- 1 What is information management?
- 2 Information Management in the Asset Lifecycle – Standardisation
- 3 Information Technology – Software & Tools
- 4 Information strategy: Where is your business?
- 5 Data management infrastructure: Cloud or On-premises?
- 6 Business Intelligence – Information Management Fully Realised
- 7 Information Management vs Knowledge Management
- 8 Communication & Collaboration – Bridging the gap
- 9 Practical Information Management applications by lifecycle stage
- 10 Conclusion
What is information management?
Information Management (IM) is specifically concerned with the value, quality, ownership, use and security of information in the context of enterprise and performance. Enterprise Information Management (EIM) is about the overall management of information assets and the principles of moving data and the conversion of information into knowledge, knowledge into action, and action into value. IM is interested in outcomes, value (of information), principles of management, and information assets.
Information management also includes data management and related activities (e.g. analysis, master data management or MDM). The principles revolve around people, processes and tools/technologies across a variety of activities, from input to governance and architecture to business processes, leading to outcomes.
The management element includes moving the information manager closer to business management, given the highly strategic function of IM, with an eye toward realising benefits and solving challenges around information. Information management and Enterprise Information Management (EIM) have a broader meaning than Enterprise Content Management. In order for IM to support organisation-wide strategic coordination, the Information Management Strategy must be aligned with other strategic planning in the organisation, including risk, privacy, FOI, ICT, procurement, and environmental management strategies.
Enterprise Content Management (ECM) and IM used to be thought of as the same, due to overlaps in definition and practice around what happens with the data, documents, information and content. ECM is a part of IM but has always had a more technological focus, looking at the relationship of content to process. This means looking directly at data from document capture (human and app created data) and governance (document, web content, digital assets, and records management) to storage, delivery and presentation, and finally to preservation.
The Association for Information and Image Management (AIIM) emphasises that the content created under the ECM process is related to and used by organizational processes, rather than being content for its own sake. Enterprise Content Management is more directly employed around the lifecycle of unstructured content and one way of approaching information management while being part of it.
Enterprise Information Management (EIM)
Enterprise Information Management is a more recent data practice than IM or ECM. Its origins are predicated on moving ECM (and classifications based on the formats of information) towards all information and the management of that information in an enterprise-wide way, or what was called “the holistic reality of information at work in a hyper-connected age”.
There are discussions as to the ongoing use of ECM given the evolution that has led to Enterprise Information Management – a more recent phenomenon – practice and competency.
A common view is of ECM as an evolved practice and a generally settled set of systems being at the core of EIM. Several elements contributed to the focal shift from ECM to the Enterprise Information Management approach, specifically through the application of management principles to information and processes in a context of business optimization, innovation, competitive benefits, performance and growth.
Information as a core business asset
Information is a core business asset. Enterprise that integrates and incorporates the full spectrum of EIM moves along a path from Ad Hoc/Digital Register to Optimised/Digital Disruptor, the latter of which is where “enterprise is aggressively disruptive in the use of new digital technologies and business models to affect markets (IDC’s MaturityScape Leadership Digital Transformation Stage Overview). Ecosystem awareness and feedback” become critical to enterprise innovation, the outcome of which is the enterprise remaking existing markets and creating new ones to its own advantage. The use of EIM to control and create markets is based on information asset awareness and engagement.
Information Management in the Asset Lifecycle – Standardisation
Capital Projects vs Operations
Like ECM and IM, Capital Projects and Operations are often confused as they share some characteristics: both are performed by people; both are planned, executed and controlled; and both have resource limitations. They are only the only two aspects of work (or combination of) in any organization.
A projectised organisation deals solely with capital projects and an operational work-based organisation is known as a functional organization. A matrix organization deals with both.
Capital Projects can be defined as “a temporary organization that is created for the purpose of delivering one or more business products according to an agreed Business Case” (PRINCE2) or as a “temporary endeavour undertaken to create a unique product, service, or result” (PMBOK Guide).
An Operation is the continuous execution of activities that produce the same output or provide a repetitive service. Operations do not produce new things, but are necessary to
maintain and sustain the system, are used to run regular business models, achieve the goals of the business, and support the business, and are permanent. Their only constraint is to be profitable.
