.

Jensen, M. C. (2001, Fall). Value maximization, stakeholder theory, and the corporate objective function. Journal of Applied Corporate Finance, 14(3), 8-21.

Latour, B. (1990). Postmodern? No, simply amodern: Steps towards an anthropology of science. Studies in History and Philosophy of Science, 21(1), 145-71.

Latour, B. (1993). We have never been modern. Cambridge, Massachusetts: Harvard University Press.

Latour, B. (2005). Reassembling the social: An introduction to Actor-Network-Theory. Clarendon Lectures in Management Studies). Oxford, England: Oxford University Press.

Mari, L., & Wilson, M. (2013). A gentle introduction to Rasch measurement models for metrologists. Journal of Physics Conference Series, 459(1), http://iopscience.iop.org/1742-6596/459/1/012002/pdf/1742-6596_459_1_012002.pdf.

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.

Pendrill, L. (2014, December). Man as a measurement instrument [Special Feature]. NCSLI Measure: The Journal of Measurement Science, 9(4), 22-33.

Pendrill, L., & Fisher, W. P., Jr. (2013). Quantifying human response: Linking metrological and psychometric characterisations of man as a measurement instrument. Journal of Physics: Conference Series, 459, http://iopscience.iop.org/1742-6596/459/1/012057.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

May 14, 2014

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Comment on Kerrey and Leeds in WSJ

November 20, 2013

Writing in today’s Wall Street Journal, Bob Kerrey and Jeffery T. Leeds note the unintended consequences likely to follow from new higher education regulations proposed by the U.S. Department of Education. Cutting to the chase, Kerrey and Leeds’ key points (emphases added) are that:

  • “Absent innovative, competitive—and, yes, disruptive—pressure to raise quality and lower costs, all the well-intentioned federal regulation in the world will not make college more accessible.”
  • “He [Secretary of Education, Arne Duncan] should insist on real and significant disclosure. Colleges should be required to post their graduation rates, job-placement rates, the average debt of their students upon graduation, their tax status and any and all information that will enable Americans to make informed decisions when choosing a school.”
  • “The department should also work with schools and colleges to address the fundamental causes of rising tuition, and hold schools accountable for student outcomes instead of their debt.”

These are, of course, exactly the themes repeatedly raised in this blog. Measurement quality is unavoidably implicated in holding schools accountable for student outcomes, in enabling consumers to make informed purchasing decisions, and in raising quality and lowering costs.

To meet the challenges we face, measurement quality must be far more than just a matter of precision and rigor. Quality must also speak to relevance, efficiency, and meaningfulness. Recent history has brought home the lesson that annual tests used solely for accountability purposes will not enable rebalanced quality/cost equations, informed consumer decisions, or fair accountability results. But how might these disparate purposes be efficiently and meaningfully realized?

It is essential that, if teachers are to be responsible for student outcomes and for raising the overall quality of education, formative measuring tools must provide the qualitative and quantitative information they need to be able to act responsibly. The irony is, of course, that the way to overcome the problems of a purely summative focus for educational measurement is to measure more! Now, measuring more need not involve devoting more time exclusively to taking tests. Instead, computerized and online assessments are increasingly integrated into instruction so that measures are made in the course of studying (Cheng and Mok, 2007; Wilson, 2004). Measures are thereby continuously updated, and are plotted in growth charts relative to long range outcome goals.

Furthermore, the qualitative information provided by the measurement process is used to inform teachers and students about what comes next in the individualized curriculum, as well as about special strengths and weaknesses. This information has been shown to be unparalleled in its value for advancing learning in the classroom (Black and Wiliam, 1998, 2009; Hattie, 2008).

But formative assessment alone will not be sufficient to the larger tasks of raising quality and lowering costs. For that, systematic quality improvement methods in schools will need to be joined with comparable outcome measures parents and students can use to inform school choice decisions (Fisher, 2013; Lunenberg, 2010).

Kerrey and Leeds rightly seek an infrastructure capable of disruptive effects, of transforming the inflationary economy of education (and health care). To state again a recurring theme in this blog, the command and control hierarchies of regulatory systems can and should be replaced with a metrological infrastructure of common metrics with the scientific, legal, and financial status of common currencies for the exchange of value. Only when such currencies are in place will we be able to set out clear paths for the informed decisions, improved quality, lower costs, and accountability for outcomes that we seek.

References

Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education, 5(1), 7-74.

Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21, 5-31.

Cheng, Y. C., & Mok, M. M. C. (2007). School-based management and paradigm shift in education: An empirical study. International Journal of Educational Management, 21(6), 517-542.

Fisher, W. P., Jr. (2013). Imagining education tailored to assessment as, for, and of learning: Theory, standards, and quality improvement. Assessment and Learning, 2, in press.

Hattie, J. (2008). Visible learning. New York: Routledge.

Lunenberg, F. C. (2010). Total Quality Management applied to schools. Schooling, 1(1), 1-6.

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

The Path to a New Consensus: A Practical Procedure for Resolving the Opposition Between Absolute and Relative Standards

August 26, 2011

The possibility of a new nonpartisan consensus on social and economic issues has been raised from time to time lately. I’ve had some ideas fermenting in this area for a while, and it seems like they might be ready for recording here. What I want to take up concerns one of the more contentious aspects of the cultural and political disputes of recent decades. There are important differences between those who want to impose one or another kind of moral or religious standard on society as a whole and those who contend that, within certain limits, such standards are arbitrary and must be determined by each individual or group according to its own values and sense of what makes a community.The oppositions here might seem to be irreconcilable, but is that actually true?

