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

4IR Implications Part 2: Work, Trade, Taxes and Government

This is the second post in a little series considering the left-field consequences of the 4th Industrial revolution (4IR). There are several technology trends leading to breakthroughs in productivity across many industries, and I think these will have knock on implications. Guided by the insights from members of the Bestem Network, I am concerned to know if we are investigating along the right track more than demonstrating that we “are right”. As in the last post, I am only going to briefly touch the upside possibilities of 4IR because information on this is now widespread and easily found.

What a year 2020 was. It gave me both time to reflect on some angles of 4IR and showed samples of the types of situations and responses that might arise in the future. Rather than write a large piece covering every aspect, I am writing a small series, each post looking at aspects in isolation. This post deals with productivity, remote working, and the effect on public finances.

Increased productivity

One common definition of productivity is the amount of output for every unit of human activity put in. Traditionally this has been calculated as GDP added per hour worked. There are lots of reasons to argue that the measure is no longer appropriate and you can read some of my previous deliberations here [LINK]

If you subscribe to the belief that we’re consuming and exploiting too much of the planet’s resources, and combine this with the productivity arguments of 4IR then it seems that we will either end up drowning in a sea of products we don’t need while killing ourselves, or there will be a lot of idle labour capacity.

The positive argument resulting from this is that it will free our species from needless drudgery, will increase artisan production and lead to a life of increased leisure. Some people advocate the requirement for universal basic incomes, of which the UK Government furlough scheme could be an example. These arguments are not new as this letter to Personal Computer Weekly in 1978 demonstrates.

Self-Driving

Autonomous vehicles reduce the requirement for physical presence of humans in dangerous or expensive locations (think of remote inspections or inside nuclear sites), it also reduced the need for drivers (commercial and private) while increasing the utilisation potential of vehicles. This will lead to reductions in labour in direct driving roles but also indirect such as driver training, motor insurance, parking lots, and staffing of road-side café. [LINK ]

Economy moves on-line

During the pandemic activity has migrated on-line. Online shops require less people in the supply chain than high-street retail, and with the rise of robotic pickers and packers perhaps will need even less in the future. This article talks about this in the context of Ocado. [LINK]

There are many arguments concluding that much economic activity will move on-line. There is, however, an imbalance between the numbers of producers and consumers. Between sellers and buyers. Here the productivity arguments become even stronger. For example, consider a video game like “Among Us” (which is now played by over 60m people daily). It only took 185 people 3 years to write, and far fewer to keep it running. There is not much employment created by this and a concentration of money from the many to the few. [LINK]

There are 350million players who use fortnite, that game is published by Epic games. The entire company employs a mere 700 people. Epic games are backed by KKR private equity. [LINK] [LINK] [LINK]

In a more professional sphere, after a massive growth spurt, Zoom still only has 2,500 employees (which is double what it had last year). It is used by 300 million meeting participants each day. [LINK] [LINK]

Who remembers Linden labs? [LINK]

Education may change

In a more traditional setting, on-line education has been a lifeline for schools and universities. However, if this type of delivery becomes normal – consider a class recorded for Physics 101 by (say) Richard Feynman. It would never need to be re-recorded. Maybe Khan Academy has this right, maybe a career in teaching is not what it used to be, maybe education will not be enough to differentiate you once many more people have access and get smart? [LINK] [LINK]

What about the other issues?

While the fourth industrial revolution will see technologies such as self-driving, self-analysing, remote working, remote control, and robotic automation become more prominent. We may see a rise in purely digital products and services – such as computer gaming – where the entire value chain exists only within computers, and consumption and delivery are not dependent on co-location.

If labour requirements are permanently reduced (and not replaced with new roles – there are arguments that this time it may be that way) then we are faced with issues of wealth distribution that free markets won’t be able to solve. There are arguments that 4IR requires a more interventionist central control to organise behaviour, set societal objectives and to distribute resources. The pandemic response may have revealed how this sort of thing may operate. [LINK]

This is all very good and well. I can envisage the upside of productivity as well as the potential problems it will engender. The arguments are well rehearsed and not yet solved. But what about second order consequences?

Central taxation reductions

All governments have endured a hit to their finances during the COVID-19 pandemic. Borrowing from future to fund today’s spending only works if governments can capture the tax revenue associated with future growth.

We have recently proved that we in a world where many can work from anywhere, hold meetings without travelling and remotely operate large plants and machinery. This is not new but since COVID it has become normalised and now widespread. The physical property of the company may only be a TEAMS server in the Bahamas and workers can be located wherever they wish to be.

