Executive Q&A: Management Roundtable

Bob Tippee, Editor, Oil & Gas Journal, served as moderator Sept. 18 at a management roundtable on risk-based decision analysis in the exploration & production (E&P) business. He brought together experts on the topic. OGJ Online Oil & Gas Writer Karen Broyles sat in on the discussion.

Bob Tippee, Editor, Oil & Gas Journal, served as moderator Sept. 18 at a management roundtable on risk-based decision analysis in the exploration & production (E&P) business. He brought together experts on the topic. They included Jerry Brashear, Managing Director, The Brashear Group LLC; John Campbell, President, International Risk Management; Truett Enloe, Manager, Strategic Planning, Spirit Energy 76, Unocal Corp.; Craig Narum, System Development Director, Business Management Systems, Landmark Graphics Corp.; Richard Rowe, Engineering Manager, Anadarko Petroleum Corp.; Michael Walls, Professor, Colorado School of Mines. OGJ Online Oil & Gas Writer Karen Broyles sat in on the discussion between Tippee and the industry experts.

At the beginning of the meeting, Tippee presented the roundtable members with a statement to serve as the launchpad and centerpiece of the discussion. �The modern exploration and production business returns capital at average rates below those of industries with which it must compete for capital," the statement read. "What is worse, it is a characteristically high-risk business in which uncertainty about commodity values compounds the exposure of investments to unpleasant�if not ruinous�surprise."

"Able to manage neither the prices of crude oil and natural gas nor the volume of hydrocarbons emplaced by nature, E&P managers face growing pressure to manage those dimensions of their investments that are within their control�or that are at least measurable. A number of statistical methods are available for evaluating physical and financial investment parameters in terms of their probabilities for success and for combining project evaluations into risk-weighted assessments of whole portfolios. The rapid development of computing power and software programs now makes applications of these calculation-intensive methods practical and economic for all but the smallest E&P companies.

Theoretically, the availability of these tools should improve industry decision-making and, in turn, improve rates of return of and on capital invested in exploration and production over time. Our purpose here today is to examine validity of these assertions, to identify hurdles to progress, and to see where current trends will lead the industry.�

Tippee: Who would like to start?

Brashear: I think that the questions it raises are: "What are the barriers?" I think there are four broad classes of barriers, all of which have solutions and some of which have been started. The first is that the lack of support from the highest level has been an impediment across all the companies with whom we've talked. Even those that have endorsed some elements of risk and portfolio and real options and so forth haven't carried the package the whole way through. The second is the organizational silos. Even if there is "top down" support, just getting the organizational units to work together in creating a corporate, E&P-wide portfolio is difficult. The third is that tools have up until recently not been adequate. But some of the modern tools are very (capable) to do the job and are becoming better all the time. And the fourth one, which I think may be the most difficult to deal with, is the oversimplification of some of the problems. It is necessary always in analysis to simplify to one extent or another, but some of the simplifications that are in use today, widely, I think have the consequence of overstating expected values, severely understating risk, and suggesting a misallocation of capital.

Narum: There�s a lot of other reasons why the returns are low�higher costs, more complex reservoirs, etc. But I think that, as a group, we need to definitively say that there�s a link between poor uncertainty analysis and the reason why their returns are low.

Rowe: One of the significant causes of less-than-stellar returns is that the companies that we represent and do business with in this room were previously focused on the United States. Now we�re stepping off into other countries and looking at far more hostile environments. As well as the geologic risk, there is the surface risk, the aboveground risks, and before, those risks had been taken care of rather qualitatively by just saying, "Well, we need a higher threshold return." I don�t know that that�s appropriate anymore, because there�s are all kinds of aboveground risks that (can) be quantified, so that we have a better understanding of what is the impact of the a currency risk or the uncertainty of project scheduling�delays�on rates of return. The host countries, these days, are getting very sophisticated and they�re not really interested in having a US company or a company from any other country come in and get very wealthy at their expense. And so, they also are very sophisticated and we need to be as sophisticated as well in order to better understand what the risks and the uncertainties are so that we can structure an agreement with them that�s mutually beneficial.

