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ANALYTICS AT THE EDGE GAVIN STEPHENSON

09 NAVIGATING THE JOURNEY TO MODERNISATION FERNANDO LUCINI

THE AI LAYER: BUILDS NEW APTITUDE13 AI IS THE FUTURE OF CUSTOMER

EXPERIENCE CONOR MCGOVERN

17 NBA 2.0 NINA FERTACZ

THE DX LAYER: OPENS NEW DIALOGUE21 A WHOLE NEW PERSPECTIVE

ADAM NAGUS

25 BRINGING INSIGHT TO LIFE WITH VISUALISATION NICK MILLMAN

ACCENTURE ANALYTICS: THE POWER OF THE NEW29 SUMMARY

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Digital consumers demanding betterAnother force driving the emergence of the Intelligent Business comes from the end-users of technology. Whether consumers or employees, they have come to expect and demand, thanks to the digital native providers, a consistently excellent digital experience. Anything that falls short is ignored or discarded.

Behind all this, there’s a vital enabling resource. Data, in huge and surging quantities. In the past, companies might have struggled to realise the promise of analytics because of a scarcity of relevant data. That was then. Now, every business has access to more information than they know what to do with. After all, very little happens in the world that isn’t captured and stored digitally.

Starting the journeyThis means every business has the potential to become an intelligent business. So how to get there? A digital roadmap is the non-negotiable starting point. Of course, it’s not a journey with a final destination, and it needs continuous leadership commitment. But the objectives never change: embedding data and analytics everywhere, available to everyone, to drive every business decision.

To deliver against these objectives, the Intelligent Business has three layers. Each of them provides complementary capabilities that, while valuable in their own right, will collectively transform how people work and the outcomes the business achieves:

1. The Data & Comprehension Layer – an agile ecosystem, creating new perspectives and unlocking new value by finding, exposing and exploiting data

This provides new ways to sense, interpret and augment data…within and beyond the enterprise, structured and unstructured. Harnessing the power of the new – IoT, drones, connected platforms, embedded sensors – along with core capabilities for managing and integrating data sets, the Data & Comprehension Layer opens up a new world of value.

2. The AI Layer – building new aptitude for acting, learning and optimising, at unimagined speed and scale

Once organisations have marshalled this wealth of data, they can understand it and access even more value by adding intelligence through AI. In all its forms, it offers extraordinary possibilities for new ways to sense, comprehend, act, learn and optimise. The ability to move quickly and innovate continuously is vital in the face of an ever more impulsive and volatile customer base, and a crowded and dynamic digital marketplace. The only way to do this is with people augmented by AI.

3. The DX (Data Experience) Layer – opening new dialogues through human-centred technology design

There’s an exciting culture emerging. People are no longer adapting to technology. The opposite is becoming the norm. User interfaces, like chatbots, voice recognition and response, and augmented and virtual reality, are giving people new ways to access intelligence, collaborate and work. And as this happens, these technologies are not only making life easier and more rewarding within the enterprise, they’re also becoming the public (inter)face of the organisation.

Based on our research and interactions with C-suites and thought leaders around the world, we’ve identified the technologies and capabilities that are at the heart of the Intelligent Business. You can read about them here end-to-end. Or draw out individual articles as conversation starters. Whatever you do, we hope you’ll find plenty of food for thought here. We look forward to discussing your intelligent business agenda.

BUSINESSES DON’T NEED A DIGITAL STRATEGY. THEY NEED TO BE DIGITAL AT THE COREA new breed of business is already out there. These organisations have embedded data and technology in everything they do and at every stage of the value chain. And they’re getting amazing results. Why? Because they’re constantly unlocking new information and intelligence that keeps them ahead of the game.

Born-digital businesses like Netflix, Amazon, Google and Baidu have never had a digital strategy. Their strategy is digital. It’s a crucial distinction. These companies have completely internalised the power of data and technology. What does that give them? Two core strengths: they can meet – and predict – new liquid customer expectations, in real time. And they consistently meet or exceed shareholder expectations for agility, efficiency and continuous reinvention.

