The power of NLP: when David becomes Goliath

“Perhaps the biggest threat and opportunity organisations face is Natural Language Processing (NLP); where ever increasingly smart robots simplify transactions for customers.”

Yet the user experience of such intelligent personal assistants can at times feel underwhelming because they lack a sufficiently broad range of services versus other digital channels. Facebook M for example relies upon human trainers to complete more complex customer service tasks requested by users and Alexa utilises ‘skills’ – tailored apps such as Spotify. None of them appear to offer the same level of complete user freedom as using traditional web browsers to access any available content.

“Any organisation regardless of its size able to master NLP can potentially compete in previously unreachable or unscalable markets.”

One way these robots could overcome these limitations is to “learn” how to use NLP to access any digital service through its front-end without the need for any technical integration or human touchpoints. All transactions could then be consumed or simplified into one customer experience accessed by a single AI.

The implication for competitive advantage is that potentially any organisation regardless of its size that can effectively master these “platform on platforms” cloud capabilities will be able to compete in previously unreachable or unscalable markets

“In this “open season” competitive environment, NLP can enable an organisation to transform its relationship with an existing customer and steal new ones from competitors.”

One such service could be an AI that searches and buys the best priced goods from competitors from their own customer-facing channels (without their co-operation or collaboration) so empowering a customer to create their own “perfect basket” free from the constraints of only shopping with one brand. These competitors would still get revenue from these purchases but critically won’t have direct access to this customer relationship or loyalty – NLP is disrupting their competitive advantage by reducing their market power.

In this “open season” competitive environment, where switching costs are practically nil for customers, NLP can enable an organisation to radically transform its relationship with an existing customer and steal new ones from competitors – David becomes Goliath.

If you would like more information about how digital transformation can benefit your organisation please contact the Sopra Steria Digital Practice.

Platforms on Platforms: Innovation by subtraction

One of the competitive advantages of Digital Transformation is that it empowers an organisation to rationalise (or subtract) processes to innovate the customer and employee experience. So as organisations face new economic and competitive challenges how can adopting such capabilities benefit them?

Disruptors like Amazon and Uber have transformed markets using a global approach that removes the need for customers to use locally based, often more expensive incumbent competitors. This advantage is generated by their high volume, fast turnaround digital platform services that enable them to achieve economies of scale that drive greater choice and better prices for customers.

One wonders what further opportunities could emerge for “innovation by subtraction” delivered using Digital Transformation

In response, we have seen incumbents imitate this platform model such as Sainsbury’s intended integration of Grocer and Retail Catalogue propositions through its acquisition of Home Retail Group (that owns Argos). Such a move not only increases the level of choice Sainsbury’s can offer to match Amazon but also offers it other advantages in terms of more efficient logistics and faster deliveries (Argos, like Amazon, offers same day fulfilment).

Yet one wonders what further opportunities could emerge for “innovation by subtraction” delivered using Digital Transformation to disrupt sectors further – not just for engaging more demanding customers, but also to capitalise on increasingly fluid labour market dynamics like the Gig Economy.

Such a model potentially confers a range of co-opetitive benefits including deeper engagement in the Sharing Economy

Could the next disruption be “Platforms on Platforms”? This is where a disruptor creates a digital platform that enables a customer to consume personalised services from any competitor through one channel, effectively removing or subtracting the inconvenience or restrictions of engaging only a single retailer? Price comparison websites, for example, are an established form of the “Platform on Platform” concept, yet they arguably lack the ability for a customer to pick and mix offerings from different retailers into one truly personalised shopping basket.

Such a model potentially confers a range of co-opetitive benefits for contributing retailers – including opportunities to sell to previously unreachable customers, logistics efficiencies and deeper engagement in the Sharing Economy popular with millennials.

Organisations creating “Platforms on Platforms” to further disrupt their sectors or markets could become a key strategic trend over the coming years

Low skilled and temporary workers could also benefit from using a “Platform on Platform” service that pulls together in one place shift opportunities or short term assignments available during the same week (or even day) from different – potentially competing – organisations. Given the anticipated impact of automation, high wage costs (like the National Living Wage in the UK) and greater demands for labour flexibility, such a service could materially benefit these workers in the emerging Digital Economy (while also removing the need for employers to search and procure such flexible people resources independently).