So how do you tax this activity? How and where can you collect payroll taxes? Where is the economic benefit created? Whose rules and laws apply? How can a government even know what is happening within its borders?

Automation in transport, manufacturing and logistics are also likely to increase pressure on labour tax revenue.

Will we see restrictions on commercial data, handling, and transmission across borders like we have seen for personal data with GDPR regulations? It’s not unheard of – in the oil industry some geological data was prevented from leaving countries for years, forcing exploration activity to establish a physical presence in country.  

Commercial property taxes and rents

Until recently landlords and local government were able to extract rents and rates from physical businesses that wanted to be located where the crowds came. Recently, local governments have even borrowed large sums to buy the properties on the high streets. They are speculating in the properties for which their previous role was to sweep the street and collect rubbish.

They do this to rent them out, trying to exploit the difference between their cheap borrowing and the return from commercial rents. So that they make enough money to pay for the street sweeping and bin-emptying that they used to charge for explicitly. They have an inbuilt advantage over private landlords because buildings left empty force the landlord to pay rates, but these just recirculate inside the finance dept of a local authority. Perhaps this will end in tears for the public (and risk-free profit for financiers) when they need to refinance and interest rates are higher and vacancy has increased? Surely there must be a better way to fund public services? [LINK]

Working from home seems likely to reduce the requirement for prime office space not only leading to worsening public tax receipts but also reductions in income for pension funds and insurance companies who own the buildings – just at a time when returns on other forms of assets are also falling, and insurance playouts are increasing. [LINK]

The pandemic saw an accelerated rise in on-line purchasing and home delivery (which is often less expensive due to lower labour costs and lower property taxes). This means retailers are going bust, rents are not being paid and rates are on hold. This causes another of problem for public revenue which means spending must be reduced, borrowing increased or new methods of taxation found. [LINK]

The end of the freelancer?

In Europe at least, workers within traditional employment structures (and public sector workers most of all) have been better protected by the government. Self-employed, freelancers and small company directors have not been supported well. [LINK]

In recent years we have witnessed the fragmentation of work and a slow reduction in the number employed in professional classes. The world of private commerce seemed to be dividing into successful owners (and financiers) and jobbing workers, with a rise in zero-hour contracts and “gig” work. [LINK]

One of the attractions of freelance work for some was the flexibility it afforded in terms of working from home, this benefit seems likely to become more available to traditional office employees in the future. Policy is likely to shift towards increased taxation of small owner-managed companies and freelancers. The benefits from freelancing are being eroded. [LINK]

Will there be a rebalancing in favour of a stable employment contract and the re-rise of big employers, or will the welfare state make new arrangements with its citizens to enable flexible, part time working? What will this mean for personal finance and the unintended consequences of “prudential lending” that have forced many to rent properties they could easily have afforded to buy? [LINK]

The role of the state and its relation to private commerce

Our elected government has been willing to incur large debts and restrict personal freedoms to protect lives during this pandemic. This brings into question, perhaps, the lack of spending up until this point for other preventable causes of death such as seasonal flu and driving motor cars.  Though one has to be careful not to downplay the seriousness of the current pandemic, the argument may be extended that intervention should increase in the future. [LINK]

Governments have stepped up to support rail operators, aviation, provide furlough schemes and give grants to the performing arts. The narrative of the free market and the accepted arguments for roll-back from state activity in commerce we’ve seen for the previous half century will likely be revisited. [LNIK]

I have noted many more articles about the collective response of public services, the requirement for us all to contribute (and not try to dodge taxes) if we want potholes filled in and have a medical service that works. We have even seen large corporations such as Tesco return COVID rates relief payments without obligation because it was “the right thing to do”. [LINK]

Perhaps we are moving to a phase where more collective responsibility will be shown, and individualism will be less valued. Perhaps we are moving towards basic universal income. Perhaps we are changing our relationship with tax and with state spending? Perhaps companies will revise their arrangements with workers? [LINK]

The UK government continues to make overtures about investing public money into science and technology research through an industrial strategy. [LINK]

We’ve seen government intervention in the hospitality sector on the grounds of public health. Perhaps it will not be “the right thing to do” to spend a universal income on gambling and drinking? Will it be “the right thing to do” to compromise your health at the expense of the nation’s taxpayers? Where will the new boundaries for state intervention in private life be drawn? How will the people who control business take steps to voluntarily increase their tax bill? What will all this mean for basis of competition and fiduciary duty to shareholders?

Conclusions

If we are to see wide-scale automation, movement of economic activity on-line and a substantial rise in remote working for those that remain employed, there will implications for tax, wealth distribution and state intervention which are likely to follow. Organisations may wish to consider how to set up systems of work that enable innovation, so they are not be left behind by these advances.