Intelligent business: the time is nowThese are intelligent businesses. And they’re the model that all other organisations will follow. There are a number of powerful forces behind this imperative. The first is the breath-taking speed of technology change. This is powered simultaneously by enormous increases in processing power and rapidly declining technology costs.

The compounded doubling effect of Moore’s Law has reached a point of inflection in recent years which is giving rise to breath-taking advances in computing power every year. And that’s setting the stage for the 'Second Machine Age'1, one in which new technologies like artificial intelligence (AI), machine learning, virtual reality, augmented reality and hugely powerful analytics engines are not just feasible, but increasingly ubiquitous. At the same time, ever-lower barriers to entry in all industries – thanks to the advances like the cloud, and rapidly declining technology costs – mean that new competition can come from anywhere at any time, forcing the pace of innovation.

1 Source: The Second Machine Age by Andrew McAfee and Erik Brynjolfsson – http://secondmachineage.com0403

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Ray Eitel-Porter Managing Director, Accenture Analytics@RayEitelPorter

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Today, everybody knows about the Internet of Things (IoT) – or at least they think they do. It’s a vast digital network connecting everything and everybody, ranging from consumers in sensor-rich environments to enterprises tapping into expanding streams of data from devices, machinery and software 'bots'. All of this puts the IoT at the heart of the Intelligent Business, as the core of its Data & Comprehension Layer.

But to generate real insights and value from its wealth of data, the Intelligent Business needs to augment the IoT with something else. That extra ingredient is analytics – and its increasing application with robotics, machine learning and cognitive computing.

Why is analytics key to realising the value of the IoT? Because, while the IoT is a vitally important source of data in vast and ever-expanding quantities, it doesn’t in itself have the intelligence to differentiate signal from noise, insight from data, action from reaction.

The journey to analytics-enabled decision-makingOver recent years, as the IoT has become increasingly pervasive, growing numbers of businesses have started to understand the powerful combination effect with analytics, and that a connected digital platform derives value far greater than the sum of its parts. While the core focus of the earliest IoT projects tended towards streaming data and device connectivity, companies have increasingly moved to apply analytical techniques and intelligence to extend IoT principles – enabling them to elevate the speed and accuracy of their consumer experience, enterprise decision-making and tailored propositions.

This is where the 'connected platform' comes to life. Extending the IoT into the world of analytics platforms and capabilities means organisations don’t just get access to the data, but can also draw out critical insights, real time, that can be deployed wherever they’ll produce the greatest value. The result is embedded throughout the business value chain in a way that was previously inconceivable.

IOT + ANALYTICS + CLOUD = A NEW WORLD OF INSIGHT

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Gavin Stephenson Managing Director, Accenture Analytics

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Leveraging cloud to expand the benefitsThat alone sounds transformational. But there’s more. Add cloud computing to analytics and IoT, and the vistas of opportunity multiply. With cloud’s scalability and pay-per-use model, old cost challenges around IoT data ingestion and storage fall away. And by integrating cloud with IoT and analytics to create innovative solutions, organisations can truly transform how they do business.

Increasingly, these solutions draw on data collected in the cloud and from the myriad of devices and sensors 'on the edge' of the organisation. To harness these data sources, organisations need a finely tuned data supply chain that can mobilise data quickly and continually for analysis and consumption.

This flow of data forms the basis for a robust analytical platform supporting sensor-driven computing, industrial analytics and intelligent machine applications – the fabric of which is woven together through automation, machine learning and cognitive computing. What’s more, applying analytics to data ‘on the edge’ dramatically improves efficiency by eliminating the latency and redundancies of traditional centralised data models. To harness this data, organisations need a modern data supply chain to quickly mobilise data for consumption.