Major differences include the unique and temporary nature of projects, while operations are ongoing and permanent. Projects are funded with a fixed budget, while operations have to earn a profit. Projects are executed to start a new business objective and terminated when it is achieved, while operational work does not produce anything new and is ongoing. Projects create a unique product, service, or result, while operations produce the same product, aim to earn a profit and keep the system running.
Completions and Handover
Completions and handover is a complicated process that, when handled efficiently, can reduce cost overruns, safety increases, and save time. Looking at Oil and Gas operations, studies have indicated that on average less than 20% of projects end on time, and less than 35% on budget. Project handover to operations becomes a very critical process, requiring executive attention and the right IT management solutions. Experts estimate that around 4% of total annual capital budgets in oil and gas are related to inefficiencies incurred in relation to data handover. A nominal improvement on that percentage would represent a significant economic benefit, before even considering added benefits in terms of safety of operations.
More broadly, oil and gas, petrochemicals, mining, and AEC stand to benefit from improved completion and handover. A poorly organized, inefficient, and ineffective transfer of asset-related information, including drawings, technical documents, and data content, necessarily translates into additional costs, inefficient operations, and safety risks.
Using appropriate technologies to drive efficiencies in completion and handover are critical. The US National Institute of Standards and Technology (NIST) published a study that sought to identify and quantify the efficiency losses in the US capital facilities industry attributable to inadequate interoperability, which it defines as “the ability to manage and communicate electronic product and project data between collaborating firms and within individual companies’ design, construction, maintenance, and business process systems.” The NIST quantified approximately $15.8 billion in annual losses, or 1% and 2% of total capital facilities industry revenues for every year of a facility’s life.
People & Process
People matter to the process. Business transformation initiatives often ignore the people aspect of change initiatives, according to IBM. A focal system from Paul Saur, CIO of the Palmer Family of Companies, suggests people first, process second and technology third.
Saur points out that success, “comes down to an emphasis on people and their processes and pulling in the reins on technology until there is a very deep understanding of the first two things … only through a deep understanding of people and their situations can you begin to identify appropriate and agreeable processes that technology can support.”
Technology is a clear solution to support people and process. However, software only make it easy to perform repetitive tasks (processes). Technology is a means to an end, and not an end unto itself.
tips when looking at your people:
- Identify all your people: Ensure that you are considering the entire set of people affected by your problem and its possible solutions. Be wary of overlooking the people you will deploy to support your solution.
- Whole person view: Consider knowns and unknowns, but do so with empathy. Ensure people are put in situations to succeed. Take into account people’s mental health, relationships with their co-workers, or other non-work factors to maximise their efficacy.
- Trust as a goal: What do you need to do to develop long-lasting, trusting relationships with the people who are asking you to solve their problems?
Key tips when looking at your process:
- Think in business terms: Work to articulate the problems and processes as Agile User Stories, whether you are working in an Agile framework or not – a user story is a tool to capture a description of a software feature from an end-user perspective. Try your best to leave technology out of the stories. Think functional requirements, not technical requirements.
- Think like a systems engineer: Look at your business as a system of systems. Review the work of Richard Turner and Rose Opengart at NASA for insights to drive cross-departmental understanding and compromise.
- Measure: When you define or refine a process, how will you measure its success/ROI?
Information Technology – Software & Tools
Plant information management ensures secure access to plant information, including engineering designs, vendor data, purchase orders, RFQs, specification sheets, and all ancillary documents. These procedures are critical to maintaining high-level data processes that secure efficient and effective projects and operations. Software solutions that have high degrees of integrity, user ease of adoption and engagement, and provide that valid, consistent, and high-quality engineering data is shared across the value chain and between facility information systems are enterprise critical.
Software solutions for EIM work if they allow for enterprise-wide collaboration, are efficient and accurate, increase feedback, and reduce project risk. Solutions should provide project-wide, web-based submission, validation, distribution, and review of data and document deliverables. Electronic workflows, distribution rules, and subscriptions built into software can ensure the correct and consistent review of deliverables with auditable traceability. These aspects reduce the cost and time associated with locating correct information, ensure critical information is subject to appropriate scrutiny, and reduces the time needed for review. These tools, reduce project costs, time to completion, and risk.
