acm-header
Sign In

Communications of the ACM

Virtual extension

ERP: Drilling For Profit in the Oil and Gas Industry


Most large companies have adopted some form of enterprise resource planning (ERP) system. A survey of IT executives in the U.S. showed that ERP was the second most important key category for investment.5 In many cases, the implementation of an ERP system was a long and expensive ordeal that involved extensive restructuring of businesses and reengineering of processes.

While the potential benefits of ERP have been extolled frequently and much has been written about individual company experiences, only limited evidence has been produced that implementation of ERP does, on average, lead to enhanced performance. To the best of our knowledge, this is the first industry analysis on ERP because previous work has been limited to case studies and industry cross-sectional analyses.

Several research studies have validated that IT provides productivity and profitability advantages. However, questions remain because it is not clear whether advantages from IT contribute, and to what degree they might contribute, to operational efficiency and profitability. For example, if the same IT is implemented by all firms in an industry, will industry profits from IT disappear? Due to the fact that for many years large companies developed their information systems independently, there have been limited opportunities to evaluate the implementation of similar IT infrastructure across companies. This study seeks to extend prior work by performing a longitudinal study of implementation of ERP systems in a specific industry.

According to Porter,8 each industry is affected by new information technology in different ways and drawing general conclusions about how new IT affects firms across industries would be a mistake. The oil and gas industry was selected because ERP plays a major role in standardizing business processes in this industry. In this role, ERP helps firms link global operations and supply chains. Also, a commodity-product industry, like the oil and gas industry, helps us control for other influences that may have affected the performance of oil and gas companies during the study period. The ERP adopting firms are those that adopted SAP.

This research applies a new methodological approach toward understanding ERP implementation because rather than looking at ordinary measures of firm performance, we look at strategic performance measures (SPM) that can only be utilized if one delves into data that is not found on the financial statements. This is the first study that shows the sources of profitability after an ERP implementation, and will help managers understand the strategic and managerial implications of ERP implementations. Our analysis compares performance changes of ERP adopting firms versus non-adopting firms over a fifteen-year period (1990–2005), which is the period when this industry was being transformed by increased use of technology in the oil and gas industry. Therefore, we see how the implementation of ERP affected firm performance during this period in relation to non-adopting firms.

Back to Top

ERP and the Oil and Gas Industry

When processes are standardized, data is consistent, as opposed to having many different systems across the company. In an industry with so much complexity and increased competition, standardization plays an important role, and ERP provides it. According to Patricia Hewlett,7 vice president of global information technology at Exxon Mobil, the ultimate payoff from standardization is not just cost savings from achieving economies of scale; it is also the competitive advantage and flexibility added to the business by allowing rapid movement into new markets and workload adjustments among offices.

With regard to assets, SAP claims that a lack of reliable information may cause some companies to delay the replacement of non-performing assets, or to replace fully functional assets that do not require replacement.9 In contrast, an ERP system will provide managers with pertinent timely information about external events and internal resources, thus improving the quality of managers' decisions.

Back to Top

Research Design

There are two components of our research design that make it unique. First, we break down profitability into its strategic performance measures.1,6 These strategic performance measures are productivity, price recovery, product mix and capacity utilization ratio.2,3

Second, the way in which we measure the performance changes in the adopting firms versus the non-adopting firms before and after the implementation. Because we catch the period when the industry was being transformed by major investments in ERP—we see successive implementations as firms adopted SAP and how their performance changed relative to firms that did not adopt SAP during this period.

