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Information Technology for Enterprise Asset Management: An ...

  1. 1. Effective December 6, 2006, this report has been made publicly available in accordance with Section 734.3(b)(3) and published in accordance with Section 734.7 of the U.S. Export Administration Regulations. As a result of this publication, this report is subject to only copyright protection and does not require any license agreement from EPRI. This notice supersedes the export control restrictions and any proprietary licensed material notices embedded in the document prior to publication. Information Technology for Enterprise Asset Management An Assessment Guide
  2. 2. Information Technology for Enterprise Asset Management An Assessment Guide 1012527 Final Report, March 2007 EPRI Project Manager J. Bloom ELECTRIC POWER RESEARCH INSTITUTE 3420 Hillview Avenue, Palo Alto, California 94304-1338 • PO Box 10412, Palo Alto, California 94303-0813 • USA 800.313.3774 • 650.855.2121 • askepri@epri.com • www.epri.com
  3. 3. DISCLAIMER OF WARRANTIES AND LIMITATION OF LIABILITIES THIS DOCUMENT WAS PREPARED BY THE ORGANIZATION(S) NAMED BELOW AS AN ACCOUNT OF WORK SPONSORED OR COSPONSORED BY THE ELECTRIC POWER RESEARCH INSTITUTE, INC. (EPRI). NEITHER EPRI, ANY MEMBER OF EPRI, ANY COSPONSOR, THE ORGANIZATION(S) BELOW, NOR ANY PERSON ACTING ON BEHALF OF ANY OF THEM: (A) MAKES ANY WARRANTY OR REPRESENTATION WHATSOEVER, EXPRESS OR IMPLIED, (I) WITH RESPECT TO THE USE OF ANY INFORMATION, APPARATUS, METHOD, PROCESS, OR SIMILAR ITEM DISCLOSED IN THIS DOCUMENT, INCLUDING MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, OR (II) THAT SUCH USE DOES NOT INFRINGE ON OR INTERFERE WITH PRIVATELY OWNED RIGHTS, INCLUDING ANY PARTY'S INTELLECTUAL PROPERTY, OR (III) THAT THIS DOCUMENT IS SUITABLE TO ANY PARTICULAR USER'S CIRCUMSTANCE; OR (B) ASSUMES RESPONSIBILITY FOR ANY DAMAGES OR OTHER LIABILITY WHATSOEVER (INCLUDING ANY CONSEQUENTIAL DAMAGES, EVEN IF EPRI OR ANY EPRI REPRESENTATIVE HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES) RESULTING FROM YOUR SELECTION OR USE OF THIS DOCUMENT OR ANY INFORMATION, APPARATUS, METHOD, PROCESS, OR SIMILAR ITEM DISCLOSED IN THIS DOCUMENT. ORGANIZATION(S) THAT PREPARED THIS DOCUMENT B. Parkinson, Consultant NOTE For further information about EPRI, call the EPRI Customer Assistance Center at 800.313.3774 or e-mail askepri@epri.com. Electric Power Research Institute, EPRI, and TOGETHER SHAPING THE FUTURE OF ELECTRICITY are registered service marks of the Electric Power Research Institute, Inc. Copyright © 2007 Electric Power Research Institute, Inc. All rights reserved.
  4. 4. CITATIONS This report was prepared by B. Parkinson, Consultant 4151 Baker Ave. Palo Alto, CA 94306 Principal Investigator B. Parkinson This report describes research sponsored by the Electric Power Research Institute (EPRI). The report is a corporate document that should be cited in the literature in the following manner: Information Technology for Enterprise Asset Management: An Assessment Guide. EPRI, Palo Alto, CA: 2007. 1012527. iii
  5. 5. REPORT SUMMARY Integration of business applications across the electric utility enterprise is a high priority in the electric utility industry to reduce information technology (IT) costs and realize a range of business benefits. Asset management, a business process that integrates with most other utility business processes, is particularly enhanced by an integrated information technology solution. Background An integrated and automated solution for asset management—from data acquisition, to calculations, to reports that exploit a utility’s current IT system portfolio of enterprise systems from both commercial vendors and EPRI—can reduce the number of applications that need to be implemented and supported. Enabling efficient integration of applications across business units can greatly reduce information technology costs and yield a range of business benefits. Similarly, improved data collection using those systems can substantially reduce the number of evaluation hours for asset managers and increase the timeliness of information for decision makers. Objectives To assist utility IT and asset managers in addressing the unique and particularly challenging needs for asset management and to focus on data collection, use of existing enterprise systems such as work management systems, and the integration and use of decision support systems for specific problems such as managing aging assets and monitoring asset health. Approach The project focuses not only on the elements of an information technology plan, but also on the progression of its development. By describing in detail certain aspects of asset management program development, the project provides the context in which the information technology infrastructure must operate and grow as well as the asset management capabilities that result. The project raises the bar for asset management considerably. While many companies can and should be happy with reaching an “organizing” level of maturity, the project lays out the potential for further growth beyond that point. This growth is within reach because many of these programmatic improvements not only have and are occurring in more competitive industries like manufacturing, but also because performance in the nuclear generation industry has improved dramatically, with some of that improvement attributable to process and information technology improvements that are described in this report. Some electric utilities have already begun to transfer nuclear power’s business improvements to other business units. The project draws heavily from a number of EPRI asset management reports in both the power delivery and nuclear generation sectors. Each has a strong asset management research program at EPRI, characterized in particular by a broad degree of utility involvement. v
  6. 6. Results The report discusses critical topics for developing an asset management information technology infrastructure. Because the needs and capabilities of an enterprise IT depend strongly on its asset management program, the report provides a self-assessment method to help either an IT professional or an asset manager determine the current maturity level of their program. The method classifies asset management programs into five different levels of maturity using seven attributes with six sub-attributes to create a table of over 130 criteria for measuring development of an asset management program. The report discusses over twenty critical topics for asset management information technology infrastructure, grouped by maturity level into three sections. Each topic contains a set of recommended steps for improving asset management information technology infrastructure and program that, when combined with the criteria, allow readers to develop a roadmap for program improvement based on the results of the self-assessment. Because of the breadth and depth of participation and experience in EPRI’s work on asset management in both the power delivery and nuclear sectors, this report represents a corresponding breadth and depth of asset management issues in an enterprise program. Finally, the report highlights important current advances in information technology, especially related to the topic of service-oriented architecture, which seems particularly amenable to advanced forms of enterprise asset management. The importance of this evolving information technology discipline is demonstrated by the substantial investment made by vendors of enterprise asset management and enterprise resource planning systems. The report shows how EPRI’s asset management technology can facilitate such an architecture and how ongoing EPRI research can lead to even further possibilities for advances in asset management. EPRI Perspective Much has been accomplished in asset management in the last ten years in terms of improved equipment reliability, reductions in cost, and increases in business process productivity. Advances have been made across the board in data, decision support, and results visualization. Asset management lessons learned abound in information integration and application. The collective experience of the industry is substantial, and as the report’s self-assessment method asserts, such experience lays the foundation for raising the bar for asset management to a new and even more effective level. Keywords Asset management Asset manager Maintenance program Root cause analysis Performance monitoring Risk management PM basis database Reliability Information technology vi
  7. 7. ACKNOWLEDGMENTS The author would like to acknowledge the contributions of the many people who contributed to this effort either by contributing directly to the report’s concepts or by contributing to the EPRI asset management reports and programs upon which a good portion of this report is based: Vince Gilbert of Model Performance, LLC and Mitch Baughman of Duke whose leadership in Nuclear Asset Management community of practice enabled the nuclear asset management process description to be written with all its attendant benefits to asset management capabilities. Maureen Coveney, of OSIsoft, who introduced the author to the true potential of Service Oriented Architecture and participated in the development of a number of the principles described in this report. Serge Hugonnard-Bruyere of EdF, who contributed a number of concepts in this report including in particular the modularization method described in Chapter 5. Jeremy Bloom of EPRI, who immediately understood the value and applicability of the PM Basis and who contributed descriptions of corporate value models and risk management. Mike Lebow of Coplaner Consulting, the prime contractor for developing the Power Delivery Asset Management guidelines and process models, the source of many insights as well as some notable words in this report. David Worledge of Asset Performance Technologies, Inc., the prime source of material and the creative force behind the failure data models upon which important portions of this proposed approach is based. John Gaertner of EPRI, whose continued support and encouragement and sage advise enabled many of these ideas to formulate into EPRI research. Rick Grantom, Drew Richards, Ernie Kee and Alice Sun of South Texas Project and Jose Gomez Moreno and Luis Adriano Gerez Martin of Iberinco for their comments and contributions to asset management requirements in general and to visualizations of asset management results in particular. Tina Taylor, Ron King and Nikki Delse of EPRI, whose many discussions and cooperative work inspired a number of important developments. vii
