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Hello and welcome back to the foresight strategy show with your host Dr. Nilda and my co-host, Rachel Calderon. Hey, Rachel, how are you?

How are you?

Today I have with me, Marie Clark. Marie Clark is an expert in the intersection between human capital and the rapidly maturing field of data and analytics. So, welcome Marie, how are you?

I’m very good. Thank you Dr. Nilda. How are you?

I am great. I’m so excited to have you here. I want to understand a little bit about how you actually became a futurist. Like, tell me the trajectory.

I just recently started calling myself a futurist. However, I have about 25 years of experience in business and have always been kind of an intrapreneur, an entrepreneur working inside of corporate America. And that involves understanding horizons, doing a lot of scanning, and doing a lot of the work of a futurist. But I suddenly became aware of the fact that there’s actually a designation and I was recently accepted into Association of professional futurists and so I know I have a name for what I’ve been doing for 25 years.

Which is heavily researched and always finding those trends and scenario planning and all of these areas that can be really intense. That’s awesome. You also do data literacy.

I do. I have always applied the research and the futurists work in the arena of data. So I’ve been working with data for about 25 years. Recently the need for data literacy is becoming more important. So I’m focused now on a data literacy and I’ve left being an intrapreneur inside of corporate America. I’ve launched my own business focused on everything from basic data literacy to an advanced data science.

You’ve been using data all along with literacy. It all comes together so of course futuring was something that was a natural fit for you because it was something that you have to do when you’re analyzing and you’re looking at data. So, this is perfect. Why do you believe that data literacy is more important to the 21st century than it ever was before?

I believe data literacy has always been important. Especially at the beginning of the computer age back when computers were first introduced to the market and we started collecting lots and lots of data. However, what’s happening right now and why it’s becoming increasingly important is that when we considered processes in the past, we’ve always thought of them in three dimensions. We think about people, process, and platform. However, since the eighties and the beginning of this computer age, we have collected so much data that it is now a four-dimensional process. When you’re looking at creating something new in business or analyzing and performing, some are improving something. So, it’s no longer people, process, and platform. It’s now people process, platform, and data. So think about it. You have now added a fourth dimension which is equivalent in size to those other three. So, that is why it is critical today that people understand data. It is no longer possible to ignore it and those who are not data literate are going to experience increasing problems as we go forward.

So, with that being said, what exactly will happen to organizations that won’t be open to data literacy throughout their organization?

Well, many people really struggle with this concept of digital transformation. You’ll hear everybody talk about it, but many people don’t fully grasp what that means. So imagine back in the computer age, right? Our embracing of computer technology using computers to do our job. In the beginning, it gave us some competitive advantage. After a while, it was an absolute must have. And after a while, beyond that, those people who did not know how to use computers fell behind. So digital transformation is not just adding a data science department or automating a few processes. It is the complete culture shift of how you think about solving problems and creating opportunities. Adding that fourth dimension data and those organizations who do not embrace that fourth dimension will begin to suffer and will not be able to compete. And those individuals who do not embrace and understand data, at least at a basic data literacy level will no longer be essential and relevant in the jobs that they do.

Can you give an example to the audience? I understand data because I come from a financial background. Data, for me, is very easy to comprehend. But a lot of people I think would shy away from this, being data literate, because they’re a little bit afraid of it. For them, it might be a little too complex. So can you give them an example where it can kind of hit home?

It’s not complex at all. It is understanding that there is data out there both inside of the companies you work for or the processes that you use at home as well as external data, right? Everybody’s got data. The government has data, right? There’s all kinds of publicly available data. So just kind of being aware of data knowing that it exists. When you have a problem at work, let’s say that there’s been some kind of a slump in sales you need to understand that there is data available that may be able to assist you. So that’s the first part is just knowing and being aware that it exists and then being able to think of places where you can get data. I have a great example. Let me do this. I have a friend who started a company and she wanted to be able to size her market. She went around to all of these agencies saying I need to know how many small businesses there are that are focused on design and on strategy. And no one could tell her that. The small business administration couldn’t tell her, our local government couldn’t tell her. So she gave some thought to the problem and she said a small business is defined as someone who’s a filing a schedule C along with their tax return. And one of the publicly available pieces of data is the title that they give themselves. So she basically said, I need to know all the people in this area that file a schedule C and who have either designer strategy in their title. And so she went ahead and did that and she was able to successfully size her market. Is she a data scientists? By no means she is actually a marketing professional and a strategic marketing professional. But she was savvy enough to know that there must be a way to define this, my target population. There’s got to be data somewhere that could help me.