Interoperability is the ability of organisations to share data and information by the use of common standards and is actively encouraged by WoVG policies. It is the ability of different information systems, devices, or applications to connect, in a coordinated manner, within and across organizational boundaries to access, exchange and cooperatively use data amongst stakeholders, with the goal of optimizing the health of individuals and populations.
Software with enhanced decision support capabilities facilitates global design, production, and life cycle optimization of an enterprise. EIM solutions to support interoperability should, from concept and design through plant maintenance, operations, and decommissioning, enable electronic management of all data assets, integrating information on the physical asset, processes, and regulatory and safety imperatives.
Information strategy: Where is your business?
Digital solutions to ongoing issues are the way to a fully realised Information Management System. Paper-based and antiquated digital systems that create information silos no longer serve the diverse, time-sensitive, and safety-critical needs of enterprise. Future-facing business leaders are working to transform and lead digitally powered organizations that are not only adaptive to change, but able to predict and drive that change.
Leadership Digital Transformation (DX) is the set of disciplines that enables businesses to develop the vision for digital transformation of products and services that are optimized to deliver value to partners, customers, and employees. “Leading DX is inherently multifaceted and multidirectional — DX leaders must have the ability to create digitally fueled business visions; to attract ‘co-conspirators’ including customers, partners, and competitors to help realize the vision; and finally to orchestrate the myriad components needed to actually execute on the vision,” (IDC Research Network).
Goal-directed solutions in digital infrastructure are informed by business objectives. Knowing the coordination, collaboration, timing, safety, sharing, logging, tracking, and reviewing needs across your enterprise, as well as which areas of the market you seek to disrupt, will assist in developing the appropriate EIM solutions.
Fully realised EIM will provide data across enterprise needs, allowing for detailed access and sharing with all stakeholders. Information silos leave gaps in information across an enterprise that reduces efficiencies and provides space for human error to be introduced.
Information use and re-use addresses how information is collected, organised, described, stored and shared. Information that is not easily usable or able to be re-used in the future is of little value to the organisation.
- Mechanisms that make information easier to use and interpret are classification systems and metadata.
- Digital continuity is the ability to maintain digital information in such a way that the information will continue to be available, as needed, despite changes in digital technology.
- Intellectual property (IP) refers to the set of legal rights that protect the results of creative efforts including copyright, patents, and trademarks.
High-quality data is necessary to compete in the modern digitally-powered enterprise landscape, and use of that data across an enterprise is necessary to move across the IDC MaturityScape – an IDC study that identifies the stages, dimensions, outcomes, and actions required for leaders to undertake successful DX initiatives. Most businesses are at the opportunistic and repeatable tiers, digital experimenters and digital competitors, respectively.
Integrated Information Systems
Fully Integrated Information Systems take data collection and application to visionary levels, collaborating across enterprise and having demonstrated ecosystem vision and cultural adaptability. Information Architecture (IA) refers to the design and arrangement of an organisation’s information and the inter-relationships of information systems. An IA document or statement will include a description of:
- business processes operating in the organisation
- which business systems store which data and records and in what formats
- the relationships between different business systems
- standards to be used when labelling and categorising information
- the design of navigation, indexing and search systems.
In a mature organisation, there will be a close and coordinated relationship between the organisation’s Information Architecture, Business Architecture and IT Architecture, ensuring well integrated information systems.
Final IM Vision
A final IM Vision involves disruptive behaviours, moving through the data collection, management, storage, and sharing sequence based on leadership that consistently evolves DX to meet changing market needs and conditions based on ecosystem vision and cultural adaptability. Leadership behaviours where organisational culture mirror continuous evolution of DX vision to deliver digitally-enabled product/service experience on a continual basis.
Optimised IM Capability
Innovative DX-driven business models drive omni-experiences to their markets. Ecosystem awareness and feedback fosters organizational culture, goals, and projects. The five key areas that drive optimisation are Ecosystem Awareness and Insight, Business Model Innovation, Organizational and Cultural Disruption, Agile Planning and Governance, and Financial and Economic Leverage, each of which is dependent on digital solutions.