Banker et al.4 performed a longitudinal examination of the multi-period impact of an incentive plan at several stores operated by a major firm in the department store industry. They used monthly store sales reports for a 66-month period for the 15 stores that implemented the incentive plan and the 19 other stores in the same geographic region that did not. Their results indicate that sales increased when the plan was implemented and that the increase persisted over time. We use a similar model to test whether the average firm with SAP outperformed the average firm without ERP both before and after the implementation. This analysis allows us to isolate the contribution of SAP while controlling for other factors that are likely to influence the strategic performance metrics. The average performance of the non-adopting firms was used as a benchmark for the performance of the SAP firms in the corresponding quarter. This controls for changes in strategic performance metrics over time due to potentially unique strategies of firms as well as seasonal and regional economy-wide effects. To ensure that time effects are removed from the data, we converted dollar data to constant 1990 dollars. We then tested for time series trends and transformed the data to remove time trends. To control for calendar year related time effects and other possible seasonal influences, a discrete indicator was generated.

Back to Top

Data

In the oil and gas industry, many companies installed SAP R/3 and other modules from SAP between 1990 and 2005. The deep penetration of SAP in this industry provides an opportunity to investigate how adoption of similar information technology (IT) infrastructure by a large number of firms in a single industry influenced the performance of those firms relative to non-adopting firms. Moreover, because SAP is dominant in this industry, it provides more homogeneity in terms of the type of IT used across firms.

Our data, obtained directly from SAP, includes information about the start and completion dates for SAP installations. Financial variables were obtained from Standard and Poors' Compustat database. For the companies that did not install SAP, we performed a detailed search of press releases and other corporate information to determine whether non-adopting companies implemented other ERP systems or did not implement any ERP system at all.

In order to verify that non-adopting firms did not adopt another ERP package, we repeated this detailed search for the sample provided by SAP without using the data provided by SAP. Using this search procedure, 28 out of 29 firms from the SAP sample were identified as SAP users, only one firm could not be identified as a SAP user so the effectiveness of this criterion on SAP users was 97%. Therefore, the criterion described here is a reliable way to identify if a firm in the Oil and Gas industry installed or did not install SAP. A possible limitation of this analysis is that there is a 3% chance that a non-adopting firm may have installed another ERP package.

Our final sample consists of 98 firms. Of these firms, 29 performed a full installation of SAP, 30 did not install any ERP system, seven installed other ERP packages, and 32 performed a partial SAP installation. Firms that performed a partial SAP installation were not included in the dataset because they could not be classified as ERP adopting nor non-adopting. Firms that were subsidiary companies of another company in the data and firms with less than two years of data were also removed. In addition, non-SAP firms with quarterly average sales less than $200 million were removed to avoid a small-firm bias in the non-adopting firms. Our primary analysis is based on a comparison between our SAP sample of 29 firms and non-ERP sample of 30 firms. For robustness, we also performed a separate analysis that included the seven firms that implemented other ERP in the non-adopting sample. See Table 2.

Back to Top

Impact of SAP adoption on strategic dimensions of profitability

Table 3 presents results of our regression estimation of the model for the following strategic performance measures: profitability ratio, productivity ratio, capacity utilization ratio, product mix ratio, and price recovery ratio. The results are robust when the non-adopting firms include both the 30 non-ERP-adopting firms and the seven firms that adopted an ERP package other than SAP, therefore validating our results from Table 3.

Our results after implementation show that oil and gas firms that adopted SAP did realize performance improvements in relation to non-adopting firms. Profitability ratio improved 9.6% after the implementation. In order to compete in this environment, SAP claims that helps companies to speed and process the flow of data, from the oil field across the entire upstream business.9 In the oil and gas industry, improvements in efficiency are manifest through greater throughput and better utilization of resources that support operations and sales. From Table 3, we see that productivity ratio improves 4.3% after the implementation. Therefore, an SAP installation leads to leaner operations, and develops more continuous workflow by integrating the whole value chain from raw material to finished product.

Capacity utilization improves 7.8% after the SAP implementation. Thus, companies that implement SAP identify demand shifts and swiftly adjust their production schedules, achieving greater capacity utilization. Better capacity utilization leads to lower average costs.

