Mitigating Risk Through Better Information

Mitigating Risk Through Better Information Scott M. Shemwell, D.B.A First published in February 2002; reprinted here with permission In one of the most colossal underestimations in business history, Kenneth H. Olsen, then president of Digital Equipment Corporation (DEC), announced in 1977 that “there is no reason for any individual to have a computer in their home.” The explosion in the personal computer market was not inevitable in 1977, but it was certainly within the range of possibilities that industry experts were discussing at the time.1

Preamble

T

he beginning of year 2002, finds the global economy at an increased level of ambiguity. Political and economic uncertainty in key petroleum geographical areas is not limited to just the Middle East and post 9-11 issues, but manifests itself in South America, Southeast Asia, as well as other geopolitical political landscapes long known to present difficulties. Well understood by politicians and sociologists, knowledge is power or rephrased it is competitive advantage. Organizational knowledge is the sum total of the synergy of normalized data transformed by software applications into information, and interpreted by the core competency of the firm into competitive engagement. This synergistic effect requires that value be derived from data being in the right format, at the right place, and at the right time2 Uncertainty manifests itself as a lack of understanding or the lack of information that reduces ambiguity to zero. In the real world, this Pareto optimal frontier can never be measured (Heisenberg Uncertainty Principle3) and even if economic equilibrium were realized, it would only be for a moment before exogenous forces would disturb the balance4.

An Uncertain World The petroleum industry has developed substantial expertise managing risk on a global scale. Most projects have several components of exposure including geopolitical, economic, and technology. Successful organizations have developed a formal risk management methodology using tools such as portfolio management to reach an expected (statistical) average level of risk, or profile, the firm is willing to bear across its global asset mix. 1

Courtney et al. developed the following four Levels of Uncertainty along with an appropriate set of analytic tools necessary for the analyses of the opportunities presented. Decision-making processes also change depending on the degree of managerial confidence and availability of the required resources necessary to evaluate prospects. © Copyright 2002 & 2009. Scott M. Shemwell. All Rights Reserved. This material is the intellectual property of Scott Shemwell and reflects the specific original research, concepts, and writings of the author over more than 20 years. It is provided for publication provided authorship is expressly recognized in derivative works in accordance with the current version of either the American Psychological Association (APA) Style Guide or the Chicago Manual of Style.

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Level of Uncertainty -Definition

Analytic Tools

Examples

A Clear Enough Future – A single forecast precise enough for determining strategy.

Ø “Traditional” Strategy Tool Kit

Ø Strategy against new local market entrant

Alternate Futures – A few discrete outcomes that define the future

Ø Decision Analysis Ø Option Valuation Models Ø Game Theory

Ø Capacity strategies for Chemical Plant or Refinery

A Range of Futures – A range of possible outcomes, but no natural scenarios

Ø Latent-demand research Ø Technology Forecasting Ø Scenario Planning

Ø Entering new international markets

True Ambiguity – No basis to forecast the future

Ø Analogies and pattern recognition Ø Nonlinear dynamic models

Ø Entering new international markets after a prolong period of political uncertainty

Uncertainty is a function of the knowledge base of the decision maker. The greater the understanding of the issue under consideration, the greater management’s confidence level. This knowledge is often embodied in the organizational culture or sometimes only in the minds of a few key individuals. The more internalized the knowledge base is throughout the organization, the better prepared the firm will be to address an uncertain world. Moreover, just because an individual or organization has expertise in a specific area it is still possible to overlook opportunities, not appreciate the risk associated with either entering a new area, or the opportunity cost / competitive risk associated with not capitalizing on the prospect. The case of the missed opening for Digital Equipment was perhaps one piece of ongoing culture that ultimately lead to the sale of that once great company to Compaq Computer Corporation several years ago.

Risk Management Risk management is one of the core competencies of any firm. Whether a petroleum producer, energy trader, or service provider policies should be developed and adhered to that, insure the organization has developed an appropriate risk profile and stays within those bounds. Economic shareholder value is realized when the firm returns economic profit, defined as the surplus of revenue over all costs, including the opportunity costs of employing all inputs.5 Economic profits cannot be realized if the firm does not develop a strategy that capitalizes on its core competency and generates earnings at an above market Return On Capital Employed. To accomplish high ROCE, the firm must be willing to take calculated risks. However, risk taking without proper governance is a recipe for disaster. The following steps outline one approach for managing under uncertainty.

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The Ten Commandments for Good Policy Analysis6 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Do your homework with literature, experts, and users. Let the problem drive the analysis. Make the analysis as simple as possible, but no simpler. Identify all significant assumptions. Be explicit about decision criteria and policy strategies. Be explicit about uncertainties. Perform systematic sensitivity and uncertainty analysis. Iteratively refine the problem statement and the analysis. Document clearly and completely. Expose the work to peer review.

This approach is an information centric methodology that provides guideposts for developing risk policy. Quantitative information forms the basis of stochastic decision support models that integrate qualitative information to improve processes and build organizational knowledge. This methodology reduces uncertainty and allows management to make better-informed decisions.

The Role of Information in Risk Mitigation Traditionally, firms are identified with the goods and services they deliver in industry sectors. Tasks are optimized through the division of labor, economies of scale achieved, and shareholder value created. Or is it?

