Business-case for non-linear world

I wrote recently about the Delta data meltdown and how the investment in technology had not been made sensibly. I’ve seen this in a number of organisations – where status-quo seems cheaper than updating. It’s an argument that would not be made for safety or passenger comforts but appears to be OK for back-office IT systems.

The world has moved on and it now relies on data as a core asset and capability. With the 4th industrial revolution this is only going to become more reliant on data and understanding how to make risk-based investment decisions will be key.

InfoWorld report that Cloud technologies could have made even a traditional business-case work [Link]

Here is my post about DELTA [Link]

This is what Delta’s CEO had to say [Link]:

“it’s not clear the priorities in our investment have been in the right place. It has caused us to ask a lot of questions which candidly we don’t have a lot of answers for.”

 

It’s just an analogy

I’ve recently been working on analogies designed to let me talk about Industry 4.0 concepts. In short I’ve been trying to find ways to explain what’s almost unexplainable, and often to a sceptical audience. This is my current favourite:

Here’s what happened lasttime

In 1993 the Internet was explained in terms of bits, bytes, modems and tunnels. Most people had no idea why this geeky stuff would be important or what it could possibly be used for in everyday life. By 2003 it was explained in terms of Amazon and Facebook. Now my mum can order shopping on-line but has no idea how the Internet works. That’s how it should be, invisible to the application. My niece uses Facebook, WhatsApp and ASOS and can’t really imagine not using them – it’s woven into the fabric of how she does things, she’s never done it any other way. Why would she? In the mean-time those that had no idea what the geeky stuff could do ignored Amazon and are now closing their retail space [link]

Here’s what’s happening now

Industry 4.0 is now explained in terms like sensors, internet-of-things, and security. There is little understanding of how to retrofit this into existing ways of working, or why all this geeky stuff is relevant. In short people think this is a nice to have but really changes nothing. In ten years I will be explaining this in terms of its application and not how it is implemented. Industry 4.0 will be a forgotten concept and we’ll be talking about its various applications – like operating and maintaining according to equipment condition. In 20 years time a maintenance engineer (like my niece does with Facebook) will have no concept of why you would (or even could) operate equipment without on-line condition monitoring, system level surveillance, and connected “helper applications” that learn from global failure modes. Why would she?

But surely we’ve already been here?

I normally get an objection at this point along the lines of this:

“We’ve had digital oilfield for years, and it’s promised a lot, cost a lot and not delivered much – why will this be different, why should I think there will be a change.”

In my view, things no longer change incrementally when platforms become ubiquitous and costs tumble 1,000 times. They “take off”. That’s what’s occurring now. Add to these exponential technologies such as machine learning (which self-improve with time and experience) and t the stage is set for big breakthroughs.

Four companies: Facebook, Google (Maps +Waze), Uber, Amazon would be impossible without the widespread adoption of horizontal general technologies. They’re interdependent and co-ordinated rollouts enabled cross-platform co-innovation at the application level.

By the way – If you think these companies are just fluff : Google is worth 356Bln, Facebook 350Bln, Uber 62Bln and Amazon 250Bln. In total over a trillion dollars. For comparison Exxon is valued at 360 Bln.

Adoption Curve is reversed

Here’s another thought – In the 1960’s Military and Space applications were modified for business use before finding their way into the hands of rich consumers a couple of decades later. Facebook-like platforms and messaging applications such as Skype emerged first in the consumer space before being adapted for corporate deployment.

I think this mode of adoption is now true for application level innovation generally. If this is so for our next wave application innovation for industry 4.0, I expect to see it emerge first in the consumer space, deploy rapidly at scale and be ready to find ways to adapt and deploy in industry. It will be people like my niece that will know how to leverage these applications with no need to have any knowledge of how the underlying infrastructure works.

Keep your millennials close at hand; you’ll need their insights.

Image Credit http://parterre.com/2011/12/01/interrrupted-analogy/

 

 

Where’s the Delta?

On Sunday August 7th 2016 Delta airlines suffered an IT outage. Earlier in the summer SouthWest airlines suffered similar.

Delta cancelled at least 740 flights by Monday (I am sure there will be more) and Southwest cancelled 2,300 flights.  (Reference link , BBC link)

My calculation, at the bottom of the post, suggests that this cost DELTA at least 60 Million USD in lost capacity –  not counting the damage to the brand and additional costs associated with handling customer enquiries.

IT and the business are inseparable in the 4th industrial revolution. For many years there have been moves to outsource IT, drive down its cost and to make it standard and commoditised.  For utility IT this made sense. It was a cost of doing business. It was a necessary qualifier attribute but conveyed no competitive advantage.  If your copy of Microsoft Word was slightly faster than mine, it was unlikely that you’d capture more business or be able to charge more.

The outsourcing movement was used to drive this process, often awarding contracts to low-cost service centres in Eastern Europe or India.

In my view cloud based services – such as Microsoft 365 and Salesforce.com will become the norm for utility IT services and remove most of this responsibility from the IT department which will, as a consequence, go the way of the typing pool. In 25 years new entrants to the workforce will scratch their heads wondering what the point of the IT department was.

The world is, however, changing and changing rapidly. IT is becoming embedded into the core operational process of business. And executives that don’t understand IT will not succeed for long. Any company that perpetuates the phrase “IT and the Business” or any IT department that talks of “The Business” as if it were something separate from the IT function will go the way of the dinosaurs.

I don’t know if Delta outsourced its IT, or what the cause of the issue was. But it is clear that the situation was mismanaged before the outage (Reliability and resilience: no hot-backup, or hot disaster recovery ). This calls into question either the competence of those charged with planning operations or the business decision to not invest in technology and systems. Either way this is a failure of management to grasp the importance of IT in the primary operations of the business. Just because you don’t understand it doesn’t make it simple, or mean the problem can be ignored. Airlines are pretty good at maintaining aircraft, there are international standards for how it should be done and inspection audits making sure it is. Perhaps we need something similar for IT?

On this occasion it was a risk management failure where the loss of IT functionality impacted availability and utilisation of assets. My guess would be though that there are many areas where IT could be applied to the primary business to drive increases in efficiency and reliability. If management is unable to understand the business case or appoint competent management for IT resilience it is unlikely that they are exploring these more nuanced applications of IT.

The airline industry is not alone.

Put this into business context

In 2015 Delta operated an average of 5,400 flights per day, so about 15% of flights were grounded on Monday. Assuming that these planes were now in the wrong position some of them would have to reposition empty (let’s say 50%). Passengers rebooked who were scheduled to fly on a grounded flight (and Delta allowed all passengers to rebook any flight scheduled for Monday). Let’s say 30% of all Monday’s passengers (those on grounded flights and a similar number who took the precaution) took the place of fare paying passengers on later days.

Then we have a utilisation impact on aircraft of:

15% of one day capacity for cancellations

7.5% of one day capacity for repositioning

30% of one day capacity for rebooking.

52.5% of one-day’s capacity utilisation (in the height of busy season) was lost due to a systems outage.

Assuming 350 flying days this is then 0.525/350 = 0.15% capacity hit for this outage.

Last year’s revenue for Delta was 40Bln USD.

My “back of the envelope” calculation suggests that this systems outage cost DELTA $60Million USD in lost utilisation.

The brand has been impaired so future passenger numbers are likely to be lower than they would have been (at least for a while, especially as they could not even take bookings on Monday). Add to this the additional cost of media relations and customer complaint handling and we’re looking at a $100m problem.

Oh and if you are a European Union passenger you are entitled to 600 Euro’s in compensation too.

image credit Link

New industrial revolution

Bill gates was quoted in Forbes today predicting a new industrial revolution. [link]. This is in his review of Robert Gordon’s new book. I agree with Bill and if you’d like to know more about the Robert Gordon (old school, grey hair, suit and tie – 1945-1980 view of business) and the post-internet view of progress have a read of my primer here [link].

Bill gates points out three key examples as Robotics, A cure for Alzheimers and Material science. I like the way he boils it down so simply. I was influenced by books in my youth including Alvin Toffler’s future shock which I read 30 years ago, it was already a classic then [link] (Poor Alvin died last month), books by Robert Beckman [link],  Edward de Bono[Link] and James Dale Davidson [Link].

I think there are two books that anyone should read if they want to prepare for the next big trends:

Industries of the Future, Alex Ross [Link]

Second Machine Age, Brynjolfsson & McAfee [Link]

Image by Kyle Bean

Let’s party like it’s 1993

It’s been a long time since I felt like I do now. 1993 to be precise.

In 1993 I was working in Paris with a ‘386 LCD screened laptop and had just loaded 40 3.5” diskettes to get Microsoft Visual C installed. Computing was difficult, slow and expensive then. Few people knew how things worked or what it could do.  Many of my bosses couldn’t work their email and none used spreadsheets. We may have used computers to desk-top publish but we still printed slides onto acetate to project them.

I was writing software for Schlumberger at the time. I was in Paris and working on Sun Microsystems boxes running X-Windows.

So why 1993 precisely?

I installed a programme called Mosaic. It was available on PC’s, Mac’s and Unix and you could download it from CERN in Switzerland using FTP, if you knew how. You could compile it using Gnu C, if you knew how. It connected to the network and let you do all sorts of clever things through WAIS, Gopher and HTTP, if you knew how.

My fellow engineers and I were blown away by the potential. It was obvious to us. When we showed this to our bosses back then they had no idea what the point of it was, how to use it or why it was important. And I couldn’t find the words to explain – there was such a gulf of understanding and so little time to fill in the blanks.

By 1997 Mosaic was Netscape and the internet boom got underway, I could buy a book from Amazon and have them send it to me in Norway and I had opened a US Brokerage account with a company called Etrade that you could access over a telnet connection to Compuserve. Now my bosses were intrigued, but still not investing. Investment in Linux version of our software and internet browsing didn’t start until 1999. Looking back that was quick, but at the time is seemed like an age.

I think about the changes that happened between 1993-2003  (just before the iPhone was launched), and the difference between 2003 and 2013 – how social media, location services and mobile internet have taken off. Life is very different now than it was 25 years ago, and it’s all driven from that set of technologies that Mosaic brought together.

Look at the difference at the productivity levels of geoscientist and data analysis with in Oil companies. That has tracked the changes in wider technology and information processing.

Now look at how little has changed in the operations of an oilfield since 1993.

Industry 4.0 feels like Mosaic did. It’s big, it’s going to be rapid and it’s going to change everything. Yet I still can’t find the words to explain it to the people I meet who are still struggling with their email. But I’m working on it.

Read this primer and perhaps you can help me explain to operations management:  https://bestemnetwork.com/2016/03/29/innovation-and-productivity-with-4th-industrial-revolution/

Innovation and productivity with 4th Industrial Revolution

This is a long post. There is a lot to understand on this topic and this is the primer you’ll need. Please do follow the links. It will take a while but it’ll be worth it.

There is much being discussed around the acceleration of technology and how exponential development in multiple areas is converging and how this will impact on industrial production. About time too really because productivity is failing to pick-up, interest rates at or below zero, cash being hoarded by companies and investment rates are low [link]. This exponential increase is actually not that new – Moore’s law’s been around since… well since Moore launched Intel, and it was a one-way flow before even Schottky was on the scene. These trends are not new and if you don’t believe me here’s a great talk from 11 years ago by Ray Kurzweil with lots of evidence and predictions [Link]. Even Bill Gates saw this in a book he published in 1999 called Business @ the Speed of Thought [link], though these days that speed would be seen as a little too slow.

In my opinion the Oil industry harnessed many of the aspects of this movement in upstream exploration during the 1990’s. It was an early adopter in the process of FINDING reserves. Then the process of adoption stopped. Productivity per geoscientist and the complexity of the information they deal with is orders of magnitude better than it was during the last oil-bust of 1986, so much so that we now have more fields and deposits than we know what to do with. We’re pretty good at finding the stuff. But we’re quite rubbish at developing and operating it at low cost – especially small deposits, which we are so good at spotting now. Development, Operations & Maintenance has ossified – contracts and work practices are stuck. From an operator approach, the production of hydrocarbons has barely moved since the early 90’s (FPSO concepts aside). In my opinion through outsourcing, procurement, short-termism and misalignment of incentives it has become positively petrified.

If the Fourth Industrial Revolution is really going to have an impact we’ll need to address development on four fronts: Economic, Social, Political, and Technical

Economics

If this is going to happen then it has got to make sense for the bottom line. That means productivity: outputs, inputs and the cost of technology. McKinsey, recently cited in Industries of the Future, by Alec Ross [Link], suggested that the manufacturing sector could raise productivity by 2.5% to 5% and save more than $1Trillion in cost annually.

In one example McKinsey says “To capture the potential, manufacturers can consider three moves. Primarily, companies can gather more information and make better use of it. An oil-exploration company collected more than 30,000 pieces of data from each of its drilling rigs—yet 99 percent of that data was lost due to problems of data transmission, storage, and architecture. The tiny trickle of data it did capture was incredibly useful for managers. But so much more can be done. The executives we surveyed said that correcting these data inefficiencies should improve productivity by about 25 percent. [Link]”

Of course some traditional economists think we’re doomed to no innovation and permanent low growth – such as Robert Gordon [Link]. There are many in the old-guard of Oil and Gas that would agree. Most of them have their secretaries print their emails out for them, and refuse to carry a smart phone. Good luck chaps, I think you’ll find the millennials don’t care what you think anymore. Others say differently [Link]

There are many big hitters with some very big numbers, they’re all pointing in the same direction. I’m backing the future, not the past. And I think that Industry 4.0 will feature in the future of Oil and Gas. There are challenges but the prize is big enough that we will overcome them.

Social

The way that many of us work is going to have to change. Luckily the Millennials are already preparing for this shift with their search for meaningful work, emphasis on creativity and individuality; and understanding that they can blend their work and leisure time in ways that the crumbly generation see as slacking and entitled. Forbes have a top ten ways in which the work place will be influenced [Link] and Linda Grattan has her views here [Link]. For me it just seems an obvious way to work. But then I’ve never been very good at dealing with routine, structure and command-and-control. It’ll be interesting to see how we can blend the command-and-control requirements of operations with the caffeine fuelled micro-attention span of people even more “wired” than me.

We’re also seeing cyber-social developments such as the creative commons movement [Link] and open source projects like the Arduino [Link] all of which are fuelling exponential cross-fertilisation of ideas. We are witnessing the rise of the sharing economy [link] and temporary configurations of people who move about often. These are all challenging assumptions about ownership and permanence that are at odds with our current ownership-model for resources.

Political

The Guardian in Nov 2015 reported that ” this revolution could leave up to 35% of all workers in the UK, and 47% of those in the US, at risk of being displaced by technology over the next 20 years, according to Oxford University research cited in the report, with job losses likely to be concentrated at the bottom of the income scale.” [link]

With modern communications and the ability to mobilise quickly we’ve already seen massive changes in the way the people (or, in Greek, demos) interact with conventional democratic systems and capitalism. This is very thoughtful piece by Yanis Varoufakis the recently deposed Greek finance minister [link]. Whether that’s the Arab spring, so-called ISIS, Brexit, the mass-migration of populations or the astonishing rise of Donald Trump, things are getting decidedly odd in traditional politics. There’s a lot of complaint and not a lot of traditional power that can be exercised in public anymore [link]. Just take a look at the mass-mobilisation of a Brazilian flash-mob to protest graft allegations levied against the establishment [link]

Cyber-politics is a whole new dimension. Whether cyber aggression is aimed at accessing private information, denying or altering the dissemination of information or compromising the physical integrity of machine-based systems the ability of people to alter the course of events through “hacking” has never been so great. China has its infamous PLA unit 61398 [Link] one of over 20 cyber-military units it controls, North Korea doesn’t like Sony much as the 2014 hack showed [Link], Iran might be the land of the rising Shamoon that hit Aramco [Link], Ukraine has got on the wrong side of Russian Hackers who shut off their power grid [Link], and who knows who might have written Stuxnet that took out the Iranian centrifuges while telling the control room all was normal [Link]? Now the actors are not only nation-states, but also corporations and little boys alone in their bedrooms [link]

We have the Geneva convention that is supposed to stop states shooting the red cross, bombing civilians, gassing troops and firing mercury-filled dumb-dumbs. We have the international court in The Hague (funded by Andrew Carnegie incidentally [link]) that prosecutes war criminals. I’m not sure who I should call if North Korea invades my X-Box or steals my Bitcoins. And if you are a corporation with cross-border operations you don’t either.

Technical

There are a number of technologies that are developing exponentially at the moment and they’re feeding into changed ways-of-working that will bring about the fourth industrial revolution. Ultimately this will help you plan to build better plant and it will help you operate what you have better. Optimising operations is a sense-and-respond problem. Prepare for the future, know what’s going on right now and do things to make it better. Technology that helps falls into four areas that increase:

  • learning about what’s possible;
  • what’s going on right now and situational awareness;
  • knowledge of interdependence, decision options and consequence; and
  • ability to execute quickly and accurately

Increased learning about what is possible

Big data has gained traction in the last decade. Grab lots of data from everywhere, apply some Bayesian stats, set a base-level and determine the probability of correlation. Works really well when you buy a book from Amazon and it suggests that you might want to buy some reading glasses to go with it. Works pretty well in finding potential hidden relationships and developing predictive algorithms for equipment failure too [link] [link]

Like a lot of developments, this area is moving fast. How do you know what’s even possible these days? It’s so hard to keep up. Data overload, over-stimulation, who even has time to read this stuff?

I remember Schlumberger creating an amazing “portal” called the hub [link], Other companies did similar [link]. Initiatives were started to capture the learnings from each employee and make them available to all other employees. I even heard a talk once describing the use of retiree mentors to help existing employees [link]. People were planning for “The Big Crew Change” when the aging workers retire and new low people come on board [link]. This all tied into concepts like “Hive Minds” which were popular in the 90’s [link].

Well “The Big Crew Change” became the “The Big Layoff” when oil prices crashed in 2014. All that experience and knowledge was not on the balance sheet but was on the P&L. So it was fired without financial impairment and write-off. But the fundamental problem remained, and probably got worse. So much to know, so much to learn and no time to do it. Welcome to one of the drivers that will build demand for machine learning.

Machines can analyse masses of information much quicker than humans can. Up until recently, however, doing that in context and to derive meaning from them has been hard. Development has been showcased by game-playing computers such as Deep Blue for Chess [link], then Watson for Jeopardy [link], and most recently a Google built machine – AlphaGo for GO [Link].

Combine learning algorithms with connected systems, however, and things get really interesting. Learning requires teaching. Unlike programming in Fortran, learning machines construct their own programs by being taught and from the situations they encounter. Distributed and cloud-connected learning is exponential, one machine learns something somewhere and every other machine knows it. Forever. Perhaps we should blow the dust off those long-forgotten “portal” promises around knowledge bases, institutional learning and corporate memory?

Here is a great TED Talk on machine learning [link]. Of course it doesn’t always go well as Microsoft found out with it’s recent “Hitler loving Sex-Robot” [link]

What’s going on right now and situational awareness

Machines that learn what matters and suggest how to respond can eliminate operator overload by removing the trivial and hiding noise. Automated actions can be taken to keep things running. I recently heard an analogy about the difference between the information received by a pilot of a typhoon (arguably the worlds most advanced fighting machine) and a world-war 2 Spitfire. The Spitfire pilot had dials telling him the airspeed, engine speed etc. All just data. The Typhoon pilot, however, could not possibly cope with all the data available. So this data is assembled to show him only what he needs to know in the current situation and that depends on context.

