The new CIO – Lessons from Salesforce.com

I’m seeing interesting parallels in the Oil and Gas sector that I first encountered when I witnessed Salesforce.com start be adopted by large corporates over a decade ago. Let me explain.

What is Salesforce.com

Salesforce.com is a company started to provide a way for small businesses to access customer relationship management (CRM) in a structured way. This helped them to co-ordinate sales activities and record information about customers, conversations that had been had between different people across the selling organisation.

Salesforce.com did this by using web-pages rather than software and thus required no software to be installed, and because the information was held in the centre, it was automatically up to date and shared among the staff. In 1999 this was a revolutionary approach.

Salesforce.com now does a lot more than just sales, and is – justifiably – used as a more general information processing platform for companies. One of my clients even runs their entire global finance function using the platform.

The Salesforce.com transition to corporates

Before Salesforce.com the problem of co-ordinating diverse sales teams and sharing CRM sales information was one that was addressed with (say) Siebel. This required an on-premise server at each sales-hub, an application on a lap-top and then some form of roll-up to a central IT system so HQ could see what was happening.

The role of the CIO was clear – gather together a cross section of users, design some screens that may (or may not) mirror the sales process, have them programmed up, check they worked like you had asked for, make a standard install and then go around the world trying to get systems to talk to each other and brow-beat the sales guys into using the software (which they hated). On top of this “senior buy-in” was required to persuade the guys on the front line to change the way they worked until it fitted in with the standard IT system.

This was the old way. The focus was all about getting the blinking technology to work in the first place. Once it did, if you were lucky, you could then outsource the management of the whole cluster f*** to a call centre that “followed the sun”.

Well it was little wonder that in 1999 the dream of shared CRM was out of the reach of small sales-teams (who would often use an odd little product called ACT!), that big company sales guys hated their IT departments, and everyone hated Oracle.

Once Saleforce.com came along everything changed. The application was not installed but was delivered over the web. Because all the data was hosted in the middle, it was naturally synchronised and could be shared. Because it ran on Salesforce.com’s servers there was nothing for the CIO, IT department and the outsource guys to maintain. It was also very easy to use and quick to customise it to tune it to your business.

Small businesses took to Salesforce immediately. It was so much better than what they had before and, function for function, much cheaper. Costs scaled with the number of users and you didn’t have to buy or maintain all manner of servers and network links. It took a while for the big companies to start to “get” Salesforce because the sales pitch had been around the cost of the solution which was very clear cut for small businesses. For big companies however, the benefits when measured with traditional business-cases and the commercial logic of the procurement department did not seem as clear-cut. Add to this that traditional “IT Departments” weren’t set up to contribute to a conversation that didn’t involve “keeping the lights on” IT – it was quite difficult to generate momentum to start with.

The ten-year pause

I worked with Salesforce.com technology and was in the middle of the transition from a world of small companies and independents to major company roll-outs using the help of big consulting firms. It was about 10 years after the SME’s started to jump on the bandwagon that the corporates started to understand and deal with a compelling business case around CRM.

Around the same time that CRM was making inroads to large companies, new technologies were emerging in various “cloud” guises. This included companies like SAP, Microsoft, Oracle or others. Enterprise on-demand platforms were becoming available. But the business case for adopting them was not clear. That was about a decade ago. Now I’m seeing the big-company adoption in oil and gas starting to address the same types of problem I saw Salesforce.com overcome. Perhaps there are lessons that can be drawn?

Make cloud work in 3 areas

In the last decade, the on-demand technology, infrastructure, bandwidth have all improved dramatically. This has made some of the lazy performance objections invalid. Now the centralisation of the technology in cloud and the provision of on-demand pay-as-you use applications, compute, storage and bandwidth just works, and works better than anything a company could do for themselves. And that applies to almost every area of activity.

The three main driving forces then were: a change in structuring budgets, capturing cost of ownership benefits and understanding where value is created within the system; the enablement of entirely new ways of organising core operations; and the role of the CIO.

What’s happend at Salesforce since I last looked?