Resolving deep-seated disagreements on this scale requires that all parties accept some baseline rules of engagement. And herein lies the rub, eh? For even something as seemingly obvious and simple as defining factual truth has proven beyond the abilities of some highly skilled and deeply motivated negotiators. So, of course, those who adhere rigidly to preconceived notions automatically remove themselves from dialogue, and I cannot presume to address them here. But for those willing to entertain possibilities following from ideas and methods with which they may be unfamiliar, I say, read on.

What I want to propose differs in several fundamental respects from what has come before, and it is very similar in one fundamental respect. The similarity stems from the realization that essentially the same thing can be authoritatively stated at different times and place by different people using different words and different languages in relation to different customs and traditions. For instance, the versions of the Golden Rule given in the Gospels of Matthew or Luke are conceptually identical with the sentiment expressed in the Hindu Mahabarata, the Confucian Analects, the Jewish Talmud, the Muslim 13th Hadith, and the Buddhist Unada-Varga (http://www.thesynthesizer.org/golden.html; http://philosophy.tamu.edu/~gary/bioethics/ethicaltheory/universalizability.html).

So, rather than defining consensus in terms of strict agreement (with no uncertainty) on the absolute value of various propositions, it should be defined in terms of probabilities of consistent agreement (within a range of uncertainty) on the relative value of various propositions. Instead of evaluating isolated and decontextualized value statements one at a time, I propose evaluating value statements hypothesized to cohere with one another within a larger context together, as a unit.Instead of demanding complete data on a single set of propositions, I propose requiring and demonstrating that the same results be obtained across different sets of propositions addressing the same thing. Instead of applying statistical models of group level inter-variable relations to these data, I propose applying measurement models of individual level within-variable relations. Instead of setting policy on the basis of centrally controlled analytic results that vary incommensurably across data sets I propose setting policy on the basis of decentralized, distributed results collectively produced by networks of individuals whose behaviors and decisions are coordinated and aligned by calibrated instruments measuring in common commensurable units. All of these proposals are described in detail in previous posts here, and in the references included in those posts.

What I’m proposing is rooted in and extends existing practical solutions to the definition and implementation of standards. And though research across a number of fields suggests that a new degree of consensus on some basic issues seems quite possible, that consensus will not be universal and it should not be used as a basis for compelling conformity. Rather, the efficiencies that stand to be gained by capitalizing (literally) on existing but unrecognized standards of behavior and performance are of a magnitude that would easily support generous latitude in allowing poets, nonconformists, and political dissenters to opt out of the system at little or no cost to themselves or anyone else.

That is, as has been described and explained at length in previous posts here, should we succeed in establishing an Intangible Assets Metric System and associated genuine progress indicator or happiness index, we would be in the position of harnessing the power of the profit motive as an economic driver of growth in human, social, and natural capital. Instead of taking mere monetary profits as a measure of improved quality of life, we would set up economic systems in which the measurement and the management of quality of life determines monetary profits. The basic idea is that individual ownership of and accountability for what is, more than anything else, our rightful property–our own abilities, motivations, health, trustworthiness, loyalty, etc.–ought to be a significant factor in promoting the conservation and growth of these forms of capital.

In this context, what then might serve as a practical approach to resolving disputes between those who advocate standards and those who reject them, or between those who trust in our capacity to function satisfactorily as a society without standards and those who do not? Such an approach begins by recognizing the multitude of ways in which all of us rely on standards every day. We do not need to concern ourselves with the technical issues of electronics or manufacturing, though standards are essential here. We do not need even to take up the role of standards as guides to grocery or clothing store purchasing decisions or to planning meetings or travel across time zones.

All we need to think about is something as basic as communication. The alphabet, spelling, pronunciation, and grammatical rules, dictionaries, and educational curricula are all forms of standards that must be accepted, recognized and adhered to before the most basic communication can be achieved. The shapes of various letters or symbols, and the sounds associated with them, are all completely arbitrary. They are conventions that arose over centuries of usage that passed long before the rules were noted, codified, and written down. And spoken languages remain alive, changing in ways that break the rules and cause them to be rewritten, as when new words emerge, or previously incorrect constructions become accepted.

But what is the practical value for a new consensus in recognizing our broad acceptance of linguistic standards? Contrary to the expectations of l’Academie Francaise, for instance, we cannot simply make up new rules and expect people to follow them. No, the point of taking language as a key example goes deeper than that. We noted that usage precedes the formulation of rules, and so it must also be in finding our way to a basis for a new consensus. The question is, what are the lawful patterns by which we already structure behavior and decisions, patterns that might be codified in the language of a social science?

These patterns are being documented in research employing probabilistic measurement models. The fascinating thing about these patterns is that they often retain their characteristic features across different samples of people being measured, across time and space, and across different sets of questions on tests, surveys, or assessments designed to measure the same ability, behavior, attitude, or performance. The stability and constancy of these patterns are such that it appears possible to link all of the instruments measuring the same things to common units of measurement, so that everyone everywhere could think and act together in a common language.

And it is here, in linking instruments together in an Intangible Assets Metric System, that we arrive at a practical way of resolving some disputes between absolutists and relativists. Though we should and will take issue with his demand for certainty, Latour (2005, p. 228) asks the right question, 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!”

