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Information Governance Framework for Engineering Asset Management Organisations

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  • Good afternoon everyone, My name is Anastasia Govan Kuusk and l thankyou for your time this afternoon in assessing my PhD proposal. The objective of my PhD research is to determine an integrated Information Governance Framework for Engineering Asset Management functions in Australian organisations. How l will do this is the subject of today’s presentation.
  • Today l will take you through why my research is important and the contributions it will provide to Engineering and Computer Information Science. We will start with some definitions of the key terms – IG, IT, OT, EAM Review the key literature Present the Research problem, questions and design Outline the Research contributions And Timelines
  • To understand the context of my research it is important to identify clearly the key concepts of IG, IT, OT and EAM
  • Firstly Information governance is the connector between technology and information (Pugh, 2011). It specifies the decision rights and a policy driven accountability framework to encourage consistent and desirable behaviour throughout the lifecycle (valuation, creation, storage, use, archiving and deletion) of information. It includes the processes, roles, standards and metrics that ensure effective and efficient use of information for organisations to achieve their strategic objectives (Caldwell, 2011). Information governance is designed to lower costs, reduce risk, and ensure compliance with legal, regulatory standards, corporate governance and market share (DeBois, 2010; White et. Al., 2007). It emerges from the science of computing (Targowski, 1998), information technology governance (Logan, 2010b) and regulation such as the 2006 amendments to the Federal Rules of Civil Procedure in the United States (Murphy, and Salomone 2011). Information governance is predicted to become mainstream in organisations in the next ten years from bottom up or top down approaches (Caldwell, 2011; Nicolett & Proctor, 2011).
  • Secondly IT defined in the International Standard IEC 38500:2008 as ‘Resources required to acquire, process, store and disseminate information’. Information technology may be more structured, transactional and of a strategic nature than operational technology, assisting commercial decision making such as in Financial Management Systems , billing enterprise resource management and email (Haider,2011;Rhodes, 2011), Enterprise Resource Planning, Enterprise Asset Management System, Customer Information System and Advanced Metering Infrastructure (Ventryx, 2011). Information Technology systems may including the capture of corporate records such as scanned invoices and approvals as evidence of business transactions (defined as approvals, financial implication or information required to be kept in accordance with legislation or regulations) into the business systems or standalone information management (IM or EDRMS) systems . The main purpose is to aggregate information for decision making, risk reduction and automate business processes to improve data quality and reducing costs through time reduction.   OT   Operational technology manages data concerned with the running of plant and equipment, is often event driven, producing real time data, managing mission critical production such as water pump throughput and stores large quantities of time series and condition data (Streenstrup, 2010). It includes supervisory control and data acquisition (SCADA), Geographic Information Systems (GIS) and Asset Management and supervisory Systems (AMS) (Haider, 2011; Ventryx, 2011) characterised by programmable logic controllers, proprietary sensors and chips, remote terminal units and telemetry networks managed by engineering staff instead of the Chief Information Officer (Jaffe, 2011; Waddington, 2008). The main purpose is to manage assets and is of a specialised nature (Koronios, Haider & Streenstrup, 2009). In summary IT manages business information not in real time and OT manages data from plant and equipment often in real time
  • EAM Engineering Asset Management (EAM) assists organisations to manage risks, meet short and long term strategic objectives and assist effective decision making for service delivery during the design, implementation and maintenance phases of infrastructure through systems and informing decision making (GAMC, 2004; Amadi-Echendu et al, 2010; International Infrastructure Management Manual; 2010; British Standards Institute, 2008; Brown et al, 2011; Too, 2011; CIEAM, 2010; Sklar, 2004). It has three core interacting components of object, entity and value providing the basis for the function of asset management to optimise performance of assets against a profile of value requirements (Amadi-Echendu et al, 2011). The core components are further highlighted by the Oxford English Dictionary (2007) definition that asset management is “the active management of the financial and other assets of a company in order to optimise the return on investment”. In tying it all together The importance of information management specifically for EAM is highlighted by several researchers. Mays Business School (2011) identified that a lack of information availability, knowledge management and use significantly correlated with increased reactive maintenance levels and with low performing companies, increasing costs and contributing to unplanned outages, disrupting clients and businesses and affecting reputation in an increasingly competitive energy market. Parekh (2007) states Enterprise Information Management (EIM) is critical to the success of utility program implementations such as smart meters. Humffray (2004) has identified that the goal of asset management is informed decision making through integrated information on condition and performance of assets.