Organisations creating “Platforms on Platforms” to further disrupt their sectors or markets could become a key strategic trend over the coming years. But to master this new form of competitive advantage will require innovation by subtraction using Digital Transformation.

If you would like more information about how digital transformation can benefit your organisation please contact the Sopra Steria Digital Practice.

How deep learning is advancing AI in leaps and bounds

by Michel Sebag, Digital Practice, Sopra Steria France

Nature has given human beings an amazing ability to learn. We learn complex tasks, like language and image recognition from birth and continue throughout our lives to modify and build upon these first learning experiences. It seems natural then, to use the concept of learning, building up knowledge and being able to model and predict outcomes and apply that to computer related processes and tasks. The terminology used to describe the technologies involved in this paradigm in computing are Artificial Intelligence (AI).

It’s just a game

In the late 1990s, a defining moment in the world of artificial intelligence happened. In 1996 chess master Garry Kasparov played IBM’s Deep Blue, originally built to play chess using a parallel computer system, and won 4-2. A year later, Kasparov and Deep Blue played another match – this time, Deep Blue won. This win created a sea-change in the attitude towards the idea of AI. Chess masters minds have to perform highly complex calculations, evaluating multiple moves and strategies, on-the-fly. They can also take their own learning and apply novel moves. Being able to mimic this process, even if applied to a specific task like chess, opens up real potential for the technology.

Out of this success, new developments in AI have brought us to the point of maturity and sophistication. DeepMind, now owned by Google, uses deep learning algorithms. These algorithms are based on the same idea that allows human beings to learn, i.e. neural pathways or networks. Again, AI has been applied to gaming to prove a point. DeepMind has taken the idea of ‘human vs. machine’ and this time used it in the highly complex game of ‘Go’. DeepMind, the company, describe the game of Go as having “more possible positions in Go than there are atoms in the universe”. So then, this is the perfect challenge for an AI technology. DeepMind uses deep learning algorithms to train itself against known plays by expert players. The resultant system is known as AlphaGo and has a 99.8% win rate when pitted against other Go programs, and has recently won 4 out of 5 games against the Go pro player, Lee Sedol.

It may seem that it’s just a game being played, but in fact, this is proving the technology, showing it can learn how to model and predict outcomes in much the same way that a human being does. In almost 20 years AI is already 10 years ahead of what was anticipated of the technology. The games have proven the capability and now the technology is entering a stage of maturity where it is being applied to more real-world problem solving. Following the AlphaGo success, Google has understood the benefits of these technologies and has promptly integrated AlphaGo technology in its cloud based Google Machine Learning Platfom.

Some definitions in the world of Artificial Intelligence

At this juncture, it is worth looking at some of the terminology and definitions of AI technology.

It can be viewed as this: Deep Learning is a sub-set of Machine Learning; Machine learning is a sub-set of Artificial Intelligence.

Artificial Intelligence: This is a general term to describe a technology that has been built to demonstrate a similar intelligence level to a human being when solving a problem. It may, or may not use biological constructs as the underlying basis for its intelligent operations. Artificial Intelligence systems typically are trained and learn from this training.

Machine Learning: In the case of the games we used earlier as examples, machine learning is trained using player moves. In learning the moves and strategies of players, the system builds up knowledge in the same way a human being would. Machine learning based systems can use very large datasets as training input, which they then use to predict outcomes. Machine learning based systems can use both classical and non-classical algorithms. One of the most valuable aspects of machine learning is the ability to adapt. Adaptive learning gives better accuracy of predictions. This, in turn, facilitates the handling of all possibilities and combinations to provide the optimal outcome from the incoming data. In the case of game playing, this results in more wins for the machine.

Deep Learning: This is a sub-set of machine learning, a type of implementation of machine learning. The typology of the system is vital; when learning, it’s not so much about ‘big’ but it’s more about the surface area or depth. More complex problems are solved by larger numbers of neurons and layers. The network is used to train a system, using known question and answers to any given problem and this creates a feedback loop. Training results in weighted outcomes, this weight being passed to the next neuron along to determine the output of that neuron – in this way, it builds up a more accurate outcome based on probabilities.