Scenario planning might consider wider societal responsibilities as well anticipating changes in rules, regulation, worker expectations, less flexible labour markets and competition from state-backed entities (possibly publicly owned). They may also anticipate changes in expectation from the public as regarding corporate citizenship and modifications to taxation systems.

4IR Implications Part 1: information and communication

Introduction

I am more concerned to know if I am on the right road than “being right” – I believe that we are at the starting phase of the fourth industrial revolution (4IR). There are several technology trends leading to breakthroughs in productivity across many industries. I am only going to touch on what these effects are – as information on this is now widespread, easily found and I don’t want to repeat myself. But if these are true, then perhaps there are far-reaching consequences and profound questions that should be considered. It is in these areas where I feel the greatest risks and greatest potential for innovation will be found.

2020 gave me both time to reflect on this and an insight the types of situations that might arise. Rather than write a large piece covering every aspect, I’ll write this as a series, each post looking at aspects in isolation. This post deals with information and communication.

How this will improve efficiency

There are vast amounts of information created, it’s easily stored and transported, and – with increased compute power and new algorithms – it can be quickly analysed. This is leading to opportunities for increased productivity. This is only achieved if we know what information to collect, can understand what it means and – most importantly – change how we act based on it.

I am finding examples in the fields of computer vision, satellite imagery and remote sensing. Technologies such as LIDAR, LoRAN, Hadoop, ESP32 are commonplace in industrial settings meaning that the cost of measurement, distribution and storage of information has fallen dramatically.

We are connected by mobile devices, we hold multi-way video calls with colleagues, customers, and suppliers. We can track packages from factory gate to end user, we can store every aspect of manufacture and store it directly on an object.

There is little excuse for not knowing exactly what is going on, understanding the consequences of that, and acting to make things better.

The unintended consequences

As an industrialist it is tempting to see all these advances in information and communication solely in terms of their positive impact on the workplace. It is tempting, and wrong, to think the world around the workplace and those working there will remain static. They will not. The world will change because the general population have access to these tools and they will impact your workforce in ways that you won’t control.

Information influences behaviour

Information has become more influential as it has become quickly available at scale. Modes of transmission have rapidly evolved; society is moving further away from long formal written communication towards short media-rich content bursts. On the one hand this is leading to rich emotion-laden communication between previously unconnected and perhaps illiterate people. On the other hand, it is reducing consideration of more complex issues and drowns out nuanced voices expressed through traditional means. It is also becoming harder to remember and prove what information led to which decisions and why.

https://www.researchgate.net/publication/313860181_Internet_Memes_-_A_New_Literacy

http://bestemnetwork.com/wp-content/uploads/2021/01/f8edc-miltner-internetmemes.pdf

Can you trust what you think you know?

There are an increasing number of artificially created video characters (referred to as deep fakes) which can either be entirely fictional people or manipulated images of prominent people made to look like they are endorsing a false message. Backgrounds and images can be created that are almost indistinguishable by humans. This means that we could soon see (or may already have seen) reports from wars and atrocities that never happened. Perhaps, even if you see it with your own eyes, you will no longer be able to believe it. Persuading emotionally charged people (who may not understand how a fake video image can be created) to change their minds might be very hard.

Have you heard of Q? He’s a fictional character and the basis of QAnon, what has become a far-right movement in the USA: https://www.nbcnews.com/tech/tech-news/how-three-conspiracy-theorists-took-q-sparked-qanon-n900531

MIT has a great primer on deep fakes here: https://www.technologyreview.com/2020/12/24/1015380/best-ai-deepfakes-of-2020/

This site creates a unique image of someone that does not exist each time you load the page. These people are totally fictious. https://thispersondoesnotexist.com/

This has been predicted for a while – Have a read of Victor Pelevin’s Babylon published in 1999 – (or watch the film) [….]Tatarsky is invited to join an all-powerful PR firm run by a cynically ruthless advertising genius, Leonid Azadovsky, who invites Tatarsky to participate in a secret process of rigged elections and false political advertising.[…]

Are you seeing the other side?

We are exposed to so much available information that a person can easily succumb to their own biases and seek out only items that reinforce their snap judgements. This has led to fractionating, polarised camps who no longer share a “Mutual Reality”. They have great difficulty in engaging in reasoned debate as each side has fundamentally different frames of reference. These frames induce them to interpret observations in very divergent and (to the other side) incomprehensible ways.

http://changingminds.org/explanations/models/frame_of_reference.htm

Will information cause wars?