Data management infrastructure: Cloud or On-premises?
Data Management Infrastructure is an infrastructure used to provide data management and enforce data management policies. A data management infrastructure includes resources such as a data repository and an information catalogue. Enterprise Resource Planning (ERP) has a critical decision to make when deciding on cloud or on-premises ERP deployment.
A hybrid cloud solution features an element of different types of IT deployment models, ranging from on-premise to private cloud and public cloud. A hybrid cloud infrastructure is dependent on the availability of a public cloud platform from a trusted third-party provider, a private cloud constructed either on premises or through a hosted private cloud provider, and effective connectivity between both of those environments.
The move from data silos and pen-and-paper-based data gathering and aggregating has opened up enterprise to not only be adaptive to change but able to predict and drive that change. There is agreement among IT decision-makers that, in addition to on-premise and legacy systems, they’ll need to leverage new cloud and SaaS applications to achieve their business goals.
Machine Learning and AI
The best solution to on-premise versus cloud deployment for machine learning and AI depends on your AI location, how intensively you plan to build out your AI capabilities, and what your end-game looks like. Moor Insights & Strategy points out that, “Artificial Intelligence (AI) and High-Performance Computing (HPC) are both computationally-intensive workloads. They demand fast central processing units (CPUs), accelerators, very large data sets, and fast networking to support the high degree of scaling typically required. All this fast hardware can be difficult to manage and expensive.”
Given workloads and the difficulty of finding “Machine Learning as a Service” or MLaaS and AI competent staff, working with cloud infrastructure is seen as a safe path toward early experimentation and evolution, especially if the cloud system chosen can migrate on-premise. Cloud systems are seen as “sticky” meaning they almost universally require that an application developed in their cloud runs in their cloud. Stickiness doesn’t have to be a bad thing. An elastic cloud service can offer a flexible hardware infrastructure for AI, Moor Insights points out. Additionally, you won’t have to deal with complex hardware configuration and purchase decision, and the AI software stacks and development frameworks are all ready-to-go.
Drawbacks of on-premises
There are major differences between on-premise and cloud-based. While cloud-based software is hosted on the vendor’s servers and accessed through a web browser, making it universally accessible across enterprise, on-premise software is installed locally, on a company’s own computers and servers. There are also hybrid deployments.
Security is often the top concern. Buyers were once wary of the security of cloud-based software, but most are less sceptical today (as evidenced by adoption rates). Reputable cloud vendors have strict standards in place to keep data safe.
On-premise systems are considered much easier to modify, but cloud deployment is rapidly catching up. The ability to customize to specific enterprise needs and requirements is critical for many organizations, especially in niche industries, such as specialized manufacturers with unique processes.
While on-premise deployment puts more control in the hands of the organization, up to and including the security of its data (necessitating robust security protocols that are built into the cloud), mobile accessibility can pose an issue, requiring a third-party client to communicate between a mobile device and the on-premise software.
On-premise deployments are also more cost-intensive up front, showing convergence over lifetime use. Setup costs (which include the work to create the hardware and software infrastructure and everything else that needs to be done before the first training run) are typically lower for cloud-based AI and HPC development.
Security with On-Premise versus Cloud ERP’s is an important consideration for internal as well as legal reasons. Compliance must be monitored to ensure that appropriate information and records are created and effectively managed and secured. Regular audits can identify gaps or problems and help to develop strategies to address issues and should include an assessment of the organisation’s compliance with legislation, standards, and internal information management policies and procedures encompassing information and data management, records management, privacy, and security.
The Information Management Governance Standard requires that a register of significant information assets must be established and maintained, and significant information assets must be assigned an owner and custodian (or equivalent).
Significant areas of concern exist around data security, including:
- Cyber threats
- Data breaches
- Compromised credentials
- Broken authentication
- Hacked interfaces
- Account hijacking
- Malicious insiders
- Permanent data loss
A common, legacy option is to store data locally. Modern solutions include cloud and hybrid storage.