Tippee: Before we go on, are you making a distinction between uncertainty and risk here in risk analysis and uncertainty analysis? Could you elaborate on that, just so that we agree on the terms?

Walls: Uncertainty is really a subset of risk. You can�t have a risky situation without having uncertainty and without having some potential for loss. That loss can be a relative loss, it doesn�t have to be a negative NPV (net present value)�but you can have uncertainty without having a risky situation, if you are, for instance, not exposed.

Campbell: I think it�s really interesting from the standpoint of actually investing money because once (the companies) do form a risk assessment, you can use the reduction in that number as a value of collecting information�whether it�s extended well testing, 3D seismic. But you need a formal risk system to understand what you�re reducing. We may not be able to show that there�s actually any money gained, but lowering risk is just as valuable as adding money to the treasury.

Rowe: The diversification (between oil and gas commodity prices) gives you options, because if one product price is down�if oil price takes a tumble�and gas prices are relatively strong and you have an inventory of gas projects, you can switch over and drill what�s hot.

Walls: Oil and gas commodity risks, for example, is clearly one of these surface risks that the companies (face). This notion of doing risk analysis is not new at all in the oil and gas industry. We�re probably one of the most advanced industries in terms of doing risk analysis, (though) the techniques we used 25 years ago or 30 years ago are somewhat primitive compared to what we can do now. The advances in technology allow us to model more complex problems, which gives us a lot more insight to decision making. But one of the hurdles that we�ve got to get over is this notion of getting managers�especially senior managers�to think more probabilistically. And, as easy as that may sound, it�s a very difficult cultural change in the way organizations operate. Because we have our own cognitive limitations to how much data we can process, it�s more natural and more comfortable for us to focus on, "What�s the NPV?" or "What�s the rate of return?" When, in fact, that doesn�t really tell you the whole picture about either a single asset evaluation or a whole portfolio of assets. I think if we ever can get over that hurdle, then we are going to be making great strides in terms of using a lot of techniques that are out there.

Campbell: It's a continuation of history in the sense that where I see the most horrible risk assessment is in exploration. But on the engineering side, when they do a cost test and order a size for a pump or compressor, it�s one number and it never even occurs to anybody that maybe that�s a little bit risky. Most of the people who are play derivatives say, "We can lock that (price) in for 8 or 10 years," but a lot of the senior management looks at you and says, "Oh, we�re a price taker on those categories and we don�t even need to be bothered with that." I think that is a classic example that they don�t even want to talk about handling risk in those areas. The risk firms maintain that they can take out the risk of almost every aspect of every project. But one of the biggest problems they complain about is that they can�t get in the door to talk to people about (reducing risk).

Tippee: Has everybody had a chance to respond to the four points brought up earlier? I think we�re hearing pretty clearly that senior management resistance to these methods is a big hurdle. Do we want to identify something else at this point?

Campbell: It is the willingness of people to adopt a new thought process, a new decision-making process that�s the problem. It�s senior management, in part, but even at the business unit asset level, there�s so much variation in what people are willing to talk about and consider.

Narum:The whole underlying concept of uncertainty analysis implies that you�ve looked at the details of a very expensive investment decision and you�ve studied the drivers. The fact that you've got an analysis adds value because the quality behind the decision and the confidence that you have when you go to the shareholders and say, "Here�s what my earnings projection is" and "Here�s what my production forecast is". I think there are studies starting to show (the correlation) between companies with good solid, robust decision making and solid performance and reduced volatility of the earning stream. That�s the kind of thing that needs to come out before this really starts to take hold.

Rowe: Perhaps the companies that are sophisticated enough to use these decision-analysis tools, have also figured out a way to create value. It�s one thing to use good decision analysis tools on mediocre projects, but I�m not sure they would be able to have sterling projects and be able to slip by on the decision-making process.

