25 Feb Keynote Address to the Alberta Internet of Things Conference
What is the future of oil and gas in an increasingly digital world? This technology paints an exciting and teasing future, but we need to embrace several difficult changes laid out in front of us.
(This blog is a transcript of my keynote address to the Alberta Internet of Things Conference. You can find the actual recording on my YouTube channel — look for ‘GeoffreyCann’. The podcast is available as episode 87 on iTunes, Spotify, Stitcher and here).
By way of introduction, I’m obligated to tell you that I’m a “retired” senior consulting partner from Deloitte, an obligation imposed by my former firm. You probably have two immediate reactions to this — how can someone who looks so young be “retired”, and you’d be right — I am not retired. According to Deloitte, partners have to retire for tax reasons, which I don’t really understand. There are many better terms that work with professional services — withdrawn, traded, graduated, discharged, paroled. Whatever the term, I have continued to pursue my passion on the impacts of digital innovation on the oil and gas industry.
That passion has resulted in my first book, which is creatively titled ‘Bits, Bytes, and Barrels: the Digital Transformation of Oil and Gas’. It’s been in the works for 2 years, and sets out my vision for the oil and gas industry if The Jetsons were in charge, instead of the Alberta NDP.
Second, I find the label “senior” to be, how to put this politely, ageist. Once your hair turns white, senior can only mean one thing — senior citizen. I prefer the other senior terms such as senior debt, senior class, and the ever popular, Senior Vice President (by the way, a micro advertisement that I am open to alternative roles to retirement).
Over my 32 year career I have been through many an oil and gas downturn, but only one other industrial relocation enabled by extensive computerization, which was the adoption of SAP, and we all have our views about the success of that effort.
I know what you’re thinking. Excel spreadsheets have also transformed the industry. Just not for the better.
We are now at the early stages of what could be another transformative change to our sector. The impacts of digital on many other industries are now plain, painful and pivotal.
In my view, the orthodoxies that guided our thinking for years and have made us the envy of North America are now the patterns of thinking that will block our ability to embrace this new technology.
What exactly are these orthodoxies?
Orthodoxies of the Industry
The oil and gas industry runs on a set of generally accepted rules that have guided decision making for decades, everyone believes them, and no one really questions or challenges them because they are generally reliable.
For example, when my children were growing up, I carefully taught them not to talk to strangers, and not to get into a stranger’s car. And now, using Uber, I call up a complete stranger and get in their car.
Here are three typical orthodoxies about oil and gas that have successfully guided our industry for decades.
1) Data is proprietary
Oil and gas believes that all data is proprietary, must remain inside the firewall, be highly protected and secure. Data is recorded as an operating cost, which minimizes the capital allocated to it. At one time, collecting and storing data was very costly, and that cost created value. In fact, we sell our subsurface data at multiples of its collection cost.
As an industry, oil and gas is blessed with enormous holdings of data, and generates copious quantities every hour, but only the biggest can afford to analyse it all with their own resources. We understate its monetary value, overstate its sensitivity, and hold dear to the idea that only human industry insiders can make sense of it.
2) Smart metal is expensive metal
Some metal in oil and gas is pretty smart—specifically, those pumps, valves and installations that are connected to SCADA systems dating back to the 80’s, but most is pretty dumb. The oil and gas industry practically invented smart metal and remote monitoring. But SCADA is expensive and retrofitting metal to SCADA is prohibitive. Many SCADA systems are merely walled gardens that keep out innovations and third party solutions. Indeed, once installed, a SCADA system guarantees a return to its manufacturer forever.
Adding new digital sensors to operating devices like pumps is usually deemed to be too costly because of the management of change process, too risky because of cyber concerns, or too uncertain given their novelty. The industry has learned to slow-walk sensor deployment, and tolerate dumb metal in the system.
3) Work is too complex to automate
We think the work to be done is complex and cannot be automated. It requires high levels of skill, years of training, and human intelligence to execute. Oil and gas is no place for robots, only engineers can engineer, and geologists alone can combine the art and science of interpretation.
There are plenty of other orthodoxies in the industry that need to change, such as transparency, competition vs collaboration, open source vs proprietary. Pause a moment and think of your favourite orthodoxy to challenge.
