 I spent a number of years being the analytics advisor ten years ago for the health service in Ireland. My analytics was used to create beautiful slides. And they were never implemented or really implemented. We don't do that anymore. And I think the variety of the different speakers today really bring to life that need and that capability to action and deliver the data science insights that you create. Quite simply, if it's not going to change what your back office or your frontline do on a cold Tuesday afternoon, don't bother creating the insight. Simple as that. So, let's start to talk. We all know the impact that digital is happening on business world. And what we're seeing really is a shift as organisations move away from their traditional business to create a new business. Now, it's actually was interesting to hear in the Irish Times speaker earlier, as she talks about the shift to online and the shift to how their content is being presented. This is common across the board. Now, this provides a challenge for organisations because if you shift too quickly to your new business, there aren't enough revenue streams there. You're ahead of the market. You go bankrupt, you die. If you shift too slowly, then you become irrelevant, obsolete and you die. So, strategy now is around managing that pivot to whatever your new business and your new organisation is going to look like. And that applies across every single industry. So, what do you need to do to drive this forward? Firstly, you need to release all of the value that's in your existing business. One, to actually deliver against your commitments. Two, also to fund that shift. And that requires a new type of transformation to the core of your business so that you've got the platforms and datas and infrastructure to enable. Then, you need to scale the new. Wherever that new business is, you need to incubate it, grow it and manage that transition as that becomes your core. And then finally, you have to manage that wise pivot, that shift over to actually becoming the new business becomes your traditional. And then you need to reflect again. Look, I'm biased. I'm a data analytics geek. Analytics insights are at the heart of that transformation. The organisations that will win in this new world will be the ones that can develop the best insights from their customer and from across their enterprise and implement them at scale. And that's what I'm going to talk about today. And you can see, look, I'm a management consultant as well, so I have a 2x2 matrix, sorry. But effectively, you can see there on the 2x2. What are the quality of the insights you are creating? And how good are you at implementing them across the board on scale? The organisations that win that will be able to do both of those. I think I'm just to highlight again that pilot hell, the one where you're creating great insights. Because this is common, it's probably the worst place to be. I've been there. There's a great line from the CIO previously of the NHS who said she had more pilots than British Airways and really encouraged you to think about the infrastructure, the platforms, the capability you have to make that full shift. So let's go in a bit more detail there. Are you collecting that data across the board? Be it machine to machine? So there was a reference in the previous talk around the explosion of data so two quick stats. Over 50% of the world's data has been created in the last two years. The vast majority of that data is machine to machine. So how are you collecting that machine to machine, that customer, that unstructured, that structured, that external data? Two, do you have the platforms in place that are going to enable you to transform that? And then three, are you creating that insight? And as part of that then there's four components just want to quickly reference. Firstly, are you launching new platforms and services? Are you able to be that agile and move? Secondly, it was talked about earlier, that experimentation. Are you failing fast, test and learn and move on? From the top to the bottom, are you a data-led organisation? Do you have the governance in place, the organisation in place to enable that kind of delivery? Are your leaderships showing that they are data-led and the decisions that they make? Cos that drives a culture as well. And then also your business model. This fundamentally shifts the type of services that you can offer your clients. Are you thinking about the commercial structure that they actually offer to them and the business model for how you're going to deliver these services and change accordingly? So let's touch on some of those in a little bit more detail. Organisational here is key. It requires a new type of agile governance. We're working with a number of organisations in Ireland just now and helping them reflect about how they build analytics at scale and how they have the executive leadership in governance that directs that but doesn't slow it down. It requires you to strongly reflect about how you make decisions in your organisation, the type of capabilities you have there, the type of reporting lines and make sure that you have that agility and decision-making built in. New smart way of working. You know, different sets of skills. Great to hear the design, I think the parts called out. We are also seeing in data science and analytics a whole new set of career paths. Wonderful to enable and give that opportunity to individuals. And then