Real world applications of AI

We’ve seen the use of AI in gaming, but what about real-world commercial applications? Whenever it comes to predict, forecast, recognize, clustering, AI is being used in a multitude of processes and systems.

At Sopra Steria, for example, we use AI components in industry solutions, including banking and energy. We are integrating Natural Language Processing (NLP) and voice recognition capabilities from our partners’ solutions such as IBM Watson or Microsoft Cortana. NLP, voice recognition – and image recognition in a near future – are now widely used and integrated in a multitude of applications. For example, for banking industry, text and voice recognition are used in qualification assistants for helpdesk and customer care services. More generally, some of the best-known modern applications include everyday use in our smart phones. Voice and personal assistance technologies like Siri and Google Now brought AI into the mainstream and out of the lab, using AI and predictive analytics to answer our questions and plan our days. Siri now has a more sophisticated successor named VIV. VIV is based on self-learning algorithms and its topology is much deeper that SIRI’s more linear pathways. VIV is opening up major opportunities for developers by creating an AI platform that can be called upon for a multitude of tasks. Google recently announced a similar path to its widely acclaimed assistant Google Now becoming Google Assistant.

Machine Learning is also used in many back-end processes, such as the scoring required to allow things like bank loans and mortgages. Machine learning is used in banking to specifically offer personalization of products giving banks using this method a competitive edge.

Deep learning is being used in more complex tasks, ones where rules are fuzzier and more complex. The era of big data is providing the tools that are driving the use cases for deep learning. We can see applications of deep learning in anything related to pattern recognition, such as facial recognition systems, voice assistance and behavioral analysis for fraud prevention.

Artificial Intelligence is entering a new era with the help of more sophisticated and improved algorithms. AI is the next disruptive technology – many of Gartner’s predictions for technology into 2016 and beyond, was based on AI and machine learning. Artificial Intelligence holds the keys to those unsolvable issues, the ones we thought only human beings could do. Ultimately, even the writing of this article may one day, be done by a machine.

What are your thoughts? Leave a reply below, or contact us by email.

2020: The family digital Christmas?

It’s the year 2020.  Digital technology is all around us. So what might Christmas Day be like? Here are some ideas…

Forget Dad getting into a sweat early Christmas morning because he hasn’t defrosted the turkey yet…in 2020 internet of things (IoT) smart sensors in the family kitchen refrigerator have been monitoring the thaw of the big bird for the last couple of days and adjusting the fridge’s internal temperature accordingly to ensure its ready on time. Other smart sensors have also got the oven warmed up perfectly for Dad’s culinary magnum opus.

It’s barely dawn and the little ones are wide awake eager to open their presents. Mum and Dad are barely conscious but have managed to roll themselves downstairs to be with the kids round the Christmas tree…a magic moment through bleary adult eyes. But in 2020 using miniature action cameras embedded on the Christmas tree every emotional, tearful moment of joy on their faces is captured and saved on the family’s private cloud. Mum and Dad will be able to cherish forever the look on young Sam’s face when she finally got the bicycle she wanted all year.

Mid-morning and the Christmas cards on the mantelpiece are dynamically updating with pictures and videos of family and friends celebrating from across the world.  That’s because in 2020 people send paper-thin OLED Christmas cards that are linked directly to their social media feeds – it looks like Aunt Liz and Uncle Ted haven’t stopping partying for twenty-four hours on their Caribbean cruise!

Christmas dinner is fast approaching and Gran’s thousand piece jigsaw puzzle of Buckingham Palace is missing the vital middle bit with the flag on!  Little Tim is not happy either; he’s only had Gigantic Bot for six hours and he’s already lost its Laser Sword accessory in the black hole known as the back of the living room sofa. So it’s a good job in 2020 there are delivery drones in the local area available immediately to pick up and replace faulty or missing Christmas gifts. There will be no tears of frustration on this festive day.

