Why Credit Rating Agencies are Being “B” Rated

In “Why Did Subprime Loans Become Such a Big Deal?“[1] the author outlined the structure of the mortgage market using a 3-story house analogy. The first level represents the primary mortgage market, the second level represents the secondary mortgage market, and the third level represents the credit derivatives market. The author also identified why credit rating agencies such as Standard & Poor’s (S&P) were essential in the growth of the securitized mortgage market, which underpinned the U.S. housing boom of 1998-2006, and how the agencies’ recklessly favorable ratings for subprime mortgage products ultimately helped to cause the subprime crisis.

The Department of Justice (DOJ) apparently agrees: on February 4, 2013, the DOJ filed a civil lawsuit in federal court against S&P.[2] This case marks the government’s first federal case against one of the country’s three big ratings firms (others include Moody’s Investors Service and Fitch Ratings). Given the current regulatory framework for credit derivatives and the business model of the credit rating agencies, in this article the authors explain why the system is still set up to fail.

exitsigncreditHistory of Credit Rating Agencies

The history of the credit rating agencies and their relationship with financial regulators is central to understanding how the agencies achieved their current overly influential position in the debt market. Beginning in the 1930s, the financial regulators began to create a financial regulatory framework reliant on credit rating agencies, whereby regulators used credit ratings as a means to oversee the financial markets. After the banking crisis of 1931, the Office of the Comptroller of the Currency (OCC) sought to regulate banks’ capital reserve requirement by requiring credit rating agencies to value banks’ bond portfolios. In 1936, the OCC and the Federal Reserve di­rected banks to hold investment grade bonds, which were bonds that were rated BBB or higher by at least two designated credit rating agen­cies. Essentially, the ratings indicated the likelihood of the debt being repaid, whether for corporate debt or mortgage-backed securities. As a result, banks were required to obtain opinions on their assets from credit rating agencies such as S&P to determine whether they meet federal capital reserve requirements.

Furthermore, in 1973, the Securities and Exchange Commission (SEC) created a new select category of rating agencies called the Nationally Recog­nized Statistical Rating Organization (NRSRO) to ensure proper compliance for measuring banks’ leverage ratio. In this way, the SEC empowered NRSRO designated rating agencies, which included the big three ratings agencies (S&P, Moody’s Investors Service, and Fitch Ratings) to give endorsements to banks. While the financial regulators were growing increasingly dependent on the rating agencies, at the same time, a fundamental shift occurred in the business model of the rating agencies. The new NRSRO designation and the resulting oligopoly of rating agencies incentivized the three big ratings agencies to change their business model from charging investors to charging issuers for ratings fees. This change to the “issuer pays” business model created high potential for conflicts of interest,[3] and the alleged abuse of this business model and fraudulent practices in relation to subprime mortgage securities is at the heart of the DOJ’s lawsuit against S&P.

What is Credit Risk and How Do You Measure It?

To explain the role of credit rating agencies, we must first explain credit risk. Credit risk, which is also referred to as default risk, is the risk that a borrower will not be able to pay back the lender. For example, banks usually take on credit risk by lending short-term money or long-term capital to companies. In exchange for credit, the debtor must pay interest on the loan as well as the principal by the end of the loan period. When default occurs, companies usually declare bankruptcy and go through a liquidation process. The amount that can be gathered relative to all outstanding debt is called the recovery rate. Also, all debts are ranked by seniority to decide who gets paid first, which is referred to as debt waterfall.

The amount of money involved in the bankruptcy process for large public companies is substantial and a major disruption in the economy. In 2012, a total of 86 publicly traded companies in the U.S. filed for bankruptcy protection with a total of $70.8 billion in combined pre-petition assets.[4]

Table 1: Top 10 Largest Public Company Bankruptcy Filings in 2012[5]

Park Table 1

Credit risk measurement is based on two fundamental concepts: default probability and recovery rate. Estimating default probability is often the job of a rating agency (for S&P, an AAA rating stands for best credit quality while below BBB is considered non-investment or speculative grade). The following 3 tables illustrate global corporate default rates:

Table 2: Annual Number of Global Corporate Defaults [6]

Park Table 2

Table 3: Annual Global Corporate Default Rates By Ratings Category[7]

Park Table 3

Table 4: Largest Global Corporate Defaulters Each Year by Outstanding Amount[8]

Park Table 4

Together, the default probability and recovery rate can give measurements as to the quality of debt and are often referred to as credit spread. Credit spread is the difference between the yield of a bond and the yield of a risk-free government bond (a good proxy would be a U.S. treasury bond). This difference in yield measures how much riskier a bond is compared to a risk-free bond. 

How Credit Derivatives Can Be Used to Transfer Risk or to Speculate

In general, derivatives are financial contracts whose value is derived from the performance of some underlying assets or market factors, created to enable investors and individuals to trade in specific risks. Since banks are in the business of giving loans, they constantly face a great amount of credit risk. Over the past several decades, banks have developed various ingenious credit derivatives to deal with the credit risk of loans. In addition to seeking various ways to reduce credit risk from debtors themselves, banks can use credit derivatives to transfer the credit risk of a loan to a third party.

Theoretically, credit derivatives can help banks and investors to isolate credit risk, price it, and transfer it to others who are willing to take on the risk for a premium. One key accounting benefit of credit derivatives is that they allow banks to transfer away credit risk of loans while still keeping the loans as assets on their balance sheets. With the development of the credit derivatives market, it is also common practice for banks and investors to speculate by holding a derivative position without having the underlying loans. Derivatives are often highly leveraged (often 20 to 1), which means speculators can make or lose large amounts of money off a small movement in price. Speculators add liquidity to the derivatives markets.

Not all derivatives are credit derivatives. There are at least five main categories of derivative products that banks engage in: interest rate swaps, currency futures, equity derivatives, commodity derivatives, and credit derivatives. According to the OCC, four banks dominate the derivatives market ($200 trillion!), and in the 4th quarter of 2012, 80 percent of the U.S. derivatives market consisted of interest rate swaps, while credit derivatives took up 6 percent.[9] The following tables show the total amount and the breakdown of derivative contracts engaged in by these banks:

Table 5: Notional Amount of Derivative Contracts[10]

Park Table 5

Table 6: Percentage of Total Derivative Contract Notional Amounts by Category[11]

Park Table 6

How Credit Derivatives are Assessed

There are several different types of credit derivative instruments. The most widely used credit derivative is called a credit default swap (CDS). In “The End of the Beginning for the Global Credit Crisis,”[12] the authors explained how banks can use CDSs to insure against default of mortgage-backed securities. In a CDS, two parties enter into an agreement whereby one party pays the other party a periodic premium (usually quarterly) over the life of the contract in exchange for a larger payment should a “credit event” occur. A credit event is a specified event that materially affects the cash flow of the referenced debt such as bankruptcy or insolvency. If the credit event does not occur, the other party does not have to pay any amount. Essentially, a CDS is a form of financial default insurance.

Pricing credit derivatives accurately is a huge challenge. Pricing credit derivatives is more difficult than pricing other types of derivative instruments such as equity derivatives because the underlying asset for credit derivatives is not a traded security. Furthermore, prior to default, it is difficult to distinguish firms that will default from those that will not. Since credit risk is a matter of probabilities, assessing the probability of bankruptcy is difficult:

  • One way to price credit default swap is to use historical probabilities. Since S&P has extensive historical data on defaults for publicly issued bonds based on their credit rating and the recovery rates according to the seniority of the debt, this information can be used to estimate future default and recovery rates. However, this methodology has several problems: first, all bonds within a particular rating category are not identical; second, the recovery rates within each level of seniority can vary widely from one bankruptcy to another; and third, historical data can ignore more recent, unique regulatory and economic circumstances—for example, historical default data provided no guidance as to future default rates for subprime cases when house prices were artificially inflated due to banks’ reckless lending practices.
  • The second and most widely used method for pricing credit default swaps is based on a mathematical model of the default process developed by Nobel laureate Robert Merton.[13] Starting by mathematically determining the process of valuing debtor’s assets, this asset valuation process is used to assess the likelihood that the future value of the assets might fall below the debt to trigger a default. (In this model, Merton applied the option pricing theory developed by Black and Scholes to model firm’s assets and liabilities. Merton’s model has been extended further by Black and Cox[14] and Longstaff and Schwartz[15].) Overall, this methodology also has some significant limitations because producing workable solutions based on mathematical models requires many simplifying assumptions.

Despite these weaknesses in the pricing models of credit default swaps, the CDS market exploded with the passing of the Commodity Futures Modernization Act of 2000, which completely deregulated credit derivatives trading (Senator Gramm (R-TX) was the head of the Senate Banking Committee who pushed through this bill in the Senate). This bill included what is now referred to as the “Enron loophole,”a financial regulation that allowed for the creation of speculative energy derivative instruments. (Interestingly, Wendy Gramm, the wife of Senator Gramm, was a former chairman of the Commodity Futures Trading Commission and later a board member of Enron.) As of the end of 2012, the global CDS market reached $25 trillion,[16] surpassing the equity derivatives market and the corporate bond market.

How Banks Can Remove Risky Debt Off Their Books Using Collateralized Debt Obligations

While a CDS can allow banks to transfer away the credit risk of a loan, while keeping the underlying loan on their balance sheets, a collateralized debt obligation (CDO) can remove risky debts off their books. After CDSs, CDOs and variations such as collateralized mortgage obligations (CMOs) constitute the next biggest share in the credit derivatives market. Usually, a CDO requires a special purpose vehicle (SPV), a separate legal entity setup by the bank that buys a pool of loans from the bank and issues the CDOs (payment is made after CDOs are created and sold). This way, the pool of loans can be moved off the balance sheet of the bank and into the SPV. The SPV then issues “tranches” of notes, based on the cash flows generated by the pool, to be distributed according to the seniority and the risk profile of each class of CDO.