Turning the potential into valueSo, when and where will all this become reality? It already is. Accenture’s digital offerings combine leading cloud-based analytics with IoT streams in a single integrated platform that can generate actionable insights in weeks rather than months, and make them available on the front line in every area of the business.

And clients are reaping the benefits. By way of example, take the leading insurance company that’s increased its fraudulent claim detection rate by 8%. And the multinational energy corporation that’s realised a 30% improvement in the accuracy of its forecasts.

Or the Asia-based products manufacturer that’s using IoT-connected drones, mobile and advanced analytics techniques to automate its supply chain, gain real-time visibility over distribution of capital and optimise decision-making.

That’s the level of insight connected platforms enable the Intelligent Business to achieve. Imagine what it could do for your organisation.

" Accenture’s digital offerings can generate actionable insights in weeks rather than months."

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Fernando LuciniManaging Director, Accenture Analytics @FernandoLucini

Until now, most companies have been more focused on collecting lots of data than on generating insight from it. As a result, the balance between information and intelligence has been out of kilter. The Intelligent Business redresses it – by thinking more about the value of its insight than the volume of its data.

This means asking at every point in the business how insight generated from data can enable it to do things better, faster, cheaper and more responsively to customers’ needs. And then, once it’s answered that question, positively acting on it.

However, operating in this way is made harder by the way most companies are set up. So making the pivot from a data-driven to insight-driven business demands a transformational change in the way the organisation is structured and operates. And that’s the modernisation we’re all journeying towards.

A handful of businesses have successfully passed this turning point already. These organisations come from many sectors – they don’t just include the internet giants that people usually highlight as digital leaders. And they’re all showing us the way forward to a more intelligent future.

Inextricably linking designers and customersSo, what businesses are we talking about here? By way of example, take the retail industry.

When we walk into a store these days, we’re faced with more targeted products than ever before. This can only be achieved through analysis of a wide variety of data that covers elements including our own wishes and desires, the views of experts, what’s happening in the world around us, and much more. Leading retailers use the resulting insights to drive our experience in their stores, by creating an inextricable link between what their designers create and what their customers buy or recommend to others.

These businesses are also agile, enabling the entire end-to-end process – analysis, design, manufacturing and distribution – to happen as quickly as is needed, without being tied to traditional seasonal cycles. And based on their customer insight, they can execute the design and manufacturing in as close to real time as possible, producing small batches at pace to match the diversity and speed of consumers’ changing preferences.

This operating model is engineered from the ground up to deliver against retailers’ core business objectives, which – for much of the industry – are selling at full price, avoiding markdowns, and minimising inventory. Analytics helps achieve these goals by enabling stock to be replenished just-in-time, and constantly keeping offers fresh and relevant to customers. This is the winning formula adopted by the leaders in the industry – and it embodies the key attributes of the Intelligent Business.

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Four steps along the wayWhat are those attributes? When you look closely at intelligent businesses in any sector, you’ll find they all share some common traits in terms of their data platforms and modernisation journey. Our experience points to four main commonalities:

1. Embracing hybrid data models Intelligent businesses take advantage of falling

storage and computing prices by continually seeking out the most cost-effective place to store or process data, in the most suitable combination of cloud and on-premises systems. This approach leads not only to a hybrid cloud solution, but also to the creation of an integrated ecosystem that combines loosely coupled technologies in the most economical way. These technologies are governed and managed together to maximise business opportunity while reducing risk.

2. Implementing a data-driven operating model Linking insights and decisions explicitly to

outcomes, a data-driven operating model consists of the foundational practices, processes and skills that support and enable a modern, diverse, loosely coupled, flexible and scalable analytics business. And it’s tightly governed to preserve the end-to-end integrity and alignment of the business, its products and its customers.

3. Adopting a continuous delivery lifecycle Until you look into your data, you don’t

know how valuable it is – so a modern data platform uses flexible data discovery techniques. It’s also highly agile, responding rapidly to changing conditions and creating prototypes quickly before building anything that goes into the live production environment. Development is iterative and uses automation to scale up quickly.

