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Skip to 0 minutes and 5 secondsSo I wanna talk about analytics maturity, so on a scale of maturity, how do you go from just having some data, which is a good place to start, and a few reports that are probably looking backwards at what's going on, to moving more into optimizing your organization? And actually starting to innovate. So as you move forward on that spectrum. So as you'd expect, as you're going from here to here, what is increasing is the value. So the value to your organization, the value you can generate, so reports look backwards, that's fine it tells you what happens. Optimization, real time changes that's where you start to innovate, changing the market that's where you start to break away ahead.

Skip to 0 minutes and 45 secondsThe flip side of that, again, as you move from here to here, the complexity also goes up. So reports, everyone can do reports, you can knock out some reports on Excel. Start to even do analytics and visualization, you can buy lots of off-the-shelf packages to do that. But getting to the point where you're making real time changes, people are buying into the process humans and data working in parallel together, that complexity gets much, much higher. But again, you know to end a positive what also goes here is the differentiation that you'll get in the market. So if you are innovating the market and making some changes, then people will be trying to catch up with you.

Skip to 1 minute and 26 secondsSo I guess, what we're gonna try and explore is where do you sit on this matrix. To try and bring this alive for you, we've got a couple of case studies, so the first case study we're going to talk about, is about NHS looking at delayed discharge and it's about how they started to look at the information they had, and actually move that forward to make some interventions and changes into their processes. Second case study, we're gonna explore is from Aggreko. Aggreko are a big manufacturing company, power is one of the big things that they do and how they optimize their processes and started to innovate in their industry. Then finally we'll lap back onto that monetization thing.

Skip to 2 minutes and 5 secondsSo if you're looking at monetizing your data, how good does your data need to be? So as we go through this week, we're gonna look at how you sit on that spectrum, where you are, where you'd like to get to and bring it to life again with tips and stories from NHS, Aggreko and some of the monetization examples.

Welcome to week 2

This week we will discuss some case studies so that you can learn from practitioners and apply their experiences to your emerging data strategy and data opportunity list that you drafted last week.

We will also introduce this data analytics maturity model, allowing you to map where you are today and where you need to get to to release the value of your opportunities identified so far.

Image showing questions and related data processes.  Data: What data do you trust? Reporting:What happened?  Analysis: Why did it happen? Monitoring: What's going on now? Predicting: What could happen?  Optimising: How do I do it better?  Innovating: Where next?Data Analytics Maturity Model (Click to expand)

I will explain the model as we go through the week but as a quick exercise, take a minute to place yourself, or your organisation, on this spectrum from having trusted data to innovating with data. Remember this is just your first impression, as we will come back to it later.

I am looking forward to sharing with you some practical advice from practitioners and using the analytics maturity model to frame your understanding of the change that lies ahead.

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Driving Value from Data

The Data Lab

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