These tranches are examined by the rating agencies and receive different ratings based on their seniority and various characteristics of the underlying assets. The general robustness of a CDO can be measured by overcollateralization and interest coverage ratios. The ingenuity of a CDO structure is: 1) it creates the flexibility of varying products with different risk profiles for the investors to choose from; and 2) it produces investment grade products from a pool of not-so-creditworthy loans with the help of the rating agencies. The CDO construction, with its reshuffling of risk profiles, can create a more liquid market for banks’ underlying, poorly traded, risky debt. This process in turn helps banks to clear more debt off their balance sheet and maintain a better equity/debt ratio.

Although a traditional CDO contains a pool of debt as collateral, the pool can be modified to include derivative products as well. When a pool of CDSs, which are derivative instruments, is used as collateral to produce a CDO, it is called a synthetic CDO. When other CDO notes are used as collateral, it is called CDO squared. It is easy to see how the collateral can be “diversified” to include as many different types of debt and derivatives of debt as one can imagine, as long as there is a market for them.

According to the lawsuit,[17] during 2004 to 2007, S&P rated $1.8 trillion worth of CDOs alone. The complaint alleges that S&P knew that their ratings were material to the investment decisions of financial institutions investing in CDOs, and that better ratings on CDOs benefited the issuers (i.e., banks). In turn, helping the issuers with better ratings brought more businesses to S&P, who charged $500,000 to $750,000 for each CDO it rated. During the years 2005 to 2007, the CDO ratings business produced close to $500 million in revenue for S&P. The complaint alleges that S&P defrauded the investors by favoring the issuers, and that they recklessly underestimated the risks of CDOs which produced higher profits for the issuers.

Conclusion: How the Ratings Game Must Be Corrected

There is a clear conflict of interest between the banks that issue these credit derivative instruments and the rating agencies: higher ratings mean more business for the rating agencies who receive fees from the issuers. Admittedly, one could argue that the root problem lies neither in derivative instruments nor the rating agencies, but in the fact that banks use unreasonably high leverage and rely upon short term debt to sustain their capital.[18] Because derivatives can create huge counter party risks which can wipe out banks’ equity quickly, it can also deplete the banks’ market for short term capital to sustain them and cause bank failures.

Although this line of reasoning highlights the dark side of banks’ business tactics and bailout politics, the “ratings loophole” must still be corrected to prevent future breakdowns. How?

  • Break up the oligopoly of rating agencies: First, it is apparent that financial regulations in the past have helped to create the current oligopoly of the big three ratings agencies. By requiring regulated financial institutions to rely on the ratings of specified ratings agencies, it has unnecessarily boosted the position that private rating agencies play in the global financial market. If the regulatory dependencies on rating agencies can be decreased and the NRSRO designations loosed, market forces can reduce the power concentration of the big three rating agencies.
  • Change the business model: Second, the issuer-pay business model of these ratings agencies created obvious conflict of interest that not only fueled the inflated demand for credit derivative products, but also caused the eventual meltdown. If the business model of rating agencies can be changed to investor-pay only and prohibit issuer-pay, the conflict of interest can be resolved.

In July 2009, the Obama Administration, as part of its proposal for financial reforms, offered legislation that would require more stringent efforts on the part of the rating agencies to deal with the conflicts of interest and to enhance transparency. More specifically, the proposal sought to limit conflicts of interest by barring rating firms from consulting with companies they rate and allowing investors access to all the pre-ratings a corporation received for a particular security before a final rating firm is selected. However, the proposed reform failed to address either of the root causes discussed above and left the rating agencies largely unscathed.

In conclusion, despite the DOJ’s attempt at a civil lawsuit, which will eventually end in a settlement, the regulatory root causes still remain unfixed. How long until the next crisis?


[1] Park, Abraham. “Why Did Subprime Loans Become Such a Big Deal?” Graziadio Business Review Blog, May 5, 2008. http://gbr.pepperdine.edu/blog/2008/05/05/29/.

[2] “Attorney General Eric Holder Speaks at the Press Conference Announcing Lawsuit Against S&P,” http://www.justice.gov/iso/opa/ag/speeches/2013/ag-speech-130205.html.

[3] White, Lawrence. “The Credit Rating Agencies: How Did We Get Here? Where Should We Go? Antitrust Chronicle, 4, number 1 (2012).

[4] Largest Public Company Bankruptcy Filings – 2013 to date, http://www.bankruptcydata.com/Research/Largest_2013.pdf.

[5] Ibid.

[6] S&P Global Fixed Income Research, 2012 Annual Global Corporate Default Study and Rating Transitions, March 8, 2013.

[7] Ibid.

[8] Ibid.

[9] The Office of the Comptroller of the Currency, Quarterly Report on Bank Trading and Derivatives Activities, Fourth Quarter, 2012.

[10] Ibid.

[11] Ibid.

[12] Crawford, Peggy J. and Young, Terry. “Will the Sub-Prime Meltdown Burst the Housing Bubble?” Graziadio Business Review, 10, no. 3, 2007. http://gbr.pepperdine.edu/2010/08/will-the-sub-prime-meltdown-burst-the-housing-bubble/.

[13] Merton, Robert C. “On the pricing of Corporate Debt: the Risk Structure of Interest Rates” Journal of Finance, 1974, Vol. 29, pp. 449-470.

[14] Black, Fisher and Cox, J.C. “Valuing Corporate Securities: Some Effects of Bond Indenture Provisions,” Journal of Finance, 1976, Volume 31, pp. 351-367.

[15] Longstaff, Francis A. and Schwartz, Eduardo S. “A Simple Approach to Valuing Risky Fixed and Floating Rate Debt,” Journal of Finance, 1995, Volume 50, No. 3, pp. 789-819.

[16] Bank for International Settlements Statistics, http://www.bis.org/statistics.

[17] Announcement of S&P lawsuit, http://www.justice.gov/iso/opa/ag/speeches/2013/ag-speech-130205.html.

[18] Gorton, Gary B. Misunderstanding Financial Crises: Why We Don’t See Them Coming. Oxford University Press, 2012.

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Achieving Enterprise Stability Based on Economic Capital

Enterprise stability and a company’s chance for survival can be improved by applying a modified approach to the role of equity as “economic capital.”

[powerpress: http://gsbm-med.pepperdine.edu/gbr/audio/fall2011/ZbigniewKrysiak_Article.mp3]


Man peers over stack of coinsIn a highly competitive environment, companies can focus too much attention on maximizing profits in the short term, while neglecting basic principles of the risk management process. Many bankruptcies, including those of big and successful companies listed on the New York Stock Exchange (NYSE), have stemmed from a failure to plan for the downside of risk. Enterprise stability and a company’s chance for survival can be improved by applying a modified approach to the role of equity as “economic capital.” This article presents an overview of the principles of economic capital for facilitating stability and survival of the company and contends that Survival Enterprise Risk Management by Economic Capital (SERMEC) can effectively create a new organizational culture based on Risk Employment for Enterprise Development (REED).

Role of Equity in Default Risk Hedging

Equity is a part of the long-term funding used by a company to support fixed and current assets necessary to run business operations and ensure an appropriate level of liquid assets for continuous operating activity. Most frequently, the capital is there as a source for purchasing assets needed for business operations.[1] That is of course an important function of capital, but companies must ensure that they have enough capital to survive a downturn as well.

Most enterprises know very well how to estimate and evaluate sales, production, and marketing projects, but often fail to account for the risk that these activities generate. For example, a company that engages in a risk such as decreasing price below the average market level, establishing a new production facility, closing 20 percent of all service offices, or extending a loan, has to be aware that, at some point, that risk is going to be realized in gains and losses. In such a case, appropriate funds have to be available to cover the potential losses. Considering the role of equity as a hedging tool against default risk offers a different approach to allocation and usage of that form of capital. Since equity has to cover the potential losses, then equity should be readily available because we don’t know when risk could precipitate loss. This suggests that some part of equity should be invested in very liquid assets.

Economic Capital Allocation

Economic capital can be defined as a level of equity that is adequate to cover losses incurred during risk realization. An enterprise should be able to identify major risk sources and monitor their impact on profit and loss. Risk sources should be perceived not as a danger or enemy, but as a driver of company value.[2] This statement is validated when the option model is applied to estimate equity value. Calculated equity value in that model reflects higher risk as measured by volatility of rates of return. They could have both negative and positive impact. Therefore identification, measurement, and control of risk sources and risk drivers becomes critical for business success. To allocate appropriate economic capital, we have to quantify negative outcomes of risk realization based on the mapped risk matrix within the organization. More general examples of risk sources are shown in Fig. 1.

Fig. 1: Examples of main risk sources to be covered by Economic Capital.

Fig. 1: Examples of main risk sources to be covered by Economic Capital.

For each segment of business shown on Fig. 1 several risk drivers should be identified and their impact quantified. To calculate the demand for economic capital, each risk type should be assessed by sources and risk drivers, type of risk events, frequency and probability of a risk event, impact of a risk event, and profit or loss as an outcome of the risk event.[3] This kind of risk decomposition is presented in Fig. 2 and could be called a five-dimensional space of risk. The risk management process requires appropriate controls in place to monitor the frequency of events and losses or gains. The magnitude and frequency of events are used in the control process as feedback to adjust risk drivers and risk sources up to the level of the risk tolerance of the company. The risk tolerance can be estimated using the utility function concept and corresponds to the level of economic capital. This means that assumed risk at any time cannot exceed the level of available capital even if the company has an opportunity to extend business by increasing sales or production activity.

