You'll learn

What data literacy is

Why companies should invest in data literacy

How to use the 'design to act' to improve data literacy

How to build and nurture a data-driven culture

Subscribe to the Marketing Analytics Show podcast

Learn everything you need to know about marketing analytics.

Join the Supermetrics Community


Anna Shutko:
Hello Lee, and welcome to the show.

Lee Feinberg:
Thanks, Anna. Great to be here.

Anna Shutko:
Yes, I’m super excited about this episode. We have another very, very interesting topic, which is data literacy this time, so we’re going to talk a lot about how companies can improve their data literacy. Lee is going to share his Design to Act framework with us. My first question to you, Lee, is why every company should invest in improving their team’s data literacy. What’s so important about data literacy?

Lee Feinberg:
Yeah, a great question to start. We could spend the whole hour talking just probably about that one. But let me give you an analogy to that. I think it will really help. Imagine I teach you Microsoft Word, and I make you an expert in Microsoft Word. You know every feature and function, but I don’t teach you anything about language, how to write, or how to make a sentence. Microsoft Word won’t really be very helpful to you.
That’s exactly what happens in the world that we’re living in today is mostly that a company takes some piece of software. Even this has been happening for 30 years. When Excel and early spreadsheets and PowerPoint and all the iterations of that, all the way through things like Tableau and Qlik and Power BI now, they teach people how to use the software, but they don’t teach them anything about the language of visualization, and the literacy aspect of reading and writing with data and visuals, and so it’s very chaotic. Everybody does the work in a very different way, and so it’s very difficult for companies to really get the value out of the data because they haven’t set up the fundamentals.

Anna Shutko:
All right, excellent. Thank you so much for outlining the importance of having data literacy. Now, let’s talk about failures. It’s funny that I have failures as the second question, but it’s very important to understand. Why do companies fail to become more data-informed, and why do they fail to make data literacy one of the key aspects of their culture? If you could continue from the first question.

Lee Feinberg:
Yeah. Part of it’s just what happens in many companies in general. There’s just not a lot of effort put behind training, certainly not to the level that needs to happen with something like data literacy or changing the data culture. Think about what most companies do. Maybe they let you take some training online, or you go to a conference once a year for a day or two. That’s not enough to build data literacy as a competency in a company. You can’t do it by sending somebody to a class for a day or two. It has to become part of how the company works, and that’s a big effort. Until somebody at the company is responsible for that kind of thinking and investment, it’s very difficult, and you have to get everybody involved with it, too, right? It’s not two people who can learn to be good at data literacy. Everybody in the company needs some skill because everybody is touching data.

Anna Shutko:
All right, that makes a lot of sense, and I really like how you mentioned that the core problem is that the companies are not spending enough time coaching their employees. They’re not spending enough time evolving them into all the aspects of data literacy, so a one-or-two-day conference isn’t enough.

Here comes the question of how a company can integrate data literacy into its culture, so can you please talk more about your framework? What is the Design to Act framework? What are the key ideas here, and how does this framework help tackle the problem of stakeholders being maybe not so involved?

Lee Feinberg:
Yeah, so it’s, I think, interesting how it came about. This thought didn’t happen to me all at once, but I think it formed over a long time working in analytics and visualization and my frustration. I kept hearing this phrase, “Data is strategic.” It’s very common today. But I asked myself, “What does that mean?” Because it was just something, people said, “Oh, data’s important. Data’s the new oil.” You could put any similar phrase behind it.

When I thought about “What does ‘data is strategic’ mean?” I realized there are other strategic functions in a company. There’s finance and marketing and, IT, HR. Every strategic function in the company has a way they do the work. There’s some framework or process. Finance has balance sheets and income statements, and IT has an Agile and software development life cycle. You could go for everybody.

But in data visualization or analytics, building data stories, there was no framework, there was no process, and that’s why there was so much inconsistency in how companies approached it. Again, it was to give somebody a tool and let them do whatever they wanted. That’s tough on somebody because how would they know how to do something? If they’ve never been taught one of those frameworks, they will do what they think is best, which we’ve seen in most cases get messy.
Once I had that idea, I spent a lot of time thinking about what that framework should be and how I could take all the different things that I’ve been involved with over the years, marketing, software, product management, data visualization, analytics, and combine them into something that people could follow pretty easily. That’s where Design to Act was born.

The other twist on it, it’s based on thinking about your work as a product. Why that’s important is that most people today who are working in this area might have an assignment or a project. It’s to develop a report or a dashboard or a data story, and when they finish it, they publish it to some server, they send out a link, they say, “Here it’s,” and then they most of the time go on to their next project. The problem is you never really know then what will happen. Did that report or dashboard do its job? Did it help somebody ultimately make a decision or take action? That’s the only reason you should be doing the project. You shouldn’t be doing the project to show numbers that people might look at and then not do anything about it. That’s a waste of time.