  8. 8. CONTENTS 1 INTRODUCTION ....................................................................................................................1-1 2 ASSESSING MATURITY OF INFORMATION TECHNOLOGY FOR ENTERPRISE ASSET MANAGEMENT............................................................................................................2-1 Asset Management Program Maturity Levels .......................................................................2-2 Reacting ...........................................................................................................................2-3 Awakening ........................................................................................................................2-3 Organizing ........................................................................................................................2-4 Processing........................................................................................................................2-4 Continuously Improving ....................................................................................................2-5 The Attributes of an Enterprise Asset Management Program...............................................2-6 Data Collection and Use...................................................................................................2-6 Performance Monitoring ...................................................................................................2-8 Decision Support Capability – General.............................................................................2-8 Decision Support Capability – Investments ....................................................................2-10 Decision Support Capability – Risk Management ..........................................................2-11 Business Process Documentation and Modeling ...........................................................2-11 Information Technology Infrastructure – General ...........................................................2-12 Information Technology Infrastructure – Knowledge Management ................................2-12 Business Analysis Role ..................................................................................................2-13 Management Support .....................................................................................................2-13 The Maturity Index Table of Criteria ....................................................................................2-14 3 FIRST STEPS FOR NEWCOMERS TO ENTERPRISE ASSET MANAGEMENT .................3-1 Developing a Good Asset Inventory......................................................................................3-2 Collecting Asset Equipment Data..........................................................................................3-5 Developing and Employing Analytical Models.......................................................................3-9 Employing Decision Support Tools .....................................................................................3-15 ix
  9. 9. 4 BREAKING OUT TOWARD A MATURE ENTERPRISE ASSET MANAGEMENT PROGRAM ................................................................................................................................4-1 Increasing Sophistication of Decision Support Tools ............................................................4-2 Ranking and Screening ....................................................................................................4-2 Ranking........................................................................................................................4-2 Screening.....................................................................................................................4-4 Systems-Level Thinking ...................................................................................................4-7 Project Prioritization and Investment Tools ......................................................................4-8 Improving Data Quality and Integration...............................................................................4-11 Developing a Data Strategy............................................................................................4-12 Ensuring Efficiency of Data Collection and Management...............................................4-15 Ensuring Data Quality.....................................................................................................4-16 Providing For Data Access .............................................................................................4-16 Employing Critical Systems in the Information Technology Infrastructure ..........................4-17 Asset Management Technology Ownership...................................................................4-18 Data Mining Capability....................................................................................................4-19 Data Acquisition Layer ...............................................................................................4-20 Algorithms and Applications Layer.............................................................................4-21 Reporting Layer .........................................................................................................4-23 5 ADVANCED INFORMATION TECHNOLOGY CONCEPTS FOR ENTERPRISE ASSET MANAGEMENT............................................................................................................5-1 Information Technology Infrastructure for Advanced EAM....................................................5-1 Use of a Service Oriented Architecture in Enterprise Asset Management .......................5-2 The Natural Role of SOA in Asset Management .........................................................5-2 Business Processes and Models .................................................................................5-4 Enterprise Asset Management Repository of Services................................................5-6 Library of Algorithms and Calculations....................................................................5-7 Modular Approach to Asset Management...............................................................5-7 Visualization Services ...........................................................................................5-10 Automating Service Implementation – Re-usable Analytics ......................................5-16 Methodology..........................................................................................................5-17 Architecture for Re-usable Analytics .....................................................................5-18 Applicability to Asset Management .......................................................................5-20 Proof-of-Concept...................................................................................................5-20 x
  10. 10. Knowledge Management................................................................................................5-22 Advanced Concepts in Data and Decision Support Tools...................................................5-24 Accurate and Useful Cost Data ......................................................................................5-25 Advanced Decision Support Tools .................................................................................5-26 Long-Range Planning ................................................................................................5-27 Use of Simulation in Asset Management ...................................................................5-28 Opportunities for Estimating Failure Rates in Real Time ...........................................5-29 Use of Risk Management...........................................................................................5-30 Risk Management for the Asset Manager.............................................................5-31 Risk Management for Asset Operator...................................................................5-31 Information Technology Requirements for Risk Management ..............................5-32 Illustrative Example for Risk Management............................................................5-33 6 CONCLUSIONS AND RECOMMENDATIONS ......................................................................6-1 7 REFERENCES .......................................................................................................................7-1 A SURVEY OF EXISTING ASSET MANAGEMENT CAPABILITY ......................................... A-1 List of Asset Management Capabilities ................................................................................ A-1 xi