What is so special about this round of technology and why is it somehow different?
What Is Digital?
To understand the impact of the internet of things, we do need to agree to terms. And despite the near universal use of the term “digital” to represent features of our modern economy, there is no shared definition of what digital actually is.
To an engineer, digital is an alternative to analog. To a millennial, digital is an integral part of everyday life. To a doctor, digital describes an awkward medical procedure involving latex gloves, some lubricant and a moment of embarrassment.
Here’s my definition. Something digital incorporates three building blocks (or the digital trinity) that together create something that most people generally concede is a digital device, solution, or service.
• Data—data is the lifeblood of digital. A digital device, solution, or service produces and uses data.
• Analytics or computational ability—a digital device, solution, or service has the ability to carry out calculations and computations on the data.
• Connectivity—a digital device, solution, or service uses a telecommunications network that allow digital devices to connect with one another to exchange or share data, or computations.
A smartphone is an excellent example of a digital thing: it has data, such as address books, pictures of my recent lunch, and maps; analytics, which are apps that carry out calculations, such as calculating the distance between two points; and connectivity, since it’s a phone. Probably the one thing I rarely use it for is as a phone.
I can think of lots of modern examples of digital things in the oil and gas world:
- Tank gauges—tank gauges are shrinking in size, cost, and power demand while expanding in capability. Australia’s unmanned out-back airports have gauges on their tanks that give fuel providers real-time visibility to tank contents, so that the tanks can be replenished when needed.
- Vehicles—Next-generation vehicles are packed with digital smarts to allow them to communicate with each other and with smart transportation environments. Porsche is embedding blockchain technology in its sports cars.
- Valves—With sensors and actuators falling in cost, even traditionally dumb devices like valves can be brought online, generate their own data feed, and tie into supervisory systems. The same for drill bits, flow-measurement devices, motors, and filters (the basic building blocks of process manufacturing).
The digital trinity are all based on a single foundational technology, which is the lowly computer chip. As chip technology advances, the cost of earlier generations of chips falls to zero (manufacturers basically give them away) and it becomes economically feasible to incorporate chips into almost everything, and to cram more capability onto them. They become smaller, thinner, lighter, safer, richer, and, most critically, they need very little power to operate. It is the chips that store the data, provide the computations, and enable the telecommunications computers that drive the network connections.
All three sisters of the digital trinity are each experiencing massive exponential growth.
Where the oil and gas industry has always worked in a world of constraint (one of its orthodoxies), digital is creating a world of abundance—abundant data, analytics and networking.
The volume of digital data we create have been growing prodigiously. IBM estimates that between 2015 and 2016, the world generated almost as much data (90 percent) as already existed in all of the world’s storage systems, much of it pictures of cats.
- A high-quality photo comprises eight to ten megabytes of data. Most of us do not even discard photos anymore. They simply pile up on our phones and home computers. We upgrade not because the software is obsolete but because there’s no more room for photos.
- A high-quality ten-minute video taken on our smartphone takes up 1.5 gigabytes. Four hundred hours of video are uploaded every minute to YouTube.
- A typical flight produces a terabyte of data, and autonomous vehicles and trucks will generate similar data volumes.
Industrial data volumes are not growing at quite the same pace as consumer data, but that’s because industry has not yet equipped all its various assets, tools, and people with sensors. But as industrial assets become data generators, they will match the prolific data generation of humans.
Beyond the growth in volume, data is also changing shape. Early generations of computer systems could only process highly structured data, such as rows and columns on a spreadsheet, in the form of numbers and letters. But modern data can take almost any shape, including unstructured data like photographs, waves, sounds, video, and sensations like vibrations and smells.
Analytics, or computational power, is also demonstrating the same rapid development and growth as data.
A smartphone has much the same capability of the mainframe systems that enabled NASA’s moon-shot programs in the 1960s, and, in just ten years, smartphones advanced from a novelty to a must-have for modern life. My watch has the horsepower of a 1990’s Cray Supercomputer.
Lots of field workers in oil and gas are wandering around with super computers in their pockets. What are they using them for? Not moonshots.