Fig. 2: Five-dimensional space of risk[3]

Fig. 2: Five-dimensional space of risk

Decomposed risk can be reflected using the following measures:

AR =Annual Rate of Event PD = Probability of Default
EAD = Exposure at Default LOC = Level Of Control of a Risk Event
RR = Recovery Ratio LGD = Loss Given Default

Quantification of economic capital can be supported by a technical tool known as the Monte Carlo Simulation and its concept is presented in Fig. 3. Probability distributions have to be determined by experts and managers involved in a particular business since this requires knowledge of the fundamentals.

Fig. 3: Quantification of economic capital

Fig. 3: Quantification of economic capital


Probability distribution of losses has two basic components. The first component is related to the expected losses denoted by EL, and the second one is called “unexpected loss” denoted by UL. These two components result in total losses for the company. Expected losses have to be covered by a risk premium included in the price margin of the product. This premium cannot be consumed, but should be kept on the balance sheet as a provision to cover losses up to the average level of total losses. Unexpected losses have to be reflected in capital called economic capital, which cannot be frozen in fixed and risky assets, but has to be invested in very liquid assets.

Risk Employment for Enterprise Development (REED)

Risk is inherent in any business activity and it cannot be ignored. Just like a start-up business, an enterprise undertaking new projects incurs costs and investment outlays before an income is generated. In each case, additional economic capital should be allocated based on an earlier calculated default probability and exposure at default. Determination of economic capital should be considered from the perspective of modern portfolio theory, which contends that correlations between particular risk components can decrease the value of the economic capital when new components of the portfolio are added.[4]

Avoiding risk or costs can lead to missed opportunities for value creation and impede development of the company. Profit as a measure of company efficiency is a very poor indicator and, for more than a decade, there has been too much focus on efficiency measures based on the company profit instead of value. From this perspective the question arises: What are the sources of company value? Risk is a major “source” of company value. The best way to increase the value of the company is to be focused on “risk undertaking.” However, not all risks should be undertaken unless that risk creates value.

Measuring the value resulting from risk is more complicated than measuring profit and requires different and more advanced skills to manage properly. Utilizing economic capital approach allows us to compare, apples to apples, the risk with the company value. Thus, economic capital is a derivative of risk and can be expressed also as “value at risk” (VaR).[5] VaR denotes how much the value of the company is in danger of deterioration. Economic capital serves as a hedge instrument to protect against this deterioration. Without such an instrument, a company’s value can be decimated in the face of risk realization. The cost association with economic capital and hedging is a small price to pay for safeguarding company value.

An Evolution of Risk Management

The concept of Enterprise Risk Management (ERM) sprung from the shortcomings of Value Based Management (VBM). This approach does not take into consideration the relative change between risk dynamic and the dynamic of value. Forgetting this type of analysis led in the past to instances of a very satisfactory and high increase in value, even though the company went bankrupt. Therefore, in the business environment, we have to estimate the value-to-risk ratio to determine if the company condition is improving or deteriorating. To make it real and decline the default risk, a new approach to company risk management has to be assumed, which can be summarized as Enterprise Risk Management (ERM).

There are several specific approaches to ERM because it is very much related to the individual business context of any enterprise, therefore each business has to find an individual “suit.”[6] Enterprise Risk Management can be defined as an integrated and holistic approach to credit risk, market risk, operational risk, business risk, and economic capital management. This includes risk control, mitigation, and risk transfer to maximize value of the company.[7] Successful ERM implementation takes a long time and requires engagement of all the managers within the company. ERM requires advanced tools and analytical methods as well as some different approaches to managerial accounting when reflecting financial results on the balance sheet.[8][9][10][11]

Increasing quality in risk management defrays reputational risk and improves financial results by decreasing volatility of profits.[12] Compared to the traditional risk management process, ERM focuses on a holistic instead of a silo-based approach. ERM is the basis of the Survival Enterprise Risk Management by Economic Capital (SERMEC) model, therefore it is important to understand how the quality of ERM can impact a successful implementation of SERMEC. The first applications of ERM took place in 2004 and were triggered by demand to comply with regulations imposed by the New York Stock Exchange (NYSE) on audit committees. Concepts and principles for implementations of ERM in public companies were derived from the Committee of Sponsoring Organizations of the Treadway Commission (COSO), created in 2004. At the same time, in the banking sector, a set of recommendations on banking laws and regulations issued by the Basel Committee on Banking Supervision called “Basel II, were being implemented. It was a big challenge that was associated with moral hazard risk.[13] Three years after commencing ERM implementation, a big crisis appeared making a hit around the world. There is some evidence that enforcement of ERM by regulators did not challenge companies to creative engagement toward good quality of ERM implementation, but rather led to opposite results.[14] Increasing maturity and awareness of managerial resources allocated for the implementation of ERM was a main factor for improvement and increasing quality of ERM, which was observable in company value behavior.[15][16]

Fig. 4: Correlation between rating of quality of ERM and financial results for companies in Europe.

Fig. 4: Correlation between rating of quality of ERM and financial results for companies in Europe.

Unpublished research studies performed by the author on a sample of approximately 120 companies operating in Europe, show that a higher quality of ERM improves financial results and decreases the volatility of business indicators. Fig. 4 presents the correlation between financial results and rating of quality of ERM. Financial results are expressed as a ratio of net profit to total balance. This research study to a certain extent proves that ERM implementation has a positive impact on value creation and increased stability of the company.[17]

The ERM process implements risk quantification to measure value/risk ratio, but it is not a sufficient condition to assure survival of the company. The economic capital reflecting the cumulated level of risk can be considered as a sufficient condition in maximizing probability of the company survival.

Fig. 5: Relationship of proposed SERMEC approach to another in the past developed concepts regarding enterprise development and its growth

Fig. 5: Relationship of proposed SERMEC approach to another in the past developed concepts regarding company enterprise development and its growth

Fig.5 presents an evolution from risk management (RM), to value-based management (VBM) and value at risk (VaR) concepts, to the SERMEC model. The SERMEC model combined with appropriate organizational structure and different then in the past organizational behavior can lead to REED concept, which is basically the new enterprise culture focused on employment of risk for company development.

Application of SERMEC Concept in Modern Business Management

The SERMEC concept utilizes past developments in finance theory and practice single tools, models, and measures which were previously applied separately. SERMEC at the final stage utilizes two important measures to steer the company development. First is Effective Probability of Default (EPD) and the second is Adjusted Weighted Average Cost of Capital (AWACC). SERMEC can be decomposed into three steps. First, where the ERM process has to conclude with determining value to risk ratio (V/σ), then based on this, in the ERMEC stage, the economic capital is estimated, which concludes with calculation of EPD. Value of economic capital is utilized to create appropriate capital structure composed of equity and debt and as well in this stage we calculate adjusted cost of capital. This leads to the conclusion that SERMEC ensures optimal enterprise development through establishing the appropriate structure of capital, which is most effective from the perspective of optimal level of financial and business results and remoteness of enterprise bankruptcy. Establishment of capital structure and adjusted cost of capital is derived based on economic capital estimation which could be called a hedge fund protecting the company against default. Finally we approach the main thesis, that enterprise stability based on economic capital could be realized through implementation of the SERMEC concept.

Conclusion

In the past decade, very little consideration has been given to the relationship between company value and the risk dynamic. Any increase in company value has to be related to an increase in risk level to make sure that the value to risk ratio is not declining. Many bankrupted companies around the world did not have adequate capital to cover the losses incurred when risk was realized. Many theories of risk management have been developed as a result, but the most advanced is the SERMEC concept, which establishes good fundamentals for creating the new organizational culture based on risk employment for enterprise development.


[1] Ross A. S. Corporate Finance: Core Principle and Applications, New York: McGraw-Hill, 2011.

[2] Krysiak Z. Default Risk Evaluation for Construction Sector in Poland, [in:] Credit Risk of Mortgage Loans – Modelling and Management, Scientific Editors K. Jajuga and Z. Krysiak, Polish Bank Association, 2005.

[3] Monahan, Gregory. Enterprise Risk Management – A methodology for achieving strategic objectives, New Jersey: John Wiley & Sons, 2008. 2.

[4] Elton J. E., J. M. Gruber, J. S. Brown, and N. W. Goetzmann. Modern Portfolio Theory and Investment Analysis, New Jersey: John Wiley & Sons, 2007.

[5] Jorion Phillipe. Value at Risk: The New Benchmark for Managing Financial Risk, New York: McGraw-Hill, 2007.

[6] Fraser, John, and Betty J. Simkins. Enterprise Risk Management, New Jersey: John Wiley & Sons 2010.

[7] Lam, James. Enterprise Risk Management- From Incentives to Control, New Jersey: John Wiley & Sons, 2003.

[8] Copeland T., Antikarov V., Real Options, New York: Texere LLC, 2003.

[9] Hahn, Joe W., and Luiz E. Brando. “Real Options: The Value Added through Optimal Decision Making.” Graziadio Business Review 13, no. 2 (2010). http://gbr.pepperdine.edu/2010/08/real-options-the-value-added-through-optimal-decision-making/.

[10] Shockley, Richard L. An Applied Course in Real Options Valuation. Ohio: Thomson Higher Education, 2007.

[11] Wiklund D., Rabkin B. The Balance Sheet Perspective of Enterprise Risk Management, Financial Executive 25, no. 2 (2009). 54-58.

[12] Shimpi P. Integrating corporate risk management, New York: Texere, 1999.