  11. 11. LIST OF FIGURES Figure 3-1 EPRI PM Basis Database: Equipment Model Example............................................3-7 Figure 4-1 Three Layer Architecture for Asset Management and Performance Monitoring.....4-20 Figure 5-1 Asset Management Module Interaction ....................................................................5-8 Figure 5-2 Example Calculation Chain Decomposition..............................................................5-9 Figure 5-3 Example Reliability-Profitability Phase Plane Graph ..............................................5-11 Figure 5-4 Example Cumulative Benefit NPV Versus Cumulative Investment NPV Graph .....5-12 Figure 5-5 Example Project Uncertainty Comparison Graph ...................................................5-13 Figure 5-6 Example IRR Versus Risk of Loss Graph...............................................................5-14 Figure 5-7 Example IRR Uncertainty Histogram ......................................................................5-15 Figure 5-8 General Analysis Flow of a Calculation ..................................................................5-17 Figure 5-9 General Architecture of Re-Usable Acquisition Component...................................5-19 Figure 5-10 General Analytic/Calculation ................................................................................5-19 Figure 5-11 Circuit Breaker Measurements .............................................................................5-21 Figure 5-12 Influence Diagram for Tree Trimming Example ....................................................5-35 Figure 5-13 Tornado Diagram Displaying the Sensitivity Analysis for Tree Trimming Example ...........................................................................................................................5-36 Figure 5-14 Ten-Year SAIDI Scatter Plot Illustrates Useful Historical Data for Risk Assessment......................................................................................................................5-37 Figure 5-15 An Analytical Risk Model (Curves) Shows the Results of a Probabilistic Analysis, Compared with the Deterministic Expected Values (Vertical Lines) .................5-38 Figure 5-16 Portfolio Risk Trade-Off (Efficient Frontier) ..........................................................5-39 xiii
  12. 12. LIST OF TABLES Table 2-1 The Maturity Index Table .........................................................................................2-15 Table 4-1 Comparative Characteristics of Asset Management Analysis Levels 1, 2, and 3 ......4-5 Table 5-1 Information Available from Circuit Breaker Counts and Related Parameter Data..................................................................................................................................5-21 xv
  13. 13. 1 INTRODUCTION Integration of business applications across the electric utility enterprise has become a high priority in the electric utility industry to reduce information technology costs and realize a range of business benefits. Asset management, a business process that integrates with most other utility business processes, is particularly enhanced by integrated information technology (IT) solutions. Asset management is also a discipline that is developing a variety of new business applications to facilitate decision-making, and it depends on those applications integrating with enterprise systems such as work management, operations data historians, and financial systems. Integrating and automating solutions to asset management (from data acquisition, to calculations, to reports) that exploit a utility’s current IT system portfolio of enterprise systems from both commercial vendors and EPRI can reduce the number of applications. Enabling efficient integration of applications across business units can greatly reduce information technology costs and yield a range of business benefits. Similarly, improved data collection using those systems can substantially reduce the number of evaluation hours for asset managers and increase the timeliness of information for decision makers. The propose of this report is to provide guidance to assist utility information technology managers and asset managers alike in addressing the unique and particularly challenging IT needs for asset management. This project devotes particular emphasis to data collection, use of existing enterprise systems such as work management systems, as well as the integration and use of decision support systems for specific problems such as managing aging assets and monitoring asset health. This report focuses not only on the elements of an information technology plan but also on the progression of their development. By describing in detail certain aspects of asset management program development, the report provides the context in which the information technology infrastructure must operate and grow as well as the asset management capabilities that will result. This report also raises the bar for asset management considerably. While many companies can and will be satisfied with reaching a certain level of maturity in asset management, described here as “Organizing,” this report lays out the potential for further growth beyond that point. This growth is within reach because many of these programmatic improvements have and are occurring in more competitive industries like manufacturing. But further evidence in their attainability lies in the improvements demonstrated in the nuclear generation sector. Performance in that sector has increased dramatically, and some of that increase certainly can be attributed to the process improvements and information technology improvements that are described in this report. Some electric utilities have already begun to transfer nuclear power’s business improvements to other business units. 1-1
  14. 14. Introduction Chapter 2 of this report provides an approach for determining the maturity of asset management programs in an electric utility and their associated information technology needs. Performing a self-assessment against this maturity index will help an electric utility determine how to develop information technology for an enterprise asset management program. In Chapters 3 through 5, this report discusses important topics related to the improvement (or maturation) of an asset management program and its associated information technology infrastructure. At the end of each topic, the report summarizes the discussion in terms of a bulleted list of steps or concepts. Together with the criteria in the Maturation Index Table discussed in Chapter 2, the report attempts to provide a concise description amenable to self- assessment and developing an asset management information technology program. This report has drawn heavily from a number of EPRI asset management reports cited in the References, Chapter 7. These reports were developed in both power delivery and nuclear generation sectors. Each of those sectors has strong asset management research programs at EPRI, characterized in particular by a broad degree of utility involvement. 1-2
  15. 15. 2 ASSESSING MATURITY OF INFORMATION TECHNOLOGY FOR ENTERPRISE ASSET MANAGEMENT This chapter lays out an approach for determining the maturity of asset management programs in an electric utility. Performing a self-assessment against this maturity index will help an electric utility determine how to develop information technology for an enterprise asset management program. This maturity index approach is built upon the concept that an asset management program and its supporting information technology program must develop in concert. If one develops faster than the other, inefficiencies will result. Either asset managers will be unable to get the information they need, or they will spend time feeding information systems that they are incapable of using. The maturity index also provides insight into the risks of programmatic setbacks that are inevitable in a business transformation of the kind entailed in asset management. Accepting setbacks and turning them into opportunities for organizational growth is an important precondition to successful enterprise asset management. In this regard, the maturity index also includes criteria related to management support and the role played by business analysts in the company. Both of these organizational factors are important to business transformation. The following maturity index is not a quantitative, percentile-based approach for self-assessment common to many utility benchmarking efforts. Few companies will fit in the highest “continuously improving” category. More than a quartile may fit in the lowest “reacting” category. Currently, there are no studies which have systematically evaluated the maturity of electric utility asset management practices upon which a quantitative quartile approach could be based. Nevertheless, EPRI research programs provide sufficient experience upon which to base a useful maturity index and self-assessment approach for enterprise asset management. EPRI research reaches both member and non-member asset management practices across the full gamut of electric utility business units. Additionally, the Nuclear Asset Management industry working group, operated under the auspices of the Nuclear Energy Institute and actively supported by EPRI, provides excellent access to the practices and lessons learned of that portion of the electric power industry. It is upon this broad base of experience that this maturity index has been built. The five-category maturity index is adapted from a similar approach developed by the Department of Transportation for asset management of roadways [1]. The DOT indices are in turn based on maturity indices for general application to software development [2-5]. 2-1
