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.

Structured work or just lucky?

I’ve been working with my clients while we’ve been under covid lockdown, and one theme has emerged more than anything else. That is the requirement for organising the activity of groups. My clients have been seeking ways to enable individual unsupervised action towards a joint outcome.

My clients want: independent action; visibility of progress; and accurate outcome. They have lost the ability the office environment gave for short-cycle intervention and guidance. They need structured ways to work remotely that replace it.

In industries that employ large numbers of people all doing sections of a task over a period of time – think of a building site, telephone maintenance crews or even an army – there are defined, co-ordinated systems of work. The modern office with it’s semi-senior knowledge workers has, in contrast, succeeded through flexibility, creatiing adhoc creative solutions and short-cycle leadership intervention.

My clients, faced with the pandemic and new ways to work and communicate, have found a new need for structured ways to co-ordinate creative work. Through my consulting company, Klynetic Innovation, I’ve been helping companies re-configure products and services and quickly commercialise them, a task that requires precisely this combination of structure, creativity, direction and focus.

One of the approaches I’ve taken is to emphasise personal responsibility and progress-without-permission at lower levels in an organisation. Then to moderate this with the checks-and-balances of good governance provided by systems and oversight provided by graphics and shared language. I’ve coached people to recognise the differences between the competence displayed by an individual and the ability of management to co-ordinate work and form organisational capabilities.

It struck me that in the last thirty years we’ve been honing our ability to encourage leadership and peronal development while, perhaps, not paying enough attention to management. I use the diagram below as as a tool to discuss this topic with senior teams and help identify what’s missing.

I’d like to know your thoughts, please reach out and email me (or comment here).

It’s all about productivity

If you have followed this blog for a while you will know that, like a broken record, I have been banging on about digitalisation, the 4th Industrial Revolution and the productivity conundrum. I have often referred to Tim Harford’s article about electrification and how long it can take to make a transition.

Recently, I’ve started to add the “Energy Transition” into my thinking on the topic. The outcome remains the same but I keep finding more and more reasons why it will inevitably happen.

One of my go-to reads is Ian Stewart, Deloitte’s chief economist. If you’ve not signed up for his Monday briefing then you really should – it’s excellent. Today I have lifted most of his post (available here: https://blogs.deloitte.co.uk/mondaybriefing/2021/06/the-looming-capex-boom-.html) not only because I’m being lazy but also because it talks to many of the points I’ve been trying to communicate to my clients over the last 7 years (since I started Bestem).

Throughout history economies have been shaped by shocks, from recessions to technological shifts and energy transitions. The Great Depression helped change thinking about the role of government, paving the way for a permanent expansion in the state. The switch from steam power to electricity triggered a vast reorganisation of manufacturing.

The pandemic and the drive to net zero are similarly epoch-making events. The pandemic has driven technology adoption and changes in business practices. The energy transition involves an overall of energy production and distribution.

The structure of the economy will change. The sectoral balance of the economy, the skills needed, the uses of capital, the allocation of capital, will shift, creating winners and losers. It will also bring opportunities to rethink organisations, invest and raise productivity in ways that had not previously been considered viable or necessary.

The unlocking of the economy has unleashed a surge of pent-up demand into an economy operating with reduced capacity. That is creating inflation and bottlenecks, and incentivising investment. Meanwhile large corporates are flush with cash, capital is cheap and institutional investors want businesses to step up investment.

The global semiconductor shortage has spurred a flurry of investment announcements in new factories. Automakers are building new battery plants to meet demand for electric vehicles. Rising freight rates have prompted a surge in new orders for container vessels. And the move to ‘hybrid’ working and the growth of online shopping require a reconfiguration of office space and an ever- rising volume of warehouse capacity.

Labour costs play a role in investment decisions too. As countries emerge from lockdowns labour shortages have started to appear in sectors including manufacturing and construction. In the UK increases in the minimum wage continue to outstrip inflation, raising costs for firms and sectors reliant on lower-income work. An exodus of some 650,000 foreign-born workers from the UK last year, equivalent to 2.0% of the workforce, and a reduced flow of less skilled labour from the EU, create new pressures. More expensive and scarcer labour would sharpen incentives to invest in productivity-enhancing equipment and skills. Machines, for instance, could readily substitute for labour in washing cars and coffee preparation (I was in a motorway service station last weekend where the queue for Starbucks led me to get the same product from a self-service machine in the next-door Waitrose. I couldn’t tell the difference).