It is possible that our future wars will be between ideologies and triggered by insults, or that – in the face of popular internal revolt – governments will launch “defensive” hostilities to stop the influence of their populations by alien states. Propaganda may cease to be a tool to assist armed conflict and instead become the sole purpose of hostilities. Perhaps the lines of conflict will not be those of countries but between ideologies, vested interests, and traditional institutions. Maybe we should watch the Hong Kong situation more closely?

https://owlcation.com/social-sciences/The-Main-Reasons-For-War

Is there a case for censorship?

In 1984 I received a UK transmitting license for a radio set. At that time (and in the decades before) the license permitted someone to use a station for experimental purposes and research into radio propagation. Of course, I also (and mostly) used mine to chat to my other geeky teenage friends. The point of bringing this up is because the government realised I was to be granted the power to communicate across the world. I, therefore, had the potential to find information and broadcast local conditions to others. Not only was an examination required to obtain a license, once acquired it was very clear about what topics I was allowed and not allowed to discuss. I had to identify myself using a centrally registered callsign. Violation of the rules would mean revocation of the privileges. Now anybody, with no training, no examination can say pretty much anything to anybody (and everybody) without restriction. They can say it anonymously. This is new in human history and the results, so far, are mixed.

https://www.theguardian.com/commentisfree/2017/aug/21/the-guardian-view-on-censoring-the-internet-necessary-but-not-easy

What is the role of cyber security?

Cyber security is currently focused on preventing people from seeing information you want kept secret or preventing people denying you access to your own files. In the future security may be required to prevent others from injecting false information into systems and influencing your or your staff to behave in the wrong way. That could be by planting rumours, or direct manipulation of operating data, financial reporting, or automated firing of workers.

https://en.wikipedia.org/wiki/PLA_Unit_61398

https://www.sciencedirect.com/topics/computer-science/data-injection-attack

https://www.wired.com/story/russian-hacking-teams-infrastructure/

Conculsion

Business has been slowly taking advantage of information and sensor data and transmitting it around the world. Remote working has been trialled and tentatively used when there were no alternatives. Now this technology is ubiquotous and in use by the “average Joe”. This is leading to new ways to communicate, new ways to manipulate the unwary and new expecations from workers.

Innovation will be the key activity for all companies that want to operate in this new environment. Setting up systems of work that promote the new and commercialising it quickly will be imperative.

I believe that it will be a responsibility for leaders – including business , political, spirtual and community – to use the tools available to them to continue to promote ordered society. Some of our most important human developments around organisation of effort, support for each other, goals for shared endeavours and, jointly agreeing what we fundamentally value, will depend on it.

6 Months into a 3 week crisis

I have lots of new ideas to share, but not the time to commit them to words.

I’ve not found time to update this blog for a while. To be honest I don’t think the uncertainty that comes with this crisis makes it wise to take too rigid a point of view. And, like many others I speak to, my days seem to be slipping past. I seem to be doing a lot of work, but I am finding less time to invest in new areas for the future and many discretionary tasks I no longer have the concentration to focus on.

Some of my friends and colleagues have noticed similar fatigue levels affecting performance in their businesses too. As one put it, we are now six months into a three week crisis.

All the emergency measures we put in place are all still there, the system is starting to creak and it no longer seems temporary. And it doesn’t really work for the long-run. We have learned new ways to use technology and have become expert in the tools for remote working. What we must now do is rethink our processes and routines to take advantage of these while making space to grow and learn.

Ken & Mark from AGM transitions, and I have been working on turning our small guides into a book. It’s now available from Amazon here: [LINK] – I hope that the practical advice and structure are something that will help you through this stage of lock down.

Here is the link to the original post: [LINK]

Responding to the Crisis: Leader’s Handbooks

What should we be doing right now?

It’s an economic emergency. Every company is having to rethink what they do and how they operate. Together with AGM Transitions we’ve asked our networks to share their recent experiences. We’ve written three guides:

COVID – Responding to the crisis – Leaders Handbook

COVID – The Transformation Handbook

COVID – Remote Working Handbook

What happened?

Since I published my post on March 9th the world turned upside down. Covid-19 is a “big one”, certainly when considering the economic impact of the measures taken to stop its spread.

Couple that with the shocks to both supply and demand in the oil world and members of the Bestem Network have been left slightly shell shocked.

What will happen next?

We are starting to understand where we are – but we’re battling to understand where we will need to go.

As Gordon Ballard said in the FT on Saturday: “In the past, activity decreased then picked up again — each time, we saw it come back,” he said. “Now it’s not entirely clear if things just come back as normal. Everything has changed.” [Link]

For some context however I should point out that even with 30% drop in oil demand we are now only at the level that was normal in 1996 [Link]

What have I been up to?