  16. 16. Assessing Maturity of Information Technology for Enterprise Asset Management However, there are two important changes: 1. the criteria of the indices in this report are specific to the electric utility industry, and 2. the criteria reflect recent developments in enterprise level information technology. Finally, the criteria reflect the experiences of the author in developing asset management and associated information technology programs with a large number of generation and power delivery business units as well as the abovementioned EPRI and industry groups. In this effort for enterprise asset management, we do not attempt to reach an exhaustive level of detail in the individual criteria. Largely, this choice reflects the fact that different business units at a utility often have uneven levels of experience with self-assessment. That said, this work is not intended to address the lowest common denominator. Rather, it is intended to be practical and effective in bringing multiple business units together to facilitate a successful enterprise asset management program. The level of detail is judged to be within reach of those with little institutional experience in self-assessment and yet still a valuable guideline for those at the high end of the self-assessment scale. The remainder of this report chapter describes the levels of maturity and their implication to enterprise asset management and information technology development. We start with the important attributes of enterprise asset management programs, especially as they relate to information technology. Finally, we present the Maturity Index Table which provides criteria or representative characteristics for each attribute at each level. In subsequent chapters of the report, we delve further into topics related to these criteria. Those topics are arranged in a manner to provide assistance in developing a roadmap for a more mature enterprise asset management program. While that discussion is at the insight level, the report makes reference to a variety of EPRI reports and other sources where the reader can look for further detail. Asset Management Program Maturity Levels This approach defines five levels of maturity for asset management programs: 1. Reacting 2. Awakening 3. Organizing 4. Processing 5. Continuously Improving Essentially, these levels vary from no asset management program to a living asset management program. 2-2
  17. 17. Assessing Maturity of Information Technology for Enterprise Asset Management In general, a company will have to move through each of the intermediate levels to reach a higher state. As with any approach to a difficult problem, it is important to take the long view on developing asset management capabilities. This long view does not mean that every step should be a small step. Rather, the long view means that every step should be measured, followed by an evaluation of results and possibly an adjustment to the overall plan. Employees are often skeptical of organization change, and asset management programs should be undertaken with the same management attention and determination given to other organization change initiatives. The levels of maturity of an asset management program are most influenced by management interest and support in asset management. Because effective asset management is an integral part of good business management practice, asset management maturity is also strongly influenced by the organizational roles of business analysts and by management adoption and employee acceptance of a philosophy of continuous process improvement. Information technology plays an equally important role in maturing asset management programs, over and above the fact that it is a focus of this report. The importance to asset management of accessing data and communicating information make information standards and data mining capabilities the veritable nervous system of a living AM program. Even more relevant are the work flows and business processes, the muscle behind turning AM concepts into productive work. These two parts of the information technology infrastructure are directed by decision support applications. These applications reside in the brain of AM. Not only do they perform the sometimes simple and sometimes sophisticated calculations that identify the best actions to take, but they also simulate the outcome of those actions. The following paragraphs describe each of the maturity levels in business and information technology terms. Subsequently, the report describes more detailed attributes of maturity and displays them for each level in tabular form. Reacting A company in the “reacting” state is really not doing asset management. Executive management may well be actively skeptical about asset management techniques. Regulatory requirements dominate decision making. Consequently, few if any employees are willing to risk moving beyond strict adherence to regulatory requirements and manufacturer recommendations. If an infrequent, but high consequence event occurs, such as a major equipment outage, it will likely catch the company by surprise, and the recovery of company performance, and share price will be extended. Investments in information technology for asset management likely will fail or have little impact at the enterprise level. But, if the experience is maintained within the corporate culture, it will nevertheless be valuable when the company “awakens”. Awakening A company in the awakening phase has management that is aware of asset management goals and techniques. Such a company is much more likely to have risk-taking employees who undertake asset management initiatives at the “local” level. But a company that is “awakening” is also more likely to have initiatives that fail. Failure generally occurs because it is difficult for 2-3
  18. 18. Assessing Maturity of Information Technology for Enterprise Asset Management a risk-taking employee to sustain asset management initiatives when they cross organizational boundaries. Capturing the lessons learned from the asset management activities undertaken by risk-taking employees is an important step in getting to the next level of maturity. If risk taking is discouraged by management, these failures could result in a fall back to the reacting phase. At the awakening level, management and employees are getting used to the role of performance indicators in process improvement. However, because these indicators are typically incomplete and sometimes difficult to use, a dangerous skepticism to asset management can result if the indicators are not improved. Web based performance indicator systems are likely, but they probably lack associated drill down and analysis capability. These capabilities are probably provided by power users of such generic tools as Microsoft Office. Valuable asset management experience is starting to be gained with the use of equipment condition information, a broadening of the role of business analysts, and the development of business processes centered on use of Enterprise Asset Management (EAM) and Enterprise Resource Planning (ERP) systems. Information technology investments in asset management are still risky, but building blocks like EAM and ERP systems are starting to be exploited. Organizing An organized company is well along on the road to success for enterprise asset management. For the most part though, they have succeeded with power users employing isolated tools, by improving data access for a broad set of users, and as a result of increased management acceptance. The organized company has made one very important step toward a high level of maturity in enterprise asset management. They have overcome the inertia inherent in large EAM and ERP installations and have begun to establish a long-range plan for information technology improvement. Geographic Information Systems (GIS) and mobility data systems are being installed and integrated. The long-range plan includes a continuous improvement effort that encourages widespread input from employees. Because of the abovementioned successes, investments in asset management information technology are much more likely to generate benefits, even if the results are not always the exact ones that were initially planned. A change in management can still threaten the asset management culture, because it is mostly leaders and power users who are exploiting the value of asset management techniques and the associated information technology investments. Nevertheless, benefits from asset management are accruing, and the foundation exists for a substantial improvement in asset management capabilities. Processing The processing company has recognized that a good asset management program involves not only enjoying successes in business improvements, but institutionally overcoming failures, including damaging ones. This attribute is in evidence in a number of ways. First, important pilot efforts are underway to improve both the information technology and the business processes surrounding and encompassing asset management. Second, cost data is created, collected, and analyzed with little or no angst or retribution. Third, organizations share information effortlessly, even while they compete internally to show the most improvement. 2-4
