Mastering Your Engineering Data – Are you in control?
In the second of this series of articles we consider the relative position of asset intensive industries to their peers and dig into the issues which sometimes presents us as laggards in the field of digital transformation.
I’ve used a point and counterpoint below to illustrate the leader and laggard debate. Of course, this is just one of many more such examples over the life of an asset.
Point – We are Leaders
The use of advanced intelligent 2D and 3D CAD design was championed by asset intensive industries and has been a standard capability for decades now, with fully integrated clash management, change management, drawing production and material take-offs. This has led to better construction and improved productivity in the design of capital projects. Process simulation, materials management, engineering analysis and CAD technologies are very advanced in our industries across the asset lifecycle, providing very well engineered projects with good control over the material procurement, construction and commissioning processes.
Counterpoint – We are Laggards
Handover of information between the capital project phase and the operation readiness phase is still a major problem area, beset with gaps, inconsistencies and mismatching data formats and configurations. The intelligent data formats created in design are very often degraded or lost as the asset undergoes change in the operating phase, reducing information management to the lowest common denominator – usually a PDF file. Contrast this with retail and discrete manufacturing where information is created, captured, used and repurposed across many business processes.
How do we account for these two very different and valid views of how we master information management within our industries? The truth is that, while we excel at the use of technology for specific tasks, we lag in the overall digital continuity relative to other industries. Why is this?
Over the last three decades there has been a whole market segment created and hundreds of millions of dollars spent on engineering information management. We’ve had more acronyms than you can shake a stick at to depict how we need to master our engineering data; EDMS, EDW, ALCIM, AIM, EDB, ECM, EDM, PIM and on and on, and of course we’ve argued incessantly about the single database versus the federated approach and which features/functions we need on specific software tools.
Software companies have brought many products to market to address the issues. All the big players in the CAD world have been involved: the systems integrators have tried, the discrete manufacturing PLM providers have tried, and of course many niche companies with great technology have come and gone on the bleeding edge of engineering information management in asset intensive industries.
Significant effort has gone into developing data exchange standards and standard data models. We have had many different industry bodies such as PISTEP, EPISTLE, Posc Caesar, Fiatech, USPINL and CFIHOS to improve our ability to exchange, collaborate and share data. Owners, engineering contractors and software companies have all had their input, but the impact of their good work is still to become mainstream.
Projects now have information managers, we have handover specifications, class libraries. Clients mandate s/w technology in the hope of achieving more value from the data by focusing on a single toolset. We talk of the “single source of truth” at every opportunity.
In truth the design and build phase of an asset has been digitally transformed to improve the process through a more digital way of working. We use incredibly sophisticated tools (intelligent 2D and 3D CAD, engineering databases etc.) to create engineering data in a very granular and intelligent form.
One problem is that the innovative use of technology and best-practice standards occurs in silos across the value chain, with the flow of digital data between these silos perturbed at best and non-existent at worst. This creates a gap between what is needed and what gets delivered. I started using this diagram below over 15 years ago to try and articulate the issue.
The EPCs create sophisticated, intelligent 2D and 3D object models and databases which they have learned improves productivity, gives them a competitive advantage and de-risks procurement and construction.
The Owner needs these object centric 2D and 3D models and all their associated data to create a digital asset that will enable them to use and consume data more productively and to repurpose that data to better support operations.
The Owner may get the data and models at the end handed over as files, but the formal method of handover is by documents organised in folders by document type, and with greatly reduced intelligence. Once in operations this get worse.
Additionally during project execution 20% of data needed to support the project is equipment data. During operations 80% of the data needed to support operations is equipment data! Guess what happens to that data?
What we are left with is a gap. A gap that means lost opportunity to exploit the data, increased risk to safe and reliable operations through missing and inconsistent data and increased cost to close the gap to reduce the risks. The data was always there – it just wasn’t “cared for” in the right way.
The information gap is much smaller in other industries such as retail, discrete manufacturing and media, where the actual technology might not be as prodigious as some of that applied in our industries but the value of the data is much amplified and hence the gap is smaller.
The answer to why our industries excel at technology in siloes but lag in the overall digital transformation lies in an appreciation of the business drivers and value chain behaviour, not the adoption of technology or appetite for innovation. We cannot unlock the potential of digital transformation and mastering our data until we identify and then address these elements that are hindering or blocking our journey.
Are we ready to drive digital disruption faster and further? Do the Boards and Executives of asset owners believe there is a compelling reason to improve? Does the return on investment stack up?