The third sister of the digital trinity is connectivity. Without connectivity, a device that has data and analytics is no better than a calculator.
Low-cost chips, analytics, and software development have helped transform the telecommunications sector in just one human lifetime to enable extraordinary connectivity.
The world is becoming highly interconnected. At the end of 2016:
- the number of households globally with Internet service was around 54 percent, compared to 80 percent that had access to electricity.
- the number of individual Internet users was about 3.5 billion;
- the number of mobile phone subscriptions, a measure of the number of users able to tap into digital services, reached 7.7 billion; and
- the number of inanimate objects or things that are connected to the Internet is estimated to be about 8 billion and will grow to 30 billion by 2030.
The volume of data that networks move provides a good indication of the penetration of and demand for connectivity. In 1974, the total amount of data that was transmitted on worldwide networks in a month was one terabyte. By 2016, worldwide networks move one terabyte every second, an increase of 2.5 million times.
The trajectory is pretty clear—smaller, cheaper, more capacity, lower power, encrypted, connected. What was constrained is now abundant. What was prohibitively expensive is now effectively free. What was privileged and elite is now common and democratic. What was novel and risky is now embedded and background. That’s 5 more orthodoxies that no longer hold.
A Framework for Digital
Yogi Berra once said “making predictions is difficult, especially about the future”. Let me share with my sense as to how this future, internet thing world will play out.
At the heart is a story about data—generating, analysing, consuming, managing and presenting data. Winning at digital means winning at data. Data needs to be viewed in oil and gas as a corporate resource on par with other assets. Data management needs to receive greater attention, data talent needs to be recruited. Accountability for data in Oil and Gas must be strengthened.
The Internet of Things Generates The Data
Where does all the data originate? The sensors and the rise of the internet of things. Sensors generate enormous quantities of data, with greater diversity in form and content, at ever declining costs. They appear on virtually everything—pumps, valves, vehicles, vessels, and people. Oil and gas, as an asset intense industry, drives demand for internet-connected things. Tolerances will have to tighten, and measurement standards must improve.
AI Interprets the Data
Only the modern tools of machine learning and artificial intelligence are able to process the immense volumes of data that the sensors generate. Yesterday’s technology—spreadsheets, personal computers—are not up to the task of storing, manipulating and analyzing the rapidly rising tide of data.
AI drives demand for data science professionals, and is a key reason why universities and technical schools are rapidly revamping their training programs to incorporate more emphasis on the data professions.
The amount of money and investment pouring into AI, coupled with the phenomenon of fleet learning—individual AI engines that share what each other learn the instant they learn it—point to constantly falling cost and improving capability. Eventually, job design starts with AI and incorporates the human attributes, rather than the other way round.
Robots Apply the Data
Autonomous technologies (or robots) consume the AI-interpreted data to carry out real work. Heavy haulers in the oil sands mines are just the first and most visible examples—their onboard cameras and sensors feed data into AI machines to interpret the real world and its hazards, and the hauler starts, stops, turns and accelerates. For the moment, a human controller is manipulating these machines, but in time even that task becomes unnecessary.
Industrial machines have on-board AI capabilities through which they make increasingly smart decisions. These decisions include, given a set of changing conditions, when to run, at what pace and using what resources at what cost. Today, only humans make these decisions, or don’t make them at all.
Cloud Stores the Data
Cloud computing is the logical place to store all the data and house the analytics. Cloud is fast to deploy, is more secure, and can ramp up and down more easily.
All those sensors need the occasional (or frequent) patches to deal with viruses and attacks, too. The only practical and cost effective way to maintain software reliability on these sensors is through cloud-enabled subscription and distribution. The end of the traditional software business model, which has many implications for how companies govern their use of technology, is rapidly approaching.
Blockchain Provides Trust
The rapid growth of sensor technology, robots and analytics drives the need for a ∫ that is not human centric—blockchain. Blockchain technology provides the immutable record over sensors, data movements, the AI engines and the robots to assure they are reliable and not compromised. By assuring trust, blockchain confers agency on the robots, allowing them to operate without human supervision or human intervention.