So Dad’s dinner went down a treat and all the family are dozing on the couch. Mum in particular feels relaxed – she hasn’t done anything today and it’s been great! In 2020, even the music and lighting of the living room is taken care of by the house AI – its smart sensors detect the slowing pace of the family in the afternoon so it moves from playing bouncy festive jingles in brightness to soothing Christmas lullabies with a cosy ambient glow from the fireplace. Mum drifts off to sleep with a smile on her face.

Christmas in 2020 sounds like fun doesn’t it?

Season’s greetings!

If you would like more information about how digital transformation can benefit your organisation please contact the Sopra Steria Digital Practice.

2017: the year of user productivity transformation – and more…?

I don’t think I can consider 2017 without first looking briefly at 2016. It is safe to say that 2016 was an interesting year across the public sector with some major tectonic sized decisions and changes.  What these will mean are still to be understood, and my colleague Steve Knights has a look at some of these in his blog ‘2017: An exceptional year of change‘.

Like the political arena, technology throughout the year has also been interesting and challenging and Local Government entities throughout the UK have taken some major steps towards embracing ‘Digital’ in the delivery of services across all aspects of their operations.

With the challenges being placed on budgets, Local Government is having to become more creative in how it utilises technology to support employees, operate the business and deliver services to a widening variety of citizen needs. Our London DigiLab innovation centre, is hosting increasing numbers of authorities eager to discuss their issues and look at opportunities to save and improve.  It is providing an important forum to help them look differently at what they do and is enabling us to identify different ways of working and new technologies that will deliver lasting benefits to their organisations and services they deliver.

2016 saw some major players in the technology sphere bring in new offerings which have the potential to change how core digital services are offered.  Microsoft opened their UK data centres offering Azure and Office365 capabilities, with a roadmap of a lot more services to be deployed throughout 2017.  IBM are bringing their Watson Cognitive technologies to UK shores, and Amazon Web Services will be opening UK data centres.  With the implications of Brexit still unknown, this collective of UK centric technology offerings will give local authorities more options to protect their data and systems.

Some of the technology trends which we saw during 2016 will continue well into 2017 and beyond. They have the potential to change how citizens engage with public services, but the biggest changes will be in how employees and businesses operate.

2017 will be the year of user productivity transformation, Systems of Intelligence and Business as a Service.

Microsoft’s Azure, Office365 and Dynamics365 offerings have matured to significant levels, giving organisations a new opportunity to embrace the possibilities of Cloud on-demand operations.

Cognitive systems, or Systems of Intelligence, started to appear as mature service proposals during 2016, but the take up has been slow as organisations struggle to understand how these can be used within existing operations.  Throughout 2017 we will see more Machine Learning and Cognitive-based offerings becoming mainstream in the business operations across local government. IBM Watson will be leading the charge as this is the most mature of the current public domain Cognitive offerings, but Microsoft’s Cortana Intelligence Suite is also maturing at a rate and will start to offer more Machine Learning services. Google’s Deep Mind is the wild card and we will have to wait and see how this will become available.  Apple will continue to explore the Artificial Intelligence space with Siri becoming more useful as a Digital Personal Assistant helping us do more with our time.

Data will continue to grow in importance and will focus on generating Actionable Intelligence using Machine Learning systems to derive insight. It will give Local Government an opportunity to look at how it can embrace a more open data culture to bring their rich datasets together in a way that can help them understand and tackle challenging areas.

How services are offered and consumed by citizens will also go through transformation as Micro Services Architecture is embraced. This will enable focused tackling of discrete aspects of service before they are then aggregated into a collective solution. Personalisation will become more of a need than a nice to have and data will be key to helping drive this understanding and service delivery model.

In summary, 2016 was a good year as organisational thinking around the use of technology matured and evolved bringing more options, solutions, innovation and ultimately beneficial outcomes. 2017 is when Systems of Intelligence will provide opportunities for the public sector to deliver more user-centric, personalised and contextual services. Some of the key technology areas that will help Local Government with this are:

  • Machine Learning – to help provide a more personalised experience which is agnostic of service delivery channels
  • On-Demand Services – to enable employees, managers and citizens to access the things they need
  • Choose Your Own model – to provide a more flexible and responsive IT function that supports employees in doing their jobs more efficiently and productively
  • Micro Services Architecture – to change the way services are designed to remove the complexity of large system redevelopment
  • API First – to provide a more dynamic approach to systems integration
  • Device agnostic services – to remove the barriers to individuals accessing the facilities they need, when they need them, through whatever means works for them

Thinking and acting differently

There is no doubt that technology has a significant role to play in helping local government achieve the savings they need, and that though a strategic approach to delivering digital services at scale, authorities can realise significant benefits.