4. Converting data to business insight Success in creating new products and services

in the digital age is linked to strategic access to data – including 'dark' data that has previously been out of reach. Digital platforms can now exploit light and dark data in flexible, wide-reaching and innovative ways to drive insights, in turn powering the creation of precisely those products and services that customers want – and will pay a premium for.

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AI IS THE FUTURE OF

Conor McGovernManaging Director, Accenture Analytics @cbm1001

There’s no doubt that customer experience is absolutely essential for brand survival. AI and analytics will increasingly be deployed not simply to support the customer experience but, more often, as the principal means to deliver it. That makes trust and transparency every bit as important as technology to achieve success.

So what are the components of customer experience? Personalisation is one key element. But there’s been a tendency to see personalisation in terms of the value and advantage brands accrue from exploiting ever-more granular customer data in real time. Instead the focus needs to be on what personalisation means for the consumer.

And some more forward-thinking brands are starting to do just that. They’re looking at their relationships with customers and their data in a new way. Mindful of the need to earn and retain digital trust, these brands are being more open and transparent with consumers. For example, some are enabling their customers to see all the data that is held about them, modify it and control how their interactions with the brand should take place.

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Fair value exchangeA more open and transparent relationship with the customer and the concept of fair value exchange sit at the heart of the customer experience in the digital era. When this is done right, consumers are willing to open up and share more, because they recognise the value that they receive and have a degree of control over how brand interactions take place.

Many of those interactions are now being managed by artificial intelligence, machine learning, chatbots and virtual assistants. As more of the consumer experience of a brand is driven by AI, the importance of fair value becomes even more important. And it’s a crucial component underpinning the ability to build ‘living brands’ that adapt and evolve with every consumer interaction – a powerful potential source of competitive differentiation.

AI becomes the face of the brand Some of the leading digital businesses are already securing significant advances on their use of AI for everyday dealings with the consumer. It’s likely that in just a few years’ time, most interactions will not require the use of a keyboard, but will instead be based on voice, gesture and augmented or virtual reality interactions. And as screen time declines, the ability to ‘own’ an interface will become both a critical goal and a potential source of disruption.

Of course, using AI interfaces as the primary source of interaction and a key source of data needs to strike a balance between offering ‘cool’ features consumers value and safeguarding against ‘creepy’ intrusions which turn customers off. That, again, reinforces the need to give consumers a degree of control that goes beyond simply setting channel preferences, to provide a much deeper understanding of how and when communications take place. That means rather than ‘real time’, ‘right time’ becomes the key attribute consumers appreciate and respond to.

Moving forwardSo what do organisations need to think about to progress with integrating AI as their spokesperson and first point of contact with the customer?

• The right operating model and governance: Pervasive use of AI to support the customer experience requires a radically different approach to operating models, processes and governance. Entrusting customer data to analytics, machine learning and AI requires the right kind of robust capabilities and controls.

• Evolving the data supply chain: AI, machine learning and analytics as the drivers of the customer experience rests on having enormous amounts of data. That data can be internal, external, structured, unstructured from right across the value chain, and augmented from other sources. In addition, overlaid on this is ‘derived data’ and consumer insight. Making all this work together depends on a sophisticated and evolving data supply chain to feed the AI.

• Keeping pace with technology change: The sophistication of analytics, AI and machine learning is increasing exponentially. Techniques are in play today that literally did not exist a few months ago. So making the right choices of technology and solutions that can keep pace with that rate of change is challenging but essential.

• People and machines working in tandem: Tools and techniques need to be augmented with people. There’s a need for human intervention and control to support AI and its adoption within the enterprise as it supports customer experience. It’s critical to constantly test and learn and develop in an agile way to keep step with the lightning-fast pace of change.