Alongside my hour’s cycling, home cooking, housework and playing with electronics:

  • Looking after my clients
  • Contributing my skills to my community to innovate systems to support neighbours in need; and
  • Working out what we have to do to come out of this ready for the next phase.

Stay Safe, together we will get through this.

 

While we were sleeping – Oil 1.4 and Solar

It’s been very busy since the Network Dinner in September. I will post an update on the discussion later this month.

In the mean time I’ve been busy working on innovation – more of that later – but I recently came across two interesting items that I think might be worth sharing.

Firstly the FT ran a special issue talking about Oil and Gas 4.0 [Link]. It’s good to see that this term is being widely applied – and a big change from when I started to talk about it a few years ago.

I wrote an article in March 2016 when I claimed that Oil and Gas were really at 2.5 while industry was going 4.0 [Link] I was concerned about the lack of urgency and technology progress. I also called out the contribution of Collette Cohen as being one of the few that seemed to get technology. She is now director of the Oil and Gas Technology Centre.

The OGTC were referred to in this article [Link]

In October, the non-profit Oil & Gas Technology Centre (OGTC) in Aberdeen in Scotland, announced the next phase in its autonomous robots project with Total of France, which is developing what it calls the world’s first offshore work-class robot. The first phase of the work saw Austrian firm Taurob create a robot to conduct visual inspections at Total’s Shetland gas plant and the Alwyn gas platform in the North Sea. A second-generation version will have a stronger chassis and a heavy-duty arm that will lift objects and turn valves. It will be tested by Total and Equinor of Norway, the research initiative’s new partner.

“A lot of our work on hazardous environments focuses on whether we can avoid sending people into those areas in the first place,” says Stephen Ashley, head of OGTC’s digital transformation solution centre.

Another article coined the phrase Oil and Gas 1.4 which is a clever take on the combination of an old-age industrial organisation embracing new digital technologies within its core business. I think I like this term better than my 2.5 one.

This article [link] makes the point that the new technology is prevalent in some areas of the business, but that the new frontier for production might be the application of technology to find economic ways of enabling enhanced oil recovery. 

Unmanned rigs are now commonplace, complex operations are monitored from a single control room, leaks and emissions of greenhouse gases can be identified by drones and satellites, removing much of the need for direct human inspection. Numerous technologies are being applied in ways that can reduce cost and improve productivity.

The key question, however, is whether the digital revolution can answer the sector’s biggest challenge: how to secure future production. Oil demand is not falling. There may be 7m electric vehicles on the world’s roads but there are also 1.2bn vehicles with internal combustion engines.

[…]

One answer must be for companies to make the most of assets they already hold. Across the world the typical recovery rate from a conventional oil or gasfield is only 35 per cent.Even after decades of production giant fields such as Prudhoe Bay in Alaska or Ghawar in Saudi Arabia still contain billions of barrels of oil. Recovery rates have slowly risen and provinces such as the North Sea, originally expected to close at the end of the last century, continue to produce oil and gas. In Norway recovery rates are typically 50 per cent — well above the world average but still leaving half the resource base undeveloped.

The point at which recovery becomes uneconomic, ie when the cost of enhanced recovery is greater than the value of the oil, is a serious constraint.

What I’ve found really interesting this year is how irrelevant the oil and gas industry seems to have become down here in London. What I mean by that is that Oil and Gas seemed to be at the crux of things in a way that, say, copper mining and concrete production wasn’t. It used to be a cool place to play with technology, travel the world and to make a bunch of money. I think those days may be over (though some predict a spike in prices around 2025). Now no-one here cares about Oil and Gas at all.

Where I am seeing a lot of action and excitement is around Solar and Wind. I thought for a while it was just me becoming aware, but now I’m onvinced that it was a sea change and it really is picking up. And the cost-curve of Solar is particularly striking.

I urge you to have a look at Tim Harford’s article on Solar [link]. As always he has an ability to grasp the implications of what he sees in ways that other’s don’t. He looks a PV cells – how in 1980 Solar was about $100 per watt ($10.000 to light a light bulb). It is now already below $0.25 / watt and falling. Utility scale production is now looking to provide generation at below $0.015 per KW/h. [link]

The thing about Solar Panels is that they are a pure manufacturing play. Once created they just sit there and make energy. No moving parts, no plat to really operated as such. We have been, and continue to be, very good at manufacturing standard products in standard factories.

Sometimes the learning curve is shallow and sometimes it is steep, but it always seems to be there.

In the case of PV cells, it’s quite steep: for every doubling of output, cost falls by over 20%.

And this matters because output is increasing so fast: between 2010 and 2016 the world produced 100 times more solar cells than it had before 2010.

