December 22, 2020Our Top Blog Posts of 2020
Welcome back to our “Analytics Leader Spotlight” series, where we get to share the stories of the people who are transforming their organizations and others with the power of data analytics. In today’s spotlight, Cort Johnson, VP of Growth at AtScale, interviews Jen Stirrup, CEO of Data Relish.
Jen, we love sharing origin stories of how people have built up their careers in data and analytics. Can you give us a quick introduction about yourself and how you got started in the data and analytics space?
A: Well, I actually started to learn to program when I was eight years old and I realize that probably doesn’t make me sound very normal. Most kids at that age are playing outside and are actually doing fun things. I just got bitten by the bug very early on. I always found throughout my career that understanding data made me absolutely essential to many businesses. Because if you understand the data, you understand the business. If organizations don’t understand their own data, then they’re not listening to what the customers are saying to them, they don’t understand the industry very well. So for me, I think if you really want to have a career that is robust and almost immune to changes in the environment, understanding data is a great place to be.
And just out of curiosity, what made you interested in starting to program? Was it that you were tinkering or trying to build computers or was it something else?
A: Yeah, so a family member used to work for a company called Radio Shack and I’m aware that probably dates near terribly, you still have radio shack in the U.S as well. I miss Radio Shack. It was great going in on a Saturday and looking at all of the bits and bobs of equipment. A family member worked for them to try and fix their computers. So somebody had this computer and they basically just said they can’t fix it. So fortunately enough, my family member fixed it up and then gave me a call and I learned to program. So it was all go-to statements. And I read about texts, the decimal, and I think there I was probably a quite strange kid. But I really enjoyed it.
Working in tech, you tend to meet more people who are like you that got excited and interested in programming from an early age. So while for some that may seem foreign, I think it’s actually becoming more the norm at this point.
A: I think you’re right. I think people are maybe more likely to admit to it now. I think that when you are a bit of a “data geek” at heart, I think it stays with you. It’s good to be the person in the room that understands the data and asks great questions. And for me that’s always been an ambition and something that I think we can all get better at. And I think that’s why it’s been such an incentive for me to stay in the data industry.
Well, that leads me into my next question. You’re considered to be the “Data Whisperer”, and also CEO of your own company, Data Relish. Can you speak to us more about what Data Relish does and what you mean by data whisper?
A: So the “Data Whisperer” tag came almost as a bit of a joke because I got quite a small quiet voice. And I think the thing with that is it was about teasing things out of the data that nobody else could see. And I like being able to do that. I think I love telling organizations things about that business that they didn’t know. The thing that I normally do is I speak to the senior leadership first, so nothing’s a surprise. And then when we speak to everybody where they’ve already had some visibility and they are not knocked off balance by someone coming in and saying, “Hey, look guys, you know, did you know that this is not working for you? Did you ever look at this avenue?”
I see data as a way of giving people an opportunity to become more understanding-driven. And that’s what we try and do at Data Relish, to try and give them a data strategy, direction and a roadmap. I think organizations sometimes feel that the industry itself is very hot. There’s a lot happening and where do you start? You can’t exactly say, “Well, I’m going to wait for things to settle before I decide to do things with my data.” The world just does not work like that. So I try to turn data into an asset rather than a liability.
When you talk about your clients and trying to help them understand their data or to get a sense of why data might be important and a strategy around it, what do you tend to find are the top data challenges, for either analytics or data that your customers or clients face?
A: I see lots of challenges in the UK and in Europe. We’ve had GDPR, the data governance, data privacy laws come in. And I think that organizations confuse those laws with data governance. So they think they understand the data and I will have checked a box, but it’s so much more than that. People, I think, don’t always understand how much data they’ve got and the amount of repetition in data as well. So that’s the big challenge that I see.
I think another big challenge is that organizations don’t always know what success looks like for them. They’ve always got different ways of measuring what success looks like. So for some, they might say, “I want to know more about my customers.” And all those people in the same organization might say “Well, I want to cut costs.” But those things are not mutually exclusive necessarily. It’s interesting to me because I want to know what they are trying to achieve overall.
We appreciate the focus because focusing can really help us to deliver measurable success that people can see, and they can feel. Normally I go in when customers are in a bad place and that can sometimes put people on the back foot a little bit. And normally that’s the result of a crisis somewhere. And that involves an executive who’s been tasked with trying to solve that. So that usually means it’s high visibility, usually high risk or some high risk has been mitigated somewhere. And you need to start to turn that around from a negative, into a positive, so we can demonstrate value really quickly. So lots of challenges, but these are good things because it allows us to create solutions where people think, “Yes, you know what, I’m really glad we did that. We’ve changed things for the better.”
You talked about a couple of challenges, one of them especially in Europe with GDPR and what that means from a potential governance standpoint or compliance standpoint. But also, understanding how much data you have and how you can use it. What do you find as being those mission critical challenges that executives end up walking into, or the “crisis” that these executives have to walk into to fix. Does it tend to be more of a compliance issue or does it tend to be more of using data for competitive advantage?