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INTELLIGENT DECISIONING AT DIGITAL SPEED

Nina FertaczSenior Manager, Accenture Analytics @Ninuusha

In the digital era, customers expect the services, experiences, content and information they receive to be, above all, relevant. If they don’t get that from providers, they’ll move on to someone else. And it’s never been easier to find alternatives. Constant relevance is a key attribute of the Intelligent Business.

There’s a cultural shift in play across all industries that’s raising consumer expectations for best-in-class experience. Meeting those ‘liquid’ expectations calls for seamless, contextual, tailored services that suit customers’ needs at any given point in time and across every channel.

When Next Best Action (NBA) was first used, it was largely aimed at retaining customers and was executed via a single in-bound channel (e.g. call centres). It then quickly evolved to include additional opportunities like ‘Next Best Product’ via upselling and cross-selling. For example, when a customer called in, depending on their call reason and context, they would be given a different offer – whether that was retention or a new product at a different price point.

Now NBA is evolving even further. It’s becoming an essential capability for all industries to deliver experiences that are always relevant, highly personal and designed to engage customers – and keep them engaged. It’s what we call NBA 2.0.

From prediction to prescriptionThe key to NBA 2.0 is data. And lots of it. Instead of collecting data from a narrow range of channels, NBA 2.0 leverages customer information from multiple sources, using unstructured and structured data, trawling social media and networks as well as traditional sources such as customer demographics, product holdings and interactions.

NBA 2.0 also applies more advanced analytics techniques to harness the depth and breadth of this data. Using machine learning and text mining, it moves from predictive to prescriptive analysis. Rather than simply predicting what customers might like next, NBA 2.0 prescribes the best action for a customer in the form of an offer or message that optimises the company’s objectives (e.g. customer long-term value or engagement scores).

Operating across the proliferation of touchpoints and channels to reach and engage with customers, NBA 2.0 guides and informs customers, helping them to discover relevant new experiences that they value and wouldn’t find on their own. It moves away from next best offer or product to experience-focused design.

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Leaders are already showing what’s possible. Take Netflix, for example. Its recommendation engines constantly generate appealing new choices for its customers. But as well as providing individuals with suggestions, Netflix also uses customer data and analytics to inform its content creation strategy. And it’s proving highly successful. Viewing figures and awards testify to that.

Putting data to work: technology and peopleThe ability to gather and operationalise the vast and growing amount of data that’s required to support NBA 2.0 defies traditional approaches. A big data platform is critical. And that, in turn, means taking advantage of the scalability and flexibility that the cloud affords. Artificial intelligence, in the form of machine-learning tools, is essential to handle substantial volumes of data at scale and speed.

Technology is part of the solution. But it’s not by any means the whole story. An operating model built to meet the needs of constant innovation and change is vital. Agile working and a commitment to testing and learning are key features of the model. Teams that can blend business and technology know-how are needed to act on new insights and maintain the pace of discovery to keep customer experiences fresh and vibrant.

Moving forwardNBA 2.0 is a significant transformation. So how should businesses get started? The key is to start small and scale. Companies need to:

• Experiment: Encourage and nurture a culture of experimentation. Develop proofs of concept, get the business excited about the potential outcomes and then move forward at scale.

• Assemble technology and strong analytics capabilities: Develop analytics models and introduce machine learning. Create a big data platform and put a customer analytics record at the centre of decision-making. Ensure that there’s a well-organised data pipeline including batch, streaming, internal and external data.

• Source the right talent: The skills and talent needed for NBA 2.0 include campaign analysts, visual analytics experts, data scientists and data engineers. DevOps, and user interface and experience specialists are essential as well.

• Test and learn: Start small and scale fast. Create a dedicated incubation team to explore data and scale up results rapidly. Apply machine learning as an overlay to existing models, helping move them from predictive to prescriptive models and driving constant optimisation. Test new and existing models simultaneously in the cloud and migrate new functionalities over time.