  • Literature overivew of key findings; The integrated holistic EAM model currently favoured has unique components in the business context Information Governance is holistic 3 problems are identified with the current EAM holistic model making OT and IT convergence difficult EAM – unique and evolved into holistic view Engineering Asset Management has progressed through many stages in the last thirty years. It has evolved from maintaining plant machinery (Sethi and Sethi 1990) to accounting for the estimation of plant life, valuation, planning for replacement and cost effective optimisation (Burns, 2000). The lifecycle includes asset design and creation, acquisition, operations and maintenance through to decommissioning. The key maintenance guides such as PAS55, the NSW government’s Total Asset Management Guide and the International Infrastructure Management Manual identify that an asset register, planning, staff communication across management, administration, engineering and maintenance tasks and systems to capture and evaluate performance information are critical to successfully achieving operational efficiencies through asset management strategies.   The ultimate goal is to optimise service output and minimise risks and costs across the asset lifecycle by organising, planning and controlling the acquisition, use, care and refurbishment or disposal of assets (CEIAM , 2010). Sklar (2004) argues that an effective asset management approach is a holistic methodology that considers both short and long-term objectives and integrates business and technology strategy with a comprehensive lifecycle asset plan. A holistic approach combining people, technology and processes across the business can also improve the critical elements of reducing risk and optimising plant performance (Too, 2010; Schneider, 2006) and is favoured by CIEAM in their latest publication guide to infrastructure management.
  • A smart grid is a digitally enabled electrical grid that gathers, distributes, and acts on information about the behavior of all participants (suppliers and consumers) in order to improve the efficiency, importance, reliability, economics, and sustainability of electricity services. They are built, maintained and converged by several different people, processes and technologies across their lifecycle.
  • For those architecturally minded here is a representation of the network in diagram format – you can see the integration of information, technology, people and processes from when electricity is generated and distributed and then used in the home or business and the transfer of information about flow, billing, maintenance issues and demand without the need for manual inspections at any stage.
  • The literature indicates that the holistic nature of the integrated EAM model such as when deployed in smart grads creates 3 key problems worthy of research; 1. The benefits of information governance are not being realised as organisations have not taken up active and consistent management of information across the EAM lifecycle. Gartner has identified that structured data is growing by 40 percent a year and unstructured data 80 by percent a year (Logan, 2012). In 2011 the International Institute for Analytics identified eighty percent of structured and unstructured information across organisations is not managed. In 2011 Mays Business School identified that a lack of information availability, knowledge management and use significantly correlated with increased reactive maintenance levels; an indication of low performing companies; increased costs, unplanned outages, disrupted clients and adverse impacts on reputations in an increasingly competitive energy market. Parekh (2007) states Enterprise Information Management (EIM) is critical to the success of utility program implementations such as smart meters. Gartner (Streenstrup et al, 2012) has identified that smart grid initiatives such as smart meter technology converges operational and information people, processes and technology to reduce financial, legal and reputational risk and improved data quality.     2. Pressure to converge unstructured and structured data, processes, IT and OT sytems and human resources implementing and maintaining EAM functions such as smart grids Operational and information technology systems have traditionally been managed separately from corporate Information technology systems (Jaffe et al, 2010). The disparateness of these and other information silo’s weaken control and expose organisations to political, economic and legal risks (McManus, 2004). Benefits include reduced hardware and network requirements, integrated life cycle management, reduced licensing needs, data quality improvements from automation, leveraging outsourced maintenance arising from use of the cloud and same skilled information technology staff, improving strategic decision making from retrievable holistic single dashboard view of the organisations information and improving competitive standing for utility assetsParekh et. Al (2007) argues the convergence of operational and information technologies provides enhanced delivery of utility services. (Streenstrup, 2011; Torchia, 2011; Newman, 2011; Shien, Gao, Koronios and Chanana, 2007; Jaffe et al, 2010; Bonnet, 2010). 3. Abundance of regulations, standards, terminology and frameworks for managing information without identification of which are appropriate for the unique EAM context References to the management of information appear in the leading asset management guidelines including PAS55 (BSI), Guide to Integrated Asset Management (Brown, 2011), International Infrastructure Management Manual (2011) and Total Asset Management Guide (GAMC, 2004), but with conflicting language and components and a lack of identified application of information governance across the preferred holistic and integrated view of the asset lifecycle. This is not confined to the EAM literature – This is a list (Abundance link) of the information governance related regulations an organisation in Australia is expected to comply with and you may notice that they refer to interchangeable terms of records, information, data and knowledge
  • This research will aim to analyse these problems by answering the principle question of We will also explore further the sub questions of
  • To appropriately identify an information governance framework applicable to Engineering Asset Management l will undertake case studies of organisations with asset management functions meeting the validity and reliability constructs indicated by Yin. The analytical generalised case study approach will utilise information audit theory which includes the six sources of evidence identified by Yin including including review of applicable strategy documents (such as strategic and operational plans, website, annual reports and audit reports), interviewing of key staff from a questionnaire at all points of the asset management and information creation lifecycles (management, administration, construction, maintainers, engineers and information controllers) and observation of information functions from creation, storage, sharing to disposal.  