Blockchain opens up entirely new business models, such as asset sharing. Instead of a business needing to own an asset, it can subscribe to the asset, and pay only for the cycles consumed, which are recorded with trust on blockchain. Balance sheets are transformed when long life, low utilization assets can be available when needed.
ERP Enables the Commercial Environment
Enterprise Resource Planning systems are themselves becoming digital and are a key part of the future where they support the commercial processes of buying, selling, tracking and measuring. In time blockchain technology displaces some commercial functions too, but for the time being, ERP is the commercial backbone.
ERP systems now embed AI engines and blockchain support within, which makes them potentially much more useful across a broader sweep of the organization. Integrating operational assets with commercial ERP data is a defining feature of digital—a compressor uses its own on-board AI capabilities to decide which power source to use based on incoming weather, and the market price of power, contract for that power, and pay for it as a single integrated transaction.
Agile Methods Are How Digital Gets Done
Digital innovation requires faster ways of getting things built and deployed, and Agile is the language and method of streamlined work practices. Hand in hand with Agile are faster ways to introduce change to operating environments (or DevOps) and better ways of interacting with technology (or User eXperience).
The logic of separate technology organizations (one for commercial technology that delivers business change in one fashion, and a different organization for operational technology and managed in a different fashion) falls away. IT and OT need to work together to deliver digital solutions and need a common way of working. Agile is the basis for that collaboration. Industry leaders merge their IT and OT organizations into one unit with one executive accountability.
People Manage Change
The future of work for people is designing and building digital environments that integrate these digital innovations. Multi-disciplinary teams that assemble new methods of working, deep data skills, process modellers, system integrators and business model designers, work together to construct new digital solutions using Agile methods. Helping people cope with change relies on our human only skills of creativity, empathy, story-telling, teamwork and problem-solving.
Business needs both new kinds of talent and purposeful re-skilling of existing talent for a digital world as the methods of working—stage gate, asset-centric—give way to Agile and data-centric. For example, robots require their own handlers, AI needs mathematicians, and the mountain of data calls out for data scientists. Dozens of unfilled jobs for individuals with these skills are listed on the many job sites, not just for oil and gas, but in many other industries that are experiencing the same digital wave.
New Orthodoxies to Embrace
To realise this future, we need to free our thinking from the constraining ideas of the past. I propose that the industry, at a minimum, adopt three new orthodoxies to replace the tired ground rules of the present
1) Set data free
We need to think differently about data. If it wants to be free, set it free. The dozens of creative digital start ups now blossoming in Calgary and beyond are abundant with capability and creativity, but starved of data. Our industry is abundant with data but short of digital know how. Combined, we can unlock the next wave of business transformation.
We need to accord data some value so that it attracts capital. We need to champion data so that the market recognizes what oil and gas already knows—we are as data intense as Facebook, but without the risk of Jeff Bezos private parts interfering in our lives. We need to free data from the bondage of human interpretation and let machines take over.
2) Dumb metal is expensive metal
We need to recognize that dumb metal, which requires human overlords, supervisors and maintainers, is the expensive metal. Metal trapped in a walled garden that can only speak the secret language of some obscure SCADA system should be treated much like a newly discovered tribe on the banks of the Amazon in Brazil—the subject of scientific curiosity, but please—avoid contact to avoid contamination.
The inverse of expensive dumb metal is cheap smart metal. We need to start design from the perspective that metal must be made smart, and stay smart over time. Smart metal (the internet of things) must be the minimum mandatory, and not the nice to have.
3) Work is too costly not to automate
South of the border, our US peers and competitors are rethinking the work. Instead of 10 and 15% improvements from digital, companies are aiming for 75-90% improvements in cost reduction, productivity gains, and asset turnover. As if they didn’t have enough blessings from their copious shale deposits, the Americans have discovered that entire production fields are better managed by artificial intelligence, provided that the field is highly bejewelled with internet of things.
If we let go of these orthodoxies and free ourselves to embrace new ones, if we move quickly to adopt digital innovations into the industry, if we open our minds to the opportunities, we can keep the industry moving forward for many years. And as I have set out, the internet of things is central to achieving this vision.
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