  19. 19. Assessing Maturity of Information Technology for Enterprise Asset Management Specific to asset management information technology, data systems are rapidly maturing with costs dropping and benefits increasing. Part of this is improvements in technology, but a process approach to data that emphasizes quality is being built upon the experience gained from the use of condition and cost data and the associated lessons learned gained during the “organizing” phase. Performance monitoring and decision support tools are much better understood and relied upon. Simultaneous improvements in business process modeling, software integration, and knowledge management lay the foundation for further information technology improvements. But most importantly, the active support of executive management and the team work between business analysts and line management is reaping benefits and setting the stage for further improvement. Continuously Improving The continuously improving company is robust and can withstand and even benefit from changes in the marketplace and regulations as well as the occurrence of an infrequent adverse event. The strength of the company is in part due to the flexibility of its plans as well as completeness of its strategy. Performance monitoring, analysis, and improvement are a way of life. Performance goals are set based on value, and their relationship to stakeholder goals is clearly specified, explicitly modeled, and measurable. Quality assurance and corrective action processes are widely embraced. Suboptimal performance is seen as a step toward optimal performance as opposed to a reason to start over. Cost information is collected, verified, and analyzed at the individual asset and business process level. Condition information is integrated with degradation models and used in a wide variety of decision support tools. Optimization and simulation techniques are employed, as are risk management techniques. Information standards and a Service Oriented Architecture (discussed in Chapter 5) are used to facilitate information technology that supports enterprise asset management. Business processes are not only modeled, but intimately associated with the IT infrastructure. Users can specify the asset management processes and techniques they want automated in their own terms, and the IT department can readily and accurately develop the corresponding services and integrate them into existing applications. Knowledge management techniques and tools are used systematically and in conjunction with decision making and decision support tools. Executive and line management has ensured that asset management is part of the corporate culture. Business analysis is consistently and routinely done by many employees. Management understands uncertainty and risk, and investments are made accordingly. Managers of financial assets and managers of physical assets speak the same language and work together to find the right balance between the constraints of the market and the constraints of the physical plant. As can be seen from the descriptions of the five maturity levels, investment in information technology for enterprise asset management is not without its challenges. The road from “reacting” to “continuously improving” can be a long one. Certainly setbacks will occur during 2-5
  20. 20. Assessing Maturity of Information Technology for Enterprise Asset Management the trip. But if an incremental approach is taken and lessons are learned along the way, continuously improving will become the natural destination. The Attributes of an Enterprise Asset Management Program This report employs seven different attributes to describe important aspects of maturity in an enterprise asset management program. One attribute addresses the information technology infrastructure directly. Four attributes address enterprise asset management capabilities which require critical support from information technology. Two attributes address organizational factors, e.g., management support, which are critical in to the success of information technology investments. Of the seven total attributes, three have additional sub-attributes that allow the criteria to focus in on key capabilities. The seven attributes and their corresponding sub-attributes are: Data Collection and Use – General Capability – Condition Data – Cost Data Performance Monitoring Decision Support Capability – General – Investments – Risk Management Business Process Documentation and Modeling Information Technology Infrastructure – General – Knowledge Management Business Analysis Role Management Support Data Collection and Use Data collection and use is a critical attribute for an enterprise asset management program. Data needed for asset management is often input or collected by others in the organization. Maintenance workers record labor hours and describe the condition of equipment. Operators record log entries and the number of times equipment has operated. Reliability engineers report equipment failures. Most times these collectors of data have different uses for the data than asset managers. Because data is often not integrated between applications, basic things like equipment names often differ, yielding inconsistencies and making it difficult to merge data from different 2-6
  21. 21. Assessing Maturity of Information Technology for Enterprise Asset Management sources. These problems are well known, even in the reacting or awakening organization, but they are difficult to solve without organizational willpower. Often it is the installation of EAM, ERP, GIS, or mobility systems – the backbone of asset management information technology – that brings these problems to the fore. Those companies that let these difficulties diminish the value of information technology will not mature. Those companies which develop work processes to ensure data consistency and accuracy, which break down organizational barriers between collectors and users, and which increasingly expose the data to use by decision support tools will improve the value of data and mature their asset management programs. Standardized data mining tools often help to contribute to success. Equally important is a high quality asset inventory that is used in multiple applications. Being able to find a variety of sources of data for a specific piece or type of equipment will naturally expose issues that need resolution, as well as dramatically increase the value of the data that already exists or is being created in the backbone systems mentioned above. Two kinds of data, asset condition information and cost information, are particularly important to the maturity of asset management programs, largely because developing them is difficult. Consequently, the maturity index drills down on these types of data. Condition data, information that exposes the health or condition of a piece of equipment, naturally develops out of an improving maintenance program. Typically maintenance programs focus on equipment manufacturers’ recommendations or historical rules of thumb, often causing maintenance to be done a time intervals that are independent of the frequency and severity of use. Generally, maintenance planning will be the first asset management application of condition data. But condition data plays an important role in life-cycle planning as well. The most mature programs combine condition data with degradation models to predict asset performance. Cost data poses other challenges. Electric utility cost data is typically driven by two considerations. Initially, cost data is collected primarily for regulatory performance reasons. As a result, costs of individual assets and business processes are difficult to determine. With the installation of EAM and ERP systems, more and better information becomes available. Yet the quality of cost data is still limited because of employee time charging practices. Generally, EAM systems are populated only with labor hours for maintenance personnel. Engineering and management charges remain as indirect costs. But since engineering and management time is often spent on problems or special projects, their costs are underestimated, and the net costs and benefits of such programs are inaccurately estimated. Another typical problem is that contracted charges are usually reported as lump sums rather than broken down by task, which can provide similar misleading indications. An important step to maturity occurs not only when these problems are solved, but when costs are estimated by activity. Activity Based Costing (ABC) is a well-known and well-described discipline that can address this need. Another important process improvement is the use of cost estimating and cost control techniques. 2-7
  22. 22. Assessing Maturity of Information Technology for Enterprise Asset Management Performance Monitoring Performance monitoring, while typically done for other reasons, is an important discipline in the asset management process. Equally important, the information technology infrastructure to support it often has ancillary benefits to asset management functions, e.g., portals and data mining tools. But performance monitoring can also be an important barrier to maturity. Many performance indicators, even those developed with improving techniques such as Balanced Scorecard, can be developed without a clear and measurable link to value. The first indication of maturity in performance monitoring occurs when more time is spent analyzing the meaning of the indicators than manually inputting data and calculating them. Once the real meanings of indicators are revealed by a record of analysis, three things can happen. First, more employees see the value of indicators and more are developed. Second, indicators become a part of a process for business improvement. Finally, and perhaps ultimately most importantly to a mature enterprise asset management program, models of value develop. The most desirable model is a corporate value model (see EPRI reports 1001877, 1012954, 1012501) that is hierarchical in nature. Such a corporate model is based at the top on models of stakeholder goals and at the bottom on models of the performance of assets, e.g., degradation models. In the middle, the corporate value model must be clearly related to the model used in decision support tools for investments. Even if these models develop independently in different organizations, it is important that they develop. But eventually those models will have to be consistent across the enterprise. From an enterprise perspective, there are two good opportunities for developing consistent modeling disciplines across business units. More and more executive management teams are comparing asset investment strategies across the enterprise, looking at investments as diverse as call centers for distribution in comparison to generating capacity increases at nuclear power plants. Another opportunity exists for maintenance and engineering departments in generation and transmission. Some of the highest valued assets in each are large transformers. Consistency here can save significant costs because monitoring these high valued assets can be expensive and the lessons learned from their use even more so. Decision Support Capability – General Decision support capabilities pose some of the most difficult problems in asset management, both from the information technology perspective and from the organizational perspective. From the information technology perspective, decision support capabilities provide intelligence or logic that should be embedded in EAM systems. From the organizational perspective, decisions on maintaining and replacing assets are often simple rules of thumb, typically based on time since the last maintenance activity or age of the equipment. Sometimes these rules of thumb are based on failures, e.g., replace a cable after two failures. These rules of thumb are easy to understand and easy to load into EAM systems. Moving behind this stage requires overcoming barriers of management and employee understanding. Skepticism of new techniques that are difficult to understand is one aspect of the problem. But, many times the developers and users of decision support capability are insensitive 2-8