A: I think more of a competitive advantage. And it’s when you start to unpack that you realize that sometimes the people in the organizations are competing against each other, which is not always great. Data can be such a political item and I think that’s when it starts to get complex within the organization to see. You have to give a bit to get a bit. I worked for one organization where the head of business intelligence walked out of the room when the head of IT arrived, because it was so much politics. You have to try and seal it. You know, we have to point all in the right direction and then to the same direction. I think when I go in and you may find this as well, you see organizations where you’re inheriting a lot of issues and it just happens to be being surfaced in the data, that the issues are there. So people think it’s a business intelligence problem, but it’s actually a chain management issue. It just happens to be visible in the data and I think that’s why data is such a political issue. It’s something that I see quite a lot. And for me, that’s a huge challenge. It’s a shame because I want people to be successful. Data seems to impact organizations in a way that technology does not. I think people are understanding that the two things are quite separate.
Even when you’re working with these executives, the political issue between IT and the business executive to your point, data is being cornered by different pockets within the enterprise. Do you find that the crises have come about through the business side of an organization, or do you find that they typically come from the technical side of the organization where some of us might think just because it’s data, it may relate better to technology than it does to the pure business component of the enterprise?
A: I think often it’s led by the business, but I do see a huge disconnect between business and IT. I think it’s a real shame. I think that’s usually because IT projects have not always been successful. When you go in, you’re inheriting all of the drama that took place over those projects. I think often I see it comes down to cost as well. People can sound about how to lower the cost and the business will come along and say “Well, we want to do all these things and we need to do this in a cost effective way. We don’t understand why things take so long.”
I think people do get quite stressed about data, but you can become quite process-oriented. Organizations need to understand that everyone should be engaged as part of the process of understanding and using the data. We’re all members of the creative class. So we can’t just bring my team when something goes wrong. I think that’s really important for people to see that they are part of that creative process. And that’s one thing I do try to explain to organizations as we see, you need to move forward from this, and we only want some bit of why this is going wrong. So my team might say, “You know, if I give the business this piece of data, they just make a mess with it. And then I get spreadsheets that I need to inherit that I need to fix and I don’t know what went wrong with them.” And then the business might say, “Well, we’re in spreadsheets because you’re not giving us good tools. And that’s why we’re here. We really need proper business intelligence.” Then it turns into sometimes an issue of, well, who’s going to pay for that. How does that get implemented in the organization? But I think unless you get real business sponsorship, it wouldn’t be that successful. I think that’s important to see data as part of the whole business.
I was with one customer and it turned out that their finance team had put out an entirely new system without consulting IT. And the only way that IT heard about this is because someone in the department raised a support call and they said, “Look, what’s the system?” And I just sat at my desk. I was sitting with the CTO. His members from the support team ran upstairs to the finance team to understand what was going on. And they just couldn’t understand how they’d manage to do this. And the reality was they had a budget, they were fed up with the IT provided contact center solution and decided just to change it themselves. So people will often take ownership of things themselves rather than doing things in a joined up sort of way. So that’s one thing I do try to emphasize. There are lots of challenges, but everyone’s responsible for taking a little piece of that and fixing it and trying to move forward from there.
I think you’re right, there’s becoming more of a gray area between the business and IT, where lines of business have the budget and somewhat of the technical chops to be able to implement technology to solve a specific problem that they have. One thing that you brought up in your answer was around the trust of the reporting. So in the business intelligence itself, making sure that you believe in the reports and believe in what they’re telling you so that you can make those data-driven decisions. I think that really comes from trusting the data itself. When you think about data and trust, why do you think so many people are struggling to have that trust of their data today?
A: I think it’s because they can’t interact with the data properly as they would like. Because they can interact with it, they don’t always see the data lineage, where the data has come from and how it got there. When you look at something like OLAP, when you’re building up those cubes and trying to understand large amounts of data, having the business involved as part of that will really help people to adopt the new systems and to start to trust the data. Otherwise they go off into Excel. There’s nothing wrong with Excel. Lot’s of businesses run on Excel, but Excel can be misused for lots of things. I know when I go into organizations, often people talk about big data. Often it’s the little data that is running the business as well. I think it’s good to try and build a very business-focused understanding of that data that does account for large amounts of data as well as the little data that’s important too.
We love that you bring up the term, OLAP, and being able to do the “what if” style of analysis is so important to lines of business because they’ll use products like Excel in order to do analysis. It’s amazing how important that tool in and of itself is still to the business and how they operate today.
A: Yes and I think people sometimes move into it because they’re trying to take the data and make it human scale. And when we live in a world of machine scheme data and machine size data, we still need to make it human scale and small so that we can understand it. We are not designed to deal with billions of data points, we do not work like that. That’s where I like OLAP so much because what you’re doing is taking that human scale and making it accessible from machine scale data. And I think that issue will become more prevalent as we get more and more data. No organization ever said to me, “You know what, we’ve got enough data now. We’re done. We’re good.” No one ever says that and it’s not going to happen. I think we need to accept at some point that this is the thing that the future business has to deal with. They need to think about scalability and how we can try and make things interactive. Because we know that organizations don’t have a set of list questions to work to when they’re examining the data. Interactivity is really important.