  • These multiple sources of evidence will provide a database of evidence from which a pattern of consistent use by EAM organisations of the framework components on the board should emerge.
  • By proposing and investigating such theory between now and August 2014 the research aims to provide practical and operational contributions to the areas of engineering and computer and information science Practical contributions include; Contributing to the body of knowledge First to apply Information Audit Theory to unique business context of EAM Identify a consistent terminology that can be used across the EAM lifecycle Identify which components of existing standards, appropriate for EAM context Operational contributions Operationalise application of existing standards Indication to organisations succinctly the optimum people, processes and technology fto realise business benefits from converging OT and IT Identify the extent to which EAM organisations are fulfilling Gartner predictions that OT and IT are converging and how. The research will also identify the extent to which information related frameworks such as ISO15489, COBIT and relevant components of PAS55 are or can be practically applied across the EAM lifecycle. The research will indicate how EAM organisations can minimize the financial, reputation and legal risks of creating, capturing, managing, securing and disposing of vast and ever increasing information volumes.
  • Transcript

    • 1. IntroductionCandidateAnastasia Govan KuuskSupervisorsProfessor Andy KoroniosDr Jing GaoTitleAn Information Governance Framework for Engineering Asset Management
    • 2. Overview of todays presentationDefinitions of the key terms – IG, IT, OT, EAMOperational exampleLiterature review findingsResearch problem, questions, and designContributions over time
    • 3. Definitions overviewInformation Governance (IG)“Decision rights and an accountability for managing information optimally”Caldwell, 2011; Pugh, 2011; Targowski, 1998; Logan, 2010bInformation Technology (IT) “Resources required to acquire, process, store and disseminate information for the strategic andoperational management of the enterprise.”International Standard IEC 38500, 2008; Rhodes, 2011Operational Technology (OT)“Physical equipment technologies for engineering asset management”CIEAM, 2010; Streenstrup, 2010, Jaffe, 2011; Waddington, 2008Engineering Asset Management (EAM)“Manage risks associated with managing, maintaining and replacing critical built asset infrastructuresuch as water, transport, sewerage and power services”Amadi-Echendu et al, 2010; International Infrastructure Management Manual; 2010; BritishStandards Institute, 2008; Brown et al, 2011; Too, 2011; CIEAM, 2010; Sklar, 2004
    • 4. Definitions - Information Governance (IG) PEOPLE Dispose Create Archive Store Information should be; Secure Discoverable Use Classified Confidential Organise Reliable Authentic IntegralTECHNOLOGY PROCESS From : Author own diagram
    • 5. Definitions - Operational Technology (OT) & Information Technology(IT)
    • 6. Definitions - Engineering Asset Management (EAM)
    • 7. Literature review key findings – EAM is unique EAM Unique & holistic integrated modelFrom : Brown, K et. Al. (2011). Guide to Integrated Strategic Asset Management. Australian Asset Management Collaborative Group: Brisbane
    • 8. A holistic EAM model in action – Smart grid From :http://www.smartgrid2030.com/?page_id=445
    • 9. A holistic EAM model in action – Smart gridFrom : Office of the National Coordinator for Smart Grid Interoperability . (2010). NIST Framework and Roadmap for Smart Grid InteroperabilityStandards, Release 1.0 . National Institute of Standards and Technology : Gaithersburg
    • 10. Literature review key findings – holistic EAM nature creates 3 problemsKey components of the integrated EAM model creates 3 key problems;1. The benefits of governing information are not being realised2. Documenting convergence of data, processes, applications and human resources for EAM in theacademic literature is not evident3. Abundance of regulations, standards, terminology and frameworks for governing information so abest fit of framework components for the unique integrated EAM environment is not evident
    • 11. Research questionsPrinciple questionThis research aims to study adoption of information governance and how it bridges the gaps ofconverging information and operational technologies in Engineering Asset Managementorganisations in Australia.The following sub questions will be explored•To what extent is information technology and operational technology converging•To what extent are organisations managing business critical information•How are Engineering Asset Management organisations adopting information governance•How are EAM organisations bridging the gap between information and operational technology
    • 12. Research contributions .From : Yin, r. (2009). Caste study research: Design and Methods. (4th ed.). Sage: Los Angeles
    • 13. Research design PEOPLE Create Dispose Archive Store Information should be; Secure Discoverable Organise Use Classified Confidential Reliable Authentic Integral PROCESSTECHNOLOGY
    • 14. Contributions over time