Proprietary Screening Model

"Indian Territory", Michael Horse (Yaqui, Mescalero, Apache, Zuni)

Proprietary Screening Model

Another important element of Rose Community Development's program is the screening of investments. In a new strategic role, parallel to that of CDFI's, Rose Community Development has developed a proprietary screening model based on a combination of (a) the kind of industry targeting which Japan used after World War II to create and then accelerate its economic growth and (b) the latest tools from complexity science currently being used for scenario planning and investment decision making, particularly "agent-based modeling". This investment selection model will target appropriate investments at both the individual Native American entrepreneur level and at organizational and tribal levels.

The fundamental logic behind the proprietary system is to accomplish all of the following within a consistent, coherent and consonant framework, in order to create sustainable economic growth in Indian country and to accelerate the rate of this growth:

A. Capacity building – Build the physical, financial, and knowledge based infrastructure to deliver value, quality and innovation in Native American businesses. Because of the clustering effects and economies of agglomeration this kind of targeted investment must be tribe specific and region specific.
B. Institution building- As many authors, scientists and businessmen have already noted, in order to solve the endemic problem of capital absorption (i.e. money which comes onto the reservation and then goes right off the reservation) Rose plans to aggressively engage in cooperative institution building with tribal councils. This includes both the development of local financial intermediaries (such as CDFI's) as well as participation and advising in the structuring of new institutions designed to meet the kinds of value creating criteria discussed by Emerson, Porter, Cortwright and others.
C. Technology Building-Through strategic alliances with commercial firms Rose plans to use technology transfer to build a knowledge intensive base for the first time in Indian country. On one side of this effort we place Rose Education and the Cyber Rez. On the other side Rose will actively seek to form strategic alliances between high technology firms in order to fulfill those firms' obligations for minority enterprise participation in such areas a defense contracting.
D. New Modeling in the Approach to Markets-Rose Community Development Corporation is committed to the use of the latest and most sophisticated methods and models from complex systems analysis in order to determine our investment strategies. In particular, we have placed a very strong reliance on the work done by W. Brian Arthur, J. Doyne Farmer and others at the Santa Fe Institute during the past decade. As indicated in a recent Harvard Business Review article, "Predicting the Unpredictable" by Eric Bonabeau, this work is now finding cutting edge application in business and investment settings.* Bonabeau begins his investigation by explaining how NASDAQ used an agent based modeling system to reduce the size of its "ticks" in order to let buyers and sellers negotiate in more precise terms, driving down the spread between bid and asked prices from a system based on eighth's of a dollar down to a system based on decimalization (one cent spreads). Because this was entirely new territory, NASDAQ hired a consulting group in Santa Fe to use agent based modeling to predict the effect of decimalization on the market. After creating a model with thousands of virtual agents to represent all the various types of investors—day traders, pension fund managers, arbitrageurs, etc, and running thousands of simulation trials, they discovered that decimalization could actually lead to a decrease in the market's ability to perform price discovery, which would lead to not narrower but wider spreads between bid and asked prices. Not only was the agent based modeling system able to handle a kind of problem, which would have been intractable to pure mathematical analysis, but also it uncovered a powerful and profoundly counter-intuitive solution, potentially saving billions of dollars.

Bonabeau goes on to explain how other companies have begun to benefit from using agent based modeling: "Macy's for instance, has used the technology to develop better ways to design its department stores. Hewlett-Packard has run agent-based simulations to anticipate how changes in hiring strategy would affect its corporate culture. And Societe Generale has used the technology to determine the operational risk of its asset management group". (p. 6)

Agent based modeling provides a wide range of opportunities for Rose Community Development to approach the selection of business, locations and Tribal cultural variables in optimizing the use of capital, building sustainable economic Native American enterprises and investments and harmonizing the requirements of socially responsible investors with the needs and cultural uniqueness of indigenous peoples.

Bonabeau uses the familiar example of a traffic jam to explain some of the technical dynamics of agent based modeling and the nature of emergent phenomena:

To appreciate the full power of agent based modeling, you first need to understand the concept of "emergent phenomena," and the best way to do that is by thinking of a traffic jam. Although they are everyday occurrences, traffic jams are actually very complicated and mysterious. On an individual level, each driver is trying to get somewhere and is following (or breaking) certain rules, some legal (the speed limit) and others societal or personal (slow down to let another driver change into your lane). But a traffic jam is a separate and distinct entity that emerges from those individual behaviors. Gridlock on a highway, for example, can travel backward for no apparent reason, even as the cars are moving forward. (p. 6)

Bonabeau goes on to describe a variety of ways in which business and society, particularly as they have become increasingly complex and interconnected,demonstrate emergent behaviors. He also explains that because of the degree of complexity involved, tradition deductive (i.e., "top-down") methods, such as spreadsheets analysis or multiple regressions and even most systems dynamics break down when it comes to handling this level of complexity. In other words, most emergent phenomena, when approached from a traditional standpoint are, at the very least, computationally intractable. Beyond that, he makes the point that the counter-intuitive behavior of many complex systems demands new tools, which go beyond the simple statistical assumptions that predictivity can be derived by assuming that the near future will look like the recent past.

One of the most successful methods for dealing with complex systems and emergent phenomena has been agent based modeling, which is a bottom-up approach that studies the problem at the "grass roots" level following what complexity science refers to as "local rules of behavior" in order to generate a model of the system at the macro level. J. Doyne Farmer of the Santa Fe Institute (see the excerpt below "Agent Based Models") compares this to the way in which physicists use statistical mechanics, building on the behavior of individual pairs or ensembles to generate a model of how the system behaves.+ Bonabeau also explains how recent increases in computing power allow sophisticated scenario planning to be undertaken through computer simulation using the analytical tools of chaos theory and complexity science to explore scenarios which would have simply been to expensive, time consuming and complex for a business to consider even a few year ago. He also explains how these models are able to take into account the complexity of individual behaviors within a whole variety of simulated environments.

One of the great strengths of agent based modeling is its ability to model heterogeneous populations. For example, in treating consumer behavior, agent based systems are able to model situations where a business must meet the needs of may different types of customers simultaneously, or architect a system which can be flexible enough to encompass complex, heterogeneous demands without become cost inefficient. As Farmer suggests in the excerpt below, much of the information needed to construct and measure such a scenario (before embarking on actual investment and implementation) is data from the customers themselves (endogenous data). Bonabeau gives the example of how researchers Rob Axtell and Josh Epstein of the Brookings Institution used agent based modeling in designing a theme park.

In this case, the problem of heterogeneity was exemplified by the different needs of a family of four (six rides, four hot dogs, two cotton candies, three trips to the restroom) as compared to a teenage couple on a date. Endogenous data (data from the park's visitors) gave them a very rich base upon which to construct models and explore new scenarios. Bonabeau explains "the agent based model considered that information to balance customer satisfaction with the theme park's goal of increasing business. The model was able to explore complex questions that were beyond the reach of traditional mathematical techniques and a pure statistical analysis of the data. (For example, what's a better solution, extending the Park's hours by thirty minutes or shortening each ride by 8.5 seconds?) Furthermore the research sparked new ideas for further investigation. What would happen, for example, if each customer were given a small hand held computing device that displayed up-to-date information on the lengths of every ride and attraction?" (p. 7)

Agent based modeling, and the insights of chaos and complexity theory are at the scientific core of Rose Community Development's proprietary screening method and will allow us to allocate assets in a way which will optimally meet the needs of socially responsible investors, while following the critical insights of the Harvard Project on Indian Economic Development with respect to building appropriate cultures and institutions to manage Rose Community Development's investments in a way which not only brings positive returns to investors but which builds a capital base, physical infrastructure and knowledge infrastructure in Indian Country as the direct result of our community economics development activities.