I tabled these ideas with a senior strategist at Salesforce.com to see what he’d seen in the decade since I sold my SFDC partner business and, to paraphrase, this is what he said:

Well Gareth, in my world I see that CEO’s are very concerned about the potential from disruption led by start-ups who can establish market share quickly. I see this in many industries and in oil and gas you have innovators such as Lord Browne combining smaller companies and driving innovation. CEOs like this need Agility, Flexibility and Speed to enable their business to react. They have tasked their CIO’s to provide tools that their people can use to innovate. The CIO has to find budget for innovation and the only way to do this is to remove legacy run cost from the existing landscape.

Platform’s like Salesforce also lower the cost of innovation by enabling point and click  / low code prototyping etc. However that innovation must be aimed at retiring legacy systems rather than add to the IT stack (and cost). Here, integration is the key. Meta-data driven API’s mean it’s easier to make changes and flex with the business needs across multiple systems.

I’ve also noticed that, since you left, we encountered a new generation of employees who are used to looking out across the web to find information. They are very surprised by how backward many of the corporate IT systems are, and how isolated information is between functions. CIOs who are deploying on-demand platforms simplify IT run and therefore reduce costs. They also have the opportunity to consolidate applications onto a single platform to ease support / dev teams and create a consistent user experience. This saves money, frees information access and makes technology help rather than hinder.

I’ve seen the role of the CIO change in the last decade. It is now to bring technology ideas and options to the table as a business partner for digital. The CIO needs to be aware of what competitors, the market and other parts of the business are doing. However, there is no-such thing as self-adopting application. It is laziness to assume that changing technology will be enough. Some companies still think that if they create a new system then if people use it then that’s great and if they don’t it’s the fault of IT for not delivering a great experience. There is no time for mistakes and we’re just accelerating the rate of change. We need to get it right first time. This means that the COO must lead the change enabled by an IT project and be accountable for its success and responsible for changing the business processes and management around it. The CIO is there to support the business change, not to foist unwanted technology on an unwilling operation.

image credit: http://www.iacloud.com/

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/

 

Interview with Patrick von Pattay

I was introduced to Patrick [Link] by our mutual friend Short Allerton [Link]. We both worked with Short in Schlumberger days, but our paths had not crossed until recently. Patrick is an exciting individual who has worked on very interesting projects pushing the boundaries of future oil and gas practice in Upstream. We got on well and he shares many of my views on digitalization, and – importantly – our opinions differ about how things may develop in some areas. It was a genuine pleasure to speak with him and he has agreed that I may publish this interview on the blog.

GD: Good Morning Patrick, thank you for agreeing to talk to me about Industry 4.0. It sounds like you are very interested in the topic.

PVP: As you might have recognized I am very passionate about the idea of a disruptive change in the oil and gas industry.  Currently I am looking into the strategic implications of digital revolution that is surrounding us and what is likely to be a time of disruption and step-changes in productivity.

GD: I agree with you Patrick digital technologies will make a big difference in upstream oil and gas, I expect to see this most pronounced in operations of existing and new plant. In my view, some fundamentals won’t experience much change – such as how resource licenses are issued by countries and used as security in the capital markets.

PVP: Just because we have not yet identified the potential disruption does not mean to me that there cannot be any.  It just means  that we haven’t thought hard enough. If it were an obvious change then it wouldn’t be so disruptive as we’d all have the ability to respond. A disruptive completive threat, by its very nature, is likely to come from left field.

GD: I’m not convinced, but interested to hear what you think the changes will be in operations?

PVP:  Leaving aside access to resources, I think there will be three main effects of the digital revolution in upstream:

Increase in efficiency:

Automatisation will be key here and I expect that activities will include predictive maintenance, artificial intelligence based auto modeling, augmented reality supported operations, automated manufacturing, Internet of things, etc.

Increasing effectiveness.

This will result mostly from faster and smarter decisions. Advanced, more complex, more integrated and holistic modeling will enable us to make more educated choices.

Improved uncertainty / risk management.

The advanced and integrated modeling will enable us to model (and therefore manage) uncertainties all the way from the reservoir to the marketing of finished products and the trading of field percentages.

GD: Yes, I agree with you on those three for sure, though it’s a bit mother-hood-and-apple pie. That’s what we’ve always tried to do, and gradually we’ve been improving there over the years. What’s going to change?

PVP: Well of course we’ve been doing that! But, things are about to accelerate and we’ll see enablers for step changes – super and cloud computing is key to holistic asset modelling – but, beyond that especially in the way we contract and co-ordinate the supply chain I expect great changes.

GD: What trends are you seeing there?

