7.1 Data driven decisions

The Digital Strategy for Wales Mission 6: data and collaboration, states:

Data and information are central to organisations operating and developing and are potentially one of their most valuable assets. Decisions based on evidence normally gained from data and information allow you to analyse your organisation to:

• make decisions
• identify needs
• track your workforce’s wellbeing
• provide evidence against objectives/targets for both internal and external stakeholders.

In presenting options, it is always sensible to have evidence to validate your reasons, which is normally a collection of facts and statistics based on qualitative or quantitative research and information.

We think of data, in the first instance, as information that has been collated digitally from information stored across, or via, digital systems. But data can also include information that has been gathered and captured from talking to others or taken from reports. Data can often be grouped as follows:

• Internal data – provides insights into your operations, finances, performance management, productivity and infrastructure. It allows for gap analysis and understanding the needs of your workforce.
• External data –often helps with analysing trends and benchmarking within your external environment.
• Marketing data –is used to understand customers’ behaviours and preferences, for example to assist HEI student enrolment and retention.

Activity 24 Data storytelling

Timing: 20 minutes

Presenting options and using data, needs to be engaging and meaningful, one approach is the concept of data storytelling. In the video below Laura Dewis (Chief Operating Officer, Full Fact) explains how you can bring data to life.

1. Watch the video and consider how you present data to others, and how you could approach this in the future.

Download this video clip.Video player: Video 24

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Transcript: Video 24 Data storytelling

LAURA DEWIS:

So there's a real range of people's expectations, and also knowledge of data that you have to think about when you are designing and communicating data. The way that we did that in the ONS was to really try to create products that worked for each of those different audiences. So if you're an expert, you want data in a table. You understand how to read labels, you understand the structure of data, that's very intuitive to you. And it also means that you can download that data in a structured way, and combine it with other data sets that might be similar that you want to cross-reference. So providing data in that way is the best way for those kinds of expert users.

At the same time, if you don't want to do any of those activities, and you simply want to find out a bit more information about something you've perhaps heard on the news, you are more likely to just want a short article with an explanation. And we really thought about it in terms of journalism. So how do news articles get written? And how do we use the inverted pyramid approach to making sure that the information that the user most wants to hear about is right at the top? So it was all about structuring and ensuring that the language we used was accessible. So that created a product for people who just wanted a very quick explanation of what was going on behind that figure from a trusted source, which is why they came to the Office for National Statistics.

Then there are other people who really want to understand the subject in a bit more depth, and they're willing to lean forward and engage with the data and interact with it. But they're not necessarily expert users of particular technology that would perhaps be used by other more expert people to interrogate that data. But they are prepared to put in some parameters, try to make sense of that data in their own context. And that can be very, very motivating to tell a personal story through the data, to be able to get people to connect with that data from their own personal perspective. A couple of examples of that are pension calculators, where people might be thinking, I want to retire early, but what does that mean for my income. So they can put in their age, and their salary, and figure that out. Or it might be a crime calculator. So what's going on with crime in my area, and how likely am I to be a victim if I compare my own characteristics to the data out there on who is affected by crime in my area?

So lots of examples of where people can interact with that data, and really understand what it means for them on a personal level. And I think there are other companies out there who are doing some really great work as well to engage people in their products. And a really nice example of that, I think, is where Spotify do the yearly review of what music that you've played on their platform. And they do that really well, because music is quite an emotive thing, and people react to emotions. And so being able to tell a story of how many things have you listened to, and what was the most popular thing that you listened to this year, really engages people in the data, but beyond the data, in a memory and experience that they had. And often it can be quite surprising, because people don't think that particular song was going to be their most popular that year. Maybe somebody else has been using their Spotify account in the family. But it can create all kinds of discussions and emotions, and that's a really nice way of engaging people in data.

Data visualisation is a really good technique to use if you want to communicate a subset of data, a snapshot in time. Data storytelling tends to look at trends and a narrative over time. One particular example of that, that I really loved, was when I worked for the Office for National Statistics, we discovered that in 2013 there were around 250,000 fewer marriages that year than there had been the previous year. When we found that data point we thought, what's the story behind that? Our hypothesis were that people were superstitious, and they didn't want to get married in a year with 13 in the date. So we looked back at what had happened in 1913, and that started a whole narrative about the trends in the dates in which people get married over time, and what had affected that like, for example, historical tax breaks if you got married.

And so it became a really interesting story, and we used photographs of people who had got married at ONS to illustrate that. And because I think most people have got a wedding photo somewhere in their house, and it's a way of engaging people in something a bit more personal, even though this is about the state of the nation, and it's about demographics and social information that we were providing. So I think the more that you can tell a story over time, often you can provide the context, and you can explain the trends in the data.

When you're thinking about data literacy, I always tend to advise people to think about how they read data. So how do they understand data, how they write data, and how they present data. And if you can think about the skills that you might need in those three areas, that can be really important. Part of it is about knowing what questions to ask. Part of it is about understanding how do you critically analyse different sources of data. So what are the things that you would look out for in terms of knowing whether a source of data can be trusted or not. And I think also to think about the different methods that you might apply to analysing data.

End transcript: Video 24 Data storytelling

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Video 24 Data storytelling

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2. Read the article: ‘Hybrid Work Is Just Work. Are We Doing It Wrong?’ [Tip: hold Ctrl and click a link to open it in a new tab. (Hide tip)] (Microsoft, 2022)

Consider how the article has been presented and how data is used to draw out the key points from the report. If you were future planning for new ways of working, how might you use the data to inform areas you might need to focus on?

Answer

Using data storytelling is a powerful way to engage others to focus on key areas. It helps to highlight information and encourage different ways to consider the information. In the article colourful visuals of the data were used to draw out key points from the report Productivity paranoia, people come in for each other and re-recruiting your employees (Microsoft, 2022). The article creates a story of the future and the needs of your employees, which for those involved in futures planning, raise complex questions that can lead to many possible different futures for an organisation.