Information Flow and the Extended Enterprise The economy and its actors can be viewed as a system of information flow.7 Firms acquire and utilize asymmetrical information to achieve competitive advantage. Information is shared and managed across the extended enterprise, and this knowledge is communicated to the market in the form of price quotes for the organization’s goods and services. Economists have developed a systematic understanding of the role of information within the firm and in the overall economy. Information movement is the fundamental underpinning of the decision making process within the supply chain. Better information leads to better competitive decisions and lower quality information leads to less market efficient choices.

This perspective capitalizes on information as a corporate asset, and not just the output of a cost center.

Treating information as a revenue generating or direct cost saving asset changes the way firms treat the acquisition and management of information. ·

Information flow is the very essence of the firm and its extension into its supply chain, including both suppliers and customers.

·

Information interchange is the intermediation process across the supply chain.

·

Information dynamics are the tangible asset of the exchange process.

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The Economics of Information Firms seek asymmetrical information to secure advantage during negotiations or transactions.8 Game theory with its set of pay-off alternatives, suggests that asymmetrical information can provide one market actor with advantage over his or her rival. On a side note, it might be of interest to note that modern game theory was first postulated by Von Neumann and Morgenstern and much of its development took place at Princeton University in conjunction with the scientific leaders who developed the first atomic bomb. Moreover, Von Neumann is credited with developing the serial architecture still used in modern computer processing.4 There is a cost associated with procuring and managing information. The deployment of a supply chain network and application infrastructure requires a level of investment. Then again, in the extended supply chain, this sunk cost may be spread across all firms if standards are adopted. Once this investment has been made, firms can begin reaping marginal cost driven benefits. According to mathematician and economist J.F. Nash, equally efficient firms supplying homogeneous energy products, all with constant marginal costs must price products at the marginal cost. Once the information management infrastructure is in place, the firm can lower its marginal cost structure by reducing direct cost of operations as well as reducing process cycle time, e.g., reducing time to first oil thus increasing Net Present Value (NPV) of the project. The CEO of a telecom firm once stated that “. . . we’ll end up with a much lower marginal cost structure and that will allow us to underprice our competitors.” 9 The same economics are at work in the commodity driven energy market place.

Risk Mitigation As an industry pioneer and leader, Ken Olson was uniquely positioned to capitalize on the emerging personal computer industry. Indeed, DEC’s minicomputer line had previously made significant inroads into the mainframe installed base, ominously allowing individual divisions to drive their own computing needs without depending on corporate MIS departments. Ironically, DEC led the way for the desktop computer revolution. Industry stature does not in and of itself confer wisdom. We are all bound by our legacy and often cannot see the forest as we are mired in our own trees. Rather, developing a corporate culture, processes, and policies that reward creative intelligent synergistic thinking by the organization and its strategic suppliers better mitigates risk. st

As an information-processing engine, the 21 century firm, including its extended supply chain, is well positioned to capitalize on both quantitative and qualitative information to make better decisions under conditions of varying uncertainty. Moreover, valid, reliable, and timely information can positively affect the marginal cost structure of the firm thereby lowering the return on investment bar management and providing real options when managing capital assets throughout their life cycle.

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Conclusions The energy industry has evolved to a high level of expertise in risk management. Moreover, it is a successful global industry that has long had to deal with a declining product price point in real economic terms. Cost management is a key performance indicator. Surviving economic actors are very good at managing their risk-reward curves and driving out shareholder value. Risk management is typically driven by portfolio assessment techniques. As business complexity and security requirements increase, firms must deploy new granularity for dealing with an uncertain world. Valid and timely information is the basis for making better decisions. It is also the foundation for new or enhanced processes that can lower the marginal cost to the firm and improve financial posture.

The Author Scott Shemwell is a leading authority on information management processes with more than 200 publications on a variety of management issues. He holds a Bachelor of Science degree in Physics, an MBA, and a Doctorate in Business Administration. His doctoral thesis was an exploratory study of business process analysis using game theory and structural equations.

1

Courtney, Hugh, Kirkland, Jane, and Viguerie, Patrick (1999). Strategy Under Uncertainty. Harvard Business Review on Managing Uncertainty. p. 4 - 14. 2

Shemwell, Scott M. & Rueff, Serge. (September 1996). A 'Value-Add' Analysis of the Information Exchange Loop between Oil & Gas Service Companies and Exploration & Production Companies: The Service Company Perspective, Proceedings of the Gulf Publishing Exploration and Production Data Management Conference. Houston. 3

Halliday, David & Resnick, Robert. (1967). Physics; Parts I and II. New York: John Wiley & Sons, Inc. 4

Shemwell, Scott M. (1996). Cross Cultural Negotiations between Japanese and American Businessmen: A Systems Analysis, (Exploratory Study). Unpublished doctoral dissertation, Nova Southeastern University, Ft. Lauderdale. 5

Rutherford, Donald. (1995). Routledge Dictionary of Economics. London: Routledge.

6

Morgan, M. Granger and Henrion, Max. (1990). Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis. pp. 36 - 44. New York: Cambridge University Press. 7

Casson, Mark. (1997). Information and Organization: A New Perspective on the Theory of the Firm. Oxford: Clarendon Press. 8

Macho-Stadler, Inés and Pérez-Castrillo, J. David. (1997). An Introduction to the Economics of Information: Incentives and Contracts. New York: Oxford University Press. 9

Gong, Jiong and Srinagesh, Padmanabhan. (1997). The Economics of Layered Networks. In McKnight, Lee W. and Bailey, Joseph P. Internet Economics (pp. 63 – 75). Cambridge: The MIT Press.

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