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Intro

Welcome everyone to the HSO Dynamics matters podcast.

Your regular sonic dive into the world of Microsoft technology related matters and much more besides.

I’m your host Michael Lonnon, and today I’m joined once again by HSOs Head of Data & Analytics, Doug McConchie for part 3, and the final episode of our special data strategy series.

In this final edition we discuss how you know when your data strategy s working and delivering value and the types of things to report back to your sponsors that indicate return.

So, grab a brew, sit back, relax, and enjoy the show.

Michael Lonnon

Last book you read?

Doug McConchie

I read a book all about data strategy by a well known author.

Michael Lonnon

As he waves his book about data strategy in front of the camera. We’re in round three here of our data strategy mini-series. In this one, we’re wrapping things up a little bit around your data strategy. So you put it into play, people have bought into it, the business is starting to get some momentum, some value out of the data you’re now measuring, tracking and using. But the question for you at this particular juncture is when do you know that strategy has reached its end goal?

Doug McConchie

First thing about a strategy is it’s really a continuous journey. In reality, you might never quite get to the end, because it carries on forever. However, there’s lots of little steps along the way and I think that’s the key thing to focus on and for each of those steps, each of those use cases where you’ve delivered something, each of those activities which you’ve carried out successfully, have they delivered, have they actually been the success that you hoped for? All of those incremental steps along the journey, and those can be in the usual way, defined, quantified, measured, when you look at those in isolation, can you say that was a success or though that one didn’t quite work, these are the lessons learnt or potentially even these were the failures, but we’ve taken away something from them. So break it down into little steps and focus on those steps and measure those and see whether they were successful and get excited about succeeding on those.

Michael Lonnon

In terms of those successes and the things you’re going to measure, would they relate back to the original reason you put a strategy in place?

Doug McConchie

Strategy isn’t just one sentence, it’s a whole raft of different activities which need to be delivered, which when combined, deliver, or go towards delivering that strategy. You might have a grand ambition to become a more data driven organisation, but what does that really mean? What are the three things the 10 things the 20 use cases you’re going to deliver, which will take you on the way to becoming that data driven organisation. It is about breaking them down. That’s why I talk about this roadmap. A roadmap is really important and has some foundational activities within it, some things that you’re going to do early on, in order to build those foundational capabilities, which will be there for the long term. It has some more innovative activities where you’re testing the water, trialling some new technology, trying some new ways of working, trialling some new quantitative sort of methods. It has a whole series of use cases, which you want to build out solutions for and those solutions will be over the next 18 months to three years. Some of them will be bigger than others. Some might be literally a report here and a bit of data science there. The others might be building out a whole platform with multiple technologies on them, multiple capabilities needing to be set up and whole teams newly recruited into your organisation.

Michael Lonnon

I was going ask about what tools you can use to measure the value from the output of this strategy. It really depends on what the focus of the strategy is about, as you said it’s about enabling a team by giving them certain things or that slightly different measurable than maybe increasing business efficiency, one way or another.

Doug McConchie

There’ll be a whole raft of things. Within the data strategy framework. We touched on things around people, people need to be upskilled. One of the if you are upskilling people in the use of a reporting tool, that’s one thing, how many actual training programmes have you carried out how many people have been certified in the use of that tool? How many people are building reports on a regular basis using that technology? Those are all little mini successes, which can be quantified, and you can see whether you’ve been successful. You might have some needs to look at data architecture and build out a new data model for particular of the business for example have the various data sets been defined. Have you thought through and categorised all of those? Have you actually got them signed off and built? Have you chosen the technology within which that data model is going to be constructed all of those, again, once combined, become that particular use case, which is better data management in that particular business area. Lots and lots of mini projects within the programme of data strategy over the course of the 18 months to three years.

Michael Lonnon

In terms of measurement of that value or the return, your executive board members are looking at this slightly differently to the things that you are as the driver of the of data change? They’re looking for more business specific transformation change.

Doug McConchie

They’re looking for return on investment, why is this initiative needed, why should I give money to this one versus another? What’s the payback going to be? What are the choices whether you deploy anything. There are always choices, there’s better ways, there’s cheaper ways, there’s faster ways? So what are the choices, why have you decided to go for this particular approach? What are the costs involved, who are the people who are going to get involved? What are all these benefits you’re telling me about? What’s the value that this is really going to bring to my particular business area and why it’s really important? Talking about success, when’s it going to come? How quickly? What does it actually look like? We need to play that back that I listed out success for who the key stakeholders who am I actually going to be rewarded with all of this value? But equally, what if something goes wrong? What are the risks? What are we going to do about those risks? How do we mitigate those risks? And literally, what is the schedule? Therefore, what’s the project plan for each of those areas? So that is a classic business case, really. Those are the things which need to be addressed across the entire data strategy.

Michael Lonnon

Do you think there’s appetite for change; an understanding that the implementation of a data strategy and everything that comes afterwards is not a short win if you want to get value from data. There’s lots of different things or steps. Do you think there’s appetite for change?

Doug McConchie

There’s no alternative. You need to be competitive today. Your competitors are doing this, they are taking advantage at the moment. They’re using their data, being more creative in their insights generated in their business. They are the ones who are creating new business models using data, and then they’re monetizing data. If you’re not, you’re going to be left behind. It is a question of at least keeping up with your competitors, and actually trying to get ahead of them by taking the advantage on doing some of these things better than they are.

Michael Lonnon

Let’s assume then that this has all landed well, and that the business is getting value from its data, after all the work that you put into data strategy, how can you maintain this momentum because, as we spoke about before, the data strategy never really stops, so how do you keep the positive momentum going so you end up with a data literate culture?

Doug McConchie

Recognising it is a continuous learning exercise, so you will not always be successful on every initiative, but as long as you learn from it, and it’s about incremental growth, that’s the key. Having a clear plan, about what steps you’re going to do to move along the journey is important. Thinking about what’s the basic skills needed, then go to the more sophisticated level from a skills perspective, is absolutely the right step. Similarly, from a technology standpoint, what’s the basic technologies we need? What are the more sophisticated levels of technology and how do we actually get maximum value out of using those technologies, sweating, the technology asset is absolutely key. From a data point of view, maybe you start off focusing on mission critical data, that which is having the most business impact. But equally, once you’ve done those, what additional data sets could be brought in to enhance that, to make it even more valuable. More insightful measures make our decision making better. It’s a question of incrementally adding to the sophistication and complexity within your data strategy, so it doesn’t stay stale. It takes you to the next level, and it adds value layer upon layer over time.

Michael Lonnon

It’s creating that foundation, building on it, and layering on top of it as time moves on and keep getting more value out of it.

Doug McConchie

Bringing in innovation too. There’s lots of things you can do, and technology is changing all the time skills are changing therefore, as a result of those technology changes, the types of thing you can get value from actually getting easier in a way that and those that there are lots of exciting things to sort of add to your roadmap over time.

Summary

The key thing to note is that your data strategy has no end. By continuous tweaking and improvement, your data strategy will continue adding value long after it is landed. Although a never-ending strategy might sound like a potential money pit to your execs, so it’s important that when reporting back return your focus is on the small wins and positive changes it has led to. It then becomes harder to question investment, whilst making it easier for execs to support you data cause, which in turn increases adoption and value.

 

I hope you enjoyed this data strategy mini-series. If you have any questions regarding extracting value from your data I’d love to have a chat with you. Until the next episode, take care of yourselves.

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