[13Credit Risk of Mortgage Loans – Modelling and Management, Scientific Editors K. Jajuga and Z. Krysiak, Polish Bank Association, 2005.

[14] Pagach, Donald, and Richard Warr. “The Characteristics of Firms That Hire Chief Risk Officers.” Journal of Risk and Insurance 78, no. 1 (2011). 185-211.

[15Ibid.

[16] Shimpi P., Enterprise Risk Management from Compliance to Value, Financial Executive 21, no. 6 (2005). 52-55.

[17] Fraser J., Simkins B., loc cit.


Additional Reading:

Smith M. David, Business Survival Skills, Graziadio Business Review, 2006 Vol. 9 Issue 2.

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In Extremis Leadership by Thomas A. Kolditz, PhD

In Extremis Leadership: Leading As If Your Life Depended On It

By Thomas A. Kolditz, PhD
Jossey-Bass, 2007

[powerpress http://gsbm-med.pepperdine.edu/gbr/audio/winter2010/review-magasin.mp3]

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4 stars: Thought-provoking and intellectually stimulating materialColonel Thomas A. Kolditz is a professor and head of the department of behavioral sciences and leadership at the United States Military Academy. While his research focuses on military, police, and fire critical-response organizations, he argues that the lessons from life-or-death situations offers “profound lessons for leadership in all settings.” The New York City Fire Department’s Deputy Assistant Chief, Joseph W. Pfeifer, sums up Kolditz’s position in the book’s foreword: “In Extremis Leadership examines those high-risk environments and provides a new understanding of how to lead not only in life-and-death situations but also in everyday situations.”

Certainly, if salaries, job security, and work environments are in order, leadership demands are not as intense. However, should conditions change for the worse, one can lead only if the preexisting foundation has been laid. Kolditz points out that some leaders rise to the occasion, but that ability is based on a fundamental understanding of what leadership requires—what he calls “authentic leadership.”

“Optimism, hopefulness, and resiliency provide the key to understanding why leaders who are authentic are also effective at commanding loyalty, obedience, admiration, and respect,” he writes. When these traits are valued, authentic leaders exert a powerful influence.

Kolditz also explores another important trait of authentic leaders—their recognition of the value of human life. “In extremis leadership always comes with a tangible moral obligation… [It is] less about power over subordinates and more about an obligation toward their well-being and survival.” If corporate management prized employees’ well-being, the author posits, employees would likely reciprocate for that caring and enhance the positive aspects of their workplaces.

Being a leader is about developing a character that is “inextricably linked to giving purpose, motivation, and direction to others,” according to the book. While it remains to be seen how much the principles of authentic leadership cross over from life-and-death situations to the business world, there is no question that many of the concepts Kolditz delineates seem sensible and applicable.

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Examining the Role of Short-Term Correlation in Portfolio Diversification

From the third quarter of 2008 to the present, the financial markets have “gone to one,” meaning that all investment options have become highly correlated. They have all gone down (with the notable exceptions of cash and government bonds). The benefit of holding uncorrelated assets is that they should not all move in lock step, so that while one goes down, hopefully another will increase. The question that this article attempts to answer is whether the long-term correlations that sales and marketing materials often quote are similar in the short term as well.




Image: Geopaul





Typically, correlation between investment assets and asset classes is calculated over extended time periods, such as 5, 10, or 15 years. But what is of greater concern to the investor is what the correlation will be next month. The use of a low 15-year correlation might obscure more recent data due to the length of time over which the correlation was calculated. Could it be, for example, that the last 12 months would show a much higher correlation between assets than the figure contained in the marketing literature?

This article looks at the near-term issues regarding correlation. Using two series of random numbers (180 observations to simulate 15 years of monthly returns) and running a short (100-trial) Monte Carlo simulation (a process that repeats the same trial), these uncorrelated random series showed significant 36-, 24-, and 12-month correlations. This suggests that investors should also consider short-term correlations between assets when attempting to diversify their portfolios. In addition, correlations should be rebalanced as often as asset allocations because investment strategies, personnel, and so forth change over time.

What is Correlation?

Most investors have the singular goal of maximizing investment return given a certain level of risk tolerance. Modern portfolio theory holds that returns are maximized in the long run when they are held in a diversified portfolio. A statistical measure of diversification is “correlation,” which is measured on a scale that runs from -1.0 to +1.0. A correlation coefficient of -1.0 or +1.0 is considered perfect correlation, knowing how one series of data moves provides perfect information on how the second series will move.

A negative correlation coefficient signifies that the two series move in opposite directions, for example, as one series increases, the other decreases. This is also known as an inverse correlation. A positive or direct correlation indicates that the series move together, as one increases, the other also increases. It is rare that one comes across perfect correlation, that is, a correlation coefficient of exactly -1.0 or +1.0.

The plus or minus sign indicates whether the relationship is direct or inverse, whereas the calculated value indicates the strength of the relationship. As the correlation coefficient moves from zero toward +1.0, there is an increasingly direct statistical relationship. Conversely, as the correlation coefficient moves from zero to -1.0, there is an increasingly inverse statistical relationship. In addition, a correlation of -0.7, then, is exactly as significant as a correlation of +0.7. A correlation coefficient of zero indicates that there is no statistical relationship between the two series of numbers, the series behave randomly with respect to one another. This is also called “non-correlation,” or, sometimes, the two series are said to be “uncorrelated.”

One important point about correlation is that it does not represent causality. For instance, in school-age children, shoe size is a great predictor of reading ability, not because shoe size has anything to do with reading, but because it is a proxy for age, older children tend to read better.

Correlation and Investing

Some investors believe that they make only three investment decisions: asset allocation, manager selection, and vehicle choice. Asset allocation is important because it is widely held that diversification is a cornerstone of investing theory. Diversification follows the logic of not putting all of your eggs in one basket. If an investor invests in a single stock, then the portfolio will do as well or as poorly as that single stock. If the investors select two stocks, they would appear to have achieved some level of diversification, but this is only at a company level. If both companies are engaged in the same industry, like Pepsi and Coca-Cola, or American Airlines and Delta, or Ford and GM, then the stock price movements that affect an industry segment will affect both stocks, that is, 100 percent of their portfolio. So, the investors might want also to diversify along company, industry, or geographical lines.

Diversification is usually quantified by correlation, that is, the degree to which the movement of one investment or asset class allows for inferences about how another investment or asset class will move. This is not indicative of causality, but simply a statistical relationship that may include causality and that can also occur simply by chance. A portfolio is not diversified if all of its holdings are correlated with one another, meaning that if one holding moves a certain way, we can predict how the other holdings will move. Brokers of commodity-based products (whether futures contracts or hard-asset ownership), infrastructure investments, and real estate funds often cite “uncorrelated with existing asset classes” as a major selling point of their products:

Issues with Non-Correlation as an Investment Strategy

Asset classes are too broad

Individual products within an asset class are not created equal; there are a wide variety of investment choices within any class. For instance, within the “hedge fund” asset class (assuming one considers hedge funds an asset class) there are over 8,000 investment choices. Treating the returns of the asset class as representative of the returns of the underlying components could be erroneous. The same is true of U.S. equities as a whole, or even when dealing with subcategories, such as Small Cap Growth, Small Cap Value, Large Cap Growth, Large Cap Value, and so forth. To be useful, non-correlation should focus on product-level asset holdings.

Not all portfolios are alike

Portfolio compositions usually differ among investors in terms of asset allocation and individual investment choices. To claim that a particular product will not be correlated with the portfolio does not give appropriate credit to the diversity of investments and the particular holdings. To be relevant, correlation should be calculated based on the returns of specific portfolio holdings, not generic asset-class returns.

Different types of non-correlation

Third, there can be different types of non-correlation. One type of non-correlation is the one people ordinarily think of when they define non-correlation, when one variable changes, the other variable will behave randomly. Another type of non-correlation operates very differently. Two series can have a low overall level of correlation even if they are 100-percent positively correlated half of the time (i.e., they have a correlation of +1.0 for half of the observations) and 100 percent negatively correlated the other half of the time (i.e., they have a correlation of -1.0 for half of the observations). In this situation, the variables clearly have some kind of relationship to one another, although the overall correlation coefficient might indicate otherwise.

Perhaps what makes correlation so interesting is that similar situations can lead to quite different results. Consider the following small series:

Observation X Y
1 1 9
2 2 8
3 3 7
4 4 6
5 5 5
6 4 4
7 3 3
8 1 1

The overall correlation is -.096, which is not even remotely statistically significant. But within that overall insignificant correlation are two sub-series (observations 1 to 4 and observations 5 to 8). The correlation of observations 1 to 4 is -1.0, and the correlation of observations 5 to 8 is +1.0, which are perfect correlations.

Now consider another small series:

Observation X Y
1 4 5
2 3 6
3 2 7
4 6 3
5 7 4
6 8 4

The correlation of observations 1 to 3 is -1.0, and the correlation of observations 4 to 6 is +1.0, as in the last series. However, the overall correlation is .72, which is on the border of statistical significance at the .10 level.

In the first case, we had an overall correlation coefficient that indicated there was absolutely no statistical relationship between the two series. However, embedded within that series were two shorter series that had extreme levels of correlation (one positive and one negative). In the second case, the observations were similarly arranged so that the first half of the series had a correlation coefficient of -1.0, and the second half of the series had a correlation coefficient of +1.0, yet the overall result was a nearly statistically significant correlation of .72.

Even when it operates as we think it does, do we want it?