" Technology is part of the solution. But it’s not by any means the whole story. An operating model built to meet the needs of constant innovation and change is vital."

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Adam NagusPrincipal Director, Accenture Analytics @ScubaDam

Intelligent businesses extend human capabilities, embedding data and technology across the enterprise to empower all their people to lead in the new. This includes establishing new ways to access, collaborate and connect.

Connecting is no longer enough. By making data more accessible and easier to understand, intelligent businesses open new ways for their people to access intelligence, collaborate and work. It’s where the immersive experiences offered by augmented reality (AR) and virtual reality (VR) can make an enormous impact.

AR and VR are evolving rapidly. Not long ago, they were the preserve of gamers. Now we’re seeing a surge of interest from businesses, with new applications being developed all the time. From training and field-service solutions to digital dashboards, virtual showrooms and interactive design labs, AR and VR are establishing themselves as natural extensions of business strategies with digital at the core.

Blurring the boundaries between digital and physicalSo, what do these technologies do? Broadly speaking, AR and VR blend digital experiences into real life. Built around natural methods of interaction, including gesture and gaze, they help users exchange data and carry out complex tasks.

AR adds digital context to physical locations, superimposing computer-generated images and information onto real-world perspectives. Smart glass, where holograms are projected onto a transparent visor, is a great example.

VR creates environments that don’t physically exist. These range from non-interactive environments where users can look around, without actually moving or picking things up, through to high-end, truly interactive experiences like the ones provided by Oculus Rift, HTC VIVE and PlayStation VR.

AR AND VR TRANSFORM HOW PEOPLE INTERACT WITH DATA

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Straight to the heart of the actionIn 2016, Accenture developed an immersive experience for the RBS 6 Nations on the Oculus Rift platform. We brought in well-known rugby personalities, like ex-England international and 2003 Rugby World Cup winner Ben Kay, to help create a storyline and interactions combining real-world rugby locations and virtual worlds.

A combination of scanning technology to capture the behind-the-scenes areas of the RBS 6 Nations key stadia, and a virtual representation of the stadium itself, transported users straight to the heart of the action.

For 2017, we’ve taken this even further. Users don’t just see this virtual world, they interact with it. This includes testing out intuitive ways of accessing analytics and data from platforms like Qlik Sense: by tossing a ball to a player, users can interact with him and see the statistics and metrics linked to that individual’s team and position.

Putting AR and VR to workRBS 6 Nations is a great demonstration of what’s already possible with VR. And this technology is growing in sophistication all the time. We’re seeing leaders using it to create totally new ways to build, sell and service their products.

Examples abound. Companies are using mixed reality to provide hands-on training that would otherwise be costly and time-consuming, to replicate maintenance and repair scenarios, and to support tasks like structural repairs in dangerous and difficult environments.

Use cases in different industries include:

• Media, entertainment and travel companies helping customers envision future trips… or travel back in time.

• Construction and design firms presenting how finished structures could look and feel, letting customers take virtual walk-throughs of buildings/experiences that haven’t been built yet.

• Utilities and telcos using AR-driven data overlays to help field-service technicians carry out maintenance and repair tasks.

• Car manufacturers using AR/VR to create virtual models of cars and collaborate on design changes, as well as giving customers augmented reality brochures.

• Manufacturing businesses using digital overlays to display equipment health to plant managers.

Into the futureIn an enterprise context, AR and VR are not standalone technologies. They’re part of a broader solution, supporting the new breed of business that embeds data and technology across the value chain.

How to get started? In an incredibly fast-changing marketplace, companies must see through the AR/VR hype to the massive potential beyond. VR and AR can be UI and UX designers’ ultimate tools. They can also be their downfall. There are vast numbers of options available in this interactive 3D world, where even the laws of physics can be bent. Selecting the best ones for the job in hand is essential.