Nowhere does Latour show any awareness of what has been accomplished in social research employing probabilistic measurement models, but he nonetheless grasps exactly how the results of that research will not realize its potential unless it is expanded into networks of interconnected instrumentation. He understands that his theory of networked actors coordinated via virtual threads of standardized forms, metrics, vocabularies describes how scientific metrology and standards set the benchmark for universal consensus. Latour stresses that the focus here is on concrete material practices that can be objectively observed and replicated. As he says, when those practices are understood, then you know how to “do the same operation for other less traceable, less materialized circulations” (p. 229).

Latour’s primary concerns are with the constitution of sociology as a science of the social, and with the understanding of the social as networks of actors whose interests are embodied in technical devices that mediate relationships. Throughout his work, he therefore focuses on the description of existing sociotechnical phenomena. Presumably because of his lack of familiarity with social measurement theory and practice, Latour does not speak to ways in which the social sciences could go beyond documenting less traceable and less materialized circulations to creating more traceable and more materialized circulations, ones capable of more closely emulating those found in the natural sciences.

Latour’s results suggest criteria that may show some disputes regarded as unresolvable to have unexplored potentials for negotiation. That potential depends, as Latour says, on calibrating instruments that can be hooked up in a metrological chain in an actual material network with known properties (forms, Internet connections and nodes, a defined unit of measurement with tolerable uncertainty, etc.) and known costs. In the same way that the time cannot be told from a clock disconnected from the chain of connections to the standard time, each individual instrument for measuring abilities, health, quality of life, etc. will also have to be connected to its standard via an unbroken chain.

But however intimidating these problems might be, they are far less imposing than the ignorance that prevents any framing of the relevant issues in the first place. Addressing the need for rigorous measurement in general, Rasch (1980, pp. xx) agreed that “this is a huge challenge, but once the problem has been formulated it does seem possible to meet it.” Naturally enough, the needed work will have to be done by those of us calibrating the instruments of education, health care, sociology, etc. Hence my ongoing involvement in IMEKO, the International Measurement Confederation (http://www.tu-ilmenau.de/fakmb/Home.2382.0.html).

References

Latour, B. (2005). Reassembling the social: An introduction to Actor-Network-Theory. Clarendon Lectures in Management Studies). Oxford, England: Oxford University Press.

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

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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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New Opportunities for Job Creation and Prosperity

August 17, 2011

What can be done to create jobs and revive the economy? There is no simple, easy answer to this question. Creating busywork is nonsense. We need fulfilling occupations that meet the world’s demand for products and services. It is not easy to see how meaningful work can be systematically created on a broad scale. New energy efficiencies may lead to the cultivation of significant job growth, but it may be unwise to put all of our eggs in this one basket.

So how are we to solve this puzzle? What other areas in the economy might be ripe for the introduction of a new technology capable of supporting a wave of new productivity, like computers did in the 1980s, or the Internet in the 1990s? In trying to answer this question, simplicity and elegance are key factors in keeping things at a practical level.

For instance, we know we accomplish more working together as a team than as disconnected individuals. New jobs, especially new kinds of jobs, will have to be created via innovation. Innovation in science and industry is a team sport. So the first order of business in teaming up for job creation is to know the rules of the game. The economic game is played according to the rules of law embodied in property rights, scientific rationality, capital markets, and transportation/communications networks (see William Bernstein’s 2004 book, The Birth of Plenty). When these conditions are met, as they were in Europe and North America at the beginning of the nineteenth century, the stage is set for long term innovation and growth on a broad scale.

The second order of business is to identify areas in the economy that lack one or more of these four conditions, and that could reasonably be expected to benefit from their introduction. Education, health care, social services, and environmental management come immediately to mind. These industries are plagued with seemingly interminable inflationary spirals, which, no doubt, are at least in part caused by the inability of investors to distinguish between high and low performers. Money cannot flow to and reward programs producing superior results in these industries because they lack common product definitions and comparable measures of their results.

The problems these industries are experiencing are not specific to each of them in particular. Rather, the problem is a general one applicable across all industries, not just these. Traditionally, economic thinking focuses on three main forms of capital: land, labor, and manufactured products (including everything from machines, roads, and buildings to food, clothing, and appliances). Cash and credit are often thought of as liquid capital, but their economic value stems entirely from the access they provide to land, labor, and manufactured products.

Economic activity is not really, however, restricted to these three forms of capital. Land is far more than a piece of ground. What are actually at stake are the earth’s regenerative ecosystems, with the resources and services they provide. And labor is far more than a pair of skilled hands; people bring a complex mix of abilities, motivations, and health to bear in their work. Finally, this scheme lacks an essential element: the trust, loyalty, and commitment required for even the smallest economic exchange to take place. Without social capital, all the other forms of capital (human, natural, and manufactured, including property) are worthless. Consistent, sustainable, and socially responsible economic growth requires that all four forms of capital be made accountable in financial spreadsheets and economic models.

The third order of business, then, is to ask if the four conditions laying out the rules for the economic game are met in each of the four capital domains. The table below suggests that all four conditions are fully met only for manufactured products. They are partially met for natural resources, such as minerals, timber, fisheries, etc., but not at all for nature’s air and water purification systems or broader genetic ecosystem services.