On-Premise: All security functions reside on-premises. This may be one location but could include several. Nothing is hosted in the cloud, meaning local servers are used exclusively. There are a few advantages, such as increased control over critical data. Areas of concern include the struggle to develop the security expertise required to keep business’ data secure and the physical security of servers, which can be tampered with, stolen, or corrupted maliciously or through environmental events like accidents.
There is also a significant investment to on-premise security. Keeping physical servers means added operational costs for maintenance, system upgrades, cooling equipment, and power delivery tools, in addition to greater electricity requirements to sustain power to these servers.
Since most businesses are now operating in a hybrid environment with Microsoft applications, while incrementally moving users to the cloud, the on-premise security model is outdated for most industries.
The cloud, however, is a virtual environment that adapts to user needs. It is scalable – making it the best choice for start-ups or smaller companies. Cloud hosting eliminates the capital expenses of hardware, software, and on-site data centres: the racks of servers, the round-the-clock electricity for power and cooling, the IT experts for managing the infrastructure.
While the cloud offers benefits like cost-efficiency, reliability, and accessibility, there are also risks to observe. There can be technical outages and downtimes and, if the internet is not accessible, utilising applications, servers, and data from the cloud is not possible.
Business Intelligence – Information Management Fully Realised
Intelligent Information Management (IIM)
Intelligent information management (IIM) is visionary-level digital integration and coordination across enterprise to collect, understand, engage, and activate data. It is a process set that enables organizations to organize, manage and understand all types of data that is created, developed, and found across an enterprise. Attributes that define IIM include integration of IP device discovery, data sharing, infrastructure databases, events and alarms, third-party integration, automated patching, and applications.
The benefits to fully realised IM are many and include:
- faster reporting
- analysis or planning
- more accurate reporting, analysis or planning
- better business decisions;
- improved data quality, employee satisfaction, operational efficiency, and customer satisfaction
- increased competitive advantage
- reduced costs and increased revenues
- saved headcount.
Above all else, Business Intelligence (BI) and IT managers see tools and platforms as a means to deliver faster and more accurate information to key decision-makers across enterprise. Faster and more accurate reporting, analysis or planning, better business decisions, improved employee satisfaction, and improved data quality top the benefits list.
Information Management vs Knowledge Management
There are significant risks associated with knowledge and information mismanagement, therefore ownership and leadership of information management needs to be clear within departments and across government. The terms information management & knowledge management (KM) are often used interchangeably or without distinction, but these two have notable, critical differences, which BI and IT will need to be aware of for effective management and integration.
1. Information management is about data and information understanding and management, whereas knowledge management is primarily focused on managing the knowledge, understanding, experience, and wisdom of people and process.
2. IM organises, analyses, stores, and retrieves information. KM is the concept of finding, gathering, assessing and sharing information and knowledge.
3. IM is easier to copy as it’s transferable. KM is hard to copy.
4. IM is “know-what”: data sets, analysis, inputs, outcomes. On the other hand, KM is largely about “know-how, know-why, and know-who.”
5. IM is a digital technology based concept, whereas KM is people and process focused.
Communication & Collaboration – Bridging the gap
For many industries, communication and collaboration between information and knowledge management will be critical. Knowledge and information management is essential for the upstream oil and gas industry. Many core workers within the industry are likely to retire in the coming years, which, if not managed properly, could lead to a knowledge gap in the industry. This is an issue across industry and enterprise. Dr Ivor Ellul, CEO of Knowledge Reservoir, a consulting firm for the upstream oil and gas industry, is clear: “With the exponential growth in technology, there’s no excuse for businesses of any size to not implement a knowledge management strategy” to complement already sophisticated and evolving information management.
If knowledge management is primarily concerned with capturing the explicit and tacit knowledge of your employees before they retire or leave, and information management is primarily concerned with collecting, processing and managing the data required to execute your organisation’s daily operations towards achieving strategic outcomes, bridging the two is the goal of holistic Enterprise Information Management.
Two abilities – capability and capacity – work together to determine the efficacy of an EIM system. Capability is a feature, faculty, or process that can be developed or improved, and individual skills that can be applied and exploited. In the case of information management, capability answers the questions:
- How can we improve our information management practices?
- What competencies do current staff have that can be applied and utilised?
- How easy is it to access, deploy, or apply any additional capability if we need it?