PVP: Services of all kind are becoming a commodity. Initially, this is focusing only on basic oilfield services such as cementing.  I expect that this will lead to more choice for me as an operator.

Maybe I will not buy such services through classic service contract models any more, but through a web-based and horizontally integrated retail platform. This will increase my flexibility, control and drive down costs. Perhaps drill bits will become a line-item on Alibaba? And maybe this is the domain where we will see most disruptions in the coming years.

GD: I see how that can work. There have been automated purchasing databases before, mainly for supplier pre-qualification and compliance checking. Services like the Achilles system, but they’ve been directed towards procurement departments and not putting the power of supply-chain optimization directly with the end-user of products and services.

PVP: Yes, as time progresses and digitalization evolves, commoditisation will include more and more complex services. Already the service companies and EPCIC contractors are integrating their services and offering me solutions.

Combining this trend with digital technologies could make even the development of a complete oil field a commodity one day (as much as building an airport would be a commodity by then).

GD: How do you see this changing the industry for project owner operators?

PVP: We must expect new players to enter the market. To thrive in this situation means we need to find new differentiators, perhaps even re-invent our business model. This will mean perhaps developing even more complex projects and integrating services/solutions along the horizontal and vertical value chain.

GD: That’s very interesting. What I think you are saying is that the low-end easy returns from deploying capital to safe projects will be competed down to the cost of capital, so you you’ll need to do more difficult things where there is less competition. Can you expand on that a little, how can you use digitalization to achieve that?

PVP: Well of course, there’s the nub of the issue. I can’t tell you everything I’m working on of course, but let me give you three areas where I think we are likely to see disruption: The Value of Data, the use of Cloud Computing and What I call “Buying a Result”.

The value of data

Artificial intelligence is a key technology in digitalization. It will allow us to assist humans in many places and to achieve results significantly quicker / with higher accuracy. In any case the key will be to train the artificial intelligence based on distinct high-quality data sets. Considering such data sets as training material makes them an asset. Trading such data against trained models will be a part of the new business world. Like Google is the best search engine because of its accumulated experience, so it will be with oil fields. Once this is cracked, experience may result in enduring competitive advantages which can be monetized by turning data into decisions in minimum time.

Cloud computing

The cloud will be the only place to store and process data in the future.  It is the most secure and cost-effective way.  A whole new landscape of solution providers will arise from this.  The classic service and software providers are establishing their cloud solutions today.

The operators I talk to are concerned about locking up with one of them and being chained to their choice forever. Their data may become trapped. This is going to drive standardisation and open platforms.  These will allow plug and play of any software in the cloud.  The availability of such a platform and the guarantee of the provider to support the integration of any service / software will provide small solution providers with a new platform to offer their products and reduce the market entry hurdle for them greatly.  We can imagine this a bit like the different APP stores.

Buying a result

Today we still buy compressors and then maintain them. In aviation, some airlines buy only accident-free-human-miles-transported from an airplane manufacturer. They focus on planning routes, marketing seats and ensuring client loyalty.  Similar things may happen in our industry. Augmented reality allowing to scale the know-how of a single expert, Internet of things, big data analytics, predictive maintenance, etc. will allow various solution providers to offer services to us like the way airplane manufactures do today.  The E&P companies will transform into managing and providing more complex solutions and business models. This will include more and more gain share models.

GD: You do paint an interesting view. In your scenario data and machines look like they will take over. That’s bad news for any young engineers surely. Why on earth would you need any people? Are operators going to be run by hedge funds and lawyers?

PVP: Some people think that many oil companies already are! But, seriously, I believe customer focus, personal interaction, social competencies, and creativity will become more valuable. As more and more complex tasks are fulfilled by machines the role of the human will shift towards creativity and social interaction.  I am convinced we will be very busy thinking about things that we do not even imagine today as we are busy with the groundwork.  It will be great fun!

Look, we know that even after all the money spent on, and focus applied, creating an Amazon a web page, it is still not the key to providing the best possible service. It’s efficient for somethings, but sterile and not very interesting for others. Even Amazon is opening physical stores and Apple has the most valuable retail operation in the world. Human contact and empathy is still important.

The key will be to hook up with the client immediately and to ensure that he/she can’t live without your service ever again. The client has choices, so this must be done through excellence not through lock-in. In the domain of super-mega projects this might simply boil down to the ease of doing business with you.