 Table

Existing Conditions Relevant to Conceiving a New Birth of Plenty, by Capital Domains

Human

Social

Natural

Manufactured

Property rights

No

No

Partial

Yes

Scientific rationality

Partial

Partial

Partial

Yes

Capital markets

Partial

Partial

Partial

Yes

Transportation & communication networks

Partial

Partial

Partial

Yes

That is, no provisions exist for individual ownership of shares in the total available stock of air and water, or of forest, watershed, estuary, and other ecosystem service outcomes. Nor do any individuals have free and clear title to their most personal properties, the intangible abilities, motivations, health, and trust most essential to their economic productivity. Aggregate statistics are indeed commonly used to provide a basis for policy and research in human, social, and natural capital markets, but falsifiable models of individually applicable unit quantities are not widely applied. Scientifically rational measures of our individual stocks of intangible asset value will require extensive use of these falsifiable models in calibrating the relevant instrumentation.

Without such measures, we cannot know how many shares of stock in these forms of capital we own, or what they are worth in dollar terms. We lack these measures, even though decades have passed since researchers first established firm theoretical and practical foundations for them. And more importantly, even when scientifically rational individual measures can be obtained, they are never expressed in terms of a unit standardized for use within a given market’s communications network.

So what are the consequences for teams playing the economic game? High performance teams’ individual decisions and behaviors are harmonized in ways that cannot otherwise be achieved only when unit amounts, prices, and costs are universally comparable and publicly available. This is why standard currencies and exchange rates are so important.

And right here we have an insight into what we can do to create jobs. New jobs are likely going to have to be new kinds of jobs resulting from innovations. As has been detailed at length in recent works such as Surowiecki’s 2004 book, The Wisdom of Crowds, innovation in science and industry depends on standards. Standards are common languages that enable us to multiply our individual cognitive powers into new levels of collective productivity. Weights and measures standards are like monetary currencies; they coordinate the exchange of value in laboratories and businesses in the same way that dollars do in the US economy.

Applying Bernstein’s four conditions for economic growth to intangible assets, we see that a long term program for job creation then requires

  1. legislation establishing human, social, and natural capital property rights, and an Intangible Assets Metrology System;
  2. scientific research into consensus standards for measuring human, social, and natural capital;
  3. venture capital educational and marketing programs; and
  4. distributed information networks and computer applications through which investments in human, social, and natural capital can be tracked and traded in accord with the rule of law governing property rights and in accord with established consensus standards.

Of these four conditions, Bernstein (p. 383) points to property rights as being the most difficult to establish, and the most important for prosperity. Scientific results are widely available in online libraries. Capital can be obtained from investors anywhere. Transportation and communications services are available commercially.

But valid and verifiable means of representing legal title to privately owned property is a problem often not yet solved even for real estate in many Third World and former communist countries (see De Soto’s 2000 book, The Mystery of Capital). Creating systems for knowing the quality and quantity of educational, health care, social, and environmental service outcomes is going to be a very difficult process. It will not be impossible, however, and having the problem identified advances us significantly towards new economic possibilities.

We need leaders able and willing to formulate audacious goals for new economic growth from ideas such as these. We need enlightened visionaries able to see our potentials from a new perspective, and who can reflect our new self-image back at us. When these leaders emerge—and they will, somewhere, somehow—the imaginations of millions of entrepreneurial thinkers and actors will be fired, and new possibilities will unfold.

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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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Debt, Revenue, and Changing the Way Washington Works: The Greatest Entrepreneurial Opportunity of Our Time

July 30, 2011

“Holding the line” on spending and taxes does not make for a fundamental transformation of the way Washington works. Simply doing less of one thing is just a small quantitative change that does nothing to build positive results or set a new direction. What we need is a qualitative metamorphosis akin to a caterpillar becoming a butterfly. In contrast with this beautiful image of natural processes, the arguments and so-called principles being invoked in the sham debate that’s going on are nothing more than fights over where to put deck chairs on the Titanic.

What sort of transformation is possible? What kind of a metamorphosis will start from who and where we are, but redefine us sustainably and responsibly? As I have repeatedly explained in this blog, my conference presentations, and my publications, with numerous citations of authoritative references, we already possess all of the elements of the transformation. We have only to organize and deploy them. Of course, discerning what the resources are and how to put them together is not obvious. And though I believe we will do what needs to be done when we are ready, it never hurts to prepare for that moment. So here’s another take on the situation.

Infrastructure that supports lean thinking is the name of the game. Lean thinking focuses on identifying and removing waste. Anything that consumes resources but does not contribute to the quality of the end product is waste. We have enormous amounts of wasteful inefficiency in many areas of our economy. These inefficiencies are concentrated in areas in which management is hobbled by low quality information, where we lack the infrastructure we need.

Providing and capitalizing on this infrastructure is The Greatest Entrepreneurial Opportunity of Our Time. Changing the way Washington (ha! I just typed “Wastington”!) works is the same thing as mitigating the sources of risk that caused the current economic situation. Making government behave more like a business requires making the human, social, and natural capital markets more efficient. Making those markets more efficient requires reducing the costs of transactions. Those costs are determined in large part by information quality, which is a function of measurement.

It is often said that the best way to reduce the size of government is to move the functions of government into the marketplace. But this proposal has never been associated with any sense of the infrastructural components needed to really make the idea work. Simply reducing government without an alternative way of performing its functions is irresponsible and destructive. And many of those who rail on and on about how bad or inefficient government is fail to recognize that the government is us. We get the government we deserve. The government we get follows directly from the kind of people we are. Government embodies our image of ourselves as a people. In the US, this is what having a representative form of government means. “We the people” participate in our society’s self-governance not just by voting, writing letters to congress, or demonstrating, but in the way we spend our money, where we choose to live, work, and go to school, and in every decision we make. No one can take a breath of air, a drink of water, or a bite of food without trusting everyone else to not carelessly or maliciously poison them. No one can buy anything or drive down the street without expecting others to behave in predictable ways that ensure order and safety.