Capacity is the power to hold, receive, or accommodate and relates to the ‘amount’ or ‘volume’. In the case of information management, capacity answers the questions:
- Do we have enough IM skills/knowledge/process/policies?
- How much is needed, now and in the future?
“The bottom line for (Enterprise Information Management)…is better information and smarter decisions, from both an organisational knowledge capture perspective and as an aid to training a transitioning workforce.” – Dr Ivor R Ellul, chief executive officer of Knowledge Reservoir, a consulting firm for the upstream oil and gas industry.
Practical Information Management applications by lifecycle stage
Front-End and Detailed Design
Front-End Engineering and Detailed Design (FEED) is an engineering design approach used to control project expenses and thoroughly plan a project before a fixed-bid quote is submitted. FEED focuses on technical requirements and approximate project investment cost. Front-end engineering helps to evaluate potential risks and is typically followed by the Detailed Design (or Detailed Engineering). FEED is applicable to numerous industries, including Chemical Processing, Construction, Manufacturing, Pharmaceuticals, and Petrochemicals.
The amount of time invested in Front-End Engineering is usually high because project specifications are thoroughly prepared and the following enterprise needs typically developed in detail:
- Project Organization Chart
- Project Scope
- Defined civil, mechanical, and chemical engineering
- HAZOP, safety, and ergonomic studies
- 2D & 3D preliminary models
- Equipment layout and installation plan
- Engineering design package development
- Major equipment list
- Automation strategy
- Process Flow Diagrams
- Project timeline
- Fixed-bid quote
Digital solutions are available for areas of FEED, including EIM infrastructure, data architecture, and security planning. Making use of BT and IT managers in the FEED process is key to being prepared for your fully integrated, EIM needs, whether that’s on-site servers or cloud security support. Think through the enterprise support that information management can provide or enhance. Modern design and engineering documents are living, synchronised, and need to be available at all stages of an enterprise lifecycle – changes are made in real time. Design changes are done in an instantaneous and enterprise-wide fashion when effective EIM is implemented from the beginning of the lifecycle.
Projects and Construction
There are many factors that affect project outcomes across industry. There is one critical factor that is commonly overlooked but has an outsized impact – predictability. It’s incredibly difficult to build predictability into an enterprise like construction because predictability needs a foundation of accurate data to help build efficiency from integrated information toward project efficacy in order to offset cost overrun and project delay. Project management is enhanced if document management is made easier through properly stored and managed data sets.
Predictability is essentially knowing an event outcome at the earliest possible moment. For construction projects, the focus is on cost and schedule predictability. It is impossible to eliminate all unknown events, however, the quicker issues are identified the better chance and more effective the action taken. Improved predictability is a precursor of heightened project control and financial outcomes.
Research finds distinct and identifiable practices affect the predictability of projects:
- Human behaviour and organizational culture
- Project characteristics (project complexity, external influences, market conditions, project team)
- Forecasting practices (forecasting methods, forecasting data, contingency management, reporting)
- Management processes (project planning & execution, contracting, risk management, change management)
Data is the key in many of these areas. How we locate data, manage data, store and access data, share data, and activate data are key to organizational culture and can mitigate externalities, limit complexity, make forecasting and reporting more efficient and universally accessible, and enhance nearly every aspect of the management process. Failure to employ EIM to support projects and construction, specifically with regard to predictability and project management, is antithetical to good business practice and foregoes the benefits of EIM.
In construction specifically, a technological void has contributed to low predictability, with executives lacking visibility and transparency at the project level to properly incentivize and drive predictability across the organization. KPMG notes that two-thirds of construction firms surveyed don’t use advanced data analytics to monitor project-related estimation and performance. Digital transformation (DX) is fast becoming a critical initiative for organizations in the Engineering & Construction industry, with firms increasingly utilizing technology to deliver projects and achieve performance targets. Benefits of EIM and project digitisation include extending organizational reach, improving management decisions, and driving efficiency across the enterprise.
