Reinventing business models: what can the public sector learn from digital disruption of business?

In my last blog I wrote about how government is challenged by technological change and globalisation. I now want to explore what governments might learn from the experience of the private sector.

Globalisation is connected to the rise of consumerism. But its attributes of brands, choices, service, access and responsiveness are no longer the preserve of the private sphere.  Increasingly, these attributes define the expectations of the public when they interact with government or use public services.

Unless public services can adapt to these new expectations, the ability to sustain a consensus for the provision of public services free at the point of use may prove impossible in the long term.

Business, of course, has been at the forefront of shaping this ‘new world’. But those forces equally challenge us.

How, for example, does business reform its governance in a way that inspires the trust and confidence of investors and is accountable to employees and the wider public?  How should businesses respond to the opportunities of the global market and new technology, both of which are producing a revolution in the way the business operates?

Let me give you just one example of how these global pressures are influencing business today.

Thirty years ago, businesses could almost entirely rely upon product cycles that lasted for three to five years and business models that could last a decade.  The great companies of the last century created products and refined their supply chains over decades. And they based their business models on relatively stable markets, high barriers to entry and a plentiful supply of relatively unskilled labour.

However many of the most successful companies today are those that have developed a capacity to reinvent themselves – not just once every ten years – but now every eighteen months or two years.

Businesses operate in a global competitive market.  They are challenged to create new value, improve productivity and respond to tomorrow’s customer needs – today.  That global competitive market ensures that today’s businesses simply cannot afford to wait five to ten years to develop a new product cycle or business model. For those companies and communities that are equal to the challenge, this relentless competitive pressure is creating new sources of wealth has increased standards of living.

Next week, I’ll be talking in more detail about innovation and why businesses might have an advantage over the public sector. In the meantime, if you enjoyed this post, I’d be very grateful if you’d help it spread by emailing it to a friend, or sharing it on Twitter or Facebook.  And if you are interested in public sector innovation you might be interested in another of my recent blogs where I wrote about how businesses learn from mistakes.

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.

The no stop checkout: what could be its impact?

With the launch of the concept store Amazon Go – where customers can walk out of the store with their chosen grocer items being automatically charged to their bank account – the age of the no stop checkout customer experience is emerging. But what could this mean for retailers if such an approach is adopted wholesale across the bricks and mortar shopping experience? Here are some ideas…

Implementation Challenge – from what insight has been shared about Amazon Go it is understood to have taken four years to develop this unique store experience that involved integrating a range of technologies such as machine learning, image recognition and mobile. The solution looks innovative but would it be feasible for a retailer to implement across potentially hundreds of its stores? Furthermore, what kind of ROI should a retailer expect from this substantive investment in cloud and physical digital capabilities?

Threat Of New Entrants – By removing checkouts means added convenience that could be exploited by existing or new competitors. For example; a disruptor could offer a platform service that compares the price of the same products across different local completing stores to enable a customer to “optimise their shopping basket”. This indirect competitor could then buy and deliver these items for a customer removing any direct engagement with the retailer.

New Forms Of Customer Experience – An opportunity and a challenge is that no stop checkouts eliminate a touch point directly with the customer physically within the store itself (even if that process is self service). The opportunity is that this enables retail staff to engage with customers in different, delightful ways such as product demonstrations or marketing promotional events – retail as an experiential destination. However, by removing this interaction also risks diluting further the unique experience of being in-store by making customers focus more on specific products and prices than the retailer’s brand.

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

Disruptive Technologies UK 2016

Recently, I had the opportunity to attend the Disruptive Technologies UK 2016 event in London and found it both interesting and thought-provoking.

The event was the first annual UK conference on disruptive innovation and included a combination of keynotes, workshops and networking sessions. Different speakers, from academia, industry and government institutions shared the stage and presented new ideas and theories.

The event revolved around the idea of fourth industrial revolution. In the last two hundred years, three industrial revolutions shaped the way we live and work. These revolutions have been initiated by major disruptive innovations, such as the introduction of steam power, electricity and IT systems.

Nowadays, we are on the verge of the fourth industrial revolution, characterised by cyber physical systems.