But we don’t just trust blindly. We have systems in place to guard against those who would ruthlessly seek to gain at everyone else’s expense. And systems are the point. No individual person or firm, no matter how rich, could afford to set up and maintain the systems needed for checking and enforcing air, water, food, and workplace safety measures. Society as a whole invests in the infrastructure of measures created, maintained, and regulated by the government’s Department of Commerce and the National Institute for Standards and Technology (NIST). The moral importance and the economic value of measurement standards has been stressed historically over many millennia, from the Bible and the Quran to the Magna Carta and the French Revolution to the US Constitution. Uniform weights and measures are universally recognized and accepted as essential to fair trade.

So how is it that we nonetheless apparently expect individuals and local organizations like schools, businesses, and hospitals to measure and monitor students’ abilities; employees’ skills and engagement; patients’ health status, functioning, and quality of care; etc.? Why do we not demand common currencies for the exchange of value in human, social, and natural capital markets? Why don’t we as a society compel our representatives in government to institute the will of the people and create new standards for fair trade in education, health care, social services, and environmental management?

Measuring better is not just a local issue! It is a systemic issue! When measurement is objective and when we all think together in the common language of a shared metric (like hours, volts, inches or centimeters, ounces or grams, degrees Fahrenheit or Celsius, etc.), then and only then do we have the means we need to implement lean strategies and create new efficiencies systematically. We need an Intangible Assets Metric System.

The current recession in large part was caused by failures in measuring and managing trust, responsibility, loyalty, and commitment. Similar problems in measuring and managing human, social, and natural capital have led to endlessly spiraling costs in education, health care, social services, and environmental management. The problems we’re experiencing in these areas are intimately tied up with the way we formulate and implement group level decision making processes and policies based in statistics when what we need is to empower individuals with the tools and information they need to make their own decisions and policies. We will not and cannot metamorphose from caterpillar to butterfly until we create the infrastructure through which we each can take full ownership and control of our individual shares of the human, social, and natural capital stock that is rightfully ours.

We well know that we manage what we measure. What counts gets counted. Attention tends to be focused on what we’re accountable for. But–and this is vitally important–many of the numbers called measures do not provide the information we need for management. And not only are lots of numbers giving us low quality information, there are far too many of them! We could have better and more information from far fewer numbers.

Previous postings in this blog document the fact that we have the intellectual, political, scientific, and economic resources we need to measure and manage human, social, and natural capital for authentic wealth. And the issue is not a matter of marshaling the will. It is hard to imagine how there could be more demand for better management of intangible assets than there is right now. The problem in meeting that demand is a matter of imagining how to start the ball rolling. What configuration of investments and resources will start the process of bursting open the chrysalis? How will the demand for meaningful mediating instruments be met in a way that leads to the spreading of the butterfly’s wings? It is an exciting time to be alive.

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A Framework for Competitive Advantage in Managing Intangible Assets

July 26, 2011

It has long been recognized that externalities like social costs could be brought into the market should ways of measuring them objectively be devised. Markets, however, do not emerge spontaneously from the mere desire to be able to buy and sell; they are, rather, the products of actors and agencies that define the rules, roles, and relationships within which transaction costs are reduced and from which value, profits, and authentic wealth may be extracted. Objective measurement is necessary to reduced transaction costs but is by itself insufficient to the making of markets. Thus, markets for intangible assets, such as human, social, and natural capital, remain inefficient and undeveloped even though scientific theories, models, methods, and results demonstrating their objective measurability have been available for over 80 years.

Why has the science of objectively measured intangible assets not yet led to efficient markets for those assets? The crux of the problem, the pivot point at which an economic Archimedes could move the world of business, has to do with verifiable trust. It may seem like stating the obvious, but there is much to be learned from recognizing that shared narratives of past performance and a shared vision of the future are essential to the atmosphere of trust and verifiability needed for the making of markets. The key factor is the level of detail reliably tapped by such narratives.

For instance, some markets seem to have the weight of an immovable mass when the dominant narrative describes a static past and future with no clearly defined trajectory of leverageable development. But when a path of increasing technical capacity or precision over time can be articulated, entrepreneurs have the time frames they need to be able to coordinate, align, and manage budgeting decisions vis a vis investments, suppliers, manufacturers, marketing, sales, and customers. For example, the building out of the infrastructure of highways, electrical power, and water and sewer services assured manufacturers of automobiles, appliances, and homes that they could develop products for which there would be ready customers. Similarly, the mapping out of a path of steady increases in technical precision at no additional cost in Moore’s Law has been a key factor enabling the microprocessor industry’s ongoing history of success.

Of course, as has been the theme of this blog since day one, similar paths for the development of new infrastructural capacities could be vital factors for making new markets for human, social, and natural capital. I’ll be speaking on this topic at the forthcoming IMEKO meeting in Jena, Germany, August 31 to September 2. Watch this spot for more on this theme in the near future.

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Subjectivity, Objectivity, Performance Measurement and Markets

April 23, 2011

Though he attributes his insight to a colleague (George Baker), Michael Jensen has once more succinctly stated a key point I’ve repeatedly tried to convey in my blog posts. As Jensen (2003, p. 397) puts it,

…any activity whose performance can be perfectly measured objectively does not belong inside the firm. If its performance can be adequately measured objectively it can be spun out of the firm and contracted for in a market transaction.