Batteries – an important parallel technology for solar PV – are also marching along a steep learning curve.

The learning curve creates a feedback loop that makes it harder to predict technological change. Popular products become cheap and cheaper products become popular.

And any new product needs somehow to get through the expensive early stages. Solar PV cells needed to be heavily subsidised at first – as they were in Germany for environmental reasons.

More recently China seems to have been willing to manufacture large quantities in order to master the technology.

Watch this space, it’s just getting cheaper, better and faster. This is where the action is – I just don’t know how to play the opportunity yet.

 

Machine Learning – more learning….

As an addendum to last week’s post about machine learning – here is an article by the BBC : https://www.bbc.co.uk/news/technology-48825761. This describes a story about an amazon employee who built a cat-flap. Fed up with receiving “presents”, he made this clever device to recognise whether his cat has come home with prey in its jaws. If it has, it refuses to open and the cat must stay outside.

I thought it neatly encapsulated some problems of machine learning I am finding, and also pointed to some possible features where this technology could be applied to generate more value.

The training problem and need for clean data

It took 23,000 photos to train the algorithm. Each had to be hand sorted to determine whether there was a cat, a cat with prey etc. etc.

This is like the oil and gas industry in that it needs a lot of clean training data that may not be available without a lot of manual input.

The Bayesian stats can work against you

The frequency of event-occurrence in this case is once every 10 days. The maker ran a trial for 5 weeks (so should have seen 3-4 instances in that trial, though in this case it’s stated as seven). There was one false positive and one false negative – giving an error rate which may be around 20% (though there are not enough samples to have a lot of confidence). If the algorithm continues to learn and say that the cat uses the flap 5 times a day on average. This means, in a year it will have 1,825 additional samples from which 35 will be positives of which 7 will be false and 1790 negatives of which 358 will be false-positives. Manual correction will be required 365 times (i.e. per day on average) and the learning rate will take about 12 years to duplicate the original training set. I don’t know, but I suspect there are diminishing returns on adding new data so how much smarter it will be in 12 years I’ve no idea.

Disclaimer – a good statistician will know my maths above is not quite right, but the principle is.

Do you trust the alarm? Do you take notice?

So in this example, quite like oil and gas operations, the issue was getting hold of clean training data. The event being detected was comparatively rare meaning that a lot of false positives are likely. In the example above an “alarm” would have sounded 365 times and 28 occasions it would have been real. With the sparsity of events the this means that the algorithm will not learn very fast and I think the alarms will be ignored.

So where can the applications be better?

Distributed learning

Parallel learning helps build better predictive models. if we had the same cat-flap for every cat, and every owner corrected the false signals and right algorithm could learn quickly and disseminate the results to all, this would speed the learning process. Self-driving cars are a good example of where this is possible, and google-search is great example of the power of parallel experience.

Products and services impossible for a human

Situations where there is so much data that manual processing is impossible. Here I don’t mean that you can collect so much data on a manual operation that is ongoing that you cannot analyse all the extra information. What I do mean is that there is intrinsically so much information it would be impossible to analyse by hand and never has been. So an ML approach is the only one possible. For instance looking at real-time changes patterns in data networks.

Simple situations where it’s expensive and boring for a human

Automated first-line help systems, call screening, password resetting etc. These are all tasks where humans can do them, but they are simple tasks which are too boring for smart people to do, where automated help can often provide a better experience. And where “sorry I didn’t get that, did you say yes?” is only mildly irritating not the cause of major corporate loss.

Conclusion

There are places that machine learning will be revolutionary, but I suspect that much of ML will be either embedded to make normal tasks a bit easier – such as auto-spell checking, voice recognition etc. Or they will tackle classes of problem such as IT security, or on-line shopping behaviour where there is inherently a lot of fast-moving data and manual monitoring is simply not feasible nor fast enough to work.

To innovation and beyond – 2019+

My first post of the year – a look ahead for 2019 – was a bit tongue-in-cheek. Now The World Economic Forum (WEF) is meeting in Davos, Switzerland, I thought I would provide a more insightful analysis.

The WEF will be considering the implications of the 4th Industrial Revolution as the headline theme for their annual conference. If you’re new to all this here is a I4.0 primer from CNBC [Link]. 2019 is going to be a year where industrial innovation takes centre stage. 

The thinking from WEF is always good, detailed thorough. I think that some of the crucial themes for unlocking innovative value will be focussed around opportunities and risks. Here are some of my current favourites.