The emergence of cyber physical systems, thanks to big data, robotics, Internet of Things, drones and advanced biology, holds the potential to revolutionise the world as we know it.

The Government has already invested billions of pounds in Catapult centres and the Innovate UK agency. This funding aims to create the right business environment to nurture and sustain the numerous new commercial ventures in this area.

The morning session focused on how the fourth industrial revolution can disrupt buildings and shape the cities of the future. Smart cities are not only connected and highly technological cities, but they should be analysed using a wider, holistic approach.

Citizens should be at the centre and the aim must be to improve the quality of life.

Local councils are already embracing this revolution and for example Cambridgeshire developed an API from which businesses can use the data collected by the council. Smart buildings will be a fundamental block of the cities of the future and thus the traditional concept of buildings must be re-thought. The overall experience of living and working in predefined places will change and technology, along with new workforce management ways, will allow people to work from anywhere, at any time.

The afternoon kicked off with elevator pitches from different tech start-ups which are looking to solve problems around parking, product design, teleconferencing and passports on mobile devices. After, two case studies have been presented. The first on Tekcapital, a company who invests in University intellectual property and makes it accessible to private companies, and the second on Epicardio, an Oxford based startup which developed a real-time 3D simulation of Cardiac Electrophysiology and Electrocardiography, set to revolutionise academia and hospitals.

The next talk explored the concept of bitcoin and blockchain. The blockchain, the technology underpinning bitcoin, carries many expectations on how it will impact the financial industry. However, many barriers, such as the lack of national and international regulatory frameworks, along with the lack of technical skills, are slowing its integration in our society. Another barrier to bitcoin becoming mainstream is the vast amount of energy required to power the pools of computers used to mine bitcoins.

The day was wrapped up by two final talks on financial inclusion and on how to holistically look at the technological landscape and not pick a particular innovation as the only “winner”.

The ideas shown and the great panel of speakers effectively conveyed the significant opportunities that the fourth industrial revolution carries, impacting businesses, people and government.

Disruption can only happen if people and communities are buying into the benefits that technological advancement can bring

For this happen, a change in thinking is required, starting to ask why instead of the how.

If you want to know more about some of the technology trends disrupting our future, why not read what we have to say about the digital horizon and smart cities or contact me by email.

Is Blockchain in the MASH for Local Government?

In their latest insight briefing, SOCITM pose the question, Blockchain technology: could it transform digital-enabled councils?

They urge councils and wider public sector authorities to follow developments around blockchain Distributed Ledger technologies with a view to experimenting with their potential use in the development of future service transformation plans.

It is safe to say that blockchain is currently one of the hot technology topics trying to establish itself as a new way of handling trusted transactions. The rise and publicity surrounding BitCoin has driven this current hype and whilst the underlying technology of blockchain is very appropriate for financial-based systems, it is still unclear what viable (and practical) uses there will be across other sectors.

UK Government has issued a number of articles and papers regarding this topic, and they are actively investigating the potential of the technology to support a number of public-facing services. But the challenge is: ‘what is the use case that can exploit the capabilities of blockchain?’.

As an organisation, Sopra Steria sees the potential of this technology to provide immutable chain of evidence based systems and we are actively working on a number of potential use cases across a number of sectors.

The opportunities for Local Government need further investigation to consider how blockchain could be used to improve services, reduce costs, or help tackle fraud. As the SOCITM article suggests, these opportunities have yet to be clearly defined and articulated. Whilst G-Cloud 8 now shows services related to blockchain, there are only two of any real substance – one from a leading provider of blockchain Distributed Ledger Technologies, and the second a consultative service on what, and how, to use blockchain.  The others simply make reference to blockchain – so there is still a substantial way to go before there are pre-defined services available for Local Government.

Should Local Government be investigating the opportunities for blockchain/Distributed Ledger technology?  Absolutely!

There are a number of potential areas where the ability of providing chain of evidence based capabilities could be used, but the challenge for Local Government is to define the business and application processes needed to use blockchain. One of the areas in which we see major opportunities is the ability of coordinating MASH (Multi-Agency Safeguarding Hubs) by providing a means of identifying master records across different agencies. The ability of establishing a clear data level trust relationship is going to be critical to delivering successful MASH services.