YES!! Though nothing is measured perfectly, my message has been a series of variations on precisely this theme. Well-measured property, services, products, and commodities in today’s economy are associated with scientific, legal and financial structures and processes that endow certain representations with meaningful indications of kind, amount, value and ownership. It is further well established that the ownership of the products of one’s creative endeavors is essential to economic advancement and the enlargement of the greater good. Markets could not exist without objective measures, and thus we have the central commercial importance of metric standards.

The improved measurement of service outcomes and performances is going to create an environment capable of supporting similar legal and financial indications of value and ownership. Many of the causes of today’s economic crises can be traced to poor quality information and inadequate measures of human, social, and natural value. Bringing publicly verifiable scientific data and methods to bear on the tuning of instruments for measuring these forms of value will make their harmonization much simpler than it ever could be otherwise. Social and environmental costs and value have been relegated to the marginal status of externalities because they have not been measured in ways that made it possible to bring them onto the books and into the models.

But the stage is being set for significant changes. Decades of research calibrating objective measures of a wide variety of performances and outcomes are inexorably leading to the creation of an intangible assets metric system (Fisher, 2009a, 2009b, 2011). Meaningful and rigorous individual-level universally available uniform metrics for each significant intangible asset (abilities, health, trustworthiness, etc.) will

(a) make it possible for each of us to take full possession, ownership, and management control of our investments in and returns from these forms of capital,

(b) coordinate the decisions and behaviors of consumers, researchers, and quality improvement specialists to better match supply and demand, and thereby

(c) increase the efficiency of human, social, and natural capital markets, harnessing the profit motive for the removal of wasted human potential, lost community coherence, and destroyed environmental quality.

Jensen’s observation emerges in his analysis of performance measures as one of three factors in defining the incentives and payoffs for a linear compensation plan (the other two being the intercept and the slope of the bonus line relating salary and bonus to the performance measure targets). The two sentences quoted above occur in this broader context, where Jensen (2003, pp. 396-397) states that,

…we must decide how much subjectivity will be involved in each performance measure. In considering this we must recognize that every performance measurement system in a firm must involve an important amount of subjectivity. The reason, as my colleague George Baker has pointed out, is that any activity whose performance can be perfectly measured objectively does not belong inside the firm. If its performance can be adequately measured objectively it can be spun out of the firm and contracted for in a market transaction. Thus, one of the most important jobs of managers, complementing objective measures of performance with managerial subjective evaluation of subtle interdependencies and other factors is exactly what most managers would like to avoid. Indeed, it is this factor along with efficient risk bearing that is at the heart of what gives managers and firms an advantage over markets.

Jensen is here referring implicitly to the point Coase (1990) makes regarding the nature of the firm. A firm can be seen as a specialized market, one in which methods, insights, and systems not generally available elsewhere are employed for competitive advantage. Products are brought to market competitively by being endowed with value not otherwise available. Maximizing that value is essential to the viability of the firm.

Given conflicting incentives and the mixed messages of the balanced scorecard, managers have plenty of opportunities for creatively avoiding the difficult task of maximizing the value of the firm. Jensen (2001) shows that attending to the “managerial subjective evaluation of subtle interdependencies” is made impossibly complex when decisions and behaviors are pulled in different directions by each stakeholder’s particular interests. Other research shows that even traditional capital structures are plagued by the mismeasurement of leverage, distress costs, tax shields, and the speed with which individual firms adjust their capital needs relative to leverage targets (Graham & Leary, 2010). The objective measurement of intangible assets surely seems impossibly complex to those familiar with these problems.

But perhaps the problems associated with measuring traditional capital structures are not so different from those encountered in the domain of intangible assets. In both cases, a particular kind of unjustified self-assurance seems always to attend the mere availability of numeric data. To the unpracticed eye, numbers seem to always behave the same way, no matter if they are rigorous measures of physical commodities, like kilowatts, barrels, or bushels, or if they are currency units in an accounting spreadsheet, or if they are percentages of agreeable responses to a survey question. The problem is that, when interrogated in particular ways with respect to the question of how much of something is supposedly measured, these different kinds of numbers give quite markedly different kinds of answers.

The challenge we face is one of determining what kind of answers we want to the questions we have to ask. Presumably, we want to ask questions and get answers pertinent to obtaining the information we need to manage life creatively, meaningfully, effectively and efficiently. It may be useful then, as a kind of thought experiment, to make a bold leap and imagine a scenario in which relevant questions are answered with integrity, accountability, and transparency.

What will happen when the specialized expertise of human resource professionals is supplanted by a market in which meaningful and comparable measures of the hireability, retainability, productivity, and promotability of every candidate and employee are readily available? If Baker and Jensen have it right, perhaps firms will no longer have employees. This is not to say that no one will work for pay. Instead, firms will contract with individual workers at going market rates, and workers will undoubtedly be well aware of the market value of their available shares of their intangible assets.

A similar consequence follows for the social safety net and a host of other control, regulatory, and policing mechanisms. But we will no longer be stuck with blind faith in the invisible hand and market efficiency, following the faith of those willing to place their trust and their futures in the hands of mechanisms they only vaguely understand and cannot control. Instead, aggregate effects on individuals, communities, and the environment will be tracked in publicly available and critically examined measures, just as stocks, bonds, and commodities are tracked now.

Previous posts in this blog explore the economic possibilities that follow from having empirically substantiated, theoretically predictable, and instrumentally mediated measures embodying broad consensus standards. What we will have for human, social, and natural capital will be the same kind of objective measures that have made markets work as well as they have thus far. It will be a whole new ball game when profits become tied to human, social, and environmental outcomes.