If two asset classes (or individual investments) are truly uncorrelated, then when the first asset class increases, the other class may increase, decrease, or remain unchanged. There is no existing statistical relationship that allows us to infer how one class will behave based on the behavior of the other, but is this random effect desirable? We can couch the issue in the following terms: When the first asset class increases, we would like the other class to increase. However, since it is behaving randomly, there is only a one-in-three likelihood that it will do so (with the three possibilities being for it to increase, decrease, and remain unchanged). Similarly, when the first asset class decreases, we would like the other class to increase, though, again, there is a one-in-three chance this will happen. Better odds can be achieved by betting “black” at a roulette table.




Photo: Daniel Haller





The Experiment

This article examines whether uncorrelated (in the long term) series of numbers (representing investment returns) are also uncorrelated in the short term. While most investment professionals will not be surprised that uncorrelated asset classes (or investments) may have short-term correlations, the question is whether the frequency and duration of the short-term correlations are what might be expected.

This study was exploratory in nature because we could not find empirical research that quantifies the type of short-term correlation that would be considered “normal.” Since we have no basis on which to a priori establish whether the short-term series are abnormal, we will quantify and present the results and establish the literature.

We began with two series of 180 random numbers representing 15 years of monthly returns. Correlations were calculated for the last 36, 24, and 12 months of the series, since these timeframes were representative of the effect that will be introduced into the portfolio. In other words, the relevant correlation is the most recent one, not the one that was evident 15 years ago. A hundred iterations of this experiment were performed.

Exhibit 1: Frequency of observed correlations resulting from 100 trials

Each trial had 180 monthly observations (15 years). During the 100 trials, the overall correlation was .20 one time, and less than .20 the other 99 times.

The correlation for each trial was recalculated over the last 36, 24, and 12 months, and the correlations for these shorter periods are indicated:

Correlation (+/-) 0.2 0.3 0.4 0.5
Overall 1 - - -
Last 36 months 27 9 2 -
Last 24 months 33 18 6 2
Last 12 months 61 39 21 10

The Results

The test revealed that, overall, the two series were uncorrelated. In the 100 trials, the overall correlation of .20 was only obtained once. When we reviewed the correlations of the last 36, 24, and 12 months, some startling results were evident. In the last 36 months of each trial, the correlation was 0.2 or more 27 percent (27/100) of the time, 0.3 or more 9 percent of the time, and 0.4 or more 2 percent of the time.

For the last 24 months, a correlation of 0.2 or more occurred 33 percent of the time, a correlation of 0.3 or more resulted 18 percent of the time, a correlation of 0.4 or more was obtained 6 percent of the time, and a correlation of 0.5 or more occurred 2 percent of the time.

The last 12 months, however, may be the most relevant period because this timeframe is the most likely to impact a portfolio. A correlation of 0.2 or more occurred 61 percent of the time, a correlation of 0.3 or more was evident 39 percent of the time, a correlation of 0.4 or more occurred 21 percent of the time, and a correlation of 0.5 or more was found 10 percent of the time. An investor adding an investment and expecting it to be uncorrelated (based on 15 years worth of data) could very well be surprised at the resultant effect.

Conclusion: Do Your Short-Term Correlation Home-Work

Our findings suggest that if an investor is adding an investment to his or her portfolio with the goal of aiding diversification, he or she should parse the long-term correlation into shorter-term metrics. The nearer and the shorter the timeframe, the greater the likelihood that the investment will move from uncorrelated to correlated. As the correlation that will be added to the portfolio is more reflective of the 180th month than the first month of the series, the additional calculation of a near-term 36-, 24-, and 12-month correlation could prove useful. Perhaps there is an investment that can be added to the portfolio that, over the long term, will provide uncorrelated returns and, therefore, aid in diversification. However, if the return stream is presently correlated to the portfolio, the investor should wait a couple of periods before adding the investment, thereby mitigating the short-term effects of correlation.

Review Investments Periodically for Correlation Shifts

An additional implication from this study concerns investments that are already in the portfolio. Once an investment is added, there is usually no further attention devoted to the correlation. This study suggests, however, that the correlations of the existing investments should also be reviewed periodically. Manager changes, style drift, and so forth may mean that the original correlation that made the investment attractive is no longer accurate.

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Private vs. Public Real Estate Markets

Investors should be aware that the indices tracking the returns of publicly traded real estate companies (public real estate) and private commercial real estate cannot be compared at face value. First, the private commercial real estate return indices suffer from artificial “smoothing” effects of infrequent, appraisal-based valuation data, and second, the public real estate returns include the effects of leveraging used by real estate companies. Although the underlying values of the properties are similar. For these reasons and more, the private and public real estate returns/risk characteristics are dissimilar.

This article highlights the informational inefficiency that exists between public and private real estate markets: prices from publicly listed real estate markets lead and predict prices in private real estate markets for as much as a year or more.





Image: Stephen W. Morris





Global Real Estate Equity Market

Within the last decade, the global real estate market has come a long way. The increase of capital flows into the real estate sector, the growth in variety and number of investment vehicles, and the increased recognition among institutional investors of the potential for real estate within a multi-asset portfolio have contributed to the worldwide expansion of both the private commercial real estate equity market and public real estate equity market (publicly traded property companies).

The size of the global investable universe of private commercial real estate equity market has grown from approximately USD $6.2 trillion at the end of 2003 to more than USD $8.0 trillion in 2006,[1] with the U.S., Japan, and UK markets making up approximately half of the investable universe.

The growth of the public real estate equity market has been even more dramatic.

The total market capitalization of the FTSE EPRA/NAREIT global listed real estate index (composed of 300-plus publicly traded real estate companies around the world) more than tripled within the last six years, with the total market capitalization at the end of 2007 reaching approximately $800 billion.

Public Real Estate Total Market Capitalization[2]

During 2007, the total market capitalization of publicly listed real estate around the world fell significantly from their tops due to a combination of market factors: rising interest rates, mergers and acquisitions of public REITs, concerns of an economic slowdown, and the U.S. subprime mortgage crisis (Read Dr. Park’s explanation of the causes of the sub-prime mortgage meltdown here). After a seven-year stretch of market-leading performance, the real estate market as a whole is currently undergoing a correction period.

Real Estate Investment Trusts

In an effort to give small investors access to real estate investments that traditionally were available only to institutions or wealthy individuals, the U.S. Congress passed the REITs Act in 1960, allowing for the creation of Real Estate Investment Trusts (REITs). A REIT is a special corporate organizational form, under the tax laws, for companies that own and operate income-producing real estate. The benefits of the REIT organizational form for investors include liquidity, limited liability, and professional management, while avoiding taxation at the corporate level (similar to mutual funds for stock investors). In order for a company to qualify as a REIT in the United States, it must comply with the requirements of Internal Revenue Code § 856. Among other things, a REIT must invest at least 75 percent of its total assets in real estate, derive at least 75 percent of its gross income as rents from real property, and distribute at least 90 percent of its taxable income to shareholders in the form of dividends. Because REITs must pay out almost all of their taxable income to shareholders, they generally provide reliable and significant dividends for investors. Currently, there are about 170 REIT companies trading on the major U.S. stock exchanges.

On a global basis, not only has the market capitalization of the publicly traded real estate grown, the number of countries adopting REIT structures has also increased significantly. Although listed real estate does not have to be in the form of an REIT, the trend reflects investors’ preferences for REIT-like vehicles, evidenced by the increased market capitalizations in countries where REIT structures already exist. The U.S. REIT experience has shown the potential benefits of including public real estate equity assets in a mixed-asset portfolio: enhanced returns, lower trading costs compared to direct real estate investment, liquidity, accessibility, and diversification. These lessons have spurred other countries, including the UK and Germany, to adopt REIT-like legislations.

Countries Adopting REIT Regimes [3]

Country REIT Legislation Enacted
United States 1960
Netherlands 1969
Australia 1971
Canada 1993
Belgium 1995
Turkey 1999
Japan 2000
South Korea 2001
Singapore 2002
France 2003
Taiwan 2003
Malaysia 2005
Thailand 2005
Dubai 2006
Israel 2006
Germany 2007
Italy 2007
United Kingdom 2007

Return Characteristics of Public and Private Real Estate

Historically, one of the most interesting questions for public and private equity real estate has been the relationship between these two markets in terms of risk and return characteristics.

The most well-known private real estate performance benchmarks around the world are the NCREIF (U.S.), the PCA (Australia), and the IPD indices in various European countries. Pubic real estate benchmarks include NAREIT (U.S.), S&P/ASX200 LPT Index (Australia), GPR (Global), and FTSE EPRA/NAREIT (Global). Taking these total return indices at face value, public and private real estate markets in the past have behaved differently, with public real estate showing greater volatility.

Comparison of Private and Public Real Estate Returns [4]

US UK Australia
Private Public Private Public Private Public
Mean Return 11.74 16.41 11.98 16.36 9.76 13.97
Standard Deviation 4.18 16.00 4.80 22.72 3.56 16.10

Furthermore, correlation studies of private and public real estate indices show that, while both have low correlations with bonds and large-cap stocks, they also have low correlations with each other, and in general, public real estate displays a higher correlation with small stocks.

Asset Class Correlations [5]

Bonds Large Stocks Small Stocks Public Real Estate Real Estate
Bonds 1.0
Large Stocks 0.25 1.0
Small Stocks 0.01 0.59 1.0
Public Real Estate 0.15 0.31 0.67 1.0
Real Estate -0.26 0.07 0.02 0.05 1.0

As for the portfolio diversification effects of publicly listed real estate securities, the private real estate portfolios with 10 percent mixes of REITs resulted in higher risk-adjusted returns for all three countries (see below). The results imply that a holding in U.S. REITs would lead to improvements in portfolio performance even if the optimal portfolio already contains private real estate.