Tippee: When I think of these tools, I think of Monte Carlo analysis, expected monetary value, portfolio management theory, decision tree modeling, real options evaluations. These things have been around for at least a while. Is it fair to say is that what�s making this possible now is the computing power that we have�we can crunch the numbers behind these theories�and, are there any other of those tools that are just coming aboard that aren�t on that list?

Rowe: I think that�s exactly right. Our industry started using discounted cash flow in the late 1950s, early 1960s, but you can do that on a ledger sheet. It was pretty easy to determine what�s the discount factor to multiply each year�s cash flow to get the present worth. But now we�re looking at Monte Carlo simulation where we do the same calculation, but we do it a thousand times. So, you really do need to have the computational horsepower to do that calculation quickly and understand the interrelationships between ultimate recovery and numbers of wells and capital.

Brashear: I think that we�ve come a long way because of the computer. One example is that we are beginning to play with aboveground scenario modeling in computational ways that we never did before. Before, we just made up one or two scenarios and said, "What would happen if?" Today, we can actually simulate whole markets. Secondly, the embedding of one tool within another is an (example of the progress we've made). You have to have some kind of a high-quality risk analysis to even think about portfolio analysis. You have to have to have some kind of high-quality risk analysis to even think about real options analysis. If you want to put real options into portfolios, we still haven�t solved that problem, but we will, and we�re at the edge of it.

Narum: One of the things we can do to help that is taking that data and simplifying the view of the data into logical formats so that decision-makers can actually use the data to make a decision.

Campbell: The biggest advances are going to be made is in the visualization of what these portfolios look like. People are playing around with doing a little 3D type of mode so they can see�if you do this portfolio, what happens and using the same tool technologies they do for the exploration side.

Campbell: Most of the major companies had programs that did risk assessment and optimization on the mainframe, but they discarded them when they went from the mainframe to the PC. Another problem was that only very specialized people could use these programs, because it was line item coding. And now, with a graphical interface, you can take any educated person and discipline and take them through the entire process fairly easily and fairly quickly. So, it�s the ease of use that has progressed as much as the actual tools.

Narum: It seems like if we can integrate the technical tools more with the economic tools into more of a dynamic simulation model to look at the physics of the reservoir properties, and then we linked information about those properties dynamically in a stochastic way to the economic model. We could then optimize the entire solution with the technical end of the business.

Tippee: Could somebody give a quick distinction between stochastic and deterministic?

Walls: Deterministic methodologies assume you know all the future outcomes and you�re optimizing on those outcomes. Stochastic means you�re characterizing the uncertainty around those outcomes and optimizing on those uncertainties.

Tippee: Twice now I�ve heard two different panelists talk about "thinking differently." So, let�s assume I�m president of X oil company and I�ve been thinking this way all my career and it�s gotten me this far�why should I think differently and what do you mean when you tell me that?

Campbell: ...I was working my way through (graduate school) doing bank feasibility studies. We did one in eastern Oklahoma and this guy got out of an old beat-up pickup truck�turns out to be Sam Walton�and we talked about the issues and what had to be done. He said, "Well, if you�re so smart, why aren�t you rich?" First of all, I was a graduate student, so I wasn�t rich. He said, "Why should I adopt some of these ideas and these concepts?" And I said that it�s not so much that you�re rich, but think how much richer you would have been if you had avoided all of those mistakes that held you back. And he said, "You know, I did, I made a lot of mistakes. Hopefully I could have done a better job if I�d used some of these tools and ideas." So, just because I�m successful doesn�t mean I couldn�t have been more successful or could be more successful in the future if I didn�t think differently about how I do things.

Walls: The dilemma here is that you have senior managers who have been reasonably successful, or they wouldn�t be in the position that they�re in today, who have moved up in organization and who, perhaps, might be getting close to retirement, have become more risk-averse to taking on new ideas. On the other hand, what�s pushing against them is the competitive environment that�s becoming much more competitive. There are incentives for them to begin to think about new ways of thinking about the world�all they have to do is look at the recent consolidations and it is oftentimes a bit of a wake-up call. It�s a question of whether or not that push to really think differently about their decision-making is strong enough to overcome whatever aversion they have to change.