In the UK government policy has set out to boost investment with the capital-allowance ‘super-deduction’ targeted at plant and machinery. The Bank of England estimates that this will have its greatest effect in raising investment in some of the most capital-intensive sectors including manufacturing and transport.

A surge in private sector capital spending is likely to coincide with rising levels of public infrastructure investment, particularly related to ‘green’ projects. So, with private and public investment likely to grow, this recovery is looking very different from the one that followed the global financial crisis. Then UK business investment took six years to climb back to its 2008 peak. Today the Bank of England sees investment snapping back quickly, ending next year almost 10% above pre-pandemic levels. A similar story is likely to play out globally. Morgan Stanley believes that global investment will stand 20% above pre-pandemic levels at the end of 2022, a remarkable recovery from last year’s downturn.

This sort of surge in capex could help shift the dial on productivity, especially if, as seems likely, it is accompanied by organisational changes and the application of technology. (While business investment fell in the US and the UK last year, spending on IT and computers rose as firms investing in remote working and new ways of doing business.)

Much of the problem of poor productivity in the UK is concentrated in the long tail of medium- and smaller-sized businesses. The pandemic may, paradoxically, have had some positive effects here, as businesses of all sizes adapted and used new digital practices to weather the downturn.

One encouraging sign comes from the retail and administrative services sectors. Both sectors have registered strong productivity growth over the past decade, defying the characterisation of these as labour-intensive, low-productivity parts of the economy. Online shopping, self-service and use of IT in administrative tasks seem to have played a big role. It may be that other labour-intensive sectors, such as healthcare and education, might in time achieve similar gains in productivity.

It won’t be plain sailing. In some important respects the pandemic and the energy transition could act as a drag on productivity. It’s not, for instance, clear how significantly increased levels of homeworking will affect productivity. A recent study of a large Asian tech company found that increased communication and coordination costs more than offset gains from reduced commuting times and reduced overall productivity . Ben Broadbent, a member of the Bank of England’s Monetary Policy Committee, cautions that lower use of offices and transport infrastructure imply a less productive use of the capital stock . Nor is capital spending rising everywhere. Some fossil fuel companies and airlines are cutting capex in anticipation of lasting weaker demand. Structural shifts in the economy risk creating mismatches between supply of and demand for labour. The interruption to education and rising youth unemployment could leave lasting scars.

The pandemic and the energy transition represent the greatest structural change since the shift to electrification and the Great Depression in the inter-war period. The question is how these changes can be harnessed to build a better future. The years after the financial crisis were marked by weak investment, productivity and wage growth. We should be able to do better this time

Here are a selection of earlier articles that talk to the same themes.

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

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]

Watch out, they are comming for you

The cost of innovation is going down, barriers to entry are falling

Keeping it special

If you work in heavy industry and are near technology, you will know that there are some very robust pieces of kit out there. What I’ve always been surprised at is:

1. how simple many of the devices are in terms of functionality; and

2. how “special” they are in terms of obfuscating the obvious.

The effects of these two factors has been, for years, to reduce competition. By making it difficult to get hold of units (via price) and creating a jargon around the obvious configuration/deployment it has promoted a closed shop approach.

Keeping up standards

In some ways keeping out the riff-raff can be promoted as a good thing – it provides assurances around quality and safety. But it slows down innovation. You might say that perhaps this is good. Maybe you don’t want to be too innovative around safety and compliance systems. Afterall making mistakes is expensive and dangerous.

Keep up!

One of the aspects of the 4th industrial revolution that will challenge that thinking is simulation. I used to think that digital twins, virtual worlds and simulation would help reduce the cost of maintenance, let the experts create new ways to work and basically bring down the operating costs for the incumbents.

What if it leads to a whole new raft of competitors? What if anyone can have low-cost access to a virtual oil rig, or virtual power station, or virtual chemical plant? Not only will they learn how it’s supposed to work, they can try things and see what happens – learn by doing, learn by breaking, but do it virtually. Perhaps this will lead to:  

  1. they might come up with much better ways to operate it that you do; and
  2. train themselves to operate it before you hired them

Result: Better ways of working, access to more talent, incumbents get beaten.

