Competitive advantage in petroleum exploration

April 23, 2001
Competitive advantage is the essence of firm performance in competitive markets.

Competitive advantage is the essence of firm performance in competitive markets. Competitive strategy is how to create and sustain competitive advantage.

The literature on competitive strategy for petroleum exploration, however, is very limited. Most of the published work is on exploration strategies, choosing what plays to enter, when to get out, what to bid for a concession.1

The recent focus in the literature is on composing the portfolio of exploration assets and efforts, most often in the context of both petroleum exploration and exploitation. There is much less on competitive strategy for the exploration outfit.

What might be the reasons for this lack of literature?

Petroleum exploration is not a competition in markets with other exploration outfits but rather a competition with Mother Nature. The effort is more cooperative than competitive as exploration outcomes can benefit others.

Strategy for petroleum exploration is simple. It is primarily an issue of good people and good tools, and a little bit of luck.

The large petroleum exploration outfits, the outfits that usually catch the interest of consultants and academics that publish work on competitive strategy, are not independent firms or strategic business units but are most often functions and departments in large integrated firms.

Modern how-to competitive strategy literature, and particularly the work of Michael Porter with his value chain framework,2 3 has not been easy to apply to petroleum exploration.

Click here to enlarge image

We report here on research that started from the premise that Porter's value chain framework (Fig. 1) is not very easy to use when analyzing strategic positioning and competitive advantage in petroleum exploration.

Our basic idea is quite simple. The value chain model is appropriate for manufacturing (think petroleum production), while petroleum exploration is primarily a problem-solving service. It solves the problem of finding commercial quantities of petroleum.

Click here to enlarge image

We have argued elsewhere that problem-solving services are better modeled as value shops.4 In value shops (Fig. 2), the primary activity categories are problem-opportunity finding (such as focusing a new play), problem solving (generating and evaluating alternative prospects), choice (what, if any, prospect to drill), implementation (drill wildcat), and post-implementation follow-up and control (evaluating wildcat results).

The distinction between value chains and value shops is not only an issue of different activity categories. It is equally if not more an issue of very different business logics, different strategic drivers of performance, and different strategic positioning options.

By expanding the repertoire of models available for analyzing and developing competitive advantage, Porter's value chain framework has been transformed into value configuration theory.

In what follows, we first review briefly the key idea behind value configuration theory.4 We then use the results from our survey and analysis of more than 60 exploration units operating in the UK and Norway as a means to elaborate on key aspects of a value shop perspective on petroleum. We show how value configuration theory establishes a clear link between modern competitive strategy and petroleum exploration.

The framework refocuses established concepts in exploration strategy, and it demonstrates the critical role of reputation as a key driver of competitive advantage. It also suggests the role of opportunity finding and post-drilling evaluation as two important levers for competitive success in petroleum exploration.

Value configuration theory

Value configuration theory starts from the premise that competitive advantage cannot be understood by looking at the firm as a whole.

Competitive advantage stems from the many discrete activities a firm performs in generating and delivering value.3 Each of these activities can contribute to a firm's relative cost position and create a basis for differentiation. The theory provides a systematic basis for analyzing and developing competitive advantage.

A firm is broken down into value activities. Following Porter, we distinguish between primary and support activities. Primary activities deliver directly value to the customer, define the business logic, and vary across the three basic value creation technologies. Support activities affect value delivered through their effect on primary activities.

Costs and value generated are allocated and estimated, all using the value chain template for manufacturing firms and value shop template for problem solving service firms. The results of this activity-directed review are used to identify the competitive strengths and weaknesses of the firm.

Consider a petroleum exploration shop (Fig. 2). Value activity analysis might determine that the shop is very effective in evaluating and selecting prospects to drill but less so in terms of its ability to generate the appropriate portfolio of leads to evaluate or in following up and learning from its wildcat drilling activities.

A second order and more fundamental analysis focuses the drivers of activity cost behavior and value delivered by activities.

Drivers are structural properties of activities such as scale, location, learning, and timing. Drivers are also structural properties of relationships between activities in the firm and activities in other firms in the value system.

An example of a structural property of the relationship between activities is how input quality assurance impacts activity rejection costs in manufacturing. Another example is how documentation activities in prospect evaluation affects value delivered by post-drilling evaluation activities.

We distinguish between cost drivers and differentiation drivers.3 Differentiation drivers affect the unique value delivered by the activity and thus the premium price that the customer is willing to pay. The logic of the value chain implies a focus on cost drivers, while a value shop business is more concerned about differentiation.

Again consider petroleum exploration. The distinguishing characteristic of the successful exploration outfit is not lowest costs, for example, in prospect evaluation activities or in drilling wildcats. Success is rather making significant discoveries, preferably as often as possible.

Competitive strategy for exploration outfits should therefore focus differentiation drivers according to value configuration theory. But before we develop this argument in more detail, let us review briefly a recent survey of exploration outfits that was designed to investigate the basis for and implications of a value shop perspective on petroleum exploration.