Tippee: How would you characterize that aversion?

Brashear: Part of it is just that the pace at the executive level is so high, that the opportunity to slow down and learn these methods and think through the recommendations is difficult. It�s hard for them to have that time.

Rowe: If people not acquainted with those concepts, all of a sudden you�re speaking Greek to them. As an advocate of the process, it�s incumbent upon us to explain it to them in terms that they understand.

Tippee: We�ve already alluded to this, but this all develops as workflows are changing, and we�re managing technical things with assets teams, interdisciplinary teams. Where does this plug into that and what difficulties are there? I can see a utopia where it all gets done on one computer, but I see a lot of trouble between now and then.

Rowe: Let me answer that from a little bit different perspective. We were talking about advancements in various economic decisions�analysis tools vs. something tangible, like horizontal drilling, fracture stimulation, or 3D seismic interpretation�and pointing out something said before about organizational silos. Some of the things that are more tangible can be developed in those silos and implemented because it doesn�t require the entire organization. The results are pretty quick and they�re measured and you can determine whether you�re doing some good or not very quickly. The stuff that we�re talking about is far more abstract�you don�t know what the present value is for quite some time and it�s arguable as to how you actually measure it. Further, you need decisionmakers across the organization [agreeing to] implement something like portfolio optimization. One of those guys could say, "Yea, that�s really good," until you cut out their favorite project. (You have to be sure) that people can see into the process and know what�s going on.

Narum: One of the things that we found with an implementation of a major company was that once we introduced the tools, and provided the process to do better uncertainty analysis, 75% of the people in our survey after the first year said it actually improved their own personal economic knowledge. It improved the entire asset management process, because they could understand the drivers and what was contributing to the value of the project.

Campbell: I think the other thing you get is consistency. The (asset management process) tends to promote an organized, coherent pattern for creating databases. By getting people to standardize, I think it will expedite the evaluation analysis process many times more than the cost and time to put it in.

Walls: It�s pretty easy for us to articulate what all the advantages are to the asset management teams incorporating these kinds of projects. The harder thing for us to describe is why there is so much... reluctance to accept it. We probably don�t understand as well as we should how to actually get companies to really want to use embrace these techniques, and that�s something that really needs to be explored.

Rowe: I think it gets back to something said earlier that the tools you use are related entirely to the nature of your business. Some companies don�t take all that much risk. Other companies focused on exploration, who make their living by taking (calculated) risk, need to have the tools at their disposal to better quantify those risks. Does Monte Carlo simulation need to be run on any and every business opportunity? Of course not. Some of these opportunities we know an awful lot about the issues, whether it�s the ultimate recovery, the cost. But a lot of those things we can manage as single-point estimates and make very valid decisions. That�s really what we�re trying to do here--make better informed decisions so you use the tools that you�re pretty much comfortable with. I think where the rub comes in is when we have a lot more risk and uncertainty that needs to be quantified to make informed decisions and whether we choose to use the new tools.

Enloe: When you introduce a new set of tools, people want to use it for everything they do. So a lot of times, you have extremes- where you�re oversimplifying your analysis on a lot of things-and then you�ll learn something new and you�ll use the most sophisticated tool on every project, which is clearly an overkill too. So it takes a little bit of time and some experience to figure out that balance of which tools do I use when.

Tippee: How does a company arrive at its tolerance for risk?

Walls: The bad news is most companies don�t arrive at their tolerance for risk (systemically). It just unfolds over time based on whatever actions they take. Is that good? No. Companies should try to be more consistent about their risk-taking. One way they can do that is to actually establish some sort of risk tolerance level. There�s lots of empirical information that would suggest that if you take a little more risk, on average you�re going to get a better return. Look at empirical data over the last 10 years for ARCO, Amoco, and Mobil, you see they were risk adverse companies. Now, let�s see what happened to them? I�m not saying that that�s the whole reason behind (their acquisitions by other companies), but what that means is there are a lot of underoptimized assets probably in those firms, because of unwillingness to take some risk.