The Opportunities

  1. Using information and reconfigurable platforms to provide new solutions to stakeholder experience. This will establish new ways to create, deliver and consume the core outputs from industrial processes.
  2. Removing the idea of separation between “IT and the Business”. The two are now conjoined. Being good at tech will be a prerequisite of being good in business. Technology will be embedded in every way that work is done, products are created, consumed and delivered.
  3. Empowering the front-line will be crucial. The winners will be faster organisations where workers make autonomous decisions and are rewarded for outcomes. As an analogy think of Deliveroo drivers. For many reasons, more refined models of work-coordination are required but the core autonomous nature of the work is being previewed here. Decentralised decision-making and autonomous action guided by technology removes many of the tasks performed by middle management. I hope we will start to see teachers, dentists, doctors and nurses no longer filling in spreadsheets and working as relecutant automatons directed by ill-informed command-and-control resource-allocation systems.
  4. With power comes responsibility. Without middle management, new forms of controls (and motivation) will be needed to spot problems and reward behaviour. Surprisingly for some, I don’t believe it is the front-line worker, but middle management, that is most under threat from AI, visual computing and big-data. I hope the CFO won’t push progress only on AIQ but that marketing and talent managers will push the AEQ agenda. It’s important we understand not only economics but also pride, satisfaction and feelings of accomplishment.
  5. Innovation may not be in new forms of technology. The tech available to us now is far ahead of our application of it. Deployment options are already available but not used. Innovation will come from the application of existing technology to new areas of business. Those stuck with old infrastructure will not be able to reconfigure fast enough to keep up. Value will arise from designing new ways of working. Capturing the value will rest on finding ways to get the rest of us to work that way too.

And now the risks

  1. Innovation will come from networks. Big companies will look to small companies for ideas, small companies will be formed from collaborative networks of individuals. Ideas will be mashed-up to cross-fertilise creativity. Guards must be in place to avoid exploitative situations – if they arise unchecked it will mean that the small-guys can’t and won’t play for long. Without them, brilliant ideas will never be used. Rights management is crucial for the distribution of the value created. In the way that song-writing credits generate performance fees for artists. Licenses for ways-of-working are needed to stimulate innovation, and society needs to enable easy access to legal enforcement to uphold claims against copying without permission.
  2. Massive generalisation follows: Young people are frustrated by old-people’s inability to embrace new ways of working. Technology savvy folks are orders of magnitude more productive than their peers. They are quicker to make decisions and to multi-task. This leads to not only high-productivity but also to high-error rates. Iterative short-cycle experimentation and learning-by-doing is the hall-mark of agile strategy. This is not an approach that has been adapted to high-risk industrial work-settings. This leads to a clash of culture and an inability to attract and retain talent.
  3. Innovative individuals will continue to pursue independent careers in increasing numbers. Old industries will die, vested interests will be disenfranchised. The world of work, taxation, social contracts, pensions and access to finance will have to evolve to cope with this. To create a consensus and establish a sense of fairness new-politicians will need not only wisdom but also to deploy the old-tools of oratory and persuasion. There will be big disagreements across society and between nations. It will be necessary to create hope for those who fear being disenfranchised. They will not go quietly into that good night.
  4. Politics of property will come to the fore – the control of assets will be important. Whether that is physical real-estate where low-paid important workers are unable to afford to live where the people who need them reside; property from an accumulation of historical data that provides an unassailable lead and monopoly positions; or the “IDEA” that one person has spent 10 years creating that is exploited by a large corporation without reward. Society will need to find ways to address the control and distribution of property in a world where labour and working-time may not function as a distribution & motivation method.

I will spend time exploring these themes during the year – I have a number of initiatives already kicking off for the year and I hope that you’ll be able to help.

Five Digital Vectors

Frameworks for Digitalisation – Part 1

I’ve been working on frameworks that help me describe concepts around Digitalisation in upstream oil and gas. I plan to publish these in several formats but so far I’ve been too busy to do this to my satisfaction – so I’m going to put them out here for comment and then work them up as packaged tools.

This first framework – five digital vectors – is designed to set the context for the strategic intent of a digitalisation initiative. This is important because senior management had better know why they are embarking on programme of change, what they expect to get from it and where threats to it will come from.

I was recently talking to the CEO of a multinational engineering consultancy based in Norway. To slightly protect his identity, I’ll call him Egil.

Egil:  “Gareth, you know [insert Big 4 consultancy here] was just in my office telling me that digitalisation was going to radically alter my business. They said just look what NetFlix did for the video store. It must be important or they wouldn’t be here. But I’m busy and, frankly, I don’t get it”.