  23. 23. Assessing Maturity of Information Technology for Enterprise Asset Management to the importance of the role played by gaining widespread understanding to achieving acceptance and use of those tools. Successful decision support capabilities often “communicate” in new, but understandable rules of thumb. On the information technology side, many decision support tools desire or require integration with diverse sources of data, e.g., data beyond that included in EAM and ERP systems. Data stored in image or text form in design documents is a good example. Eventually, as decision support tools are applied to an increasing number of assets and as they increase their need for the amount and type of data, software integration becomes desirable. Only recently have EAM and ERP systems begun to open up their integration capabilities. Even if a utility has procured an open brand of EAM/ERP system, they still have to upgrade to obtain the capability. Consequently, the maturity of decision support capability eventually becomes linked to the maturity of information technology. Another important concept behind the maturity of decision support tools is the maturity of the models upon which they are based. Maturity in models is best assessed by their sophistication and their documentation. Typically models first develop in the awakening or organizing phase and are based on judgment of employees and facilitators. Such models have several distinguishing characteristics and corresponding limitations. First, the models tend to be qualitative and the basis for the relationship between the observed value and condition is often not clearly documented. Second, observed conditions are often limited to what is readily knowable rather than what is needed to be known. Third, when the models do have a number of concerns being represented, the criteria used to represent the concerns may overlap or even be contradictory. Fourth, the models may not be tied to specific actions corresponding to the conditions observed. Basically these types of models lack the rigor of an integrated and comprehensive view. Maintenance planning tools often contain models with these types of limitations. The most common approach uses a “stop light” in which green, yellow, and red represent okay, watch, and act. The conditions that determine the light’s color in the maintenance planning tool are often related to the existence of one or more indications of component degradation. (A quantitative approach would estimate failure rate or remaining life based on observed equipment condition and a degradation model.) More than one negative indication typically produces a red light. (But these indications can easily overlap. For example, consider a case with two negative conditions, one caused by exceeding a code condition and one caused by a concern about personnel safety. If the basis of the code condition is also personnel safety, the same concern is counted twice.) A red light tells the maintenance planner that maintaining the component high priority. Because the component is high priority, the scheduled maintenance activities for that component are high priority. (An alternative is triggering the maintenance activities corresponding to the observed degradation mechanisms.) However, use of models with limitations is part of a maturing asset management program. Gaining experience with these simple models and gaining management and employee acceptance are usually a precondition for obtaining the resources to develop more sophisticated models. A maturing asset management program must overcome organizational barriers like employee and management acceptance. Learning how to implement an approach with limitations is much more 2-9
  24. 24. Assessing Maturity of Information Technology for Enterprise Asset Management valuable organizationally than learning nothing at all. Equally important, the “sub-optimal” approach is almost always better than the traditional approach based on rules of thumb. Utilities will find it difficult to mature beyond the organizing level if they do not make a concerted effort to document the bases of their models. Sometimes this documentation can be developed as part of a knowledge management effort, including efforts to capture knowledge from an aging workforce. As the documentation improves, models used throughout the organization become more consistent and often times the same or similar models can be used for maintenance planning, project prioritization (investment), and even operations risk. When models become consistent with information standards and when they become compatible among finance, business processes, and equipment, a truly mature asset management program exists. The organizational growth from simple to complex models follows the progression of decision support tools based on ranking to those based on optimization techniques. The simple to complex path also lends itself to the application of screening techniques. Screening techniques are critical because they allow simple models to be applied to simple problems, thereby reducing the cost and turnaround time for overall evaluations. Two or three levels of evaluation are probably sufficient with the lowest level being a bounding calculation and the highest level including detailed measures of uncertainty and risk. Decision Support Capability – Investments Decision support tools to evaluate investments, sometimes called project prioritization tools, are one of the most important aspects of asset management maturity. Project funding often starts based on regulatory requirements and capacity additions and, when additional capital is available, possibly some limited modernization. As maturity increases, regulatory projects no longer become sacrosanct but instead are evaluated more rigorously. The temptation to add project scope to beyond regulatory requirements often overwhelms the reacting and awakening company. But as projects become more precisely evaluated and broken into smaller parts with a variety of alternatives, it becomes organizationally easier to increase the sophistication of investment tools. Developing alternatives is important, but maintaining them in the investment decision process until final budgeting is even more crucial. Another characteristic of a maturing asset management program is the increasing precision of long-range plans. Long-range plans help avoid surprises in increased expenditures and reduced levels of service because of the need to replace large assets. They also provide a repository for unfunded projects which may be good investments in other years. Long-range plans also provide a framework to monitor changes in technology and to create a vision for its incorporation into an electric utility asset base well known for its long life time. In a mature asset management organization, long-range plans include contingency plans for dealing with uncertainties. Lastly, as companies mature, their focus on capital begins to extend to O&M. The extension first appears in large, infrequently scheduled O&M activities, like major overhauls or refurbishments. Since these do not necessarily occur in a levelized manner, it is inefficient to include them in a routine maintenance budget. Often O&M budgets are the same as or a percentage different from prior years. Said another way, they are not strictly based on need. But employees are less fungible than capital, so often there is logic to small swings in O&M budgets. 2-10
  25. 25. Assessing Maturity of Information Technology for Enterprise Asset Management But companies with the flexibility to move people from O&M projects to capital projects, from one large asset to another or even from one department to another will have the greatest capability to take full advantage of asset management techniques. In a mature asset management organization, capital costs trade-off against O&M costs in a lifecycle cost analysis. Decision Support Capability – Risk Management Risk management is becoming an ever increasing expectation in our world. Shareholders want to know that needless risks are avoided and that unavoidable risks are being hedged or mitigated. Investors and regulators have seen that companies with risk management programs often run more efficiently. The public expects interruptions in service and sudden price increases to be minimized. Risk management tends to enter the asset management program in higher levels of maturity. The data and modeling techniques needed are often the most complex of the tools in the asset manager’s toolbox. Similar to condition information and decision support tools in general, there is a logical progression from simpler and qualitative to more sophisticated and quantitative analysis of risks. What is most important though is the understanding that uncertainties in investments are a risk that can be managed, often using the same basic concepts that financial asset managers use. Once a company can understand the level of risk it wishes to accept, with effort it can find an investment portfolio that matches that risk. Often it can identify hedges for the risks as well, ranging from traditional