Brashear: Someone, just in passing, said that it was difficult, sometimes frightening, to see how people will combine vastly different kinds of underlying analyses into the same portfolio analysis. That�s the origin of a great deal of just plain "error," because you can�t combine things. It�s hard to figure out how you can even combine expected values when some analyses take certain things into account and other analyses take other things into account. They�re simply not of a comparable nature. And that�s one place where the new tools and better communications�the internet and intranets within companies�are making giant strides that way. Now, you�re able to use templates company-wide so at least the procedure and the thought pattern is comparable.

Campbell: I agree with you exactly on the issue about the broad range in techniques in using to describe the risk and uncertainty of projects. Part of that has to do, though, with how much do we know about each one of those investment opportunities. Some of them are already well in hand, and we�re fairly far along and have done a lot of investigation. But, depending upon our planning perspectives�some of us plan 2 years, others 5 years�some of those things that we�re going to embark on in 3 years we don�t know that much about and they�re contingent on a lot of other things. One of the challenges of having a system that will allow us to incorporate all of these things together is having the flexibility and high degree of detail of certainty in early projects and (the unknown) that allows us to incorporate distributions of cost and ultimate recoveries and the interrelationships between current projects and future projects.

To make portfolio management or portfolio optimization work, this really needs to be an evergreen tool. Something you don�t just do it once at the planning cycle and then put it in a drawer and pull it out a year later to see how you�re doing, but to use it to your best advantage, every time something changes that�s significant, you upgrade the model. When we were first looking at these tools, the computers and the underlying software were pretty simple and it required that you couldn�t optimize but on maybe 8, 10, or 12 projects. That's pretty coarse detail. Now, we�ve got more sophisticated software and better computers that allow us to be able to optimize every project.

Brashear: It�s true of any kind of portfolio analysis that you can add up the expected value of a group of projects and talk meaningfully about them, because they are averages and means, and can be added. But you can�t meaningfully (talk) about how the risks interplay without putting them all together into a portfolio analysis�they are not additive. The magic of all this is trying to find ways of increasing expected value while reducing the risk by the interplay and substitution of projects or the recognition of real options. When people talk about embedding real options in portfolios, they�re beginning to talk about putting contingency plans at the project level together, such that strategy now begins to become something where capital can really be allocated to it.

Tippee: Is that the next energy level, then, is the embedded option?

Brashear: It�s one of them. First, you have to get the basic risk analysis working, but it has the tendency to want to oversimplify. When assets are being evaluated today, many times people will say, "It�s an exploration project, so we�ll only count the primary cover," knowing full well that there will be an infill program or there will be a water flood following or there will be some kind of enhancement of production. Frequently, those (kinds of things) are ignored, and if they�re ignored, then you misstate the value of the project. Similarly, there may be downside risks that you capture in sort of a blind way�it will over penalize a project that could be sold off or farmed out to someone who might like to have it. By not recognizing real options, you tend to not get a true valuation but there are a lot of other technical issues that are going to have to be solved at the same time. Some of the more robust tools that capture interdependencies between events and projects into the portfolio optimization are beginning to come onto the market.

Narum: (I want to) throw out this one loose caveat...about the implementation and the take up of uncertainty analysis. Once the value is seen, one of the things that we need to be a little careful about is trying to implement it too fast. Some companies might think that once you start doing this, you can have your whole portfolio completely modeled and done in 2-3 months and then you�re ready. That�s going to lead to disaster. Companies have to have the right mindset that this is a 2-3 year journey that involves quality processes, tools, buying and proving the concepts.

Rowe: I think that there�s a real danger of overpromis(ing) what the capabilities of it are, and I think you absolutely have to (implement) it in a measured way. Because you really have to get (everyone on board)�not just at the top, but all throughout the company�and a lot of it has to do with the style of the organization, whether it�s a top-down or a bottom-up organization. If you have a top-down, you can implement some things pretty quickly, but does that mean that (employees are buying into it?) No, not necessarily. On the other hand, if you have a bottom-up organization, it may take a little bit longer to get something going, but once you do, it may move a little bit smoother.