Impact of Adding 10 percent U.S. REITs to Private Real Estate Portfolio[6]

US UK Australia
Private Mixed (10% REITs) Private Mixed (10% REITs) Private Mixed (10% REITs)
Mean Return 11.74 12.21 11.98 12.42 9.76 10.43
Standard Deviation 4.18 3.88 4.80 4.70 3.56 3.84
Sharpe Ratio 1.55 1.79 1.55 1.68 1.15 1.24

Several other studies show similar results. According to a portfolio diversification study performed by Ibbotson Associates in 2006,[7] adding REITs to a wide selection of diversified portfolios, from 1972 to 2005, enhanced risk-adjusted returns as compared with portfolios without REITs. Furthermore, research sponsored by the European Public Real Estate Association showed significant portfolio benefits to using real estate securities from six European countries.[8]

Despite these findings, however, investors should be aware that public and private real estate indices cannot be compared at face value due to the appraisal-based smoothing effects in private real estate and the leveraging effects in public real estate. For these reasons and more, the private and public real estate risk and return characteristics appear to be dissimilar at face value, although the underlying values of the properties are similar.

Appraisal Smoothing and Leveraging Effects

In the case of private commercial real estate, since market transactions are relatively infrequent, the standard practice is to use professional appraisals on a quarterly basis (or even less frequently) to derive market values. The appraised valuation data are then used to generate indices for the private real estate market. When the availability of price information is limited in the private real estate market, due to lack of trades or confidentiality of transactions, appraisers must make an assessment of value based on fundamental variables and must efficiently extract relevant information, while filtering out “noise” from the asset market. This process often leads to appraisal smoothing or appraisal lag. There is substantial empirical evidence documenting the existence of appraisal smoothing in the private real estate market.[9]

The existence of appraisal smoothing significantly reduces the usefulness of real estate rates of return series computed from unadjusted appraisal data, particularly because the variance measurement is artificially depressed. This type of smoothed series underestimates the riskiness of the real estate asset class and also distorts its correlations with the rates of returns of other assets.

On the other hand, the publicly listed real estate market does not suffer from appraisal smoothing; however, it does contain the effects of leveraging. While private commercial real estate values are measured on an all-equity basis, the returns generated by publicly listed real estate companies include the aggregated leveraging effects of these companies.

Because of these two crucial differences, public and private real estate indices cannot be easily compared at face value. Taking the private and public real estate performance benchmark indices for the U.S., UK, and Australian markets for a 10-year period and applying unsmoothing for private real estate and unlevering procedures for public real estate,[10] produces the following results:

Unsmoothed and Unleveraged Comparison of Private and Public Real Estate Markets[11]

These results support the finding in Pagliari et al[12] that when smoothing and leveraging differences are accounted for, the differences in the average returns and volatility of the private and public real estate performance indices are not statistically significant.

Price Discovery

In finance, “price discovery” refers to a process by which new and relevant information becomes incorporated into the market price of an asset. If there are many market participants and high volumes of trades, information is incorporated quickly into prices. If there is a lack of reliable information and a low volume of trades, there is inefficiency in the information flow, which leads to a market price that deviates from fundamental value.

Of particular interest in the nature of relationship between the private and public real estate markets is whether there is price discovery occurring between these two markets, after correcting for smoothing and leveraging effects. In other words, when two markets have a common component value (real estate) and these assets are traded in two different markets simultaneously (public and private markets), the important question is whether relevant price information is discovered first in the more informationally efficient market (public) and then transmitted to the less efficient market (private). This effect can be tested and evidenced empirically by positive lagged correlation in the returns across the two markets.

The result from the above study supports the finding in previous studies,[13] which indicates that, in the U.S. and UK property markets, the private real estate market contains some amount of predictability by the publicly listed property market, with the price information not fully transmitting to the private market for as much as a year. This effect of informational inefficiency appears to be strongest in the UK, followed by the U.S., and then Australia.

Conclusion

This article suggests several practical implications for investors. First, despite the widespread claim that publicly listed real estate offers unique return characteristics with portfolio diversification effects separate from private real estate, the difference in the risk and return characteristics between the private and public real estate markets are due to leveraging and appraisal smoothing effects. Second, from the risk-adjusted return perspective in the medium- to long-term, investment in public real estate can produce comparable average results as investment in private real estate, considering leverage and appraisal smoothing. Third, in the short- to medium-term, because the paths that the unadjusted indices take are sufficiently distinct from one another, broad index-level investments in the public real estate market can be used tactically to diversify investments in the private real estate market. Fourth, based on the evidence that the prices from the publicly listed real estate market lead and predict the prices in the private real estate market, for as much as a year or more (due to inefficient information flows between the two markets), there are potential arbitrage opportunities.

In recent years, the global real estate market has evolved as a distinct asset class that merits inclusion in the mixed-asset portfolio. This article highlights the differences and similarities between the public and private real estate risk and return characteristics. The results from the author’s study indicate that investments in publicly listed real estate companies, in particular, can create distinct opportunities for enhanced risk-adjusted portfolio returns for global investors.


[1] UBS Global Asset Management.

[2] FTSE/NAREIT/EPRA Global Real Estate Index.

[3] Updated from EPRA 2004 REIT Survey, UBS, Cohen & Steers.

[4] NAREIT, NACREIF, IPD, GPR, PCA, 19952005.

[5] Lehman Aggregate Bonds Index, S&P 500 Index, Ibbotson Small Stock Index, NAREIT, NCREIF Property Index, 19782005.

[6] NAREIT, NACREIF, IPD, GPR, PCA, 19952005.

[7] Ibbotson Associates, “Portfolio Diversification Through REITs,” research presentation, sponsored by NAREIT, 2006.

[8] G. Newell, “Diversification Benefits of European and Global Property Stocks,” EPRA, research report, 2003.

[9] R. Barkham, D. Geltner, “Price Discovery in American and British Property Markets,” Real Estate Economics, 23, no. 1 (1995): 2144; J. Clayton, D. Geltner, S. Hamilton, “Smoothing in Commercial Property Appraisals: Evidence from Individual Appraisals,” Real Estate Economics, 29, no. 3 (2001): 337360; J. Fisher, D. Geltner, “De-Lagging the NCREIF Index: Transaction Prices and Reverse-Engineering,” Real Estate Finance, 17, no. 1 (2000): 722.

[10] R. Barkham, D. Geltner, “Price Discovery in American and British Property Markets,” Real Estate Economics, 23, no. 1 (1995): 2144.

[11] NCREIF, NAREIT, IPD, GPR, PCA, U.S. Treasury, Reserve Bank of Australia, Barclays Capital, 19942005.

[12] J. Pagliari, K. Scherer, R. Monopoli, “Public Versus Private Real Estate Equities: A More Refined, Long-Term Comparison,” Real Estate Economics, 33,no. 1, (2005/3): 147187.

[13] J. Gyourko, D.B. Keim, “What Does the Stock Market Tell Us about Real Estate Returns?” Journal of the American Real Estate and Urban Economics Association, 20, no. 3 (1992): 457486; F.C.N. Myer, J.R. Webb, “Return Properties of Equity REITs, Common Stocks, and Commercial Real Estate: A Comparison,” Journal of Real Estate Research, 8, no. 1 (1993): 87106; R. Barkham, D. Geltner,” Price Discovery in American and British Property Markets,” Real Estate Economics, 23, no. 1 (1995): 2144. (link no longer accessible).

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Moral Markets by Paul J. Zak, (Ed.)

Moral Markets: The Critical Role of Values in the Economy

By Paul J. Zak (Ed.)
Princeton University Press, 2008

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5 stars: Stop what you're doing and read this book!Moral Markets is a collection of essays based on the premise that markets are driven by virtuosity, an ambitious argument in today’s climate of market distrust. The authors’ goal is to raise the awareness of market stakeholders, a category that includes almost everyone, that markets are “good” today, and have been throughout time. By no means is this an “airport” book on management; the reader is challenged to engage in a profound study of human behavior and values.

Moral Markets is edited by Paul Zak of Claremont Graduate University, who is known for his work in neuroeconomics, a transdisciplinary study of how decision making, risk, and trust produce good economic outcomes. The book is organized into five parts: Philosophical Foundations of Values; Nonhuman Origins of Values; The Evolution of Values in Society; Values and the Law; and Values and the Economy.

We are reminded early on that “moral markets” that is, economies where exchange is fair, good, truthful, efficient, and productive are really communities of individuals whose practice of personal responsibility has proven to yield the best possible outcome for society at large. The takeaway is that for the individual, the good life translates to the good life of the community, and it is fueled by individual achievement through the maximization of talents. The authors affirm that moral markets are not only the place where society participates in good exchange, but they also serve as a means for individuals to derive purpose from their life endeavors. They write, “Meaningful human activity is that which intends the good rather than stumbling over it on the way to merely competitive or selfish goals, and the predictable outcome of such behavior is not the mysterious result of an invisible hand but of our own good intentions, amply rewarded.”

Economies ebb and flow because of traditional business cycles. These same economies can shutter and collapse when the morality of their markets is compromised this phenomenon is more evident today than it has been in decades. The future of the economy does not hinge on a dose of public policy or even an infusion of morality. Instead, as Moral Markets asserts, we need to reevaluate the entire spectrum of values and virtues, from the core of the individual to the soul of the society. Moral Markets provides the serious student of business, government, and society with the necessary intellectual tools to reengineer their knowledge and practice of virtue, and perhaps enlighten them on why and how “goodness” ultimately serves society.