References

Coase, R. (1990). The firm, the market, and the law. Chicago: University of Chicago Press.

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. No. http://www.livingcapitalmetrics.com/images/FisherNISTWhitePaper2.pdf). New Orleans: LivingCapitalMetrics.com.

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

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

Graham, J. R., & Leary, M. T. (2010, 21 December). A review of empirical capital structure research and directions for the future. Available at http://ssrn.com/abstract=1729388.

Jensen, M. C. (2001, Fall). Value maximization, stakeholder theory, and the corporate objective function. Journal of Applied Corporate Finance, 14(3), 8-21.

Jensen, M. C. (2003). Paying people to lie: The truth about the budgeting process. European Financial Management, 9(3), 379-406.

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The Moral Implications of the Concept of Human Capital: More on How to Create Living Capital Markets

March 22, 2011

The moral reprehensibility of the concept of human capital hinges on its use in rationalizing impersonal business decisions in the name of profits. Even when the viability of the organization is at stake, the discarding of people (referred to in some human resource departments as “taking out the trash”) entails degrees of psychological and economic injury no one should have to suffer, or inflict.

There certainly is a justified need for a general concept naming the productive capacity of labor. But labor is far more than a capacity for work. No one’s working life should be reduced to a job description. Labor involves a wide range of different combinations of skills, abilities, motivations, health, and trustworthiness. Human capital has then come to be broken down into a wide variety of forms, such as literacy capital, health capital, social capital, etc.

The metaphoric use of the word “capital” in the phrase “human capital” referring to stocks of available human resources rings hollow. The traditional concept of labor as a form of capital is an unjustified reduction of diverse capacities in itself. But the problem goes deeper. Intangible resources like labor are not represented and managed in the forms that make markets for tangible resources efficient. Transferable representations, like titles and deeds, give property a legal status as owned and an economic status as financially fungible. And in those legal and economic terms, tangible forms of capital give capitalism its hallmark signification as the lifeblood of the cycle of investment, profits, and reinvestment.

Intangible forms of capital, in contrast, are managed without the benefit of any standardized way of proving what is owned, what quantity or quality of it exists, and what it costs. Human, social, and natural forms of capital are therefore managed directly, by acting in an unmediated way on whomever or whatever embodies them. Such management requires, even in capitalist economies, the use of what are inherently socialistic methods, as these are the only methods available for dealing with the concrete individual people, communities, and ecologies involved (Fisher, 2002, 2011; drawing from Hayek, 1948, 1988; De Soto, 2000).

The assumption that transferable representations of intangible assets are inconceivable or inherently reductionist is, however, completely mistaken. All economic capital is ultimately brought to life (conceived, gestated, midwifed, and nurtured to maturity) as scientific capital. Scientific measurability is what makes it possible to add up the value of shares of stock across holdings, to divide something owned into shares, and to represent something in a court or a bank in a portable form (Latour, 1987; Fisher, 2002, 2011).

Only when you appreciate this distinction between dead and living capital, between capital represented on transferable instruments and capital that is not, then you can see that the real tragedy is not in the treatment of labor as capital. No, the real tragedy is in the way everyone is denied the full exercise of their rights over the skills, abilities, health, motivations, trustworthiness, and environmental resources that are rightly their own personal, private property.

Being homogenized at the population level into an interchangeable statistic is tragic enough. But when we leave the matter here, we fail to see and to grasp the meaning of the opportunities that are lost in that myopic world view. As I have been at pains in this blog to show, statistics are not measures. Statistical models of interactions between several variables at the group level are not the same thing as measurement models of interactions within a single variable at the individual level. When statistical models are used in place of measurement models, the result is inevitably numbers without a soul. When measurement models of individual response processes are used to produce meaningful estimates of how much of something someone possesses, a whole different world of possibilities opens up.

In the same way that the Pythagorean Theorem applies to any triangle, so, too, do the coordinates from the international geodetic survey make it possible to know everything that needs to be known about the location and disposition of a piece of real estate. Advanced measurement models in the psychosocial sciences are making it possible to arrive at similarly convenient and objective ways of representing the quality and quantity of intangible assets. Instead of being just one number among many others, real measures tell a story that situates each of us relative to everyone else in a meaningful way.

The practical meaning of the maxim “you manage what you measure” stems from those instances in which measures embody the fullness of the very thing that is the object of management interest. An engine’s fuel efficiency, or the volume of commodities produced, for instance, are things that can be managed less or more efficiently because there are measures of them that directly represent just what we want to control. Lean thinking enables the removal of resources that do not contribute to the production of the desired end result.

Many metrics, however, tend to obscure and distract from what need to be managed. The objects of measurement may seem to be obviously related to what needs to be managed, but dealing with each of them piecemeal results in inefficient and ineffective management. In these instances, instead of the characteristic cycle of investment, profit, and reinvestment, there seems only a bottomless pit absorbing ever more investment and never producing a profit. Why?

The economic dysfunctionality of intangible asset markets is intimately tied up with the moral dysfunctionality of those markets. Drawing an analogy from a recent analysis of political freedom (Shirky, 2010), economic freedom has to be accompanied by a market society economically literate enough, economically empowered enough, and interconnected enough to trade on the capital stocks issued. Western society, and increasingly the entire global society, is arguably economically literate and sufficiently interconnected to exercise economic freedom.

Economic empowerment is another matter entirely. There is no economic power without fungible capital, without ways of representing resources of all kinds, tangible and intangible, that transparently show what is available, how much of it there is, and what quality it is. A form of currency expressing the value of that capital is essential, but money is wildly insufficient to the task of determining the quality and quantity of the available capital stocks.