fuel futures contracts to additional research in new technology. Measuring the options value of projects, especially additional generation, is becoming more commonplace and is more often expected by investors and regulators alike. Another aspect of risk is preparing for and, if possible, designing against so-called low probability, high consequence events. Often traditional engineering does not explicitly address these types of risks, whether they are natural events, such as hurricanes, or attributes of complex technological systems, such as our increasingly interconnected grid. Often these events lead to very high losses and dislocations, when prudent, low cost investments would have been available to prevent or mitigate them, had they only been increased in priority. Other times, prevention requires substantial investment; risk management techniques will help to make an informed decision on raising the capital necessary to implement them. Business Process Documentation and Modeling For the most part business process documentation and modeling has ranged from a capability many managers think is routinely done to an esoteric capability that management has little desire to sustain. But two important developments are changing that perspective. First, business process modeling has more and more been included in benchmarking initiatives that have led to important improvements in efficiency and consistency in company business practices. As utilities grow larger through mergers and acquisitions, common business processes are seen as a way to increase significantly economies of scale. More and more, utilities are realizing that modest and determined investments in business process modeling can yield improvements in 2-11
  26. 26. Assessing Maturity of Information Technology for Enterprise Asset Management generating capacity and service levels as well as capturing knowledge from an aging workforce and demonstrating prudence to regulators. The second important development is the increased use of business process models in the development of effective information technology infrastructures. Technologies like workflow have been particularly important to improving the effectiveness of EAM systems. New initiatives like Service Oriented Architectures (SOAs) are also dependent on good business process models. In this latter approach, described more fully in Chapter 5, business processes become the specification for information technology services like asset management. Because business processes can be described by asset managers, the “I’ll know if you’ve provided it when I see the software” syndrome can be better managed or hopefully even avoided altogether. Information Technology Infrastructure – General Of course, this chapter must turn directly to the infrastructure upon which the other asset management technology is based. Perhaps the best indicator of maturity of an asset management infrastructure is the success of investments in IT. That does not mean that more investment is necessarily better. Rather, it means that getting effective results out of the information technology infrastructure is a strong indicator of the readiness of that infrastructure to support the complexities associated with mature asset management programs. Because of this strong relationship, this report recommends (see Chapter 6) that electric utilities strongly consider using asset management business processes as the test cases for some information technology infrastructure improvements, including for example Service Oriented Architecture, Knowledge Management, and Mobility Systems. The first indication of maturing asset management programs is the successful installation of EAM and ERP systems. Here we stress the word successful. These installations are difficult and sometimes just getting them done is a success. But as we have mentioned above, seeing the installation progress to the point that good data is loaded and that new data is both valuable and accessible is equally important. For distributed assets, GIS capability becomes equally important. Mobility systems are likewise an indicator of maturity, as long as they are accompanied by a business process which ensures the data needed by asset managers is captured. When moving into the processing and continuously improving phases of asset management programs, information standards facilitate a flexible architecture and go hand in hand with SOA and knowledge management. Similarly, improvements in integration techniques characterize the higher states of maturity. Finally, we have already pointed out the potential gains from information technology infrastructure when it is accompanied by business process modeling. Information Technology Infrastructure – Knowledge Management Knowledge management is important to asset management over and above the critical aging workforce concerns that the electric industry faces. Knowledge management also is an important enabler of model development and business process modeling, largely because capturing knowledge from people in a systematic way is so important to those efforts. 2-12
  27. 27. Assessing Maturity of Information Technology for Enterprise Asset Management In this regard, it is important to truly recognize the amount of undocumented information that resides in employees heads about how business is done and how equipment functions and fails. Besides the areas we mentioned already, qualitative approaches to condition assessment and to risk management are often based on expert judgment. The more that information is captured when the organization is in the organizing phase, the easier it will be for the company to progress to higher levels of maturity. The reason is that knowledge capture techniques would first be piloted on simpler models and decisions, yet those decisions would be sufficiently business critical to gain organizational interest initially and organizational appreciation when the pilots are completed. In the most mature asset management programs, knowledge is captured as a matter of course with rigorous methods. Similarly, such knowledge is easily accessed, verified, and modified by interested parties. Because that knowledge (otherwise known as “bases” for models and processes) is captured effectively, decision support tools can grow in complexity while at the same time remain understandable to managers and people who participate in the process. Business Analysis Role The last two attributes are truly organizational in nature. While they do not involve information technology directly, they do affect the likelihood that asset management information technology will be used effectively. This attribute relates to the organizational role played by business analysts. In less mature organizations, business analysts play a more traditional role involving reacting to management and line organizations. As organizations mature, business analysts work more closely with line organizations until they even become embedded directly in them. In the most mature asset management organization, the principals of value creation and costs are so well understood by employees as a whole that it almost seems like each employee is a part time business analyst. Another aspect of the role of business analysis in a mature organization is reflected in changes to the budgeting process. Budgets move from annual to quarterly. Risks of exceeding the budget are known, and the conditions or events that underlie those risks are known and monitored. Management Support The second organizational attribute and quite probably the most important attribute in asset management is management support. Management benefits most from asset management techniques and associated information technology, largely because the type of information they need to do their jobs is provided in a more timely and accurate manner. But it is more than that. Management can better explain to shareholders and regulators why decisions were made as they were and the difference between bad luck and bad management can be distinguished. Another important benefit to management is realizing the value they receive from the investments they are making in the EAM and ERP systems that form the foundation of the enterprise asset management information technology infrastructure. Seeing that investment bear fruit is a critical part of their job performance. 2-13
  28. 28. Assessing Maturity of Information Technology for Enterprise Asset Management Consequently, management support is a natural outcome as well as a natural precondition to asset management success. Asset management matures as management takes interest in the topic, whether it be because competitors use it or because they need to justify large IT investments. As management works through the organizational transformations in asset management, they become a critical part of the process, and executive sponsorship is necessary. In the highest level of maturity, executives, managers, and employees all become asset managers, and asset management processes themselves appear seamless. The Maturity Index Table of Criteria A company’s progression along these seven attributes will necessarily vary with management interest, employee capabilities, and information technology. It is expected, for example, that cost data collection and use may progress slower than general data collection capabilities or that risk management might lag other decision support capabilities. In part these differences in maturity can be due to different conditions or management priorities. For example, sometimes a moderate or high risk event must occur before management aggressively pursues risk management. A utility with financially oriented management may move earlier to improve cost data. Engineering oriented management may move more quickly with condition data. This subsection provides a table of criteria to help measure what level of maturity exists for each attribute and sub-attribute. The criteria are intended