In a paper entitled Digital Vortex, produced by the Global Centre for Digital Business Transformation, 941 business leaders across 12 industries around the world expressed their views and activities to embrace (or not) digital disruption. Interviews revealed that Oil and Gas and utility leaders feel the least threatened by digital disruption, believing that their businesses are less susceptible to this phenomenon than technology, media, finance and most other industries. 45% of respondents said digital disruption was not a board level concern and 43% did not have an active policy in place to address it. I wonder if they have read “Who moved my Cheese?”
Due to the capital-intensive nature of the business and life of assets, digital disruption may not be such a dislocation but I wonder if you asked the EPCs that serve the Oil & Gas industries how susceptible they feel to digital disruption, what they would say.
Intelligent CAD transformed their design processes in the 1990s. With work now performed globally, 24/7, due to advances in communications and design software, EPCs have seen their entire execution models change. Artificial intelligence will be the next wave to hit EPCs starting to automate many of the more rule based and administrative functions. Historically established EPCs traded on their rich knowledge pools and operating procedures but these are eroding as those experts leave the field of play and digital transformation starts. Therefore, new players willing to adopt new technology with more agile business models will provide strong competitive pressures.
A recent white paper on ‘Digital Transformation Initiatives in the Oil and Gas Industry’, produced by the World Economic Forum (WEF), notes in the executive summary:
“As other capital-intensive industries (such as aviation and automotive) have revolutionized their business and operating models through a holistic application of digital technologies, the opportunity for the Oil and Gas industry to leverage the transformational impact of digitalization has become more evident. The industry is now beginning to pay heed. The growing consensus is that the Oil and Gas sector is on the cusp of a new era. A second wave of business and digital technologies looks set to reshape it, propelled by a series of macroeconomic, industry and technology trends.”
Two of the key themes of the white paper are directly relevant to any senior managers involved in the asset lifecycle of asset intensive industries, namely, Digital Asset Life Cycle Management, which will require a digital asset strategy and Circular Collaborative Ecosystem, which will start to reshape the supply chain using digital platforms.
In addition, the CEO of AKER BP, Mr. Karl Johnny Hersvik, talking on a panel session at GE Oil & Gas 2017, reported in an article by Gas Processing, made a similar comparison with regard to the power of data to transform industries and our lagging behind other industries, the need for new more collaborative ways of using and consuming data in a more visual and context sensitive manner. He also noted that other things (business management, quality and value chains) must be aligned and transformed in parallel.
For me these are key points that illustrate:
- We are laggards behind other industries in our ability to monetise data. We need to take more interest in using data more effectively across the value chain.
- We need a common (and different) way of consuming and using data. The document paradigm has served us well historically but now it must initially be supplemented with a digital (asset) approach and eventually replaced.
- It will not be achieved through technology alone and must consider people, processes and technology together and most importantly must span the value chain.
In summary the Oil and Gas businesses, which are typical of asset intensive industries, are not early adopters of new approaches, but in the new economic conditions there is a movement toward digitisation. I believe this will increase faster because of the advent of intelligent devices and the Internet of Things (IoT) which will create more disruption, the data volumes will increase, the analytics will help differentiate the disruptors and there will need to be an object centric information model (Digital Asset) to help organise, visualise and consume the data.
How can we capitalise on this emerging C level view, and why haven’t we been able to do so already?
Let’s start by considering what Clayton Christensen of Harvard Business School has observed:
“The reason why it is so difficult for existing firms to capitalize on disruptive innovations is that their processes and their business model that make them good at the existing business actually make them bad at competing for the disruption.”
Our industries’ operating models can be characterised as:
- Complex financing with many stakeholders including IOCs, NOCs and venture capital.
- Usually one-off projects but sometimes with multiple assets.
- Long lifecycles comprising 2-5-year design and build cycles and multi-decade operating.
- Owners organised into capital project and operating departments, usually with small technical and engineering teams relying on the supply chain for design and engineering across the asset lifecycle.
- Business performance measured by business units normally organised by business line and geography. Capital project performance and operating performance not aligned well.
- Multiple EPCs engaged on projects usually based on competitive tendering per project.
- Complex material supply chain usually based on competitive tendering per project.