Today’s education, health care, human resource, and environmental quality markets are the diametric opposite of the markets in which investors, producers, and consumers are empowered. Only when dead human, social, and natural capital is brought to life in efficient markets (Fisher, 2011) will we empower ourselves with fuller degrees of creative control over our economic lives.

The crux of the economic empowerment issue is this: in the current context of inefficient intangibles markets, everyone is personally commodified. Everything that makes me valuable to an employer or investor or customer, my skills, motivations, health, and trustworthiness, is unjustifiably reduced to a homogenized unit of labor. And in the social and environmental quality markets, voting our shares is cumbersome, expensive, and often ineffective because of the immense amount of work that has to be done to defend each particular living manifestation of the value we want to protect.

Concentrated economic power is exercised in the mass markets of dead, socialized intangible assets in ways that we are taught to think of as impersonal and indifferent to each of us as individuals, but which is actually experienced by us as intensely personal.

So what is the difference between being treated personally as a commodity and being treated impersonally as a commodity? This is the same as asking what it would mean to be empowered economically with creative control over the stocks of human, social, and natural capital that are rightfully our private property. This difference is the difference between dead and living capital (Fisher, 2002, 2011).

Freedom of economic communication, realized in the trade of privately owned stocks of any form of capital, ought to be the highest priority in the way we think about the infrastructure of a sustainable and socially responsible economy. For maximum efficiency, that freedom requires a common meaningful and rigorous quantitative language enabling determinations of what exactly is for sale, and its quality, quantity, and unit price. As I have ad nauseum repeated in this blog, measurement based in scientifically calibrated instrumentation traceable to consensus standards is absolutely essential to meeting this need.

Coming in at a very close second to the highest priority is securing the ability to trade. A strong market society, where people can exercise the right to control their own private property—their personal stocks of human, social, and natural capital—in highly efficient markets, is more important than policies, regulations, and five-year plans dictating how masses of supposedly homogenous labor, social, and environmental commodities are priced and managed.

So instead of reacting to the downside of the business cycle with a socialistic safety net, how might a capitalistic one prove more humane, moral, and economically profitable? Instead of guaranteeing a limited amount of unemployment insurance funded through taxes, what we should have are requirements for minimum investments in social capital. Instead of employment in the usual sense of the term, with its implications of hiring and firing, we should have an open market for fungible human capital, in which everyone can track the price of their stock, attract and make new investments, take profits and income, upgrade the quality and/or quantity of their stock, etc.

In this context, instead of receiving unemployment compensation, workers not currently engaged in remunerated use of their skills would cash in some of their accumulated stock of social capital. The cost of social capital would go up in periods of high demand, as during the recent economic downturns caused by betrayals of trust and commitment (which are, in effect, involuntary expenditures of social capital). Conversely, the cost of human capital would also fluctuate with supply and demand, with the profits (currently referred to as wages) turned by individual workers rising and falling with the price of their stocks. These ups and downs, being absorbed by everyone in proportion to their investments, would reduce the distorted proportions we see today in the shares of the rewards and punishments allotted.

Though no one would have a guaranteed wage, everyone would have the opportunity to manage their capital to the fullest, by upgrading it, keeping it current, and selling it to the highest bidder. Ebbing and flowing tides would more truly lift and drop all boats together, with the drops backed up with the social capital markets’ tangible reassurance that we are all in this together. This kind of a social capitalism transforms the supposedly impersonal but actually highly personal indifference of flows in human capital into a more fully impersonal indifference in which individuals have the potential to maximize the realization of their personal goals.

What we need is to create a visible alternative to the bankrupt economic system in a kind of reverse shock doctrine. Eleanor Roosevelt often said that the thing we are most afraid of is the thing we most need to confront if we are to grow. The more we struggle against what we fear, the further we are carried away from what we want. Only when we relax into the binding constraints do we find them loosened. Only when we channel overwhelming force against itself or in a productive direction can we withstand attack. When we find the courage to go where the wild things are and look the monsters in the eye will we have the opportunity to see if their fearful aspect is transformed to playfulness. What is left is often a more mundane set of challenges, the residuals of a developmental transition to a new level of hierarchical complexity.

And this is the case with the moral implications of the concept of human capital. Treating individuals as fungible commodities is a way that some use to protect themselves from feeling like monsters and from being discarded as well. Those who find themselves removed from the satisfactions of working life can blame the shortsightedness of their former colleagues, or the ugliness of the unfeeling system. But neither defensive nor offensive rationalizations do anything to address the actual problem, and the problem has nothing to do with the morality or the immorality of the concept of human capital.

The problem is the problem. That is, the way we approach and define the problem delimits the sphere of the creative options we have for solving it. As Henry Ford is supposed to have said, whether you think you can or you think you cannot, you’re probably right. It is up to us to decide whether we can create an economic system that justifies its reductions and actually lives up to its billing as impersonal and unbiased, or if we cannot. Either way, we’ll have to accept and live with the consequences.

References

DeSoto, 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. (2011, Spring). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), in press.

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

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

Latour, B. (1987). Science in action: How to follow scientists and engineers through society. New York: Cambridge University Press.

Shirky, C. (2010, December 20). The political power of social media: Technology, the public sphere, and political change. Foreign Affairs, 90(1), http://www.foreignaffairs.com/articles/67038/clay-shirky/the-political-power-of-social-media.

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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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