She broke it down small enough so that people can say, Oh yes, that would be me. And that’s how she was able to open up into that area.

What you’re saying is that organizations are a company, no matter how big or small, because the example that you just gave was not somebody who had a huge company. She was a startup. She knew she needed to have this information, but do you find that people shy away from data? With my masters, I had to do a lot of research. I needed to analyze data. Of course, when I went for my doctorate it was even more so. But I find that I was one of those people that was very afraid of data. I was like uh I don’t know what I am supposed to do with those numbers. I was afraid of statistics. Do you find that a lot of businesses shy away from searching for the information and once they have the information actually using it?

Yes. First of all, not everybody needs to learn statistics and not everybody needs to be an analyst. But it’s more about a way of thinking and including data and what data is available and the techniques that can be used. It’s that level of awareness that’s necessary. We don’t all have to be hands-on data analysts or data scientists. There are a lot of companies that don’t really know what to do with data or they’re trying, I’ve seen examples where people have learned about control charts, which is a statistical process control. And I saw one organization, they had a team in India producing 300 control charts a day. I have no idea who was looking at them and if they understood what they were doing, they would realize that they were measuring a process that could not be controlled with a control chart. But they were producing 300 a day. And I have no idea how many people were involved, but there was a significant effort. So, people either shy away from data or they embrace it but don’t really understand how to use it effectively. I see both of those things happening.

With the example, that you gave earlier. I would say that you don’t necessarily need to be a mathematician because the data that your friend was looking for was something completely different. She was actually looking for titles and there were certain things that she was looking for. So data doesn’t necessarily have to only be numeric am I correct?

Absolutely.

I always have been huge on spreadsheets and understanding spreadsheets and being able to do projections and looking at my business from a very analytical standpoint. As a matter of fact, a few days ago I was with some friends and their business has all these moving parts and nobody really communicates with the other. So, I said if you have the spreadsheet, you’re able to look at the information in one place and it makes it easier. And so they were like, oh my God, you’re so organized, you drive me nuts, but charts make it easier for me. So Excel is my best friend. I use it for everything and that’s really data analysis. That’s data literate. You have that information and you could look at it in one place rather than having to pull from different places to be able to create the information or to be able to gather information. That’s very abstract when it’s all over the place and when you have it in one place you start seeing patterns. You start seeing what’s working, what isn’t working. Things are much easier measured when you have it on a spreadsheet, would you agree?

Absolutely agree, but I also, if you will allow me, I want to give a slightly different definition to data literacy. So what you’re talking about is absolutely data literacy and it does really enhance the work that we do and for some of us we love spreadsheets. I personally am a spreadsheet fanatic. I measure everything but the reason I am so passionate about data literacy and I’m such an evangelist is because I had an experience in 2011. My daughter was diagnosed with severe health issue and the doctors in order to come to the diagnosis they used kind of a facial analysis software. They took photographs of her and they fed it into a computer algorithm and they came up with this diagnosis. Now I’ve been teaching algorithmic thinking and I’ve been teaching advanced analytics for 25 years. The diagnosis that they gave me did not make sense. However, because a doctor said it and because the computer said so, I didn’t challenge that at first. It took me about two years. First I had to overcome the loss of having this diagnosis at all and all of the things that we were facing. And I had to adjust my life around her needs. Once my brain started functioning again, I started to think, wait a minute, how is that even possible? That can’t be possible. Something’s wrong. So as time went on, the diagnosis made less and less sense. So about two years. So now we’re talking about 2013, 2014. I started talking to every doctor that would listen to me and say something’s wrong. This diagnosis is not correct. Well, seven years and three doctors later we finally discovered what the issue is. The particular algorithm that these doctors, and let me tell you, it is being widely applied by all medical professionals in this specialty.  Everyone is using it, but it hasn’t been sufficiently tested. And so it was primarily tested on Caucasian children. My daughter was adopted abroad and her facial features are not that of a Caucasian child. So therefore her facial features through what we call a false positive. So, she does not have this severe health condition. Now she has other health conditions, right? But their diagnosis was inaccurate and I have to say how many other children are being negatively impacted by this faulty tool or this tool that hasn’t been sufficiently tested. And I don’t blame the doctors because they are given a tool and they are told this is great. Everybody’s using it. There was no warning label on it that said we’ve only done limited testing and this is the population of children that we’ve tested it on. So now seven years later, I am just now to the point where I probably will have a correct diagnosis in March. So it has taken that long to get somebody to listen to me and to do research on this algorithm. So that personal experiences is a really stark reminder of how powerful and consequential data can be, right? And how it can truly impact our lives. And so being data literate means that if it doesn’t make sense, I don’t care if it was a doctor that said it or a computer, we have to be educated enough to push back and say, I’m sorry, that doesn’t make sense.

