Alexis
Hi everyone. Welcome to another episode of Data Dave Dives Deeper. I’m Alexis, your host of this podcast as well as our favorite podcast Talk Tech with Data Dave, and I’m here with Dave and a new friend. So, hey Dave. Hey Tom. 

Tom Redman
Hey, thanks for having me. 

Data Dave
Good afternoon. This is Dave, Data Dave, and I’m delighted to be here with Tom “The Data Doc” Redman who we met and spoke to at length at DGIQ last December.  

We’re here to have a conversation about data, and the way that data behaves, and the way data drives business. And so, I’m delighted to welcome you to Dives Deeper Tom! Why don’t you say a little bit about yourself and a little bit about how you got into data in this space. And why you are called “The Data Doc”? 

Alexis
Yes, I’m really interested in that. 

Tom Redman
Fair question and thank you so much for having me. I’ve been looking forward to our session since we met.  

Look, I trained as a statistician and after I got my degree, I went off to Bell Labs at a time when the telephone network was converting from an analog network to a digital one. What it was carrying was converting from voice to data. Really, my goal was to try to help understand the performance of that network and how we could make it work better.  

And I got this idea that if we could apply control charts which were all over the factories all over the world and adding so much value in factories if we could apply those to the operation of the telephone network, then we could make it perform even better.  

So, the great thing about Bell Labs at the time was if you had an idea if you could pull on a thread, if could find somebody to sponsor the work and so I was 0 for about, you know, 8 million on that over the course of 18 months or so. But one day, I got a call from a fellow and he said, “Well, Tom, I don’t run the network, but I pay these access charges. They’re about $20 billion a year. They’re our single biggest expense and it’s an unholy mess. Will control charts work on those?” But I had absolutely no idea, but that was the kind of thing that we were looking for, and it turned out he asked exactly the right questions.  

We applied control charts to the generation and verification of access bills. That structure brought out so many problems, basically simple problems, that we were able to attack and based on that experience we created a little lab called the Data Quality Lab and I was lucky enough to lead that lab for, I don’t know, some eight years, ten years or whatever it was.  

And so that was my start. Now you asked how I got the nickname “The Data Doc”. I left Bell Labs in the mid 90s and hung out my shingle and that turned out to be terrific too. I got to work on all kinds of problems with all kinds of people. But one day a guy named Chris Enger sort of gave me the nickname “The Data Doc”. Like, “Tom, this is real cool. You’re like a real data doctor,” you know kind of thing.  

I don’t know. I kind of thought it was silly for a while, but I tried it on and then, you know, I tried it out on people and they said, “Gee, it’s a terrific nickname. So, I have Chris Enger to thank for the nickname “The Data Doc”. 

Alexis
I love that. that’s kind of how Dave got his nickname. My partner in crime and I were like, “We should have a podcast with Dave and call him “Data Dave”.” And then it happened. 

Data Dave
Just stuck. 

Tom Redman
So right, I mean if you can have a brand with one word in it, like “Cher” or “Adele”, that’s best. Two words like “Data Dave”, that’s second best. I got three in my title, so. 

Data Dave
I’m not sure I can pull off “Madonna”. 

Alexis
But Tom, the real reason we had you here today was to talk about a book that you recently published. I know Dave has some like, really specific questions for you about all these things, but I would love to just hear the title of your book and a quick, like, here’s what it is. 

Tom Redman
The new book is called “People and Data”.  

One of the things that I learned when I was in Bell Labs, what was so great about it was I had one foot in these enormous AT&T problems and another foot in a laboratory setting, and they were working back and forth. We were taking hard business problems and trying to understand them at a little level of abstraction in the laboratory and work out solutions and then bring those solutions and tailor them to work in the business. I found myself just ideally suited to this duality.  

Most of the time throughout my career I’ve managed to have this company that allowed me to do both. So, with respect to “People and Data” – COVID hit, as everyone knows, and small businesses we got hurt pretty bad. I took that as an opportunity to go back into the lab.  