GD: Thank you for your thoughts on this, it’s very insightful. Where do you think, we go from here?

PVP: Reflecting on our conversation, I might even agree that the oil & gas industry will not change in the fundamentals of exploration – development – production – abandonment.  But the landscape of players will shift due to digitalisation and this might be the disruptive change for us all.

GD: Thank you, and good luck. Will you please come back and tell me and my readers how you get on?

PVP: Sure, I’ll keep in touch, and I’d I love to have feedback on my thoughts

Digital disruption landscape for upstream oil and gas

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

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

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

Demand for Oil and Gas

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

Access to Resources

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

Development and Operation of Resources

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

Sale and transport of product

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

Human elements

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

 

 

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

 

 

O&G – Exploration and industry 4.0

In an earlier post [LINK] I briefly introduced the four areas of upstream value chain that could benefit from the 4th Industrial Revolution. Here I put forward some potentially controversial points about how this may (or may not) affect Exploration.

First of all my definition: Exploration is concerned with finding and appraising new deposits of Hydrocarbons trapped under the surface of the earth. It’s the identification of these that I am addressing here, not how (or if they can be) exploited.

There have been many advances made in technology in the previous 25 years that have transformed the process of finding deposits. The two most notable have been around the use of remote sensing through Seismic Data, and the accuracy with which deviated wells can be drilled. Seismic acts like an x-ray into the composition of the rocks, while new wells use precision direction control and combine it with analysis of real-time feedback from rock measurements surrounding the drill bit to let operators steer the trajectory in real-time.

Many of the advances that have been harnessed could legitimately be described as pioneering in the technology of sensing, big-data, simulation and automation. These are the key technologies underpinning the 4th industrial revolution. Exploration got there first.

In my work with small companies seeking investment I continue to see a slew of new start-ups with fancy seismic algorithms claiming to be able to spot even more obscure sources of previously unidentified hydrocarbons. Maybe they work. Who cares?

In my view the major gains from the 4th Industrial Revolution have already been captured in exploration. Perhaps we are close to entering an era of more stable oil prices – driven by: elasticity of supply from shale; abundant reserves released from both tight reservoirs and hydrates; and managed demand through smart technology, electric drive-trains, renewable generation and batteries. So the commercial pressure to find obscure resource pools may have gone.

In the North sea there are over 300 pools of hydrocarbons already discovered but not yet developed [LINK]. So the question is: even if the new technologies are successful will they have a significant impact for operators? I suspect the answer is no.

New algorithms and systems may provide marginal gains around the edges of existing fields and provide additional in-fill development opportunities. They may reduce the number of people in G&G dept 10%. Commodification of techniques (as happened for 3D animation) may see the demise of some companies and job-roles. But I don’t think it’s going to provide a revolutionary impact. Of course, I may be wrong.

If I am right, this suggests that there will be two main opportunities for companies providing technology here – either to provide an “add-on” to the main interpretation platforms (Petrel, OpenWorks) and then sell small numbers of seats to operators in special circumstances, or attempt a wholescale assault to replace the platforms already in place. Neither of these are revolutionary for operators and result in minor cost reduction by pitting service company against service company.

I think the 4th industrial revolution is likely to provide only a small impact on the dynamics of this part of the value-chain. There may be a displacement of revenue from one software vendor to another, there may be some marginal in-fill development opportunities that will add more elasticity to oil supply (and help to further stabalise prices) but neither of those are going to be massive nor revolutionary. I think that the 4th Industrial Revolution gains have been captured already – AI, auto-pickers, attribute statistics, simulations, integration, cloud, geolocation, computing power in the hands of individuals – the main technologies are already in place. Gains from here-on-in will be marginal.

There is one thing that may change my view, however. If this happens it will have a profound impact and swing power towards the national resource owners. If these innovations are adopted at the level of the nation state things may change.

National Data Banks were established in the 1990’s (example LINK) to hold archives of seismic and well data and make them publicly available. These may get a boost.  Cloud technology and on-line AI-based mining-algorithms may change the way that license economics work by de-risking exploration and encouraging competition. If this is combined with a stable oil price there is a potential recipe for reduction in the incentives needed for exploration companies. That could change the economics and the structure of the discover, farm-down, refinance, develop and keep carried-interest process that is used today.