Supply Chain and Procurement
Supply chain management (SCM) is designed to take the information you already have and use it more effectively. SCM is an ongoing process – one that your enterprise is already engaged in – and applying EIM to the process will enhance many areas by including showing you how to manage the supply chain to optimize revenues, cash flow, and customer satisfaction. The most important part of SCM is your core business information system and the EIM that governs it.
SCM involves diverse data sets of differing information: material lists, product descriptions and pricing, inventory levels, customer and order information, supplier and distributor information, and current cash flow. This necessitates increasing amounts of communication and coordination with suppliers, vendors, subcontractors and other parties, both on and off-site. Given time and resources limitations, staying abreast of the information and communication required to keep SCM running in a way that’s most profitable for your business is a difficult proposition. Scattered or out-of-date information makes managing the supply chain more difficult than necessary. Better SCM means activating your data.
Not all SCM software will work for your application and any SCM software you use will only be as good as the data. Your business information needs to be complete, consistent, current, and accessible for your SCM to have a net positive impact on overall enterprise needs. EIM is your solution: secure, mobile integrated, in cloud-hosted or server-based databases that are centralized and secure, are critical to competing in the modern digital marketplace.
EIM has a role in supporting improvement in handover solutions across industry, as identified in a study by IDC Energy Insights conducted around the maturity of IT systems adopted to manage handover. The study focused on analyzing business practices, system architecture, IT infrastructure, and applications in support of project portfolio management, enterprise content management, business analytics, and construction management.
Only 14% of surveyed companies manage content related to capital projects with company-wide common processes and sets of IT applications. IDC Energy Insights estimates that about 45% of oil and gas engineering department staff time is devoted to locating and validating information available in disparate systems.
Best practices for completion and handover in these critical industries include:
- Creating a single view of assets along the entire plant lifecycle with complete and integrated document management enabling collaboration across multiple stakeholders and internal departments.
- Having a full plant hierarchical view and making it possible to start at the plant level and navigate up and down to units, mechanical equipment, electrical equipment, and instruments to find all the relevant and contextualized asset information.
- Building a solid platform capable of managing massive amounts of asset information, including technical and engineering data, documents, and drawings (2D and 3D) generated during the construction, commissioning, handover, and operations phases.
- Having that platform used across multiple departments and business functions (such as engineering, technical services, asset integrity, quality control, project management, maintenance, and operations) and having partners and contractors using web-based access or a cloud environment to exchange information and documents, enabling external collaboration.
- Managing the continuous handover inherent in the plant’s lifecycle.
Operations and maintenance
Management systems enumerate enterprise-wide expectations for operations, defining common protocols and terminology—shared concepts that unify the organization and allow everyone to communicate clearly about tasks and objectives. Antiquated systems for managing operations can have the effect of diminishing operational excellence, causing enterprise issues or incidents, increasing the likelihood of delay and cost overruns, or interrupting daily processes.
According to Bain & Company, operational excellence management systems (OEMS) are an effective way to “share best practices, ensure compliance and instil a culture of continuous improvement throughout an organization. Digitising these systems makes them more valuable and responsive to the needs of managers and frontline workers.”
EIM connects mobile and tablet apps employed by frontline workers to the entire management system to ensure work is completed in accordance with company standards and making all operations and maintenance activity loggable, trackable, and reviewable. Well coordinated and integrated digitalization of management systems provides a seamless way to transform the organization with technology and process upgrades that are clearly tied to the company’s strategic goals. Mobile and tablet apps are only the beginning, as devices and stakeholders across an enterprise can help to collect and aggregate data that is employed to inform strategic decisions about operations and contribute to a culture of continuous improvement.
Across industries, digital transitions are leading the way to enterprise enhancement in a host of sectors. Enterprise Information Management is a visionary set of processes that seeks to enhance the overall management of enterprise information assets by employing the principles of collecting and analysing data, converting that data and information into knowledge, moving that knowledge into action, and turning that action into value. Industry has changed as technology has evolved and it is no longer feasible to use information silos, pen-and-paper, or antiquated data systems to manage complex and potentially dangerous systems and processes in modern enterprise.
From information management in the asset lifecycle to business intelligence and practical applications across a project lifecycle, employing software systems that take enterprise to visionary levels of enterprise information management is the path forward for enterprise that seeks to disrupt and dominate industry.