Welcome to Agile analytics. If you are a product manager or product owner or otherwise responsible for helping a team to find success and iterate towards an objective with Agile, this course is going to help you improve your practice of Agile, and your drive to value for your user. If you're an analyst or a data scientist, this is going to help you help your team ask better questions and make more out of your analytics by increasing the actionability of those question and answer pairings. Lets unpack this a little bit. I'll start at the beginning of this catchy title, Agile analytics and explain what do I mean by Agile here? What does it have to do with analytics? How is this going to make your practice of Agile more awesome? So by Agile I will just refer to this manifesto. It's only around 68 words. It was really short, and this is a summary of it. As you can see, this is really more a set of outcomes that you're trying to get to than a specific how to of how to get there. That said, there are a bajillion different things out there to help you do that. There is Scrum, there's XP, there's SAFe, various agile scale things or scaled Agile things. As a team, you've got to pick and choose the practices that you want to apply, because you certainly can't use them all. I think it's useful to have a few key focal points for your practice of Agile, and your drive to value with the customer, and I like to use this product pipeline to help my collaborators and the learners think about that. In this product pipeline, you have certain observations about what might be valuable to your user. You go through this process you see here, and then you have released product that is in front of the users, some digital experience that is hopefully awesome. With Agile, you're iterating, so you're closing this loop a lot, and our question is, how do we use analytics to iterate more purposefully? So that we're instrumenting observation into everything we do, and when we get answers or metrics out of that observation, the actionability that is implied or at least already contextualized. So as we iterate with Agile, we know what to do next, and the analytics are helping us make better, more purposeful decisions about that. So if we back that out a little bit, I think that there are these three areas that are really important in the practice of Agile. One is continuous design, where we're trying to make sure that the proportion of features that we release to our total features that, that ratio of those features that have high engagement is as high as possible. That has to do with, of course, increasing the amount of winds, but also creating focus and allowing our team to build fewer things with more purpose, and more thoughtful work. Nothing will supercharge your practice of Agile like helping your team build fewer things better with more focus. So as we transition from here into Agile development, which is just a lot about output and how many features we're releasing really, there's this focus of continuous design and instrumenting analytics against that will help a lot. Design is not art. Design by definition has a specific objective. So it is really a very natural mirage to use analytics with our design, and ask ourselves with this design, what constitutes success? How will we assess that? That will really help focus your practice of Agile especially as you iterate. Finally, continuous delivery is important. We're not going to specifically talk about this as much in this course as we have if you've joined me for instance in the Agile specialization, however, nothing will make time for due you invest in a more continuous product pipeline, like building fewer things more purposefully. So in summary, I think you're going to get three big things out of the course. Number one is making a habit out of creating clarity about what constitutes success using analytics. Number two is instead of trying to use analytics to make sense of what happened with your software after the fact, you're going to make a habit of instrumenting purposeful observation into your work as you go along, all the way from idea, to design, to code. We're going to look at how we instrument analytics, how we use analytics as a team to focus and clarifying what we're doing. Thirdly, as you iterate with Agile, you're going to have actionability for these analytics, so we're going to really focus on how do we act on these analytics? How do we make sure that we're asking questions, getting nice focused answers, and we know what those answers are going to help us do next? So that we're iterating more purposefully. Why is this important? end up with a big backlog, a team that is constantly stressed out, trying to get more output out the door in hopes, in the uncertain hope that one of those things is going to be a big hit and solve all their problems, and that is a really hard way to work, and it's also not a very reliable way to get to good valuable outcomes for your user. So with Agile analytics, I think we have a great solution to that problem, and that's what we're going to learn in the course. Lets get started.