Exploration outfits survey

Data on exploration success for 62 exploration units active in the UK and Norway in 1996-1998 were obtained from secondary data sources.5

In addition, more detailed information on activities, on stakeholder evaluation of own and other exploration units, and on exploration budgets was obtained via a mail survey addressed to exploration managers. The survey was administered in June-September 1998 to the exploration managers for all exploration outfits. We obtained a response from 30 exploration units.

Click here to enlarge image

Exploration performance is measured with two indicators: net number of discoveries per exploration well and net reserves added per exploration well in million barrels of oil equivalent. Size is measured using different activity indicators but also the size of the geology and geophysics staff (Table 1).

Click here to enlarge image

We sampled relatively large exploration units, and the wildcat discovery rate is relatively high. A closer look at the actual distribution of net reserves per exploration well clearly has the familiar log-normal distribution, while the discovery rate is less skewed (Figs. 3, 4).

The exploration shop

Click here to enlarge image

What can we learn about the distinctive aspects of the value creation logic (and thus business logic) of exploration shops?

If we were to apply a value chain logic to exploration shops, then one might argue that the exploration inputs are leads and the exploration outputs are discoveries. This simple articulation ignores that getting good leads is key and that not all leads are drilled, nor do they always produce discoveries. In short, the process is not one of transformation, but rather one of selection, screening, and sorting. This is also evident from the data in our sample.

Click here to enlarge image

Table 2 shows key activity statistics in terms of average number of leads, number of prospects, number of wildcats, and number of discoveries (also see Fig. 5). There is clearly a narrowing of focus where on the average 73 leads are pruned to 29 prospects, 29 prospects are pruned to 4 wildcats, and 1 out of 4 wildcats is a discovery. Not surprisingly, the strongest pruning is from prospects to exploration wells as it is the drilling decision that commits significant funds and attention.

Click here to enlarge image

The screening, pruning, and sorting of problems and opportunities implies that the basic unit of production, such as number of discoveries, is in general not a very meaningful measure of activity levels in an exploration shop. It is more appropriate to use some measure of project load relative to both capacity and the exploration funnel. One relative load measure is the number of prospects per G&G staff (Table 2).

What are some of the other implications of looking at petroleum exploration as a value shop?

Click here to enlarge image

A key point is the relative strategic and competitive importance of the different value activities. Management focus and professional attention in an exploration department are often on problem solving activities (delineating and evaluating prospects) and implementation activities (drilling) as this is where most of the exploration costs are incurred. Fig. 6 shows an estimate of the relative composition of exploration costs (using average figures for the 30 exploration outfits sampled with the mail survey). The figure illustrates the relative cost importance of particularly execution activities (drilling). The main value-creating activities, however, are probably problem finding and learning from post-drilling evaluation.

Another related implication of a value shop perspective is the relative importance of cost drivers and differentiation drivers.

Scale and capacity utilization are often used to illustrate the concept of drivers. In manufacturing (value chains) these are generally key drivers of cost: Unit costs drop with scale and capacity utilization. In value shops, however, costs are often secondary to the issue of solving the client's problem. In the shop we are more concerned about value: healing the patient, winning the case, finding hydrocarbons, and thus differentiation drivers. Restated in petroleum exploration terms, it costs about the same effort to make a large discovery as one that is barely commercial.

What are the critical differentiation drivers in petroleum exploration?

Our survey asked exploration managers what they considered were the critical success factors for achieving and maintaining a high performance exploration outfit. Their answers suggested three main categories of success factors (that covered over 85% of the factors identified): assets, management support, and people.

The most popular category was one that we labeled "assets:" leading edge technology, a good portfolio of licenses, and a creative culture and good knowledge base.

The second most popular factor was "management support." Under this category respondents' comments included predictable funding, willingness to take risks, consistent strategy and focus, and short decision time.

The third most frequent response was "people" as a key success factor, with comments such as competent, knowledgeable, and motivated staff.

The management factor can be interpreted as having supportive clients as most of the respondents were responsible for exploration in integrated petroleum exploration and production firms.

How is the exploration shop to get the best acreage, the best people, and solid client (management) support? Value configuration theory argues that it is by being successful. This brings us to what we argue is the critical differentiation driver in value shops: reputation.

Reputation is critical in value shops because of the basic information asymmetry that is built into the relationship between the shop and its clients. Clients consult a shop precisely because the client believes that the shop knows how to solve the client's problem. The client consults the shop because the shop knows something that the client does not know.

The client needs to be sure that the shop makes a best effort at using its specialized knowledge. Success signals not only expertise but also commitment.

Click here to enlarge image

Success drives reputation. But reputation also drives success as good reputation gives access not only to the best projects but also to the best personnel. Over time there is a positive feedback loop where success gives access to the best projects (acreage and prospects) and also attracts the best professionals (Fig. 7). In short, success and reputation lead to the accumulation of the assets and competences that ensure future success.

There can be different sources of reputation and different types of reputation: a reputation for having the best people, the best activities, but most important the best results in terms of success. For the exploration shop, the critical result is the discovery rate and reserves per exploration well. These are clear and public results.

However, active professional involvement in professional forums is also a means to manage reputation. Exposure through alliances and partnerships is another source not only for signaling success but also of managing reputation capital.