The first step is to carefully evaluate and identify processes that could be enhanced by these technologies. Next, develop a use-case that’s practicable to prototype. Then design experiences that make maximum use of immersion, create business-focused goals and use analytics to track results.

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Picture the scene. You’ve applied analytics to unlock new intelligence across your business – creating deeper insights to drive better decisions, new behaviours and higher value. But you know that what really drives value is not insights, but concrete actions taken in response. So how do you make this final step to action as fast and easy as possible for your people?

To answer this question, think how the expectations of today’s information users have changed. In the digital world, the pressure to act at pace is unrelenting. And people expect their sources of information to reflect this pressure – enabling them to find, absorb and act on relevant, insightful intelligence faster than ever before.

Secondly, we’re all familiar with using (mostly) intuitive apps to perform everyday activities in our personal lives, like checking a bank balance or getting a taxi. This raises our expectation levels around how we consume information at work. Very few of us want to spend time scrutinising pivot tables or combing through weighty BI reports to track down the key information we need to do our jobs more effectively. Instead, we want and expect to be guided to the right insights.

MAKING THE PROGRESSION FROM INTELLIGENCE TO ACTION FAST, EASY AND INTUITIVE

Nick MillmanManaging Director, Accenture Analytics @MillmanNick

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" This means fewer decisions made on the basis of gut-feel, and more based on hard, verifiable business insight."

Putting insight front and centreThis is where visualisation comes in. By presenting insights from data in an easily accessible pictorial or graphical format, it plays an essential role in the Intelligent Business, helping decision-makers grasp what needs to be done instantaneously and with minimal effort or technical training. It does this by putting the key intelligence front and centre, making it obvious to the user rather than hiding it away in lines of data output.

As well as boosting speed for users of information, this capability also drives value for the organisations they work for, by escalating and accelerating the adoption of data-driven decision-making across the workforce. This means fewer decisions made on the basis of gut-feel, and more based on hard, verifiable business insight.

Catching the user’s eyeTaking all these benefits together, the question about implementing visualisation in the Intelligent Business is not whether – but how? The key here is that delivering visualised analytic insights in a way that’s effective and engaging for human users demands a knowledge of much more than analytics alone. Also required is a deep understanding of user experience and people-centric design thinking.

By integrating all these areas of expertise in multi-skilled teams, we’ve come up with a methodology we call ‘design-led analytics’. It combines the ability to generate key business insights with expertise in optimising the positioning of those insights on a screen – whether that be smartphone, tablet or PC – to catch the user’s eye and maximise the impact on decisions. The benefits can be increased

further still by linking the visualisation to the outputs from predictive models – a type of solution for which the Accenture Insights Platform (AIP) Design Studio is seeing growing demand from clients.

Adopting a continuous delivery lifecycle Along with design-led analytics, the other key factor in making effective visualisation happen is a delivery approach based on agile techniques. This is a further cross-over into the broader digital world – leveraging the delivery models that would typically be used to build an eCommerce website, for example.

The benefits of adopting these agile delivery models are shorter elapsed times to get an initial minimum viable product released to the users, and far greater responsiveness to changing needs than is possible with traditional waterfall release cycles.

This agility can even extend to adopting DevOps principles. Imagine having Development and Operations teams working together, complemented by a suite of tools and processes for managing a configurable code base, to produce a new production-ready version of a visualisation application on a daily basis. This might seem too good to be true – but it’s precisely what we’re now doing for a major global pharmaceutical company.

Given the scale and range of benefits that visualisation delivers, we think it’s inevitable that it will ultimately become the new normal for presenting data-driven insights to users. Put simply, one day all information will be delivered this way. And the sooner organisations embrace this visualised future, the bigger their competitive advantage will be.

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THE POWER OF THE NEW

Our offerings are asset powered:

• Accenture Insights Platform (AIP): Comprehensive, pre-configured end-to-end solutions are comprised of an integrated suite of leading technologies that can be rapidly provisioned to generate actionable insights within weeks.