That is the perfect example because I’ve had that with my own health and they’ve also experienced that with my mom’s health. Blood pressure keeps fluctuating from very high to very low, very high to very low. I’ve been keeping track. I’m like, she’s not doing anything different. This has to come from somewhere else. My mom is completely healthy, no diabetes, no have no blood pressure in her family. Again, following those numbers, keeping track of testing her several times a day, I realized it has to be something else. So when I go to the doctor, I went with a piece of paper and I said, look, this is what’s going on. I see this, but there’s no change in what she’s eating. There’s no change. I kept the pattern of what she was eating, her exercise regiment, everything, and he was like, wow, this is amazing because I was that accurate. He was like I wish everybody did this, but I guess I come from the spreadsheet, it just organizes my life. But that’s one of those things that I feel we really have to pay attention to.

We have to use data in defense of our families, in defense of our own personal health. We have to be savvy consumers, we have to use the data at our fingertips to make good decisions, buying decisions, educational decisions. We have to be the ones to start benefiting from the data.

Even in business, you have to use that data to your benefit because that information is critical information and it helps you make wise decisions.

And also, what, what I think is that although Artificial Intelligence, which is one of the things that we use for our data and a lot of these doctors are using is all well and good, it’s only however much we as humans have inputted into that system. They cannot necessarily go through every single scenario that we go through. Is this why you use the tagline data science without data scientists?

Yes. I think that would be an excellent example of the fact that everybody thinks that to be a data scientist you have to have a Ph.D. And really what data science is, it’s not one individual person, it’s not, a scientist. Data Science is a discipline. It is a discipline of looking at problems and using data that is available to help you understand that problem. And as you said, make better decisions. It’s basically using data to solve problems and to identify new opportunities. Now, do we need Ph.D. level data scientists? There is no doubt, absolutely. They certainly have an important role. But they can’t be the only one’s data literate. It’s about every single one of us has to get better at tracking things, seeking patterns, asking questions, being critical. And only then are we going to really experience that digital transformation that everybody is talking about.

And I liken this Marie, to us being more responsible for our health. We have to be more responsible in every area of our lives with our health. We’re taking a lot of responsibility for our health. We’re minding what we eat, we’re minding our exercise regiment. We’re taking over. We’re no longer going to the doctor and saying, I feel this kind of have a pill. So just like we, we’ve become literate in that area the data, the information, understanding trends, developing scenarios, all of this that’s basically what this is. So you look at it because now you’re responsible for your business. You’re responsible to give the customer what they need and want. But you need to know your customer to know what they want to know what they need. So that’s why this information is so critical. You’re looking at your business from a totally different perspective. That’s what I find fascinating about what you do, about what we do collectively, each of us futurist and how we look at things and that’s why I’m such an advocate. I call myself teaching the gospel of futures because it’s so critical. Again, just like we take care of our health, we have taken our health back. We no longer go to the doctor for everything not that we should never go to doctors because everything has its place right? But there are certain responsibilities that you need to take. If a futurist comes to you and you have this information it’s much easier for them to help you to be able to get to that next level, to be able to create those scenarios because you’re keeping track, you have data, you have information that you’re analyzing. And you’re saying, this is my conclusion tell me what you think.