Reputation, exploration success

Click here to enlarge image

In our survey we asked each exploration manager to identify the three leading exploration outfits in the UK and Norway, respectively. The results were weighted according to whether an outfit was listed first, second, or third. Fig. 8 shows the reputation score distribution over the 62-unit sample in the UK and Norway, while Table 3 shows the top three exploration outfits in the UK and Norway, respectively.

Click here to enlarge image

As is apparent from the reputation score distribution, reputation is very unevenly distributed. The distribution underlines the potential strategic importance of reputation. Our data support the proposition that there is a positive link between reputation and success as measured by discovery ratio and net reserves per exploration well. This result holds even when controlling for size.

In other words, the link between reputation and exploration success is not just capturing that the larger exploration units are better known. The list with the ranking of the top exploration outfits in each country (Table 3) is consistent with this finding. For example, Enterprise's Norwegian affiliate is not the largest exploration outfit in Norway.

At this point in time we cannot show statistically that high reputation drives future exploration success. However, as we have developed above, many arguments support this proposition. The driver effect of reputation would appear to be particularly apparent in settings where access to acreage is based on a "beauty contest." But more generally, exploration shops with the best reputation get a first look at the best prospects, they are often the preferred partners, and they attract the best professionals.

Managing success becomes critical for exploration outfit performance. This is true irrespective of whether the exploration shop is an independent firm (a prospect generator), a strategic business unit, or a function in an integrated petroleum E&P firm.

What are some of the other implications that come from viewing petroleum exploration as a value shop? We think that there are many. They pertain to issues such as:

  • What kind of exploration business to be in?
  • How to configure the activity portfolio?
  • The role of scale in exploration.
  • The role of location.
  • The sourcing of ideas (leads).
  • The role of learning.

We focus on configuring the project portfolio as this provides a direct link to strategic positioning in terms of differentiation drivers.

Configuring the portfolio

Click here to enlarge image

Positioning of activities must be relative to both opportunities and other exploration shops. Some key statistics from our survey of activity configuring are: share of prospects in frontier areas, share of prospects generated internally, and share of prospects in others' acreage (Table 4).

A prospect can be viewed as a project in an exploration shop. As noted earlier, projects are the relevant activity level indicator in shops. They compare to production volume in manufacturing. Exploration shops handle exploration projects.

The percentage of prospects in frontier plays (plays where the presence of hydrocarbons remains to be proven) indicates both the maturity of the exploration province and the strategic positioning of the exploration shops serving in the province. The low average percentage of prospects in frontier plays is consistent with the view of the UK and Norway as relatively mature exploration provinces. Still, some exploration shops focus as much as 80% of their exploration on frontier plays.

The percentage of prospects internally generated reflects the amount of problem and opportunity trading between exploration shops. On the average, more than 50% of the prospects considered were generated internally. Low internal generation might reflect that the shop is really a "partner" considering the prospects proposed by other exploration shops. It could, however, be an indication that the exploration shop is actively approached by a large number of other firms and thus has expanded the reach of its exploration effort.

We see an analog to this situation in the pharmaceutical industry, where external shops and research institutes are a major source of creative ideas. The critical issue is whether the shop gets first look or only gets to see prospects that have been worked over by more attractive partners.

The percentage of prospects in own license area is another measure of how the exploration shop scans the opportunity frontier, both to actively manage acquisition of externally generated prospects and to learn from the efforts of other exploration outfits. Exploring in areas where the shop does not have a license is potentially not very rewarding as license ownership is a pre-requisite for appropriating a significant share of the value of exploration activities.

Conclusion

Value configuration theory establishes a clear link between modern competitive strategy and petroleum exploration.

Not surprisingly, the framework refocuses established concepts in exploration strategy, but it also clearly demonstrates the critical role of reputation as a key differentiation driver and determinant of long-term success. It also suggests the role of both problem (opportunity) finding and post-drilling evaluation as two critical levers for competitive success in petroleum exploration.

References

  • Megill, R.E., "Long-range exploration planning," PennWell Books, Tulsa, Okla., 1985.
  • Porter, M., "Competitive strategy-techniques for analyzing industries and competitors," Free Press, New York, 1980.
  • Porter, M., "Competitive advantage-creating and sustaining superior performance," Free Press, New York, 1985.
  • Stabell, C.B., and Fjeldstad,

    The authors

    Click here to enlarge image

    Charles Stabell is professor of strategy at the Norwegian School of Management. He is also CEO of GeoKnowledge, a developer and vendor of decision support tools for stochastic evaluation of risks, resources, and value in upstream petroleum. He taught at Stanford University (GSB) and the Norwegian School of Economics and Business Administration and was a system engineering manager with IBM Norway. He holds a B.Engineering degree in electronics from ENSERG (Grenoble, France), an MBA from McGill University, and a PhD in management from Massachusetts Institute of Technology. E-mail: [email protected]

    Click here to enlarge image

    Norman Sheehan is a doctoral candidate at the Norwegian School of Management. He has worked for several years in the petroleum and mining industry, most recently in Petroleum Geo-Services as corporate controller. He has a B.Commerce degree from University of Alberta and an MBA from Norwegian School of Management. E-mail: [email protected]