The question I ask is “Well, why is progress in all things data moving so slow?” I spend most of my time in data quality and everybody knows it’s important and everybody who does it right gets these amazing results, but most ignore it. Similarly, with advanced analytics, people who are serious about it get great results, but most ignore it.  

I really wanted to understand why things were going so slow, and I talked to a million people and rethought everything that I thought in the past and looked at my own successes and failures and others people successes and failures and did some hard analytic work to understand why things were going so slow. And the number one reason that came up was that we don’t include people- all of them- in our program and I see you’re shaking your head up and down like it’s so obvious in retrospect once you see it. 

By the way, I mean it even goes further that so many “regular people” I call them, when they get into data, they are so empowered. It is life changing for them. So, I wrote “People and Data” to try to capture this enthusiasm I have for regular people empowering themselves and getting involved. And then this sort of I guess it’s a mandate or instruction or a proposal that companies, and especially those of us leading data program, really emphasize getting people involved to the greatest degree we can, as early as we can. 

Data Dave
Absolutely. As completely and as much as possible is what we always say. We always get people saying, “How much should we have the business users and people involved in a data program?” And our answer is, “All the time from the very beginning and don’t give up at that point because they’ll be doing it for long after us.”  

Tom Redman
Every day! It’s kind of obvious when you see it like… we think if you’ve got data in your title, you’re doing all the data work. But you look at the larger organization, everybody else is doing data work every single day. 

Data Dave
Absolutely. We see it all the time. There’s people always think this is an IT or a technology or a data or a mathematician problem, and it really isn’t. So the data is only showing evidence of what people are doing, and they’ve just got to embrace it and move through that. 

Tom Redman
If you could sum up like the total amount of time people are spending in data in the company versus that fraction of the time that’s spent by people with “data” in their title. I mean, I bet you’d get a ratio of 30:1 or 50:1 or something like that. And by the way, these people aren’t giving any training. They’re not giving any support. And it’s just so… you know, once you see it in this way, it’s so obvious. If we get them doing the right stuff, then not only are they going to have more fun, do better work, but everybody’s going to benefit. 

Data Dave
Absolutely right, I mean. Everybody in the company touches data. Everybody, everybody, That’s something we’ve talked about a number of times is the fact that data is just evidence of people’s behaviour. It’s evidence of people doing things, so therefore everybody is creating data. Just by the act of doing something within the company, you are creating data, and therefore you have a responsibility to the quality of that data and the quality of your job and the quality of your output. 

Tom Redman
Yeah. Let me build on that a little bit. I mean, everybody has two roles. They’re a data creator and a data customer. And the data customer role’s just as important as the creator role.  

Too often people fall in the trap of saying, “You know, I work on sales. I got these leads from marketing. They’re wrong. I’m going to have to fix them up,” rather than just reaching back out to the marketing department and saying, “Why do you keep sending me this junk? Like, let’s work together so I get better stuff.” And so people stepping into the customer role and avoiding the trap of thinking they have to fix everything is just on the same plane as people stepping into their creator roles. 

Alexis
It’s amazing, Tom, the way you said that. Dave and I just recorded an episode of Talk Tech with Data Dave, where we were talking about change management and one of the things that we kept leading back to was culture. Dave, I don’t if you have more that you want to speak to that, but like, exactly what you were just talking about was what we were just discussing in the podcast. 

Data Dave
Exactly. I mean, one of the things that we talk a lot about is the change management and following through with data. Where data gives you the ability to measure almost anything that is happening in the business.  

And it’s interesting, you mentioned control charts. I’ve got a strong Six Sigma background, so control charts are core to my heart to a certain extent. And so it’s interesting, you were talking about that and talking about bringing the statistician, the deviation from norm, if you like, to this. And we were talking about change management and data and using data to start to say, “How is your business performing well, performing badly?” Not at the, sort of, macro-finance level, but at the micro. “Is this action in this process doing what it’s supposed to be doing in the most efficient way?” And using data to measure that and then get back to, “Well, if I’m now going to change it, I’m actually changing people’s behavior. I’m taking people forward into what are you going to do differently to cause this process to be better?” 

