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Fujitsu – trends in energy IT outside upstream

Thursday, November 8, 2018

Digital Energy Journal was invited to a London user conference by Japanese IT giant Fujitsu, where we learned about trends in digital technology as used in organisations other than upstream - and much of it seems relevant to oil and gas sector

Digital Energy Journal was invited to a London user conference by Japanese IT giant Fujitsu, where we learned about trends in digital technology as used in organisations other than upstream - and much of it seems relevant to oil and gas sector.

The theme of the day was 'human centric innovation, co-creation for success'.

Fujitsu recently conducted a survey of 1626 business decision makers from all industry sectors, and found that '74 per cent of digital projects are not delivering'. Retail and banking said 30 per cent of projects were 'successful,' and manufacturing sectors said '20-25 per cent' of projects were successful.

In the same survey, 72 per cent of people agreed that 'shadow projects are the only way to deliver meaningful innovation' meaning projects not under the control of the CIO or IT team. 66 per cent said failed digital projects put them off pursuing in the future.

Also 86 per cent said they thought the company's 'ability to change' was critical to future success.

Dr Joseph Reger, CTO, EMEIA, with Fujitsu, says a common misconception he sees is that you can do 'generic data analysis', feed a bunch of data into a machine and get something useful. He equates this to 'trying to do a painting with just one colour'. You need to know what the data is about beforehand.

On the subject of 'digital transformation,' Dr Reger observes that we are getting 'industry specific solutions for almost everything' now.

Dr Reger is interested in so-called 'explainable Ai', AI systems which can tell you why they made a certain decision. This is applicable to situations where an AI system might make a decision affecting someone (for example a loan application) and the person wants to know why that decision was made. A standard AI system cannot reveal anything apart from billions of numbers.

Dr Reger believes that blockchain systems can 'create trust in a formalised way, or eliminates the need for it.

Dr Reger sees 6 factors as important in a company's 'digital muscles' - good integration between digital system and the business, a good digital ecosystem (with partners), and the ability to get value from data. Within the company, you need leadership, people with the right skills, and agility.

'Digital transformation must be the responsibility of the CEO,' he said.

In a panel discussion, participants agreed that 'IT is a culture, not an organisation.'

Also, 'a lot of solutions fail because they are thought of as a 'solution', delivered in a point in time,' rather than embedded in how the company works.

Another common problem is that people don't understand the experts on solving data problems are very different to the people with traditional computer science skills.


Impact from Artificial intelligence

A session was held on how to 'create impact and develop strategy' with artificial intelligence, with David Snelling, program Director Artificial Intelligence at Fujitsu, and Dr Milos Milojevic, Industry Analyst, Digital Transformation, IoT & AI with software advisory firm PAC UK.

Mr Milojevic noted that AI has probably been 'buzzword of the year', heard even more than blockchain, with a narrative both positive and negative, and so much talk about different applications and use cases.

Mr Milojevic's preferred definition for AI is 'using algorithms and mathematical models to enable a computer program to perceive, learn and interact with the environment, to improve business operations.'

It has been around since the 1950s. He sees three 'AI winters' since then, when there was little interst in AI, of 1974 to 1980, 1987 to 1993, and 2000 to 2007. As Mr Milojevic sees it, the recent explosion in interest was led by the growth in AI-driven popular voice software, Alexa and Siri.

Mr Milojevic sees 3 important ingredients to make AI work in companies - plenty of data (about operations and customers), lots of computation power available (e.g. on the cloud), and lots of 'brain power' - human experts.

The company surveyed European professionals in 5 business sectors which could use AI, to find out where they perceive the value to be and where their biggest challenges are. (see further details online at http://bit.ly/fujitsuai).

Companies said that what they saw as most useful contribution from AI was the ability to provide a more personalised software experience, a conversational interface, and real time responsiveness.

When asked if they already had an AI strategy, 11 per cent said they had one in place, 29 per cent said under development, 35 per cent said in 2 years, 26 per cent said it was 'being discussed'.

25 per cent said they thought AI is 'strategically important'. 53 per cent it is not strategically important but can solve some business challenges. 22 per cent 'not strategically important'

Fujitsu's David Kelly noted that this is still a fairly superficial application of AI - it is not yet being used to evaluate a business strategy, for example.

Of the supply chain management professionals surveyed, 83 per cent said they see value in AI, and the biggest area was identifying the best procurement strategy.

The finance and accounting professionals surveyed said they saw the biggest benefits in predicting a future financial situation (such as cash flow), doing automated invoice management and fraud detection.

The production professionals surveyed saw the biggest potential in predictive maintenance and improving production efficiency.

The sales and marketing / service professionals thought AI could help understand customer reactions by analysing faces, and target customers with personalised offers.

The IT professionals surveyed thought AI could be used to improve cybersecurity, and also to monitor the use of different assets, to improve availability, and tune / optimise infrastructure.

Mr Milojevic said that companies are already using AI to drive chatbots (to support customers), process customer e-mails, and make minor business decisions - airline EasyJet uses it to predict how much food is need on flights.

Mr Kelly noted that many 'everyday data analytics' projects are labelled 'AI projects' now.

Companies will get more value out of it if they make a decision to adopt it, rather than conduct endless experiments, he said.

The most commonly cited obstacles are inflexibility in the vendor ecosystem, legal obstacles, and a company's internal process and culture.

Mr Kelly said you commonly read in the press that 'AI is taking over the world' - but 'the reality is completely different'.

The recommendations for getting value from AI in a company are to first fully understand your biggest business challenges and problems. Then to make biggest use of your available data, technology and talent. You should get to know AI use cases (where it has provided value elsewhere).


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