And I would say that our job also is that when our physician tells us something that doesn’t make sense, that we have to have a voice and we have to say help me understand that because that just doesn’t make sense to me. We have to challenge them to think and make it clear that they are beholding to us and that we are an active participant in our own health like you were saying.

And I think that also in business as well, we need to not just accept this is my financial status and let me just leave it like that. No, try to find out what the real problems are. Like back when I was in the financial department, that’s what I did. I didn’t necessarily go by what my spreadsheet was saying. I would actually physically call the customer and sometimes there were seasons where I found out their business would go down. So, I would come up with a solution for them to continue purchasing, but not necessarily at the quantity that they would at their highest or their peak season. So I would tell them, okay, so in peak season, since you need this, why don’t we stock up this merchandise during the season so that when you’re at your lowest point, you still have merchandise.

You’re bringing up a very critical point that many people don’t yet realize since we have so much volume of data, right? We have kind of tended to go towards this quantitative bias, right? So we analyze the numbers and we come to a conclusion, but what you’re talking about is the collection of qualitative data. Calling the customer, talking to people. We’ve kind of lost sight of the need for qualitative data and in order to combat the quantitative bias, we have thick data. What that means is that is really just the renaming of qualitative data and it is essential, especially as futurists because the methods we use to predict the future, many of them are based on past performance. And so what are you not going to see? You’re not going to see what’s coming that we’ve never experienced before. And there’s a great, example which is Nokia. Everybody had Nokia’s back in the day when we used flip phones, right? And they had an ethnographer in China who was studying how the Chinese people were using cell phone technology and what the introduction of smartphones would mean to them. And she came back to Nokia and she said, this smartphone thing is going to be huge. And they said, we’ve got millions of data points and they’re not telling us that you only interviewed 100 people. That can’t possibly be true. Well, how many people own a Nokia today?

I don’t think anybody.  Well, my mom.

She’s a futurist. She was able to see that through her interviewing people and studying their lives, she was able to see that this smartphone thing was going to be absolutely huge. Her data scientist ignored that thick or qualitative data and they weren’t able to see because they were basing all of their projections on the questions they asked their customers. Well, of course, they limited the data they had and they couldn’t possibly see something that was going to be this new and this revolutionary.

Right. Which is what Steve Jobs did, except he did not go by what they were telling him. Again, the customers can only tell you, which is not a bad thing, but they are only able to tell you what they’ve experienced so far. They didn’t know the possibilities. And so that’s why data and qualitative is so awesome because you’re looking at it from that possibilities standpoint. Where you’re saying, yeah, this is what we have, and you think this is great. It gets better. But they don’t know that because they haven’t experienced that so until they’ve experienced that they can’t tell you, this is great. Like right now, smartphones are all the rage, but this is all we know so we can’t tell you what’s even better. But if you’re making your clients’ lives better, then that’s going to be all the rage because anything that simplifies their life, things that they need that they may not even know they need that’s what you’re looking at. So you have to look at it from a subjective standpoint rather than an objective standpoint because then it’s only numbers. You have nothing more than the numbers and you’re analyzing the numbers. The numbers can be very biased because again, it’s only going by the current experience.

This elevates the position of the futurist. This elevates the need for Futurists because these are people that are consuming vast amounts of data, synthesizing it, talking to people,  and trying to see what’s coming next and that is a critical input to all of this prediction. So, we’re in a very good field right now. A lot of people are afraid of all of this change because compared to in the late 19th century, right, when people left the farms and they moved into cities and they started doing mass production, that was a very difficult transition for humanity. And a lot of people got hurt. This time they’re predicting that going from the computer age, into this fourth industrial revolution that they’re terming the cyber physical age will happen at 10 times the speed and 300 times the scale. So we will feel this transformation that we are entering. People have no idea how fast it’s going to happen and how much it’s going to impact. And so they’re saying that compared to those people that were forced from their farms into the cities, we will feel the transition about 3000 times more, which is kind of scary. However, what’s important to keep in mind is that this type of disruption and this type of change breeds opportunity. We shouldn’t be fearing what’s coming. We should be looking for what’s in it for us? How can I benefit from this? What can I be doing? This is literally the biggest opportunity since the late 19th century. This is absolutely huge. And those of us who are not afraid and who are going to try to learn and try to figure out ways to make this stuff work for us. Like we did with our smartphones, right, right. We’ve embraced that and it’s, it’s adding some value. We are going to benefit greatly if we can kind of let go of the past and really embrace what’s happening and look for opportunities for ways that it improves our life or that we can actually maybe have more fun doing what we do for a living.