Tom Redman
I want to build on this a little bit. I mean, I also think there’s some context, and it’s not just about making a particular task more efficient. It’s about making the whole organization more effective and efficient. 

Data Dave
Absolutely yes. 

Tom Redman
I think…I don’t know, I’ll be interested in what you think about this Dave. I think that there’s a certain immaturity and some use of metrics in a lot of organizations where they want to cut it down very, very narrowly and miss the larger point.  

I’m going to write an article sometime that’s called you can’t measure love. And the point about that is, is we all agree that, like love, it’s really important in life. Well, nobody’s developed a love-o- meter. Nobody’s figured out the components of why two people fall in love or how relationships with their kids go and so forth. And it seems to me, sometimes like people lose sight of the overall effectiveness of an organization to dive down into some incredibly tiny efficiency metric where it ought to be way, way more hoistic. 

Data Dave
I couldn’t agree with you more to be honest. I really couldn’t. We’ve got a model that we use for this. We look at two things. So, we build requirements around data programs around two areas. One we call the “Articles of Faith” and the “Articles of Faith” is, “We believe the world would be better placed if our data was better.” It’s the noble goal. It’s the macro. It’s very big. “How do we make the whole organization more effective?” At the same time, it’s, “What are the immediate benefits of doing this?” 

So, looking at those two dimensions, those two areas of benefit and saying, “Am I improving the Articles of Faith? Have I got my North Star in site? Am I moving towards this North Star metaphor? Am I fulfilling my Articles of Faith? Am I believing that the world is becoming a better place?” And at the same time, you can’t get away from, “Joe wants to improve this tomorrow.” 

Tom Redman
Right. 

Data Dave
But by Joe improving that, are you also moving towards that North Star, in general terms. The reason we use a North Star rather the stake in the ground or any other metaphor is because we wholly believe in this space, you never actually get there. You’re moving directionally towards it, but it’s a nebulous destination. You never quite get there, and you might meander along the way to get roughly towards the North Star. 

Tom Redman
Look, I think that’s a really good analogy, and I want to build on it a little bit too. All data is not created equal. Some is way more important than others, and there’s an awful lot of data that nobody ever uses for anything that people spend a lot of time worrying about, “Well, how are we going to curate that, and how are we going to store it? How does it relate to this and that?” while ignoring that thing that you were talking about, “Well, Joe needs to deliver this package tomorrow.” 

Data Dave
That’s right. 

Tom Redman
There’s a storm going on there. “How are we going to get this there?” You really do have to balance those two, but part of it is just making space for both, and the way to do that is, stuff that nobody cares about, just completely run it out. 

Data Dave
Ignore it, ignore it. We collect too much data. Stop collecting the stuff nobody’s gonna look at.  

We look at it ,and I’m interested in your opinion here, we look at it very much as a cultural direction, which is the idea of putting in these programs at the various levels that we put them in at… the North Star and then at the Joe must do this… is to get a lot of Joes doing the same thing and kind of recruiting people into the movement, if you like. So, this data world is a movement within an organization. So how do you recruit people into this movement? And get all the Joes, all the Marys looking at, “How do I make this move forwards? Make this better for myself?” while keeping sight on that North Star. Keeping things moving and keeping that momentum going and building this culture of change and culture of improvement. 

Tom Redman
I’m really glad you asked that question. One of the things I think was most important in “People and Data” was I very explicitly listed five things that I think companies should ask regular people to do 

And the first of those things is they should become better data customers and creators in quality programs. And the second is, they should be using data to improve their business processes and their teams business processes. And number three is, they should be collaborating on larger efforts such as with AI or data monetization. Number four is they should be guardians of the companies assets in privacy and security programs. And number six is is they should… Everybody should be figuring out how to use a little more data. Excuse me, number five is how do you use a little bit more data to become better decision make? Right? 