Communicating strategic intent is important. I am as guilty as anybody about trotting out tired lines about how digitalisation will disrupt industries and then helpfully pointing out that Uber has no cars, AirBNB no property and Amazon no shops. This may be intriguing but it’s no longer precisely true (as all three are busy making strategic bets in traditional assets), and it’s of very little help if you’re in Oil and Gas wondering how this applies to your business.

Using this Five Digital Vectors framework provides a way to classify the objectives of an initiative, how innovation in the area may cause competitive shifts and explain where to look in order to measure success. There are Five main vectors for digitalisation. They are:

  1. Pure Digital
  2. Digitally Enhanced Products and Services
  3. Digitally Efficient Operations
  4. Digitally Effective Supply Chain
  5. Digital License to Operate

I’ll explain a little about each of these, and then hopefully you’ll get the idea. If you take each in turn you can look for potential disrupters and initiatives and decouple them. Some of these will be more likely to impact your business than others. At least now you can decide which few to concentrate on first.

Vector 1: Pure Digital

Pure Digital strategies work when a product can be codified as information. Think Music, E-books, Films. Once the physical product is removed massive scale economies accrue to storage and distribution. What is called “long-tail” economics kicks in around inventory and specialisation, customisation and choice. In Oil and Gas, we may see some spare parts digitised, emailed and then 3D printed on-site. This will reduce carrying costs and delays. We may also see pure information products trade more freely (such as production forecasting, planning, sub-surface models, training data sets and educated machine-learning algorithms).

Vector 2: Digitally Enhanced Products and Services

Digitally enhanced strategies arise when the fundamental “product” becomes augmented with information. For instance, Uber generates a fair portion of its demand not only on price, but also because it provides information about where the cars are, when they will arrive, the route they take and the price you will pay. They then ease the transaction by collecting payment and supplying receipts. However, all the digitalisation in the world will be useless without the underlying physical product (in this case, a car to take you home). In upstream oil and gas we may see that a supplier of products such as spare parts, services or even crude oil become a preferred option when they supply accompanying information before their wares arrive and when they keep you informed while they are in service.

Vector 3: Digitally Efficient Operations

In oil and gas this is the area where I am witnessing most digitalisation activity.

Using information within your own business to reduce waste and increase accuracy is hardly a new idea, but digitalisation changes the game. As more information becomes available – because of better connections, more sensors and accumulated history – so it becomes possible to change the way you do things. Prioritisation, scheduling, just-in-time: these concepts work better when you can access more information and use it sensibly. Today’s engineers entering the workplace can probably not remember a world that didn’t have an iPhone and Google (Google is almost 20 years old). So, they are used to being able to think of a question and get an answer quickly. If you can harness this creative real-time problem-solving ability (by making information available) you can improve your operations.

Vector 4: Digitally Effective Supply Chain

Both vertically and horizontally there is potential to add value through more efficient exchange. The digitally efficient operation strategy will reduce the waste and hence cost within a single company (see Porter on what it will do for price). Supply chain strategies focus on removing friction between companies so inter-company waste will also reduce. This is, in many ways, a move from Digitally Efficient Operations to Digitally Efficient Industry. It is about expanding the focus from the individual company to the collection of companies.

For this to work requires standards, data compatibility and platforms where buyers and sellers can transact. Some suppliers (think about a stationery company) will supply various industries – say automotive and oil and gas. So eventually some standards will need to be cross industry, whereas others (say for drilling services) won’t be.  Though the benefits can be large, there are two main problems: co-ordination of participants; and allocation of cost and benefit.

Vector 5: Digital License to Operate

This is an interesting insight that came to me when I was discussing the apocryphal case of a town inviting bids from contractors to build a pipeline through it. One bidder offered to expose in real time the contents of the pipe, the corrosion status, inspection procedures and compliance, the leaks and seeps and other such. The other company claimed it was confidential. Guess who got the permission to build.

Whether the information was confidential or whether the quality of it and how to access it was suspect, I don’t know. But we see similar exposure of operational data for services such as trains and busses through simple APIs. This data is then “mashed up” by active citizens for public good to help people plan journeys or avoid breakdowns.

In the future, perhaps it will be a requirement of regulators that operational, safety and environmental data is made available to the public in real-time, if not – then you won’t be allowed to operate your field. Once that data’s out there you can expect to be held to account for your actions. Welcome to CSR in Industry 4.0.

Summary

The five vectors described here help to provide a primary direction for an initiative. For maximum impact, like all good vector mathematics, the magnitude of value delivered will increase as the direction of the vectors align. This tool helps to focus the mind on the primary vector and provides insights to the effect on the others to enable informed choices to be made.

As always, email me direct or leave comments here and I’ll do my best to respond.

Image credit http://www.kimonmatara.com/vector_ops/