to be useful for both self-assessment and guidance for improvement. The criteria were developed based on a variety of sources (1, 6) as well as previously mentioned experience of the author and the institutional experience of EPRI. In subsequent chapters of this report, the report drills down on important topics organizing them loosely by level of maturity. Some other topics are described separately, in part because they are ubiquitous and in part because to avoid distraction from the more important topics. Chapter 3 describes first steps for those who fit the reacting and awakening maturity levels. For example, Chapter 3 focuses in on data collection and use and initial steps with decision support tools and performance monitoring. Chapter 4 focuses on what is often the pivotal level of maturity, namely Organizing. At this level, the foundation of asset management information technology infrastructure is in place, namely the EAM and ERP systems. But the use of ranking techniques and condition information has also opened up new interest in improving the management of assets and greater understanding of the benefits and challenges involved. Not many years ago, the Organizing level was close to the pinnacle of asset management maturity. But with the advent of improvements in management techniques and information technology, most of which are particularly pertinent to asset management, new opportunities exist for even more mature asset management programs. Chapter 5 talks about some of these improvements, the most important of which may be the Service Oriented Architecture. All of the above mentioned topics in Chapters 3 through 5 are addressed by the criteria in the Maturity Index Table. The table puts them in perspective with how they fit into the bigger picture offered by all the seven attributes. 2-14
  29. 29. Assessing Maturity of Information Technology for Enterprise Asset Management Table 2-1 The Maturity Index Table Maturity Index Reacting Awakening Organizing Processing Continuously Attributes Improving Data Collection and Use Data collection and Investment made in Data collection Data integration Both the collectors - General Capability processing, including data collection and capabilities include efforts have and the users of data equipment and processing mobility data. eliminated many collection and process failures, capabilities often has inconsistencies and processing systems serves primarily limited influence GIS capability, e.g., reduced data are involved in regulatory beyond the map-making collection costs system specification, requirements. immediate user and capability, is in use. development, use, many investments fall Equipment data and continued Inconsistent and short of their original Some success has collection is primarily improvement. unreliable data is the goals. been achieved in automated norm. multi-organizational Information collection initiatives, e.g., Data collection and standards play an operations and use is treated as a important role in engineering. process, with data streamlining and quality and feedback improving data Data mining tools being key objectives. collection. begin to be standardized across Data collection business units activities increasingly include business A well-thought-out processes. and verified asset inventory, developed perhaps for EAM and ERP systems but used in multiple applications, helps to standardize access to data. 2-15
  30. 30. Assessing Maturity of Information Technology for Enterprise Asset Management Table 2-1 (continued) The Maturity Index Table Maturity Index Reacting Awakening Organizing Processing Continuously Attributes Improving Data Collection and Use Little if any condition Condition data has Asset managers are Condition data is Condition data and - Condition Data data is collected. limited and aware of the variety increasingly used with degradation models haphazard use in of available condition degradation models are well-linked and maintenance or information and have to predict asset validated. operations and is begun to tap that performance. infrequently used in information for high Use of expert opinion engineering or valued assets and to generate condition lifecycle decisions. business processes. information is well- controlled and well- A significant fraction understood of condition data is input by experts, but the associated processes are typically ad hoc. Data Collection and Use Cost data is collected Cost information is Cost information from Activity Based Cost information is - Cost Data primarily for available in EAM/ERP EAM/ERP systems is Costing is collected, verified, regulatory purposes. systems but is not mined and evaluated, implemented and and analyzed at the validated. but expenses like deficiencies in cost individual asset and contractor, data collection are business process Cost data is not management, and identified and level. widely used, but may engineering costs are evaluated for be used by selected not detailed. improvements. Time charging by departments or asset and business individual power Life-cycle costing is Time charging by process is company users. beginning to be done asset and business policy, and its effectively. process is initiated. importance is understood by Cost control employees. techniques are routinely employed. Variability in indirect costs is understood. 2-16
  31. 31. Assessing Maturity of Information Technology for Enterprise Asset Management Table 2-1 (continued) The Maturity Index Table Maturity Index Reacting Awakening Organizing Processing Continuously Attributes Improving Performance Monitoring Performance Performance Portals and data Performance Performance monitoring serves Indicators exist, e.g., mining capabilities monitoring is widely monitoring, analysis, primarily regulatory Balanced Scorecard, support performance accepted. and improvement are requirements. but few if any monitoring and allow a way of life indicators are based access to a much Employees show throughout the on models and greater amount of individual initiative in company. analysis of historical data, but that data is developing and data. primarily used by exploiting their own Performance goals power users. indicators are set based on Data processing to value and their maintain the Performance indicator relationship to indicators often takes models become more stakeholder goals is more time than is commonplace. clearly specified, spent evaluating the explicitly modeled, indicator results. and measurable. Performance monitoring and resource allocation are clearly related. Indicators of risk are monitored. 2-17
  32. 32. Assessing Maturity of Information Technology for Enterprise Asset Management Table 2-1 (continued) The Maturity Index Table Maturity Index Reacting Awakening Organizing Processing Continuously Attributes Improving Decision Support Regulatory Decision support Decision support Decision support Decision support Capability - General requirements tend to tools begin to be used capabilities include tools are used widely, capability includes dominate decision by individual ranking and what-if and managers and optimization and making. innovators. However, analysis. executives simulation tools. accurate input data understand their Rules of thumb and and management Screening or bases and results. Models are used manufacturer acceptance lag. importance analysis routinely for finance recommendations are techniques are used Decision support and business the basis for most to determine the level tools for asset processes, as well as asset repair and of detail for decision replacement and for individual assets replacement support analysis. maintenance planning and systems. These decisions. use condition models are well Management information and documented for ease Staff skill and awareness of degradation models. of understanding and experience is the decision support is update. basis for most increasing. Probabilistic decisions and that information is Staff skill and knowledge is neither Ranking techniques beginning to be experience is managed nor are used extensively developed and used. incorporated in captured. in maintenance models and decision planning. Data collection for making as a matter of ranking applications established process. is increasingly automated, and management has confidence in the results. 2-18
  33. 33. Assessing Maturity of Information Technology for Enterprise Asset Management Table 2-1 (continued) The Maturity Index Table Maturity Index Reacting Awakening Organizing Processing Continuously Attributes Improving Decision Support Regulatory A process for A robust ranking The strategic Investment risks and Capability – Investments requirements evaluating capital process emerges for planning, project returns are evaluated dominate capital investments exists, capital investment. prioritization, and and balanced. investment decisions but the resulting budgeting processes for existing major investments are still Large O&M are well integrated, O&M budgets are assets. strongly influenced by expenditures are and decision support increasingly flexible in management separated from O&M tools are used responding to O&M budgets are preferences. budgets and ranked. throughout. changes in based primarily on investment strategy. prior year spending. A robust set of Long-range plans for alternatives are capital investment are The hidden costs, generated as projects developed and risks, and benefits of are defined. comprised of new technology are individual projects. well understood. Alternatives are Optimization considered techniques are throughout the employed in decision process. determining the project investment Project cost and portfolio, including the performance are selection of measured and alternatives. compared against original estimates. Lifecycle costing is used to trade off capital and O&M expenses. All major assets and asset types have long-range plans. 2-19

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