working in an agile factor. Two week sprints, continual. Continual improvement and an ongoing assessment to improving move to ultimately what will be a new refined business model. And I think this is the key thing for me and actually why I come to work in Accenture. That needs to be able to deliver at scale. And I think just to illustrate that, I'm sure there'll be other illustrations later on. One of the things I like about Accenture is we have industrial-wide analytics platforms. So our water analytics platform is what drives Tim's waters operations. Be it for leakages, be it for predictive acid maintenance, be it for supply and demand prediction. We are doing some really interesting work in the digital plants. Island is number one in the world for high-value manufacturing. Much of that is down to bio-farmer life sciences. Barry Heavey is actually my colleague talking after this, I'll show you how we're using that digital plant to actually help those Irish businesses and the 50,000 jobs that depend on it continue to innovate and continue to be the best in the world. And then actually, both from the life sciences, pharma, co-vigilance and intelligent patient in the healthcare side, changing how health and life sciences work. The intelligent patient services is around cardiovascular patients and trying to stop patients being readmitted or admitted to hospital. And actually to highlight those two because they are two that were built in the dock and actually now industrialized across the world. So let's pick up a couple of other examples as well. So first I want to highlight this is a European insurer that we've been working with. I think this is an interesting example. And it's interesting because of the scale of the value that it's delivered, 15%. Roughly about 11 euro, 12 euro per policy. We are embedding analytics into the customer journey. We are going to a micro-segmentation of one. We are using optimization techniques at the portfolio level to confirm where their investment is going to be spent across different customers and fundamentally in changing that customer engagement for insurance. In an incredibly competitive market, that analytics is enabling a 15% improvement in the profit. Now I need to reflect on what I've been saying to you today as well about that new commercial model. In a world where we believe that the solutions we're talking about can deliver that type of value, I need to think about what new commercial models should my clients expect from me. And I think that's an interesting evolution that all of the analytic suppliers and platform organisations are thinking about as well. To give you another example, health claims. And I think I quite like this because it's four different aspects of it. So we process about 20 million health insurance claims a year. There's four things that we've been doing to it. Firstly, we've been using RPA. I actually don't like RPA plus some analytics to automate 520,000 cases. I'm actually a fan of RPA. The problem sometimes with RPA is the benefit of it is overstated. If you combine RPA though with artificial intelligence and advanced analytics, you can see significant value. Second thing is we're using machine learning to drive basically triaging those cases. This looks like a relatively easy case, but we can't yet automate it. Let's send it to our newbie team. This is a really complex case. And we think it's going to actually, there's going to be an appeal. Send it to our expert team and let's get it right first time. Third thing, and Dublin is our global centre for innovation for fraud as well. We have over 300 algorithms customised to find health insurance fraud. Health insurance fraud is primarily driven by white collar fraud. Let's be clear about it. I know in my own country there are a number of political parties that like to push the idea that health insurance is, you know, fraud is driven by health tourism or something like that. It's driven by healthcare professionals doing things they shouldn't be doing. So low volume, high value. Over these 300 algorithms that evolve over time as well and improve and expand, we've been able to save three billion across a variety of clients, including a client in Europe that I work with where we doubled the fraud yield that they were doing for the same number of investigations. And now we're also working with the doc to apply artificial intelligence, in particular looking at the detailed case notes to identify undiagnosed conditions that are in that detail. So, for example, we're helping find people that have got COPD, but it wasn't mentioned by the doctor. So how do we incorporate that insight into an ongoing management? The thing I also wanted to say is this is now the new normal. This is actually my favorite quote. What we are seeing now is the people in this room, the people that are seeing analytics data science as the career pathway we want to take are not tomorrow CIOs. They're tomorrow CEOs. And the organizations that win in this new digital world are the ones that are digitally led and analytics led. And I think that's one of the things we want to touch with across a number of these other presentations as well as we look to assess what is that requirement to be both winning at creating the best insights you can around your customers and your enterprise and also having the platform capability, decision-making process to deliver that at scale. Thank you for your time. I'll now move on to our next speaker.