For me, grounding in… no company is going to do all of these things at once, but as a North Star, “This is how we see people contributing”. And then if you see that, then you ask the question, “Well, how do we build our data organization to make it easier for them to do that?”  

You get very, very different chief data officers. You get very, very different people associated with them to the point we started this on is you think right away about culture and change management, right? And the good thing we have on our side is, people like these roles. I’m not going to say everybody likes every one of these roles. But on a by and large basis people like being data customers, they like improving their work, they like contributing to larger things. 

Data Dave
That’s a really interesting point. I mean, one of the things that frustrates people more than anything else is not having the tools to do their job. Data is one of the key tools as to what you need in order to do your job and to move this forward. And keep that view, that mindset on, “We’re not starting with data people.” The data people are a supporting organization. They’re not a leading organization. It’s the business that is leading in the changes around the five points that you just mentioned. We got these five areas of every business that we’re trying to improve with a view on the North Star, and we’re trying to drive that forward and trying to support people to have better tools to do their job. 

Alexis
I love hearing both of you say this because and Tom, I don’t know if you know this, but Dave, obviously you do and some of our listeners do, but my day job, I just do podcasting as a side job. My day job is in human resources with D3Clarity. And so my job is people. and I love hearing both you like intelligent men, been in the data world for years and years and years, saying, ”You know what’s so important? PEOPLE.” And I’m like, yes! Yes, I love it. I love it. I love it. Okay. I’m sorry. I didn’t mean to interrupt you. I just had to be excited for a minute. 

Tom Redman
We can’t say that point over enough. You can’t talk about transformation. There’s a lot of talk about digital transformation, and it kind of goes, “Well, open process, insert new technology and deal with the wet ware.” And you know “wet ware” as people, and I hope you find that as offensive as I do. Transformation is fundamentally about people and the way they think and the way they do their work and how they contribute and so forth. You don’t have to go back very long when like, all HR departments at big companies had great change management departments, not as many of them do anymore. But if you’re interested in somebody listening is, “Well, I’m an HR, you know. Is there a future in this data stuff for me?” There’s an awesome future for you. Get into this change management stuff. Dig in! Dave and I bring a set of tools. But I’m a statistician. I’m not sure what your background is, is but bring those elements. Help us flush it out. Help us understand communication better. Help us make it easy on people. You can make an enormous contribution. 

Alexis
I just love it.  

Data Dave
I’m a hardcore engineer that fell into this by a number of different mechanisms. 

Tom Redman
We need more poets than data.  

Data Dave
I honestly think you’re right. I do. Because I think there’s a huge part of that. And the number of people that we’ve spoken to in Dives Deeper in other areas, who are from the line of business, whether they’re nurses or HR people or salespeople, or various people that suddenly realize the data was broken, or their accountants or different things, and then they say, “Well, I fixed the data over here and suddenly my life got better,” and then they get anointed with, “Well, you did it once. Now do it again.” 

Tom Redman
Yeah, right. 

Data Dave
I find that absolutely fascinating, which is why we start these with, “How did you get here?” I’m fascinated that you’re actually a statistician. This has been absolutely great. I would love to collaborate with you more going forwards and talk to you more if there’s areas you’d like to dive deep into, we’d be very happy to have you back and talk more about change management.  

One thing I would like to ask is ,what do you see as some of the challenges, the biggest challenges going forwards and also if you don’t mind a good success story? 

Alexis
Ohh, I’d love to hear that too. 

Tom Redman
So, let me start with the good success story. I’m going to talk about one that’s in the public domain, so I can talk about it a little bit.  

I wrote a little HBR article with a woman named Mai Alowaish in I don’t know, maybe it was April or May last year, but Mai was the new Chief Data Officer at Gulf Bank in Kuwait. So she reached out to me and says well, you know, how am I going to get my arms around this? And we talked through various scenarios and one of the things that we did was we spent a lot of time asking Gulf Bank veterans, “What will work well in this culture?” And you know, Kuwaiti cultures, a lot of young people eager to learn. And veterans told us that people in the bank will love this idea that they’re a data creator and a data customer. So okay, we’ll explain to them what that means. Turn them loose, get some improvement projects going. 

