Proven Method for Assessing the Value of a Digital Oilfield Investment - Part 1

By: Scott M. Shemwell, D.B.A.
Digital oilfield 1

The Challenge
Since the advent of the modern digital computing era, with the arrival of the ENIAC (electronic numerical integrator and computer), understanding and articulating the Return on Investment (ROI) of information systems has often be equated to hocus pocus. Although not fully functioning until the fall of 1945, the economic justification of this first machine was World War II.

For over 60 years, a number of different financial and economic rationales have been applied to capital expenditures in the information technology sector. By the early 1980s, IBM’s System/360 machines were touted as providing users with more rapid response times for the user because of faster system response time. The resulting increase in productivity was deemed a function of the user not having to wait on the machine as well a lower cost per computing cycle. These transaction cost reductions were difficult to accurately measure and would like vary greatly by organization.

Readers, particularly those in the IT procurement process would not be surprised to learn that not much has changed in the sales value proposition “pitch.” In fact, the stereotypical sales presentation is so ingrained into Western culture that a Google search for “funny sales pitches” generates almost two million hits including videos and even poems.

Economic Value
Economists have developed a set of tools to help identify components of value for economic solutions such as Marginal Utility Theory—the value of one more unit of change in a variable. Moreover, the petroleum industry measures Return on Invested Capital (ROIC), effectively the return on capital employed as one of its Key Performance Indicators (KPIs). From these two constructs, the following model was developed by the author previously and is reprinted as follows:

One measure of the dollars of economic value, economic profit is a function of return on capital (monetary measurement) over a single period (fiscal year) and can be expresses as,

EP = IC x (ROIC - WACC) Where,

EP = Economic Profit,
IC = Invested Capital (operating working capital + net fixed assets + other assets),
ROIC = Return on Invested Capital (Net Operating Profit Less Adjusted Taxes divided by Invested Capital or, NOPLAT / IC),
& WACC = Weighted Average Cost of Capital (equity and debt).

ROIC is a better analytical tool for understanding performance than the traditional industry metric, Return on Assets (ROA), because it focuses on the true operating performance of the firm. The other variables in the EP equation are robust as well and take into consideration a number of micro and macro-economic factors that are both under control of management and outside the control of management.

From marginal utility theory, we can deduce a new concept, the expected value of marginal information, EVMI. Readers should note that we are using the economic definition of marginal utility; the amount of satisfaction obtained from consumption of the last unit of a good or service.

Thus, when added to the firm’s estimate of the probabilities associated with the uncertain outcome of a decision can be expressed as follows:

EVMI represents the probabilistic maximum cost of new information to the decision process. As long as the real cost of new information does not exceed EVMI then the information is adding economic value to the firm. In other words, it is the threshold value proposition or NPV (net present value) =0 for new information.

An NPV in excess of the marginal utility of information represents economic value to the firm.

Taken together, this enables the assessment of investments in information technology in terms management is familiar with and is consistent with the CAPEX process used for other capital investments in plants, equipment and assets. This has the additional benefit of quantifying the returns and extends earlier metrics into the 21st century.

The final component of the model is the comparative value of asymmetric information. The author previously defined:

“Comparative advantage is structural by nature. It is developed as part of a firm’s core competency and are the actions taken based on asymmetric information the organization possesses about its customers, processes, assets (capital and labor), and markets.

Asymmetric information has value and is acquired at a cost. However, in and of itself it has no economic value. Only when acted upon can the organization realize the value. Asymmetric information is not confined to one process or even one set of interrelated processes, it often manifests itself throughout the firm’s value chain. Likewise, information obtained in various segments of the value chain may be of interest to those whose value creation took place earlier in the process.”

This theoretical construct, based on established economics provides the basis for assessing the economic value of investments in the digital oilfield. The Economic Value Proposition Matrix model (EVPM) has been extensively vetted by both operators and suppliers of digital oilfield solutions. It speaks the language of management and addresses both hard and software variables.

Parts 2 of Scott Shemwell’s “Proven Method for Assessing the Value of a Digital Oilfield Investment” is available here.

Part 3 is available here.

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