We did not find significant values for improvements in price recovery and product mix. Although price recovery provides information about a company's success in meeting customer needs while effectively managing its supply chain, in a commodity-product industry such as oil and gas, there are no improvements in price recovery. Concerning product mix, while this ratio can be higher for companies that adjust their product mix swiftly in response to demand shifts, we do not see improvements because the oil and gas industry uses non-interchangeable dedicated assets. We drilled down as deep as oil versus gas, and this was not sufficient to detect the impact of SAP on product mix.

Back to Top

Conclusion

This study contributes to IT literature in three important ways. First, we utilize an alternative methodological approach that requires information beyond that which is provided by financial statements. This alternative framework uses a sophisticated model not used before in IT literature. Second, this is the first empirical work to utilize such a model to measure the strategic performance of firms in the oil and gas industry. The source of competitive advantage comes from productivity and capacity utilization. Thus, efficiency gains from enterprise systems are not easily duplicated. The implementation of the enterprise systems bestows process efficiencies and pushes the production frontiers further out, allowing the leading firms to sustain a competitive advantage. Third, previous work has been limited to individual case studies or cross sectional analyses. Here, we extend previous work on the impact of ERP by providing clear metrics to gauge the impact of ERP by focusing on a specific industry. Focusing on a specific industry has an advantage because each industry is different.

Information about the association between profitability and ERP enables managers and senior executives to recognize the potential contribution of ERP and its strategic and managerial value. As shown in Figure 3, the multidimensional strategic performance approach tells us that ERP impacts productivity and capacity utilization positively and these are the sources of profitability. The results for capacity utilization provide evidence of significant improvements in capacity utilization for SAP-adopting firms versus non-adopting firms after the implementation. Because ERP systems enhance the ability of the company to collect, process and use information about input supply, output demand and internal production, companies are able to add value for its customers by more closely matching their production to customer needs. This effect can be appreciated in the productivity ratio, where improvements in productivity are realized because ERP systems enable better coordination between different productive units.

Back to Top

References

1. American Productivity Center. Total Productivity Measurement Houston, TX, 1981.

2. Banker, R.D., Chang, H., and Majumdar S. A framework for analyzing changes in strategic performance. Strategic Management Journal 17 (1996), 693–712.

3. Banker, R.D., Chang, H., Majumdar, S. Analyzing the underlying dimensions of firm profitability. Managerial & Decision Economics 14, 1 (Jan. – Feb. 1993), 25–36.

4. Banker, R., Lee S., and Potter G. A field study of the impact of a performance-based incentive plan. Journal of Accounting and Economics 21 (1996), 195–226.

5. Kanakamedala, K., Krishnakanthan, V., and Mark, D. CIO spending in 2006. The McKinsey Quarterly (Spring 2006).

6. Miller D. Profitability=productivity+price recovery. Harvard Business Review 3 (May/June 1984), 145–53.

7. Mitchell, R. Exxon Mobil: Focus on flexibility. Computerworld 40, 44, (2006).

8. Porter, M.E. Competitive Advantage. Free Press, N.Y. 1985.

9. SAP. SAP for oil and gas: Strategies for profitable growth. 2004.

Back to Top

Authors

Jorge A. Romero ([email protected]) is an assistant professor of accounting at Towson University, Towson, MD.

Nirup Menon ([email protected]) is an associate professor of management information systems at George Mason University, Fairfax, VA.

Rajiv D. Banker ([email protected]) is the Merves Chair in Accounting and Information Technology at Temple University, Philadelphia, PA. He has published extensively on the business value of information technology and the balanced scorecard extensively.

Mark Anderson ([email protected]) is an associate professor of accounting at The University of Texas at Dallas, Dallas, TX.

Back to Top

Footnotes

DOI: http://doi.acm.org/10.1145/1785414.1785448

Back to Top

Figures

F1Figure 1.

F2Figure 2.

F3Figure 3.

Back to Top

Tables

T1Table 1. Definitions of each variable

T2Table 2.

T3Table 3. Results for Components of Profitability Ratio

Back to Top


©2010 ACM  0001-0782/10/0700  $10.00

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.

The Digital Library is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc.