It’s not what you do, it’s the way that you do it……

This post is about competence, capability, and behaviour. Three words that many people are comfortable using but ones for which, when asked for an explanation of meaning, I have uncovered hundreds of different underlying concepts.

I’ve found that words really matter because they shape the way people think and behave. I’ve found that people can use the same words but mean different things. This gets in the way of organising group activity.

I pay more attention than many people I know to this. I take time to clarify and develop shared understanding. Maybe it’s because I’ve worked in many countries and cultures. Maybe it’s because I was trained in solution selling early in my career. Maybe I’m a pedant. I don’t know.

My roles in sales, marketing and as a consultant have presented me with opportunities to interact with hundreds of different companies across different continents and to observe their approaches to structuring work. I find it fascinating to uncover why things are the way they are, and how to make progress in different settings.

I find that people are often unaware of their own assumptions – what they believe to be objective truth is probably only so within an accepted framework, and that framework can sometimes be just an opinion. Maybe it isn’t accepted by others.

I have found that with careful choice of words it’s possible to influence individual performance and create improved group outcomes.

So here is my simple definition of competence, capability, and behaviour.

Competence

This is something that an individual person can do. They have a level of competency ranging from “incompetence” to “mastery”. An example might be “carpentry” – and may consist of sub-competencies such as “joint making”, “cutting to size”, and “veneering”. Competence is a combination of knowing what to do, the skill to do it, the number of times you’ve done it before (accumulated practice), and how recent the last time you did it was.

Capability

This is something that an organisation can do. In a one-person company it’s essentially the same as competence. It is strongly correlated with competency in a lone-wolf role such as rain-making sales. In other areas, capability relies on the successful organisation of different competencies brought by more than one person. In these circumstances an organisation can create capabilities that no single person is competent to perform on their own.

Behaviour

This is the “manner” in which work is performed. Are people polite to each other? Does a person have “presence” and “gravitas”? An organisation can exhibit collective behaviour – which is related to but not the same as culture, another word often understood differently. An individual can exhibit behaviour – which is related to but not the same as personality.

In both the case of capability and of competence it is possible for organisations and individuals to exhibit different behaviours but still be equally capable and competent. In this case they may well achieve different outcomes, especially if they must influence others.

What do you think?

What do you think of these definitions? How can you help improve them? Please comment here or email me directly.

How are you going to innovate?

This year everyone appears to be talking about innovation. Many think it’s being driven in response to the pandemic. If that were so, all we would need to do is wait until the vaccine is delivered and we can forget about it and go back to the way it was. Almost no-one believes this to be true.

The commercial world is evolving, and the end state is not yet known. This means traditional budgeting, planning, efficiency drives and cost reduction will not be enough for success. Organisations must accelerate their innovation agenda – this is not about inventing something new; it’s about taking what you know, reconfiguring it to be relevant and continuing to adapt and evolve.

In the previous three posts I set out some of my thinking about the fourth industrial revolution because I think this model serves well to explain why we are experiencing change. As part of your innovation thinking you may want to consider seven fundamental factors that underpin the revolution. They may not have an immediate impact on today’s business but as Wayne Gretski almost said – it’s best to skate to where the puck is going, rather than where it is now.

It is hard to untangle these factors because they influence each other and form self-re-enforcing feedback loops (which accelerates change). I find it useful to use this when considering issues and deciding where to focus, I hope you do too.

1. information creation and connectivity

The ability to create, share and access information has implications across social, political, and industrial spheres. Whether as flash-mob revolutions, exposure of tax fraud, mob-trolling of celebrities or remote monitoring of industrial plant and machinery.

​Transparent information undermines authority by revealing the inconsistencies, lies and hypocrisy required to govern. Anonymous transmission of ideas on social media leads not only to emboldened action but also to misinformation and on-line bullying. Information is conflicting and unreliable and knowledge and certainly is displaced by opinion. The ability to sift and evaluate data and then apply rational analysis is not evenly distributed among populations.

​The cost and availability of creation, capture, and transmission equipment has reduced nearly to zero. It is ubiquitous. The creative idea, installation of capture equipment and the editing of results is rare and not free.  One cannot go back and measure the past, so value may be found in stored experience. If you can curate information and control its presentation, then there is power to influence perception.

​Commercial innovation is likely to arise from creative firsts, unique archives, collection networks, influencing curation, and low-cost data organisation, error-correction, and editing.

2. understanding and acting upon information

Advances in computing power have led to new ways to analyse information, methods to learn and infer meaning and procedures to decide how to act. This leads to automation – unattended service, purchase reccomendations, warehouse picking and self-driving vehicles.

​Too much data causes problems with human-led processing such as overload, decision biases and selective world-models. We have evolved to make binary conclusions “being decisive” and “acting with confidence” are perceived as star qualities. Leading based on flexible decisions resting on the probability afforded by analysing emerging information is uncommon. Motivating others to make swift progress in the face of uncertainty will require a new set of leadership skills.

​Commercial innovation is likely to arise from increased quality of service accurately targeted towards needs, as well as reduced cost of provision. Companies that can harness learn to direct activity and make progress under conditions of uncertainty will also benefit.

3. additive manufacture

This is not just 3D printing. Many things are traditionally created by removing material using techniques like cutting, drilling, thinning, and shaping. This wastes material, energy, and time. The materials we use – cement, steel, rubber, plastics are chosen because they lend themselves to these processes.

Additive manufacture will change the materials we pick, it will reduce waste in production and change the shapes we create and the material performance we obtain. It will not only impact factories but also it will change extraction industries and trade routes. It will be possible to email design files and create what’s needed on site without the need to ship raw materials, sub-assembled parts or finished goods.

We are seeing the rise of extrusions and laser-melted metal powders and will shortly embark on assembly at the molecular level. This will mean the same forces that change building materials will impact other wasteful processes including agriculture, slaughtering, drug formulation, paper making and paint manufacture. We can expect to also see different flow-processes with lower temperatures and pressures, lab-grown meat, structured drug design and smaller-batch runs. Additive manufacture principles will impact a diverse range of industries including specialist machine makers, house-hold construction, manufacturing, farming, and medicine.

Commercial innovation is likely to come from creative designs, disintermediating supply chains and creation of innovative not-possible-before shapes and material-performance. There will be insights for applying this technology to industries not considered before.

4. planet maintenance, collective responsibility

Some call this activism or environmentalism, but whatever you call it there are growing movements encouraging (and forcing) vested interests to consider the impact they have on the wider world. This encompasses the materials consumed, the energy used, and the waste products created.

​Fuelled by information and analysis governments have concluded that there is a climate emergency which calls for rapid decarbonisation. This is leading to energy transition, smart-grids and electric drive trains on the one hand, and examination of the energy intensity of industry and ways of living on the other. It has also given rise to the notion that resources on earth are finite which leads to the circular economy (where goods are recycled into new goods) on one hand, and the drive for mining of materials from asteroids and the seabed on the other.

​Commercial innovation is likely to occur around opportunities afforded by legislation – such as carbon pricing, outlawing of practices as well as the inclusion of sustainable methods and transparency of operation. Smart ways to redirect and reuse energy will become valuable.

5. organisation of labour

We now have remote working and video conferencing; people don’t need to go to the office. People don’t need to be in the same town or the same country.  The COVID crisis of 2020 saw mass adoption and made it normal to use.

On-line retail, automation, self-driving cars, and additive manufacturing will reduce demand for labour in many sectors and, due to our global supply chains and clustering of industries, this is likely to create geographic areas where traditional work will become scarce.

The gig economy is at one end of a spectrum of employment that runs from employee, through contractor, project team into gig work. The quantum of work purchased is becoming smaller and pay is more related to outcome rather than time spent on a task. Bonds and exclusive service to one employer is becoming less common.

​Commercial innovation is likely to encompass ways to facilitate remote interactions, telepresence, and ways to build trust (both emotional and technical). Ways in which goods and people are transported will change leading to opportunities in non-traditional geographies and innovations are possible in the way labour is accessed, motivated, managed and rewarded.

6. culture, art, craft and beauty

The 4th industrial revolution moves us more towards a world where less human labour is needed to produce and distribute the goods, services, and energy we need. Other factors will come to the fore in determining what is more “valuable”.

​Where we are used to optimise for low-cost production, we will increasingly favour products, services and experiences that appeal on an emotional level. Emotions will become more important. This is occurring already via inclusion policies, social movements, and campaigns for various forms of justice. We can see on-line culture forming value through influencers and followers whose product is purely an experience and a connection between people with similar perceived values.

​How one spends time will become more important. Dedicating large amounts of time to an employer will seem less likely to determine level of “success”. This will lead people to choose to do more things that they like – leading to more artisan production.

​Commercial innovation may occur in the labour market by enabling people to find their vocation and navigating the changed expectations required to transition career thinking to match the 4th industrial age. The types of products and services sold, and the labour conditions required for workers will increasingly require taking account of design, beauty and evoke emotions, resonate with the values of buyers and be fun.

7. politics of wealth and power

This is likely to be the slowest area of the 4th Industrial revolution to mature. But it will be the most profound and biggest determinant of outcome. While it is tempting to ignore this because it does not lend itself to traditional commercial analysis, it is likely to prove one of the biggest source of disruption and should not be left unattended.

Changes in this factor are likely to occur in (possibly hotly debated) jumps because this deals with fundamental and, for many, unimaginable changes to basic principles of societal organisation. If labour is no longer in short supply this could lead to what used to be called mass unemployment.

I believe that we are less likely to tolerate wide-spread poverty such as that experienced when people moved from the land into the cities during the first industrial revolution. Perhaps we will find a way to allocate resources to people other than by labour, while still maintaining civil and ordered society. What was once called welfare may become a universal basic income.

Accepted definitions of wealth may change to include more than money. Because time is an immutable constraint, this may become a currency. How it’s spent may differentiate between rich and poor. Manners, deportment, compassion and popularity may be qualities that people will support to determine unequal reward for others. Honour and shame may become fashionalbe once more. In some socieites this may instead become enforced compliance. Human groups naturally form hierarchies. When traditional methods of determining who has more worth changes then so will our definition of who is more worthy. Some people want to be “top-dog” and will use every method to be so (or remain so) – not only by pulling themselves up, but also by pushing others down.

As information asymetry combines with confirmation bias, we are likely to see politics become more fractional. Groupings will emerge like sides on a battlefield. They may be wealthy industrialists with their capital and bankers, career politicians with their nationalistic tendencies, intellectually enlightened middle classes, disenfranchised and once-proud working classes and individuals who want to be made to feel special and better than their peers. These interests will come with different ideas about what to optimise for success and how to go about doing it.

Different factions with competing ideas, their votes, their followers, and their financial means will be pitted against each other. They will use new technologies, historic resources, traditional oratory, and brute force. They will use the structures and institutions of society – as well as whatever form of subterfuge is available – to further their conflicting objectives. Human history suggests that without acceptable compromise frustration will lead to anger, irrationality and even violence.

Conclusion

Commercial innovation here may be hard to achieve but being alert to the political and social dimensions will provide early warnings and adaptation may keep you on the right side of history.

For more information please see:

4th Industrial Revolution Implications parts 1-3

IR4 Part 1: Information and Communications LINK

IR Part 2: Work, Trade, Taxes and Government LINK

IR4 Part 3: Energy Transition LINK

Earlier thinking around the subject

Innovation and Productivity with the 4th Industrial Revolution LINK

Digital Disrtuption Landscape for Upstream Oil and Gas LINK

Get out of the way of digital Crhis LINK

Digital disruption landscape for upstream oil and gas

I was recently asked by a client for assistance in examining how their business strategy might be affected by Digitalisation. This company is a mid-tier upstream operator with a mix of assets mostly non-operated but does have some where it is the duty-holder.

So I’ve propose the following five point map to classify where the disruption could occur in the upstream business. This helps to define not how, or when,  but where disruption is possible. This framework helped us examine what threats and opportunities are likely to emerge in each area and I thought I’d share.

Please feel free to comment and I will keep this updated  for the network.

Demand for Oil and Gas

  1. Digitalisation in the wider economy may affect the demand for energy through different transport usage, renewable control, demand management and micro-grids.

Access to Resources

  1. Access to operate resources may change as national owners find different partners to help them monetize geological wealth
  2. Opportunities to become a non-op partner may change as operators get more certain about their outcomes and require less diversification in their portfolios
  3. Competition for resources increases as development and production services become purchasable/tradeable activities
  4. Transparency of operation and methods to extract changes what is required to retain a license to operate
  5. Better techniques for collecting and interpreting data leads to more resources being found and better development pre-planning (westwood puts the commercial success rate at between 30% and 50% https://www.fircroft.com/blogs/less-drilling-more-success-the-state-of-exploration-drilling-so-far-in-71921114313 )

Development and Operation of Resources

  1. Digital planning and modelling combined with better logistics and manufacturing/construction techniques reduces the capital requirements for fields meaning lower barriers to entry
  2. High frequency low-cost drilling reduces the sunk-cost nature of investment, reduces cyclical volatility of supply/demand imbalances and hence expected return on capital
  3. Better information leads to increased recovery factors and ultimate value of assets. (Currently this is estimated to be below 40% http://www.spe.org/industry/increasing-hydrocarbon-recovery-factors.php )
  4. Better information, co-ordination and reduced waste leads to lower operating costs per hour of activity (for some bench marks check here https://knoema.com/rqaebad/cost-of-producing-a-barrel-of-crude-oil-by-country )
  5. Better prediction of failure and real-time optimization of fields leads to higher efficiency and hence accelerated cash-flow (currently 73% in North Sea https://www.ogauthority.co.uk/news-publications/news/2017/uk-oil-and-gas-production-efficiency-rises-to-73/)

Sale and transport of product

  1. Better information about the crude quality and refinery / other consumer plant configuration leads to higher yield / lower cost processing
  2. Information about the location of supply and demand enables better optimized transportation and reduced costs
  3. Better prediction of both future production and future demand enables balancing of both. This leads to changes in the premium available from trading and who captures it

Human elements

  1. Automation leads to different models for distribution of wealth among the middle classes (no longer based on work)
  2. Automation leads to people choosing to add creativity and seek challenges in different environments and under different conditions
  3. Changes to the working motivation scheme means modernization is required for operating model for Oil and Gas industry to attract talent

 

 

Image credit: https://www.pmfias.com/natural-gas-distribution-world-india-petroleum-gas-value-chain-upstream-midstream-downstream-sector

 

 

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

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]

 

 

Digitally disrupted operations

I have already said that I believe the time is now for O&G operations to become digital. Radically different cost models are going to be needed and digital is one way they will be achieved.

“When assessing the implications, consider the fact that that new digital business models are the principal reason why just over half of the names of companies on the Fortune 500 have disappeared since the year 2000. And yet, we are only at the beginning of what the World Economic Forum calls the “Fourth Industrial Revolution,” characterized not only by mass adoption of digital technologies but by innovations in everything from energy to biosciences.” Pierre Nanterme – Accenture CEO [Link]

For me this revolution started with a computer programme called Mosaic, the first internet browser – which I discovered in 1993 while goofing around using Kermit, WAIS, Gopher, FTP and downloading cool stuff from GNU. I was being paid to generally muck-about and call it work. Since that moment I have witnessed a massive rise in computing power, information storage and interconnectivity that has left me gawping in awe. The chart below, from The New Machine Age, illustrates the trend.

Five Phases of Disruption

I model this disruption in 4 overlapping phases that are well established (each relying on the ones before it to progress) – and we’re about to see the fifth phase make itself felt.

Phase 1: Pure Information Industries

This was the first to be disrupted. It started with libraries, newspapers and advertising. As technology progressed this then disrupted industries requiring higher information capacity (bandwidth & storage) such as music and radio, and is now doing the same for television and cable companies. Bi-directional communication led to the X-Factor, the Huffington Post and any number of citizen journalists and bloggers.

Phase 2: Customer Engagement

As more people started to have access to and use the internet it was a small extension to make commercial transactions and shopping. As this ramped up customer experience of retail, customer-service departments and opened up access to a vast array of diverse products that could never be held in stock on the high-street. Now there are very few consumer engagements that do not have to integrate a digital channel into their offerings. Coffee and haircuts can’t be online – just about everything else can. Even there Starbucks is integrating a digital offering into their coffee order-to-pay process.

Phase 3: Co-ordination and logistics

It started with on-line parcel tracking, cross-docking and behind-the-scenes scheduling algorithms. Adding mobile GPS and mobile data allowed supply chain and logistics to start its transformation. Firstly on the containerisation and automatic freight and now down to warehouse location, stock control and soon perhaps delivery by dedicated drones [Link]. Phases 1, 2 & 3 have combined to give me my Occado delivery today at 12:30 (sharp).

Phase 4: Asset and resource sharing

This phase is still young and we’re seeing it play out in the consumer space first – a reversal I’ll elaborate on later. Companies like AirBNB, Uber, ZIPCar and others. In general this is the idea that Assets are not fully utilised by their owners all the time, and spare capacity can be made available through a brokering and booking service – and then scheduled and delivered.

Phase 5: Machine-optimised operations

Remote sensing, predictive algorithms, human-machine teaming – integrated with maintenance planning (plus all the attributes in phases 1-3) should lead to more reliable plant constantly optimised and operated by fewer people. This phase is being referred to as The Internet of Things.

“The Internet of Things (IoT) is changing manufacturing as we know it. Factories and plants that are connected to the Internet are more efficient, productive and smarter than their non-connected counterparts. In a marketplace where companies increasingly need to do whatever they can to survive, those that don’t take advantage of connectivity are lagging behind.”  Forbes Magazine [Link]

The reversing order of adoption

Sometime between 1992 and now a reversal in adoption sequence occurred. Prior to Mosaic the sequence of adoption was: Military, Big Business, Small Business, and Consumer. There was also a geographic sequence that meant technologies emerging in California took a few years (5+?) to make it to Europe and the same again to make it to Asia. The order has now reversed and the spread of ideas is both bi-directional and super-fast. For instance we’re going to see individuals install HIVE before most plant install remote operations. So I think we can already see the new technologies and ways-of working being successfully deployed for consumers – the question is how will the Oil and Gas industry adapt them for its use?

How could real-time sharing of Oil and Gas assets and equipment be made to work? How could we create an “Oil-Uber” for self-employed drilling engineers? How can we scale-up technology like HIVE, algorithms for maintenance diagnostics, combined with the GPS on a tag like that in my £100 Garmin watch attached to and despatch the most available uber-spare-part.

Of course, innovations will sneak up on us through lots, and lots, of small changes but the effect will dramatic – looking back we will see the change, but it will happen gradually with the companies that use more efficient technologies buying assets from those that don’t – or, more accurately, buying assets from their officially appointed receivers.