The project operating model brings a lot of diversity and flexibility. Each asset is almost its own business and so you might think they have a lot of opportunity to disrupt as they don’t carry the same “process and business model” baggage. However, a project is transient: it starts with the knowledge and processes of the team players, there is little time to innovate, the project culture itself carries its own model based on managing risk, and it is difficult to effectively carry forward new ideas and improvements to the next project which will have a different team.
The perturbed contracting model and the encumbered ability to look at enterprise wide programmes rather than projects further conspires against a holistic view of digital transformation across the lifecycle of an asset.
A Senior Manager in an international engineering firm, when asked about the opportunity to improve the material supply chain commented “yes, I can see what we could do to improve, but the suppliers won’t play ball because there is nothing in it for them, and how can I sell it to management? Most of our work is reimbursable and this would reduce the hours we spend and the client is not pushing us for it.”
Similarly talking to the Operations arm of an International Oil Company (IOC) and trying to get across the possibility of optimising the sparing requirements through better information management during the project stage, an Operations Manager commented “yes, but if I get more spares than I need from the project that’s great because I don’t pay for them as they are part of the capital project.”
Another Corporate Information Manager, who was charged with improving reliability centred maintenance, noted how hard it was to move new things forward when the field business model was still very much man-hour driven and new improvements would a) cause extra work to initially implement, and b) reduce the man-hours (revenue).
So, even with strong corporate support it is difficult to industrialise a new more digital way of working. This, combined with the fragmented contracting and organisational model creates “information leakage” throughout the asset lifecycle.
If we dig a bit deeper into the project world we will find that the Information Managers are lone voices in the project. They fight to close that information gap, but in the heat of battle of a project, the benefit of a more strategic lifecycle view of data is often drowned out in the noise.
If we look at the software vendors we will also find they are constrained in their ability to disrupt due to product legacy and sales models. New entrants can have a profound effect on digital innovation, but very often the s/w solutions are siloed by department.
I think the best example of product legacy is 3D CAD. 3D visualisation is a core part of any digital asset strategy as it supports visual thinking and digital working. Why hasn’t 3D made the jump from design to construction and then into operations support? There are early adopters out there using 3D in construction and operations but still it is not industrialised as it is in the design stage. I think there are two main reasons for this:
Firstly, projects are still run based on document deliverables for progress and payment milestones, rather than the development of a 3D Information Model.
Secondly, CAD stands for Computer Aided Design; software vendors have focused on pushing the design application as the means to maintain and use the 3D data over the lifecycle, but the 3D data needed in construction and operations (without all the design baggage) needs to be liberated from the CAD application itself.
To sum up why we are laggards in the holistic view of asset lifecycle digital transformation and why we are failing to close the information gap:
- A Project culture doesn’t foster innovation across contractual and organisation boundaries. We are too project centric rather than lifecycle centric.
- Our world is still too document centric, evidenced by the strong document control function and the weak information management function. We need to be object centric, where objects mean physical, logical and system components.
- Too much focus on technology being the answer, whereas it’s a small part of the answer and its use must be meshed in with the processes, people and DATA led, NOT application led.
- We consider our assets very much as single businesses which makes enterprise wide adoption of digital asset strategies difficult. We are too asset centric rather than enterprise centric in our business models.
The biggest issue for me is that we don’t have a cogent view of what information management across the lifecycle means and we don’t have an accepted brand for that view which everyone can get behind. The building industry which is a long way behind our industries in terms of the adoption of data management and modelling has rallied behind the Building Information Modelling (BIM) initiative, which is global, has government support, it’s a big idea covering the subject in a holistic manner (people, processes, technology and data) and its got a brand that says what it does on the tin. Similarly PLM in the discrete manufacturing industries is well understood as a discipline. Neither of these approaches and technologies is a good fit for us, but we can learn from them, and improve.
The next article will look at opportunities to be realised by taking a pragmatic and phased approach to digital transformation of the engineering landscape. This, combined with understanding the challenges outlined herein, lays the final piece of groundwork to guide us to a sustainable roadmap, branding and approach for digital continuity, which is a pre-requisite for true master data management and digital transformation of the business.
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In this series, I will be looking at:
- Why we are seen to be laggards with regards to digitisation
- The opportunities for those that embrace digital transformation pragmatically
- Possible visions for the future that fit with an Industry 4.0 agenda
- The key concepts for success in a digital transformation program
- Common misconceptions that trip us up
- Creating a winning strategy
- Ensuring success through phased and practical execution
All articles will be published on our website www.digatex.com and posted on LinkedIn over the next few weeks.