At Sopra Steria we are seeing local authorities thinking differently about how they can approach their current challenges and looking to external partners to help them embrace a more agile service delivery model.

What are your thoughts for Local Government as we head into 2017? Leave a reply below or contact me by email.

Reflecting on 2016: what was all that about?

If you were in the business of predicting the future, you could probably choose a better year than 2016 with which to try to take a guess at just what might come to pass. There’s no doubt that it has been a tumultuous year internationally, with the repercussions of huge social, economic and political changes still being felt across the globe.

Undaunted, Sopra Steria’s intrepid Horizon Scanning team, set out back in January with the aim of identifying those technological trends likely to have an impact on our clients, their businesses and their customers not only in 2016 but in the three to five years beyond that.

Creating the frame of reference below, within which to make our observations and tell their stories, the team has been working in Sopra Steria’s DigiLab throughout 2016 with clients across both public and private sectors to test and explore their observations and insights as the key disruptive technologies which they have identified have begun to evolve.

six topics + intersections between them giving us 15 lines of enquiry for 2017: see a text version of this diagram below

In this, the team’s final podcast of 2016, along with my colleagues Richard Potter and Ben Gilburt, I reflect on what we have seen and consider just what 2017 might have in store for us.

See more about Aurora and our London DigiLab.

What are your thoughts about 2016 and the technological trends for 2017? Leave a reply below or contact me by email.


Text version of Aurora’s horizon scanning topics:

Vertical view

  1. The digital human: interacting with services and each other through ubiquitous devices and data-driven experiences
  2. The organic enterprise: flexible, distributed, collaborative and networked organisations
  3. A smarter world: a crowded, ageing, more connected and fluid world

Horizontal view

  1. Intelligent insight and automation: the increase in the application of prescriptive analytics and automation to augment or displace human activity
  2. Ubiquitous interaction: the growth of sensing and interface technologies that make interactions between humans and computers more fluid, intuitive and pervasive
  3. Distributed disruption: the growth of decentralised processes enabled by the adoption of technologies which assure and automate security and trust

2017: An exceptional year of change

In recent years digital technologies have driven an extraordinary pace of change in the way we do business, live our lives and interact with each other. According to a report conducted by digital and marketing intelligence group eMarketer, e-commerce sales will this Christmas exceed 20% of total retail sales during November and December, an estimated £16.9 million of online sales. This continues a year on year upward trend for retail digital transactions that shows no signs of slowing.

The challenge for Local Government is to keep up with this trend and match the expectations of their citizens who increasingly want digital solutions to all of their business interactions.

For many reasons 2017 looks to be a pivotal year for Local Government.

New structural changes such as Devolution will give both opportunities and challenges, particularly in the way that large scale infrastructure projects are commissioned and delivered. Transport improvements will offer not only a major boost to the construction industries throughout the development phase, but upon completion will deliver the connectivity – both nationally and internationally – needed for economic growth.

Key customer-facing services such as the delivery of welfare benefits are at the forefront of the introduction of digital services to both improve the point of contact with the customer but also to streamline the delivery of crucial benefits to those in need. Likewise, the pressures on health services are increasingly being addressed with digital solutions that can help to relieve the unsustainable demands placed on our doctors and nurses.

But as well as the transformational changes that we are seeing in the way that we do business, 2017 also brings us exceptional political change.

A Trump presidency and Brexit are likely to overshadow both world and domestic politics for many years to come.

As we enter this year of change, we offer – by means of a short video – a few thoughts on some of these issues.

What is absolutely certain is that by the time we reach 2018 we will be entering a very different world to the one we leave in 2016. The period of change in between will be 2017 – so be ready for a roller coaster ride!

What are your thoughts? Leave a reply below or contact me by email.