Paul Smith, former UK RAF Pilot says “Bring all these [sensor and interpretation] elements together and it becomes clear why we talk about Eurofighter Typhoon operators having the ‘Combat Edge’ – the situational awareness and a suite of flexible weapons options that offer pilots a real advantage in the battlespace.” [Link]

Building on this, if the aircraft systems detect a heat-seeking missile closing, it launches flares automatically and tells the pilot afterwards – no point in raising an alarm and waiting! Same for the oil and gas sector, why do automatic fault development detection systems write a report and wait. Why don’t they just order the parts, consolidate shipments and schedule engineers for the next maintenance activity? It’s a small example but Amazon is already letting washing machines re-order soap powder [link], Imagine what Amazon-like logistics would do for the Oil and Gas industry.

In order to know what’s going on right now requires a lot of sensors talking to each other and reporting back. Too much detail for a human system to ever cope with properly. The data needs to be reporting to systems that learn what’s important, what actions it should take and how it should present its findings to its operators. The system needs to learn how to behave. These systems need to be aware of the situation and act accordingly. Cloud computing is also an important vector this mix, where systems are connected to each other through internet, and keep each other in synch sharing learning and preparing information so that it can be shared widely, securely and scalably. Google are letting developers play with their learning platform [link]. This is an area where we will see rapid innovation that Oil and Gas can benefit from.

Of course there are some very boring building blocks that will be needed. Connecting systems together will of course require a lot of plumbing – don’t underestimate the size of this problem, here is an example of the type of architecture you might need [link]. Companies like Eigen (www.eigen.co), Tibco (www.tibco.co.uk), BEA (www.bea.com) are active in this area. And it’s important that we really know that our data is correct – as in this case when a demolition crew targeted the wrong house and blamed it on google maps [Link]. So companies like datum360 (www.datum360.com) and Informatica (link).

Decision making & Interdependence

Knowing what’s going on is great, but what do you need to do to make your situation better? That’s the question that quickly arises once teams get sight of data and information in context. Firstly it’s important to know what the options could be – but also how choices in one system effect another.

Simulation is one of the keys to understanding the consequences of decisions – that’s why chess computers work out 100’s of moves ahead and choose the best one to use now. To simulate the decisions on a plant requires a digital model of the plant and its behaviour against which to run tests. The digital model is sometimes called a “Digital Twin” and this allows you to make a change or react to a fault condition and see what the knock-on consequences of selected actions will be in the future. This can be used to test options and optimise outcomes. Hit the model with a series of possible actions in an automated way and it’s possible to uncover the best sequence of actions and back-calculate why, rather than the normal forward progression. It’s very powerful – here are some articles discussing simulation of plant [link]

Integrated planning enables you to make a decision about sequencing events in such a way as to minimise down-time by running jobs in parallel within real-world constraints. This might mean being prepared and ready-to-act when an opportunity unexpectedly arises. Understanding system-wide effects is the key to getting this right, and with more complex interconnected systems with cross-ownership (like present in the UK sector of the North Sea) it not easy – and the owner stakes in oil fields can lead to misalignment of financial interests. Bain has a good article on integrated planning [link].

So far it seems that human + machine combination provides the best mix for solving problems. The creativity of the human is key and augmented decision making with rapid feed-back loops from simulation enables optimisation of decisions. From the first simple spreadsheets that appeared in business the testing of “what-if” scenarios has meant that we have been able to tune procedures across many areas of operations. The combination is not a new concept, here is a very relevant paper from Carnegie Mellon 1998 [link]

Increased speed and accuracy of execution

One of the issues that I’ve come across is the “precision” approach of some operators in the field. The best plans are of no use if they are not executed properly, if parts aren’t damaged and if the wrong parts were not fitted. It happens. Sometimes, of course, the instructions make no sense and the field have to modify them to make them work. That modification of instruction is rarely fed back into the system so little learning takes place. Sometimes the plant is updated and records not updated. All this leads to mismatch between what is recorded and what the plant operators “know”.