If you have ever witnessed teenagers playing fortnite, you will know how fast their thinking can become and how fast their brain-hand connetion is. Imagine how quickly they will be able to react to real-world situations and think through the information being thrown at them.

Examples

I’ll provide two examples of where “public access” and “new ways of working” are already influencing established hierarchies. It won’t be long before these mechanisms appear in heavy industry.

Don’t expect today’s engineers to enter the workforce unprepared nor unwilling to take on the establishment. Watch out for competition from smart people who are not part of the established hierarchy. Don’t think the way you work today, will be the way you work tomorrow.

Example 1: Team Huub-Watt bike

I was lucky enough to see this cycle team win gold at the Track Cycling World Cup in December 2019. The team is comprised soley of amateur racers and they ran a completely novel strategy calculated using simulations and software. Their budget is £15,000 per year. They beat Team GB who have the best coaches, facilities and trainers available – and a budget this year of £26m. That’s over 1,000 fold decrease in cost and substatially BETTER performance.

Response from the establishment was to change the rules, enforce the status quo. This may not work forever. It probably won’t work for you.

https://www.tri247.com/triathlon-features/interviews/huub-wattbike-uci-interview

They were not, however, afraid to make use of the technology for their own ends. Zwift is a cycle simulator that people can use at home and join in real-time cycle events and ride-outs while collecting performance statistics. It is now being used by pro-teams to identify and recruit talent.

https://www.cyclingweekly.com/news/latest-news/i-want-to-ride-in-the-worldtour-how-british-cycling-are-using-zwift-to-help-identify-young-talent-454806

Example 2: British Touring Car Championship

In the gentleman’s toilet at the Royal Automobile Club in Pall Mall – in the heart of establilshment London – there are a series of framed caricatures of some of motor racing’s greats from the last 100 years. These include W.O. Bentley and Mike Hawthorn. Motor racing is glamourous. And costly. The money needed to race in formula 1 are legendary, but even the karting in a 125cc class will likely cost you the best part of £50K a season. Developing cars, tracks and drivers costs money.

So what do you think will be the outcome of last weekends win for James Baldwin in the first of the British GT Touring Car championship races? It’s a pretty big series, and winning a race is not easy.

Especially if it’s your first race you’ve ever competed in.

James honed his skill as a driver in a simulator he set up at home for under £1,000. And his talent was found when he entered a competition in an “E-Sports” event.

Turns out that the simulation prepared him surprisingly well.

https://www.goodwood.com/grr/race/modern/2020/8/worlds-fastest-gamer-wins-on-british-gt-debut/

https://www.bbc.co.uk/news/newsbeat-53554245

2020 Vision

Sorry for the title. It’s not very original. Everyone’s been using that for the last decade, but still it seems appropriate. Every January I’ve made a post predicting the year ahead. I normally write this in December and publish it at the beginning of the year. It normally makes a few tongue in cheek exaggerations to in order to raise a smile. I stole this idea from Old Knights Almanac that used to appear each year in the RETRA magazine [Link ]

Today is the day we leave the European Union. My advice is to ignore this and go and buy today’s FT. It has many stories that summarise the transition we’ve witnessed and sets out the stall for next year. Below I’ve taken extracts and headlines and they tell the story. The one thing not mentioned is the UK Government’s industrial strategy, more on that in another post. Oh, and my watch phrase for this decade is “Society 5.0” – I think we’ll be hearing more about this in the comming while.

First here is an extract from this story (https://www.ft.com/content/b64b692e-4387-11ea-abea-0c7a29cd66fe).

This caught my eye because it illustrates the emerging tech leadership that is flowing from a very entrepreneurial and exceedingly smart China, the comming tech trade-wars and how there is a shift in earnings among tech players reflective of the shift in tech approaches – showing even when you are the innovator you have to keep innovating!

BT has said the cost of implementing the UK government’s cap on the use of Huawei equipment will cost it £500m over the next five years as it reported its third quarter figures.

[…]

There’s a bumper crop of earnings to report: Microsoft reported a 14 per cent advance in revenues, to $36.9bn, helped by cloud revenues which grew 39 per cent to $12.5bn, Tesla has notched up its first-ever back-to-back quarterly net profits. The electric car pioneer called 2019 “a turning point”. AT&T’s entertainment business WarnerMedia revealed a $1.2bn hit due to costly investments in its upcoming streaming service to rival Netflix. Nintendo’s quarterly operating profit rose 6 per cent to $1.5bn, missing expectations. Samsung Electronics confirmed its fifth straight quarterly decline in profits but said it expected memory market conditions to improve in 2020.