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The Book Corner

Featured in this issue:

The Triple Bottom Line

By Andrew W. Savitz with Karl Weber

Jossey-Bass, 2006

Recommended by Rick Hesse, DSc, Professor of Decision Sciences

I recommend The Triple Bottom Line for anyone interested in running or being part of a sustainable organization. The triple bottom line is a concept that emphasizes economic measurements, environmental impact, and social responsibility. Some have dubbed it Profit, People, Planet. This book gives many good illustrations of successful and unsuccessful company strategies and carefully explains each part of the triple bottom line phenomenon.

Focusing solely on profits can backfire if a company drains its resources, both natural and human. Over 2200 CEOs have signed the UN Global Compact, which encompasses human rights, labor standards, environment, and anti-corruption, so if your company is not involved, your competitors certainly are. Furthermore, such endorsement does not affect just CEOs; every manager and business function needs to be involved. Approximately 3000 companies around the world voluntarily publish reports on environmental, social, or sustainability issues. As proof that it pays to be socially and environmentally conscious, the Dow Jones Sustainability Index (DJSI) and the FTSE4 Good Indexes of these companies have also outperformed various market indices.

The authors provide a good historical perspective of companies and the factors that are pressing modern companies to be more socially responsible. In a freer, more interdependent and wired world, companies have more opportunities and threats than ever before.

Sustainability is not about being social do-gooders or philanthropists. It is a matter of finding the commonality between doing good and running businesses well. The book examines initiatives such as Toyota’s hybrid automobiles, GE’s Ecomagination projects, and PepsiCo’s development of drinks for healthier lifestyles. Such companies are consciously seeking to integrate profitable alternatives with social benefits.

The book examines three ways to sustain businesses:

  1. Protect the business: Reduce the risk of harm to customers, employees, and the community.
  2. Run the business: Reduce costs and the amount of resources needed, including energy and unsustainable inputs. For example, by raising salaries 3 to 5 percent over the industry average, Wegeman’s grocery has cut its labor costs by 13 percent of revenues, resulting in provision of unemployment insurance, lower turnover, and reduction of lost productivity.
  3. Grow the business: Find new markets, new products and services and improve reputation and market share. Listening carefully, even to critics, and learning to partner with your business community and suppliers can pay big benefits, as Wal-Mart is slowly learning.

Savitz and Weber also do a credible job of looking at the backlash and criticism of the concept of sustainability. They acknowledge that companies do not always start with a problem-free environment, so the authors therefore devote time to showing how companies have turned problems into opportunities. For example, Nike finally turned around its problems related to using child labor, and the fast-food industry is currently facing the rising public concern about obesity linked to consumption of convenience foods.

Finally, this book explains how to launch your own business’s sustainability program and manage stakeholder engagement. Developing measures and reporting results completes the cycle of creating a culture of sustainability. In short, I highly recommend this book.

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A Leader’s Legacy

By James Kouzes and Barry Posner

Jossey-Bass, 2006

Recommended by Ann E. Feyerherm, PhD, Director of MSOD Program

The primary organizing scheme of this book is built around the question “What difference do I want to make?” This question requires not only self-knowledge but also a deep regard for others. Legacies are about the world which others step into when a leader steps away. The provocative essays are organized by four themes; Significance, Relationships, Aspirations and Courage.

This modest volume is full of thoughtful advice for new and experienced leaders. Even though you could argue with some of the claims (for example, it is better to be liked than respected), there will be invitations to examine your own leadership style and philosophies. It might even be reassuring—the “tough truth” about leading is that “sometimes you hurt others and sometimes you get hurt.” The authors are not “in your face” about your own leadership style, rather they are suggestive of behaviors and beliefs worth pondering. There are no “skill building” exercises or practice frameworks. There are several stories of the authors or respected peers and leaders to jog your own memories.

A useful mindset while reading the book is one of curiosity. A journal by one’s side to jot down reactions and your own stories and learning would be a way to approach this book. It could also be a companion to any leadership development program; perhaps a chapter a week for conversation between members of a leadership team or a pair in a boss/subordinate role.

If you are a follower of Kouzes’ and Posner’s earlier works on leadership, you will note several of their themes echoed in this volume—the importance of trust, of forward-thinking, of listening to and speaking from the heart, of courage, and that leadership is everywhere, not just by virtue of title. These are themes worth hearing again, and cast in the light of leadership legacy, take on new meaning.

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L.L. Bean: The Making of an American Icon

By Leon Gorman

Harvard Business School Press, 2006

Recommended by Sam Farry, MBA, Adjunct Faculty of Applied Behavioral Science

It would be difficult to find a more relevant management topic than values based management. In the wake of HP, WorldCom and Enron, everyone is talking about ethics. Often treated in an overly simplistic manner, ethics is much more than merely “doing the right thing.” Values cut both broad and deep. They are connected to all aspects of an organization. You have to grow with and nurture them.

This book is a case study of L.L. Bean, of Freeport, Maine, whose core business is catalog sales, a company that has struggled with and been managed by explicit, straightforward values. An extremely successful company for nearly 100 years, Bean has addressed key issues and has consistently questioned and redefined itself in the face of needed change with regard to establishing an authentic corporate identity, building and explicating its brand, continuously improving service and value for customers, and maintaining and accelerating growth.

L.L. Bean formulated a set of values that has endured to the present time: honesty, self reliance, thrift, and love of the out-of-doors.

  • To sell fully tested, high quality products of the best functional value;
  • To provide superior and personal customer service backed by a 100 percent satisfaction guarantee;
  • To write honest, straightforward catalog and advertising copy that builds trust and mutual respect in customers;
  • To sell through a catalog channel that can reach a national market from Maine and its outdoor heritage.

The book’s author, Leon Gorman, the grandson of L.L. Bean and the company’s longtime president, provides an intimate view of the interdependence of a key leader and his company as they strive continuously to grow yet hue to standards that simultaneously respect all key stakeholders: customers, employees, vendors, owners, and community alike. In his commitment to maintaining the company’s integrity, purpose and growth, Gorman’s development as a leader progressed from central entrepreneur to professional manager to a team-oriented strategist who helped spell out a “platform for growth” to facilitate management succession.

This book spells out how the relevance of trends such as Theory Y, Total Quality Management (TQM), Process Engineering, Structural Redesign, and Strategic Management have emerged at L.L. Bean from the ongoing fluctuating needs of the organization derived from measurable data and from the insights of its president and employees in their attempts to gain the most from major change initiatives.

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Taking Advice: How Leaders Get Good Counsel and Use It Wisely

By Dan Ciampa

Harvard Business School Press, 2006

Recommended by Jeffrey Schieberl, JD, MBA, Practitioner Faculty of Business Law

Dan Ciampa’s new book addresses the assertion that how to accept advice and utilize it effectively has not been given the attention that it warrants. He has been on the giving advice side of the giving/receiving advice equation for quite some time. His experience has been that there are very few “smart clients”—that is, clients that understand how to utilize and optimize the benefits of advice that they received. Mr. Ciampa clearly states that the “core premise” of his book is that contemporary leaders or those “in charge” must be “shrewder and more discerning advice takers.” It is his view that this is important especially during times of change.

In the Preface the author tracks the history of management consulting including its transformation from a profession to a business. He explores why even experienced leaders need advice as well as what he refers to as the “help paradox.” His assessment of leaders who seek out help is truly refreshing in its candor. Inadequacies as to the advice given correlates well with the acknowledgment that those who are giving advice must do a better job.

Fundamentally, Ciampa considers advice taking as a skill. The author offers the reader an intriguing, viable framework for taking advice. In addition, he considers the types of advice and kinds of advisors in a practical understandable manner. The attitudes and behaviors of effective advice takers are also discussed. Lastly, the book characterizes listening as the “master skill” and explores its key success factors.

I found this book to be thoughtfully organized, concise and substantive. It offers invaluable insight for contemporary leaders relative to the skill of seeking, taking, assessing, and applying advice.

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The Kindness Revolution: The Company-Wide Culture Shift That Inspires Phenomenal Customer Service

By Ed Horrell

AMACOM, 2006

Recommended by William Bleuel, PhD, Professor of Decision Sciences

I really liked this book. I could relate to almost all of the examples in the book and the author’s approach to customer service. The two aspects of the book that were most appealing to me were (1) the examples of real companies who have demonstrated remarkable success with much of the success founded on excellence in customer service and (2) the perspective of bringing kindness into the business environment.

I was so taken by the concept that I thought I would go out of my way to offer some extra kindness to everyone I dealt with for a short period of time to see if kindness really made a difference. It did—not a surprise! The results of my very brief and non-statistically valid experiment were both a personal sense of well being while treating every one with kindness and receiving a very warm response in return in every case.

The book starts out with a discussion of owning customers and the value that comes from owning customers. The author makes the point that when you own a customer they are not vulnerable to competition. The key ingredient to losing customers, according to the author, is indifference. On the other hand, the key to owning customers is superior customer service.

Seeking companies that have superior customer service, the author found that all of them are well known and that each practice kindness in one way or another. The conclusions that the author reached are that superior company performance is achieved by superior customer service and that superior customer service begins at the top of the organization.

In line with Pepperdine’s approach to a values-oriented curriculum for management, the author concludes “that values play the most significant role in determining how employees and customers are treated in any organization.”

The book is an easy read with 185 pages and can be completed in an evening of casual reading.

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The Business Impact of Change Management

If your company is considering a major change project, anything from a software implementation to a merger/acquisition, this article may help you as it focuses on the results of studies (over the last ten years) on organizational change management (OCM) and its impact on obtaining a high project return on investment (ROI.)

What advice would you give a friend or business associate if they said to you, “I just heard about this great investment and I am really excited about it because it has so much potential. In order to get involved, I have to put a lot of money down. And the only negative seems to be that the return on investment (ROI) is zero.”