• Design Studio: AIP hosts a portfolio of 90+ advanced analytics applications and an integrated design–build–run studio environment that enables the agile development of industry and function-specific solutions.

• Robust industry and function offerings: We have a broad portfolio of function and industry-specific analytics offerings that cover the entire business analytics services stack.

We have a deep talent bench with over 36,000 digital professionals, including more than 1,300 data scientists, and unique relationships with academic organisations such as the Accenture and MIT Alliance in Business Analytics in the U.S. and our alliance with a leading European business school, ESSEC.

We put analytics innovation at the heart, with more than 23 Accenture Innovation Centres, including five focused on advanced analytics, where we innovate and incubate business solutions using AI and machine learning that can be applied now.

Accenture has an extensive network of alliance relationships with 100+ technology market leaders.

We’re famous for delivery: The scale and scope of our Global Delivery Network are unmatched in the marketplace, and deliver innovative, high-quality, industry-specific solutions for our clients.

ACCENTURE ANALYTICS:

BUILDING TOMORROW’S INTELLIGENT BUSINESS…TODAY

UNIQUELY QUALIFIED

FOCUS ON BEING THE DISRUPTOR, NOT THE DISRUPTED

To meet new customer and shareholder expectations, businesses must free up capital and capture decisive advantage from new digital technologies. It’s where the power of analytics is so critical – enabling approaches that can identify and extract previously hidden or unreachable economic potential.

A new breed of business is arising. These businesses embed data and technology throughout the operating model, providing the intelligence that they need to unlock this hidden value. These intelligent businesses have more than a digital strategy. They are digital to the core.

Through Accenture Digital, we combine our capabilities in interactive, mobility and analytics to help our clients provide better experiences for the customers they serve, create new products and business models and unlock new intelligence – that empowers people to do things differently, and do different things.

We help organisations focus on being the disruptor, not the disrupted: growing and transforming their core businesses to drive up investment capacity so they can pivot to the new.

To find out how we’re making this happen today, visit accenture.com/intelligentagenda.

As an analytics authority, technology powerhouse and creative agency with an established innovation architecture, Accenture is uniquely qualified to power the development of the Intelligent Business.

Our strengths come together to deliver intelligent, industry-specific solutions that create new perspectives, build new aptitudes and open dialogues to unlock new outcomes and business models.

Our differentiators Accenture Analytics is a recognised industry leader in business analytics, including a leader in the Gartner Magic Quadrant.

Our view of analytics is uniquely tied to industry: Our clients span the full range of industries around the world. With expertise in more than 40 industries across 19 industry groups.

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About Accenture Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialised skills across more than 40 industries and all business functions – underpinned by the world’s largest delivery network – Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With more than 394,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at www.accenture.com.

About Accenture Digital Accenture Digital, comprised of Accenture Analytics, Accenture Interactive and Accenture Mobility, offers a comprehensive portfolio of business and technology services across digital marketing, mobility and analytics. From developing digital strategies to implementing digital technologies and running digital processes on their behalf, Accenture Digital helps clients leverage connected and mobile devices; extract insights from data using analytics; and enrich end-customer experiences and interactions, delivering tangible results from the virtual world and driving growth. To learn more about Accenture Digital, follow us @AccentureDigiUK and visit www.accenture.com/digital.

About Accenture Analytics Accenture Analytics, part of Accenture Digital, helps clients to use analytics and artificial intelligence to drive actionable insights, at scale. Accenture Analytics applies sophisticated algorithms, data engineering and visualisation to extract business insights and help clients turn those insights into actions that drive tangible outcomes – to improve their performance and disrupt their markets. With deep industry and technical experience, Accenture Analytics provides services and solutions that include, but are not limited to: analytics-as-a-service through the Accenture Insights Platform, continuous intelligent security, machine learning, and IoT analytics. For more information, follow us @ISpeakAnalytics and visit www.accenture.com/analytics.