When you think about it as a product, just like when you build a product, right, you’re a software company, you don’t just build software and hope that people find it and know how to use it, and right, you market it, you educate people, you do all kinds of things to make sure that it’s successful, and then you also want to find out that it’s successful. Are your customers using it the way it’s intended? Is it helping them do the things they want to do? That’s the gist of the framework that you need one, and I explained why because it’s data-strategic, and this idea is based on a product model.

Anna Shutko:
All right, excellent. You mentioned that your framework includes the elements of marketing product, maybe a little bit of IT, and many other different aspects, which is also, in my opinion, because it helps people get a very holistic view of how they can approach data literacy, so you’re looking at the topic from a variety of different angles. But let’s break it down into concrete steps now. You’ve mentioned that everybody needs to adopt a product mindset in one way or another, to treat data and data literacy as if it were a product so that the dashboard would encourage people to take action.

What’s the first step when companies apply this framework, and what does it look like in practice? Do you start with some sessions? Do you ask people to think about the goals their dashboard could have? What’s the very, very first step?

Lee Feinberg:
Yeah. We tend to work with clients first by giving them a grounding in the ability to just write visually. It has nothing to do with technology. Think about when you… I’ll go back to Microsoft Word, if you want to write in Word or Google Docs, you still use the same skills as if you were to pick up a pen and write on paper, and so we want to equip people that way because it doesn’t matter what application they use, we still want them to have the same foundation, and we want it to be consistent across a team, so we want everybody to learn those same skills, so when you think about literacy, we call that “grammar.”

It really understands just the basics of visualization. How people process that information, and when you understand that, and we don’t get into a lot of technical jargon. We break it down to some really simple, practical things people can do. We don’t think they need to understand the brain, which is like, “This is how it’s. This is the rule,” right? When you learn a language, they don’t get into the details of it. They say, “Here it’s, and just do it,” and so we take that same very practical approach.

That gives them the starting point so that when they’re actually using whatever software they’re using, whether it’s, say, PowerPoint or Tableau, Excel, now they actually understand what’s what that means to the person who’s viewing it and how it’s going to be processed. That way, they can make the best choices, not just pick a chart, because many things you see are people saying, “I’m going to pick a whole chart to represent this idea.” Rather, you should understand how to build that chart. It’s like knowing your letters, words, and sentences and making a paragraph. You don’t just pick a paragraph, right, and say, “Here’s a whole paragraph for my idea,” you build it up, so we want people to have that same skill of just understanding the basics.

We try to keep it to a few points again because we don’t want it to be so overwhelming. I know that when I started learning a language, they hit me with so many details about how to make 27 versions of a verb you lost sight of the fact of what the verb is, and you couldn’t get conversational. We want to avoid that kind of a problem and give people some simple things that can get them started, like 80/20, right? We’ll give you the 20% that helps you with 80% of what you need to do on the job.

Anna Shutko:
Right, I think this is a very smart approach. I definitely agree with maybe not overwhelming the team with too much information but rather giving them actionable tools to start building these dashboards visualizing this data.

My next question is, how can you ensure the team has enough skills to move to the second stage, to the next step of your framework? Then what does this step look like? After everyone is coached and they know the basics of data literacy, how can they actually start using these skills in practice?

Lee Feinberg:
Yeah, that’s what we do if we force them to use them. One of the things I built into the program was thinking about my own experiences, going to any training, or a conference, learning a lot of great information, and being very kind of pumped up to go back and do something. Then I’d sit down at my desk, and I wouldn’t know what to do. It all sounded great, but then I didn’t really know how to start once I was back on the job, so we forced people. When I say “force,” we put them in a position when they’re learning this to actually practice it in a safe environment, right? There’s no stake here, they’re just learning among peers, and we want them to try it out because, again, they’ll sit there and nod their heads and go, “Oh, this is easy to do,” and then when they try to do it, they may really get stuck, and so we want to give them that jumpstart where they can apply it.
We do it in a way that they’re not just sitting there doing it on their own. We try to get them up, do role-playing, present their work so they can really get a feel for it, and work out the kinks, get rid of that, maybe the jitters they might have about it so that when they face it on the job, they don’t get nervous, and just go back to their old behavior because that’s what everybody does, right? Myself included. When you’re trying something new, if you don’t really have the confidence in it, you typically go back to what you’re comfortable with, even if it’s not the right thing. You just can’t help it because we’re human, and so we want to help people get off to a good start that way, so that’s always critical. It’s just keeping the practice going throughout the whole experience, no matter your level.

Anna Shutko:
All right. Yes, that does make a lot of sense. Another question I had here was how does the team collaboration look at this point? If you’re to roll out these training sessions to a larger group of people, do you involve people from multiple departments, say, sales and marketing, for example, which might have quite different data needs, or do you tackle this problem case by case? First, you approach the marketing department and help them acquire data literacy within the context of the marketing data. Then you move on to sales and ask these groups of people what their goals are and how they could improve their data literacy within their specific context. What do this team collaboration and team-based approach look like?