Tippee: We are using these tools to essentially make decisions about the deployment of capital, but what about the deployment of technology? Where is the industry in using these tools to know when to do something sophisticated and when to hold back?

Brashear: One of the most important applications of these tools is one that doesn�t happen very often. In the exploration end of the business, as someone mentioned before, there is a lot at risk. Then there�s development. With (exploration and production) technologies, it�s very important to do the risk analysis because a lot of those risks are hard to measure intuitively, they don�t come easily�they come out of the interdependencies of a lot of variables, both technological and reservoir and economic. And thus, it�s very, very important there. Now we�re beginning to see some more of that happening, partly because we�re beginning to see new financial forms and very large projects. We�re beginning to see people having to communicate with the financial community or with third party funders, and they want to know precisely what some of those risks are, particularly for large offshore projects or pipelines and projects in remote areas. I think we�ll see this beginning to be applied more because third parties were required, but the payoff for applying risk analysis and rolling it up into portfolio analysis of advanced technologies is enormous. I think that�s what we�re going to see several of the leading companies increasingly applying the same methodology philosophically to exploration, production, acquisition and even projects under depletion�because even depleting projects have risks attached to them. They also have the possibility of being divested in order to free up capital to buy other projects. So, the are just as much a part of the portfolio and excluding them from the portfolio optimization typically gives you a solution that�s not quite right.

Campbell: I see exploration using (risk analysis) all the time, whether it�s on reserve volumes, probabilities of success, drilling is probably next. And beyond that, it�s just, "Let�s ignore it. We don�t need it." And I think at the end, they have got a formal risk assessment of what happens. It�s very easy to show that if you ignore the risk of the number of wells, size and type of production facility. Scheduling is probably one of the biggest risks in project evaluation, but if you don�t handle those directly, you are going to grossly underestimate the risk of your project. I still see (people) doing it, except on very rare occasions. I�ve seen people spend tens of billions of dollars and never even worry about the risk associated with the scheduling of completing a pipeline.

Rowe: If you�re using deterministic methods, the problem is that prices don�t always stay high and they don�t always stay low, they bounce around all over the place. But the trouble is that we�re making investments that may not come on production for 1 to 5 years or 10 years and they last a long time. And so what happens tomorrow with oil and gas prices doesn�t really matter too much on the economic viability of the project. Even if you hold everything else constant and just look at the volatility of the prices and see what that does to the NPV, performing an economic evaluation of a project several hundred or thousands of times allows you to see what the distribution of the outcomes looks like.

Brashear: When you understand that volatility and what it can do to your overall economics, it puts you in a position to begin to do something about it, such as diversifying. It�s possible, in many places in the world, to negotiate production-sharing agreements where prices are pretty much not an issue. The only uncertainty that you�re faced with is cost and production rates. Those are a big offset against high volatility in the commodity prices. Even though they might not be as large, it�s possible to take certain financial hedges, even to sell forward is not a bad way to capture (value). Although you might miss some upside, you will also remove some of the downside.

Campbell: Even at the project level it�s important. Because if I�ve got price volatility, I start looking at an FPSO vs. a spar or how many wells I can drill. Because the risk profile with all the options�which I do control, as an engineer�are very important for me to understand when I make my investment decisions. Without that thought process that we�re describing here, you�re not really valuing things, you�re just ranking things based on a big fixed number, which usually suboptimizes, (or takes on more risk than needed at an expected return level) your valuation at the project and at the corporate level.

Brashear: I think that that would be a characteristic of most of the operating portfolios in the E&P industry today. The question is how much uncompensated risk have they undertaken, and I don�t think that anyone really knows that. Some probably very little, others massive amounts.