To avoid the risk of plagiarism I am going to direct you to today’s FT (go buy a copy or have Amazon deliver you one). The headlines from these stories paint the picture and tell the story all by themselves.

Why Microsoft and Tesla are the decade’s big disrupters

https://www.ft.com/content/b3e659fc-4380-11ea-a43a-c4b328d9061c

Ginni Rometty steps down as IBM tackles cloud era

https://www.ft.com/content/aabee59a-43aa-11ea-abea-0c7a29cd66fe

Rich and famous turn to ‘personal cyber security’ to protect phones

https://www.ft.com/content/96c79040-40ea-11ea-bdb5-169ba7be433d 

The Apple effect: Germany fears being left behind by Big Tech

https://www.ft.com/content/6f69433a-40f0-11ea-a047-eae9bd51ceba

Elon Musk jolted by German protests over Tesla factory plan

https://www.ft.com/content/8b10555e-4345-11ea-abea-0c7a29cd66fe 

The UK’s employment and productivity puzzle

https://www.ft.com/content/a470b09a-4276-11ea-a43a-c4b328d9061c 

For today’s oil market the real threat is to demand, not supply

https://www.ft.com/content/5bf49cb0-41cb-11ea-bdb5-169ba7be433d 

Shell to slow investor payouts after earnings fall 50%

https://www.ft.com/content/4e1fa700-4334-11ea-a43a-c4b328d9061

Orsted/offshore wind: Go-Greta:

(Henrik Poulsen has turned a national oil company into the world’s largest offshore wind builder and green energy champion)

https://www.ft.com/content/719dd81d-2527-4b83-8aed-e6624476c191

Competition rules stymie co-operation on climate goals

https://www.ft.com/content/b3e0da9c-3eba-11ea-b84f-a62c46f39bc2 

I wish you a healthy, hearty,happy and prosperous 2020.

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.

Machine Learning — Data First

With all the attention on Machine Learning (ML) that I encountered at London Tech Week, I thought I better find out a bit more about it. I wanted to verify my view that it won’t have a dramatic impact on the Oil and Gas industry and see if this was actually true.

My findings, so far, is that ML might:

  • Speed up some analysis
  • Change the spread-sheet paradigm (for better or for worse)
  • Enable people with the right level of expertise to create predictive analysis (whether this will be at all valuable is a different matter)
  • In a myriad of small ways, change minor tasks (removing annoyance, reduce low-value add data & reporting work, change interfaces)

None of these applications are dramatic in themselves, but over time they may add incremental benefits that provide a moving improvement-front. A bit like a six-sigma or Kanban.

What will you need in order to drive broad-value from ML

You’ll only be able to take advantage of that if four things are true:

  1. You have clean, historical data available
  2. You can access and combine quality-controlled, time-dependant data in near real-time (ideally from multiple sources)
  3. You have wide-spread knowledge of how to apply the new analysis tools – like those based on “R”. (think how many people can use Excel today for collecting, analysing, querying and reporting on data – varying degrees of proficiency, but who do you know that can use “R”)
  4. You are prepared to reorganise the way work is performed to take advantage of the new possibilities created by: data analysis leading to demonstrated-fact-based / probability-assessed management decisions & employee actions.

Low cost hardware is the trigger

The interest in machine learning is spawned from the dramatic drop in the cost of hardware and software required to perform the number crunching required. Because of this, not only has the complexity of the addressable problem increased but also the inefficiency of code that can be supported increases the usability of tools and techniques leading to their application by practitioners outside pure decision sciences.

If you attend any of the IoT conferences – or speak to the large vendors of real-time industrial data, you’ll hear a lot about how edge-computing and Machine-Learning will change things for industry. “Edge” means placing computing power in the field with low-power and small costs.

Putting this alongside the sensor enables pre-processing information to send back only the results. This helps to reduce data bandwidths and increase responses.

For a view on how cheap this type of technology now is – and how undramatic the applications of ML really are I invite you to have a look at this video (from the hobbyist market) showing what can be done for less than $100. Listen out for the references to “TensorFlow” one day that will be important, there are also some passing references to cloud-based resources that may be of interest.