Automation Risk

We have recently seen some very high-profile failures of IT systems – whether by Cyber Attack (WannaCry and Varients [LINK]) or by poor operation risk control [LINK]. Something is wrong in the way things are managed

Insurance companies are starting wake up to their potentially unexpected liabilities around this risk [LINK]. They will certainly start to price this risk; this will mean that risk-reduction investment will have an immediate identifiable financial benefit. Perhaps it’s time to take a different approach

For years, I have railed against the distinction between “IT and the Business” [LINK]. I think the time has come for this gap to be finally put to rest. They are now truly inseparable.

Statoil has recently announced its response to the 4th Industrial Revolution (or Digitalisation). [LINK]. The most significant part of this is that the initiative is led by the COO. Of course it is!

If we were to take any other industrial process technology in Oil and Gas (say compressors) the management line looking after these runs up through the COO. There is not a Chief Compressor Officer who reports through the CFO and imposes compressor decisions (or delays) onto operations.

In that case, why would computerised operations technology report through the CFO via the CIO as is the case in many organisations. This should be part of the COO role. This recognises that IT is now central to operations. This is how it should be, because it is now at the heart of the current automation of operations [LINK].

In line with this I propose that the COO needs to own a new risk – Automation Risk. One of the advisors to the COO would be an Automation function – responsible for assessing and managing benefits and risks as well as defining policy across the organisation. Operational assets should comply with policy and work with Automation function around standards, risks and controls. Assurance functions can then audit compliance via the Chief Risk Officer – the right checks and balances would have saved a few hundred million dollars across the airlines in the last 12 months, perhaps a billion dollars across the industries hit by the WannaCry virus.

Automation risk planning means that the COO knows what risk sources there are that cause automation systems failure and what is the consequences of that failure would be. Importantly, he also knows what actions could be taken to reduce the likelihood and impact of a failure.

Then he can approve a business decision to choose which reduction measures are implemented. The COO must then know the real-time status of the mitigation measures – are they ready to work in case they are called upon and what is the current risk status of the organisation, is it acceptable and – if not – what is being done about it?

Contact me if you want to know about planning using Bow-Tie models and how you might be able to monitor current compliance in real-time, set-up alerts and manage your automation risk.

[Image credit: https://smlrgroup.com/universal-cyber-risk-model-part-1/ ]

Levels of Automation in Oil and Gas

One of the aspects of the 4th Industrial Revolution [LINK] is automation.

I am often asked if automation could ever add value to oil and gas? I contend that there is a good reason to think it will because benefits could come from:

  • accurate control and adjustment leading to higher throughput;
  • self-repairing (or self-scheduled repair) leading to higher uptime;
  • more accurate execution of plans by reducing manual error; and
  • less distracted management leading to higher-value decisions;

Many people are sceptical that we can ever “automate” an upstream oil and gas production facility.  I agree that “full” automation is unlikely, but I would argue that partial automation is already present. What we need then is a way to describe “levels of automation” so we can define what we are talking about and reach agreement about what to do.

Autonomous cars are in the news for good reason right now, and are making great progress. Perhaps we can create a common language for “level of automation”. The SAE introduces itself as:

SAE International is a global association of more than 128,000 engineers and related technical experts in the aerospace, automotive and commercial-vehicle industries

It has defined 5 levels of automation that has now been adopted by the US Department of Transport. Here’s an explanation from wired magazine [LINK].

What dimensions could be used to classify degrees of oil and gas production automation? My definition of the process of automating is: “Reducing the friction between sensing what is going on and taking the right action”. This can be used to underpin a maturity matrix.

If we can sense what’s happening, reduce the friction before acting to zero and be exactly right in the actions we take – then this achieves perfect automation. Of course this then leads to the need to define in more detail: sense, friction and right.

Some of the steps that can lead to more automation are:

  • Improved sensing of the environment;
  • Distribution of sensing data;
  • Transformation of data into information (e.g. production vs. target);
  • Exploring related information, history and context (e.g. maintenance records)
  • Understanding the consequences of the information presented (prediction);
  • Checking possible actions and their impact (simulation);
  • Delegating decisions to reduce management delay; and
  • Feeding back observed results to scientifically tune future predictions (learn)

Contact me for more information about how it is possible to incorporate the above into an assessment of your organisation’s automation maturity and readiness for change.