Narum: One of the things that you might find is that there might be a perception by some folks that you can�t change anything. (To Walls) I don�t know, you had an example, I think, that you talked that was kind of interesting before?

Walls: One of the major oil companies had a suite of assets, and they were really interested in seeing whether or not the mix was appropriate in terms of optimizing on a risk and return basis. In this particular exercise, after we received all their data from them and characterized all the uncertainty, they told us that they really didn�t have any flexibility to move anything around. Well, in fact, that�s not really true. We worked through that process, but it really spoke to this whole issue of how companies sometimes getting entrenched in what they are doing and don�t think about trying to match their available opportunities to what their strategy is. I think that�s probably an extreme example, but there�s degrees of that in almost every company.

Rowe: I think one of the things that comes out of the exercise of portfolio optimization is that�the planners have to have a clear understanding of what it is they�re trying to accomplish. It�s one thing to maximize net present value, but there is always usually some other constraints that are involved or some secondary goals. It might be that you need to replace production every year or achieve a certain finding and development cost or seeing certain net cash flow profile. I think just examining, setting and quantifying those objectives can be a real interesting exercise in and of itself.

Campbell: Or could they be in conflict with each other as well too?

Brashear: One of the points that Richard is alluding to is that if you do a full portfolio analysis�and, of course, if there aren�t some counter-intuitive conclusions that come from it, you wonder why you did it�it will be filled with counter-intuitive conclusions. Just being able to calculate the impact of taking those strategies into account is a sobering thing for a lot of companies. They look at that and they say, "I did not realize that being a low-cost producer was costing me that much. I did not realize replacing my reserves every year was costing me that much on the financial side." And that makes the strategic planning process begin to connect up with the reality of the capital allocation�the real planning process�that basically has to do with opportunities and real constraints, not just slogans.

Tippee: I wonder if there�s a threat that this gets out ahead of the investment community. Are investors thinking this way? Say, an enlightened CEO goes to an analyst presentation and says, "We�re doing this" and starts talking about these methods. Are the people in that room going to respond to that or are they going to think it�s just a black box and they don�t want to mess around with it?

Walls: It may communicate to the investment community that the firm is being systematic about its risk management process, which I think can have positive results in terms of the way the investment community looks at that firm. The counter argument is that the investment community doesn�t care, because they�ve got the risk by portfolio. They�re not really concerned with your business-specific risk, because they can diversify away all of that risk in their own personal portfolio. However, the fact that they may not care in a theoretical world does not imply that the manager still does not have a responsibility to efficiently allocate his capital to the resources available to him. In my view, the markets react to three things when they value a firm: how good your investment decisions are; how well you finance those decisions; and how well you manage those assets once you have them. That third component�managing the assets�points to the issue of using their decision processes, and I think the market will react positively to that.

Brashear: The direct consequence of using some of these tools is that the outcomes become somewhat more predictable. For reasons I�ve never quite understood, the market loves predictability and punishes (companies' stocks) if they're a few cents short of their promises. (The fact that these) tools tend to make the outcomes more predictable should make quarter-to-quarter and year-to-year performance more predictable and therefore closer to the analysts� expectations.

Enloe: When we talk about risk, we�re talking generally about some kind of a loss from a NPV standpoint. A lot of times, I think, you�ve got the shorter term risk that we don�t necessarily measure very well because you do have to deliver a set of earnings and meet some expectations. I don�t know that we�re very good about, even internally, understanding about what that volatility is and then trying to manage those expectations.

Tippee: In terms of the potential reward from the use of these tools, how much is the industry getting from what is potentially there?

Walls: There�s kind of a continuum going all the way from doing simple expected value analysis to Monte Carlo simulation to decision trees. On the high end of the spectrum, I think it�s about 2% and on the low end, I mean, Monte Carlo simulation is getting to be a pretty well-accepted technique, I�m not sure what the percentage is again, but probably 30-40% anyway, that companies use that technique. So, as the level of sophistication gets higher, I think that percentage really drops dramatically, so you kind of have to look at what suite of tools that you�re really referring to.

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