So, what the question is. Well, how do you, like, she’s got this little team of five or six people. The banks got 2000 people in it like, “How are we going to create some leverage for her?” And we developed this notion of… I use this notion called an “embedded data manager” and she said, “Tom, I’d really like to call it an ambassador. Can we call it an ambassador?” 

Data Dave
Nice, good word. Good word. 

Tom Redman
Yeah, it was awesome. But we built this network. Of 100 and I’m going to guess forty. Don’t hold me to that number precisely. But a network of every work team had an ambassador, right? Somebody who was a first point of connection to Mai and her team. Of course, you know, how are we going to get people to sign up for ambassadors? And so, Mai had to go to the management committee and say, “Look, I’ve got this job, so I need your help. I need to name these ambassadors.” and the management committee then named these ambassadors and the value proposition she made with them is “Look, I want you to be the tip of the spear in your team for data. But what you’re going to get in return is you’re going to get world class training and you’re going to get world class support.” And she put this five-part training program together to really, like, get people into it. And I went and delivered one session. I felt like I was like a rock star for a week. 

Alexis
Like a data doctor? 

Tom Redman
Yeah, well, yeah, right.  

We tailored it. And of course, you never know how it’s going to work out. It worked out far better than I imagined. It doesn’t always happen that way. But we started with, “What’s going to work in this culture? What will people see that they like?” 

I mean, like, I mean, she had nine million things she could have done. She needed to get traction and her boss was enormously supportive. Her boss, by the way, made this incredible contribution when we talked to him, he said, look, because she’s talking about well, “Do I need a quick win?”, and it kind of got him on a high horse. He said, “You know, I’ve been in this industry for my whole career, I’ve never seen a quick win work. Let’s do it right. I don’t care what you pick, but I want you to do it right, okay?” 

Data Dave
But that’s an interesting move that a lot of people don’t take is to say, “My first step is to recruit people. My movement and bring everybody along!” Rather than go for, “I’m going to do this, particularly that or whatever,” it’s “Let’s create a wave. Let’s create a movement. Let’s create a purpose and a culture within the organization.” That’s a hugely different way than most people think about it. 

Tom Redman
Yep, I want to just add one other thing to the story, and that was the other person that Mai reached out to was the head of HR, right? I know somebody’s going to smile when I say that and say, “You know, look at what we’re trying to do. You know, can you help us?” and the head of HR she was just awesome! And provided so much help and shaping things and turned out her budget was bigger than Mai’s, so she supported a lot of the training and so forth. But I mean, she could see how this change was good for the bank. All what was in it for the bank and for HR. And so I’m… her name, by the way to Salma Al Hajjaj. You know Salma is high on my list of data heroes. 

Data Dave
I like that term as well: data heroes. 

Tom Redman
Yeah, that’s a good recent story. It’s in the public domain. People can track it down if they want and hear it in both our voices rather than just mine. 

Data Dave
Excellent. That’s a great story. I love it. I love the movement by the culture. 

Tom Redman
Right. 

Alexis
This has been a wonderful conversation, gentlemen. I have really enjoyed talking about data to The Data Doc and to Data Dave. This has been great. Like I said earlier, I just love hearing you guys both say that the answer to data is people, it’s just wonderful. 

If you get a chance, definitely check out Tom’s book, “People and Data” that you, I’m sure, can find everywhere and anywhere where books are sold. He’s nodding yes, that’s what I like to see. And then of course, we would love for you to listen to our podcast Talk Tech with Data Dave.  

And if you are interested in joining us for one of these Data Dave Dives Deeper bonus sessions ,please reach out to us at the talktech@d3clarity.com e-mail address and we’d love to have you on the show.  

Thank you, gentlemen, again so much, for talking with me today and answering all my questions. This has been fantastic. 

Data Dave
Right. And thank you, Tom “The Data Doc”. Thank you very much for speaking to us. 

Tom Redman
Thank you for having me.