Sopra Steria supports SOCITM’s call to identify the appropriate uses and applications of blockchain which will stand the test of time. As an integral part of their design process, councils should now be considering the advantages of using both blockchain, and other emerging technologies, when shaping future transformation programmes.

Take a look at our paper, “Blockchain: harnessing the power of distributed ledgers”, earlier posts on this topic on our blog or leave your thoughts on this subject below.

Blockchain – survival of the fittest

Recently, I took part in a discussion on blockchain broadcast by Digital Leader’s DLTV team. Guided superbly by the BBC’s Kate Russell, myself and three others (Maja Zehavi, Anish Mohammed and John Bertrand) wandered through the latest thinking and future possibilities of the world of distributed ledgers.

And it left me with something really quite striking.

Blockchain is complicated – we know that. It relies on a vocabulary that includes sophisticated cryptographic terminology and brain-aching concepts around decentralised consensus models. And yet, the principles are beguilingly simple. Aside from the complexity of the solution, the concept of everyone involved in a transaction having open, trusted access to a distributed ledger is something that a rapidly expanding community are eagerly pursuing.

And it’s the speed at which this community is collaborating that is so striking. We are at very early days in the development of this technology. (Never mind the applications, many of the core protocols are still being debated.) Despite its formative state, research and development around blockchain is distinctively collaborative, with start-ups, big business, regulators and academia all openly sharing knowledge about what works and what doesn’t.

In the programme, one of my co-speakers, Anish described this as being ‘Evolutionary’, in a Darwinian sense. Progress is being made through collaborative experimentation and a form of natural selection that enables progress to be made at speed through ‘generations’ of iteration.

It’s an approach that reflects our digital times. The value of knowledge is now ephemeral. It’s the application of knowledge that is key. The accessibility of digital technology – be it blockchain or otherwise – invites us to develop new use cases, test solutions and refine them. Openly. Collaboratively. And rapidly.

And in the end the fittest ideas survive. ‘Distributed Digital Darwinism’ in action courtesy of the blockchain.

Why not watch the episode on YouTube? and read our latest thought leadership paper “Blockchain: Harnessing the Power of Distributed Ledgers”.

Sopra Steria is proud to support Digital Leaders – helping to organise and host digital salons for Digital Leaders Scotland and Digital Leaders Northern Ireland. Learn more about Digital Leaders.

What are your thoughts about blockchain? Leave a replay below or contact me by email.

What will be disrupting our world in the next 3 – 5 years?

In 2015, we used this blog forum to talk about how our future digital business world is being shaped by some key technologies, what impact they are having and the resulting societal challenges they are bringing about. You may have listened to the podcasts from ‘Aurora’, Sopra Steria’s horizon scanning team that discussed digital automation and human augmentation.

In 2016, we are broadening our research and focusing on three areas of disruptive technology and the effect they have on us as individuals, the world of work and the planet as a whole. We are even more fascinated by where these stories interconnect, as shown on the matrix below:

(See end for text description of this image
Aurora horizon scanning: our six areas of research in 2016

Listen to our first podcast of 2016 where we describe the approach for our research and an insight into areas that we are interested in – and getting excited about!

We are hoping to include guest speakers for our future podcasts, so let us know your ideas for them and thoughts about our areas of research for 2016.

Leave a reply below or contact us by email.

Don’t forget to follow the team on Twitter:

@timdifford
@richpotter_
@ben_innovates

And enjoy our Flipboard magazine on iOS, Android and Windows devices.


Description of Aurora’s six areas of research in 2016

  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. The connected planet: a crowded, ageing, more connected and fluid world
  4. Intelligent insight and automation: the increase in the application of prescriptive analytics and automation to augment or displace human activity
  5. Ubiquitous interaction: the growth of sensing and interface technologies that make interactions between humans and computers more fluid, intuitive and pervasive
  6. Distributed disruption: the growth of decentralised processes enabled by the adoption of technologies which assure and automate security and trust