Sometimes the physical effort required to perform an inspection means that it cannot be done as often as you’d like, or perhaps is skipped by a crew unwilling or unable to schedule. Autonomous vehicles are in use for inspection activities firstly replacing deep divers and latterly, as costs have gone down they are found in inspections roles as Drones taking cameras into inaccessible places. Perhaps it won’t be long until we have small UAV’s mapping plant and equipment in huge detail. Here is a TED talk that demonstrates what’s already possible [link]

On-site machining of parts may soon be replaced by on-site manufacturing. Additive manufacturing (a broader term than 3D printing) is finding its way not only into printing of small intricate parts but emerging are the start of large-scale construction. It’s not there yet, but imagine what this would mean for logistics or construction in hostile environments. Here is an example of a team in Amsterdam who are in the process of printing a Steel bridge over a canal. That could change some of our approaches to Maintenance and Modification one day. [link]

And, of course, there will always be people involved. But multi-skilled and informed. Augmented reality displays – identifying parts, performing on-the-fly risk assessments and acting as advisors. This will change the way that operators will be able to apply basic skills augmented with real-time instruction and feedback. Meron Gribetz demonstrates here a virtual reality system that could revolutionise the on-shore-off-shore interface, as well as providing just-in-time information. Here is his TED talk [link]

And if you don’t think a Robot can replace people on platforms – have a look at this [link]

 

 

ITF Aberdeen: Oil 2.5 vs. Industry 4.0

I was at the ITF Showcase in Aberdeen last week. It was an interesting event, if mildly concerning in some ways. Here is the link to the presentations [Link]. The encouraging notes were that there appeared to be some money being made available and that the industry had focussed on key themes around the MER UK forum [link]. Less encouragingly for me is the speed, energy and sense of urgency that was lacking.

I noted that the room consisted of 90% men (often in grey suits) and I reckon 75% were older than 50. So where are all the young people?

I have always been impressed with the approach of Colette Cohen [Link] from Centrica, a strong proponent of adopting technologies from other industries. Despite being a fully-fledged, dyed-in-the-wool oil and gas executive she retains an energy of purpose, nurturing of young people and a curiosity needed to drive innovation. She was on fine form and provided a welcome boost to the enthusiasm of the room while being the voice of reason when asked why wire-guided rockets couldn’t be tested on Centrica wells. Can we have more pioneers like her please?

I am based in London and the innovation and technology events I attend (and the informal networks I am part of here) feel very different. There is an energy and drive in the FinTech and internet sector that appears missing in Oil. Also when I go to events I find plenty of trendy young people brimming with ideas, and there are plenty of women there too (still not 50% but still way better than last week by a country mile). Diversity will be important for innovation. To be successful we must learn to harness the view-points that come from all sorts of diversity: racial, sexual, age, experience, industry, education – and find ways to encourage and shape ideas.

My next post is going to cover some thoughts on innovation, the fourth industrial revolution and what will drive productivity in the next 20 years. But suffice to say it will rely on data and automation, but many speakers [I’ll name no names] took great pleasure in informing the audience that they didn’t believe in the cloud and that they had piles of paper on their desk. When describing new tech there were plenty of references to “if you don’t understand this tech, then ask your kids”. It reminds me of ancient bankers who use fountain pens and a paper diary. It’s not cool it’s deliberately Luddite and crusty and an attitude that will kill our industry. Perhaps it’s time to get with the program or step aside.

One thing that stood out was the problem of accessing markets and testing new product. In my experience operators are generally not too interested in experimenting with new tech, and often their operating philosophy revolves around large frame contracts which means that they don’t really control access to the supply chain. The consolidation of suppliers, the integrated nature of their offerings and the point-nature of new technology development does appear to lead lock-outs and stifle innovation.

The Graph above is from Colette’s presentation. It’s an SPE graph, it shows that Oil and Gas has been great on innovation in the past, and we haven’t had a breakthrough for a while. What strikes me is that since 1946 all the innovation has been in finding or developing fields. My money is on operations and maintenance to join the party. And that will be driven by what the cool kids call “Industry 4.0” [link].

031716_1806_ITFAberdeen2.jpg

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