Seeing the absurdity of this potential opportunity, you would probably tell them not to invest. This scenario, as preposterous as it might seem at first, actually illustrates a common phenomenon or trend that is happening to companies worldwide.

What is this trend? Companies are spending millions for business improvement projects whose costs will far out weigh their realized benefits. At first glance this might even seem difficult to believe much less be accurate. That is, until you begin to look at the evidence. In this article the authors look at over ten years of independent studies that show the average rate of return on all large project implementations is negative. The review of the studies begins with the McKinsey study, in which the projects of over 40 companies were investigated. From the results of this and the other studies, this article will begin an inquiry that will help to answer the following questions:

  1. Why are so many companies making the same mistake?
  2. What could companies who do not want to fall into this trap do differently?

The Common Project Success Denominator

The McKinsey study examined many project variables and in particular, the effect of an Organizational Change Management (OCM) program on a project’s ROI. The study showed the ROI was:

  • 143 percent when an excellent OCM program was part of the initiative;
  • 35 percent when there was a poor OCM program or no program.

What do those these results mean? A 143 percent ROI means that for every dollar spent on the project the company is gaining 43 cents. On the other hand, a 35 percent ROI means that for every dollar spent they are losing 65 cents.

The 11 most unsuccessful companies in the McKinsey study had poor change management, which showed up as the following:

  • Lack of commitment and follow through by senior executives;
  • Defective project management skills among middle managers;
  • Lack of training of and confusion among frontline employees.

The 11 most successful companies in the study had excellent OCM programs:

  • Senior and middle managers and frontline employees were all involved;
  • Everyone’s responsibilities were clear;
  • Reasons for the project were understood and accepted throughout the organization.

Measuring A Project’s Return on Investment

For a project to get approved, there has to be a compelling business case. A business case looks at the cost of improvement project and weighs that against the benefits the company will gain. If the benefits outweigh the costs, the ROI is positive and thus the project is approved.

The formula for calculating Return on Investment (ROI)[2] is:

The Benefit Of Project is based on the project’s purpose. The purpose could range from increasing sales to reducing the cost of handling customers. One generally estimates that making certain changes to the business, installing new software, making processes more efficient, etc., will yield a particular project benefit that has a dollar amount associated with it.

The Project Cost includes hard costs, such as hardware and software, as well as what is sometimes termed soft costs. While the paradigm for many accounting systems has not shifted, the research also shows that these so-called soft costs are actually as or more important to a project’s success than the hard costs. As a result, these costs should no longer be termed soft costs because they have a defined, bottom-line effect.

Soft costs, for example, can include items such as the salaries for the time period people are on the improvement project. Salaries are important to include because the time employees spend on the improvement project should be seen as a cost to the organization. The longer the project takes, the longer employees will be away from their primary job whether it is sales, marketing or manufacturing. If they are working on an improvement project, they cannot spend the same amount of time they normally would on their regular job.

If a project experiences delays due to politics, lack of planning, unforeseen issues, or other reasons, as is often the case, the overall cost of the project increases because the time to implement the project has gone beyond the original estimate. As the costs increase, any potential benefit starts to be chipped away and in some cases more money is spent on the improvement than the improvement ends up providing. An organization that does not consider soft costs as hard costs is putting the organization at a huge financial risk because the project’s scope, timeline and therefore budget increase (Figure 1). Within this context of project ROI, the following section will examine more studies that have evaluated the success or failure of project implementations and their ROIs. Again, in this context ROI is taken to mean that the project provides more financial benefit than it costs the organization in a reasonable time period.


Figure 1: Increased scope, timeline, and budget put an organization at risk because they erode the project’s potential benefits.

The Survey Says: No Change Management Means Poor Project Results

Over the past 20 years of implementing projects, the authors have collected our own data and case studies as well as collected research from independent groups. Disappointing implementation results are being reported in all kinds of projects: Customer Relationship Management (CRM), Contact Centers, Enterprise Resource Planning (ERP), Share Services, Supply Chain, mergers and acquisitions, new pricing strategies, cost reduction initiatives, and including changes in a university’s method of recording hourly wages. The following examples show the trend that no project is immune to ROI failure, regardless of who conducts the study.

Results of a study by Boston Consulting Group that examined 100 large companies found the following:

  • 52 percent reported achieving their business goals
  • 37 percent could point to a tangible financial impact for their projects[3]

A study entitled Six Ways IT Projects Fail[4] published in Darwin (2001) revealed the reasons were due to the following:

  1. Lack of executive sponsorship
  2. Lack of early stakeholder input
  3. Poorly defined or changing specs
  4. Unrealistic expectations
  5. Uncooperative business partners
  6. Poor or dishonest communication

A study published in DestinationCRM.com (August 2003) entitled Six Barriers to CRM Project Success[5] showed that the failure of CRM projects was due to the following:

  • Lack of guidance
  • Integration woes
  • No long-term strategy
  • Dirty data
  • Lack of employee buy-in
  • No accountability

In 2004, a study entitled Software Disasters Are Often People Problems[6] was published on CNN.com. This study showed that at that time serious, preventable errors were related to poor management of the people part of the project. For example:

  • Passengers wait at McCarran International Airport in Las Vegas on September 14 for flights delayed by a communications system failure.
  • New software at Hewlett-Packard Co. was supposed to get orders in and out the door faster at the computer giant. Instead, a botched deployment cut into earnings in a big way in August and executives got fired.
  • Retailer Ross Stores Inc.’s profits plummeted 40 percent after a merchandise-tracking system failed.

The study’s conclusion was that even as systems grow more complicated, failures are related less to technical malfunctions and more due to bad management, communication, or training during project implementation.

Gartner’s industry analysts report a staggering 55 to 70 percent of CRM projects fail to meet their objectives. In Bain and Company’s survey of 400 executives, 20 percent of respondents felt their CRM initiatives actually damaged customer relationships.[7] When the objective is to build strong relationships with customers, why is this goal eluding so many companies especially when they are spending millions and sometimes billions to reach it?

What Is Failing?

In contrast to these studies about the people part of business, a Forrester Research study showed that companies implementing, for instance, a new technology like CRM, are satisfied with the actual software application’s functionality and capability.[8]

So, if the technology is not failing, what is? A study done by ProSci, a recognized leader in change management research, again pointed to the ability of the organization to efficiently and effectively manage the changes the project was bringing about in the organization.[9] The ProSci results showed that a project’s greatest success factors are the following:

  1. Effective and strong executive sponsorship
  2. Buy-in from front line managers and employees
  3. Exceptional teams
  4. Continuous and targeted communication
  5. Planned and organized approach

The ProSci study results also showed that a project’s greatest obstacle factors are:

  1. Employee resistance at all levels (Surprisingly, the effectiveness or correctness of the actual business solution, process, or system changes was cited only 5 times in over 200 responses.)
  2. Middle-management resistance
  3. Poor executive sponsorship
  4. Limited time, budget, and resources
  5. Corporate inertia and politics

Another study by AMR Research, a firm whose analysts focus on independent, leading-edge research that bridges the gap between business and their technology solutions, found companies that had successful software implementations spent 10 to 15 percent of their project budget on OCM.[10] All of the success criteria found in each of these studies is what comprises an OCM program that increases a project’s ROI.

Organizational Change Management (OCM)

These studies show that many different analysts and research companies have found very similar results. Clearly, continuing to deploy projects without change management is not a profitable way to do business. The purpose of OCM is to mitigate the risks of a project, including costs, scheduling, and performance. OCM does this by facilitating greater economic value faster by effectively developing, deploying, and aligning the company’s assets for a given project.

As businesses face shrinking margins, global competition, and the need to deliver on loyalty-creating customer experiences, they will also face the need to change the way they do business. As companies evaluate improvement projects they should consider the financial contribution that OCM makes.

While there has been some skepticism on behalf of the business community to accept OCM as a necessary business discipline, as seen in the McKinsey, ProSci, and AMR studies, as well as from the authors’ collective experiences and research at Hitachi Consulting,[11] clearly some OCM methodologies work. In a future article the authors will address why not all OCM methodologies produce the high rate of return for the money spent on them, and how OCM actually reduces the risk of a project and keeps it on schedule with regard to budget and scope.


[1] “Change Management That Pays,” McKinsey Quarterly, 2002.

[2] Integrating, People, Process and Technology. by Anton, Petouhoff and Schwartz, Santa Maria, CA: The Anton Press, 2003.

[3] Boston Consulting Group. (2003). Research study. In Integrating, People, Process and Technology. by Anton, Petouhoff and Schwartz, Santa Maria, CA: The Anton Press, 2003.

[4] Ulfelder, Steve. (2001). “Six Ways I.T. Projects Fail And How You Can Avoid Them.” Darwin magazine. Retrieved June 2001, http://www.darwinmag.com/read/060101/dirty.html.

[5] Myron, David. (2003). “6 Barriers to CRM Success And How to Overcome Them.” DestinationCRM.com, August. Retrieved from http://www.destinationcrm.com/articles/default.asp?articleid=3316.

[6] “Software Disasters Are Often People Problems.” Retrieved Tuesday, October 5th, 2004, CNN.com.

[7] Research study by Bain Consulting Group. Integrating, People, Process and Technology. by Anton, Petouhoff and Schwartz, Santa Maria, CA: The Anton Press.

[8] Ibid. Research study by Forrester Group.

[9] ProSci. (2003). “Best Practices in Change Management.”

[10] AMR Research Report, 2003.

[11] Change Management Case Studies, Hitachi Consulting, http://www.hitachiconsulting.com/page.cfm?SID=2&ID=searchresults&searchString=change+management.

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