Lee Feinberg:
Yeah, that’s an interesting question because I hate to say “it depends,” but it depends, and here’s why: It’s really up to how each organization is set up because some companies have a centralized group that might be responsible for doing analytics, right, and so every other group in the company goes to them, and so that group must build their skills up in this space so that they can support their organization.

Others might be mixed, where maybe everybody, let’s say it’s a marketing group, so the marketing group might have their dedicated analysts, so in that case, it might make more sense to bring in, maybe not for the entire program, but for parts of the program, bring in their customers in marketing because it’s equally important that the customer understands what’s going on in terms of changing the process. Because if you and I, let’s say, are used to working together in a certain way, and one day I come in. I just started having a completely different kind of conversation with you. You’re going to be wondering what’s going on. You might be more resistant to that because you’re not comfortable with it, even though I’m now, and so if we can bring people along that way, it’s really good.

Even if we didn’t have that kind of a mix when we’re going through the programs, we’d teach the analysts, or whoever’s in the program, how to have that kind of conversation with somebody. How can you introduce it to your customers that you’re working with internally? Or maybe it’s an external customer, but they’re still a customer. How do you introduce this to them so that they’re not surprised or that they at least understand that you’re changing something and that you’re going to be asking them to go along with you and see how it works out, and then you can talk about it afterward so that they don’t just immediately say, “No, I don’t want to do it that way. I just want to do it how we’ve always done it,” right? Because we’ll never make any progress that way, and we all know that we’re getting inundated with data and lack of skills. So the more we resist in the organization, the further we’re going to fall behind in really being competitive in this space.

There are a lot of cultural issues that we have to tackle along the way. It’s not just blocking and tackling of teaching people how to do visualization better or how to organize it into a story. We have to teach them these other softer skills that would definitely be overlooked when you’re just learning how to use a tool in very technical, straightforward training.

Anna Shutko:
All right. I like this detailed answer. I also do agree that a combination of hard skills and soft skills is very, very important. Now, you’ve already partially answered my next question, but maybe you could elaborate further.

Lee Feinberg:

Anna Shutko:
The team has adopted your framework. You’ve trained them on how they can actually use data in their day-to-day life, the communication is set up, and when it’s time for your team to finish the coaching sessions, and when the program comes to an end, how can you make sure that the practices that people learn throughout this course or training stick within the organization? You’ve mentioned data literacy being a very important part of a company’s culture. What are things companies could consider to make sure they implement these data literacy programs well so that everybody even subconsciously thinks about data when making their data decisions after the program is finished?

Lee Feinberg:
Yeah, important to me in the design of the way we work with our customers because, just like I mentioned that we want them to understand if their work is being successful, I want to make sure that their work with me is being successful and implemented. There are different ways that clients do it, but typically what we do is continue after we’ve finished the core learning is make sure everybody’s doing a project. It’s almost like entry to being in the course. If you’re getting sponsored into this at your company, you come in with a project to work on from the beginning, so you continue to work on that project throughout and launch your product, right? I said it’s a product, so eventually, you have a product launch.

After the launch, you then still have work to do. As we said, you have training and education, and then you actually want to find out it’s performing the way you had intended. If I built a product for you that was supposed to help you make some, say, sales allocation decisions for your sales teams, where you wanted people to be spending their time. In the end, I’d like to find out if that happened, so we go all the way through to the end with somebody, and there’s continuous coaching. There are some things where the teams come back together to do recaps and evaluate where they’re at.

Also, there’s typically a sponsor for this, so that person inside the company is watching, right? They have an expectation that they just put you through this pretty intense skillset training and they want to know that you’re doing it, right? It’s not just to go. Again, you go to a conference, and nobody really follows up with you and says, “What’d you learn?” Sometimes you have to give some little readout, but typically, it’s you just go, and you come back and do your job, and that’s it. You keep going. Here, that person really wants to know because it’s an important part of their strategy that that group of people needs to have this new set of skills, and needs to put them into action, so there are a lot of different pieces where we keep working with an organization to make sure that everybody’s really getting the most out of it.

At some point, they will be on their own, right? I’m not going to be there to hold their hands forever, but you want to get them off to enough point where they see that there’s value in it. Once somebody sees value in anything they’re going to, they should keep doing it. I won’t say they always will, but generally, people keep doing something if they see how it helps them do their job better and makes them more successful.

Anna Shutko:
All right. These are very, very good tips. Thank you so much for sharing. Now, if the audience would love to learn more about you, and I’m pretty sure they will, where can they learn more?

Lee Feinberg:
Well, the easiest way is to just go to decisionviz, V-I-Z, .com, and they can pick up some information about the framework we just talked about. It has some more explanations about that, and there are other good resources out there, some eBooks and videos with some conversations with other industry folks that have some good views on this.

Anna Shutko:
Excellent, Lee. Thank you so much for coming to the show.

Lee Feinberg:
Thanks so much, Anna. It was great.

Try Supermetrics for free

Get full access to Supermetrics with a 14-day free trial.
No credit card required.