Can you share a success story? Because we want to bring awareness to, to our audience and sometimes like you said, disruption can be a little bit scary. There’s no need to be scared. I’d like you to share at least one success story that can benefit the audience.

The average worker is experiencing what we’re calling robophobia. They’re terrified for their job. It is the leadership of the company’s responsibility to help to reduce those fears and to focus on the positive. So I’m aware of one company that I worked with, it’s a medium size company. They were kind of in a very old fashion type of manufacturing type industry but they had a lot of employees who were terrified that they were going to be laid off, that they would be losing their jobs, that robots were going to come in and take over and they developed an approach. I was working with them, we looked at the situation and we decided to start small. So we started with what the leadership called innovation challenge. They found a problem, right?   They had data and they had an issue which was basically a spike in cancellation rates. They were experiencing a spike in cancellation rates. So they brought together a team of three brave volunteers. Those people who are willing to raise their hand and say, I don’t know how I’m going to do this, but the three of us are going to get together and try to solve this problem. Leadership got all of the employees focused on the work of these three people, encouraging them, supporting them. There was a lot of positive support for these three people and when they found the solution to the spike in cancellations, they received tremendous accolades from leadership so that leadership was able to turn around this dying business filled with terrified employees thinking that they were gonna lose their jobs. Some of them had been there 20 or 30 years to now they’re clamoring to get on the list because they want to be in an innovation challenge. And you don’t have to be a data scientist. You could be a domain expert, maybe somebody who’s in an operational call center who kind of understands what the customers are talking about when they do cancellations. So you pull together teams of people. Everyone has a role in using data to solve problems and find opportunities. And that company had huge success. So they now have employees who are no longer afraid of change. They see this as a way for them to enhance the work they do. They see it as a way to get a lot of positive recognition from their leadership and for them to kind of raise their status and become essential and relevant and their company. It has transformed their culture.

And that’s really what we would like to see so many companies do because although there is change, there are opportunities everywhere. You need to start thinking creatively. You need to not be afraid of looking at those numbers, not be afraid of looking at the things that you’re seeing and look at, okay, so what can I do? What’s the opportunity for me? I think that’s awesome. Marie, thank you. This has been a wonderful interview. I want to have you back because this is information that I know that the audience needs and wants. So, we’re going to keep this conversation going at a later date.

I thank you so much for having me. It’s been a pleasure speaking with you and you guys are doing great work.

To the audience, we thank you for being with us again. My goal is that every time you listen to another one of these fascinating futurists that you’re learning a little bit more, so we’re going to get you there. We are moving you right along. I’m praying that you’re getting discoveries with every futurist that we bring. All right guys, until next week we’ll see you. Bye. 

Our Guest

Marie Clark is an expert in the intersection between human capital and the rapidly maturing field of data and analytics.

Through consulting, speaking and teaching, Marie helps clients build “data-ready." organizations that will thrive in the Digital Age. Marie’s training programs teach “Everyone." how to leverage data in their jobs, giving them major advantages in solving problems and identifying opportunities.

Marie is a member of the Association of Professional Futurists, a founding member of Howard Dresner’s Real Business Intelligence Community and a member of the Expert Network at the International Institute for Analytics founded by Tom Davenport.

She has 20 years’ experience working with Fortune 50 companies, including General Electric, United Healthcare, and Optum Technology, along with 10 years’ consulting experience with clients of all sizes and in all phases of maturity.

Guest Link

http://ambientintelligence.global/

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