When you work with your clients and even before you start an engagement, how do you think about success? How do you create metrics of success and then how do you ultimately measure that success come the end of a project?
A: I try and measure things like data cleanliness. I tend to use a rag system right down the green. I know that’s not very colorblind friendly. I do apologize. But often it gives me a very clear way of saying, “Look, you know, we found all these issues and that can be anything really. It could be missing data. It could be even an analysis to understand the data that your competitors are capturing when they onboard a new customer, as opposed to the data that you capture from a new customer. That can tell you a lot as well. You know, if there’s just a difference, what are they doing that you are not. Sometimes you can even look at the currency of the data. How often does the data move and how often do you need that data refreshed? Where would you like to be?” So I try to just do that rag status first. I do try to make things very number oriented. I tend to find that people get very much doubt down and bogged down by the numbers. And I thought, well, “Let’s just make it simple and move people from a Red to an Amber. And then that’s some success that people can see.
That’s fascinating! Going from a Red to an Amber, is it a qualitative, quantitative or blend of those two in order to make that move?
A: It tends to be a mix of both. So when I look at a database or a system, I might say “Look, how much missing data have you?” It’s quite easy to do an analysis and you can show with a metric to say that “80% of your data is missing. Why is that?” I found cases like that, and then I’ll go back to the business and they say “Well, the interface has to be good. And the interface doesn’t ask us the right question and it doesn’t have the right drop downs. Where are my customers?” They make me laugh. I did an analysis of their customers and it turned out that most of their customers were Afghani people andI thought “Why is it that about 70% of their customers are three years old and from Afghanistan?” And it turns out that the web form, when they onboard a new customer, they don’t make it compulsory to specify your nationality or your age. So the age was three years prior to the current date. And so that was the default. And Afghanistan came to the top, because it was first in the list alphabetically. So I get back to the customer to say “70% of this data is just not filled in. You don’t know where your customers are coming from. You don’t know their age.” I still cringe when I think about it. It’s what the data captures.
There’s obviously a process around understanding your customers and recording their data that you’re not getting. So one of them blew up because they said, “I teach how to fix that problem. So then we’re back into the politics again. So I had to say, “Well, I can see that these people signed up yesterday and you know, they’re mainly Afghanistan citizens who are a few years old.” It was just awful. I don’t like going in with these sort of things which do embarrass people. But until they see it, they can’t do anything with it. So I must say I’m not always popular. But I think that’s the sort of metrics where they can show a difference. Then I could go back. It’s only a few weeks to seal it. You know, we’re now showing much better representation of what your customers look like. So that then becomes easier to show that the voice of the customer is there. So that was more quantitative because I can move from, three year old Afghani children, to something that looks more sensitive.
That plays into your point about trusting the data too. If you’re not capturing the data accurately, then there’s a lack of trust there. I’m sure that was another metric of success that you were able to use in that project specifically.
A: That’s right. And sometimes that’s just qualitative. I have gone around to all IT departments and business teams and said things such as “Well, how much do you trust the data?” They give me a Red, Amber, Green, and then I can get back and say, “Well, one hundred percent of people said red.” And it’s just mortifying. But then I can get back and say, “Tell me about consistency.” And that just opens up a whole bunch of things as well. Normally I can put these things together and then I can say, “Look, there’s clear requests from your teams to have a new system.” Then you move forward from there.I think sometimes these complaints about data don’t always get there. So they make some teams appear as support systems, but then it becomes easier to build a business case to say, “Look, we have all of these problems right across the business. We can solve these by implementing something that’s much more business-focused and much more business-friendly and also more consistent.”
Absolutely. Building the business case for solving a problem is necessary, especially at that enterprise level. You’re such a wealth of information. And obviously we love following you on Twitter and all of your social outlets. I’d be curious to learn more about where you like to get your information and to stay on top of what’s going on in the ecosystem.
A: Yes. I do a few things. I use a solution called Sighteer. They send me great tailored information every day. I give them a list of things that I’m interested in, leadership and data science. Then they send me a curated list using artificial intelligence. And they do that everyday for me. So that really helps me a lot. I also tend to read up on industry blogs. I love data visualization, so I always follow what Steven Fuze is doing. I follow your blog as well. I love thought leadership. You’ve got some really great thought leadership there and that’s what I like. I like things that feel relatable, that I can understand the business perspective. I think if sometimes people go too deep into the technology, then it’s a sort of bits and bites kind of level. I think it becomes harder for business people to relate it to what their problems are. So I think that can be a tough thing for getting the right audience for very technical information.
That’s very kind of you to say about the AtScale blog. We try to do as much as we can to be as educational across the different persona types in the business, because to your point earlier, a lot of these data problems or business problems. The better we can do to articulate solutions to a business person, the easier it is for them to try to solve the problem.
A: Yes. Cause I really think that leaders do need that advice. I feel quite strongly about that because when I speak to the C suite, sometimes when they get to trust you a little bit, they will see things like, “You know, I just don’t want to feel and look like an idiot in front of my team who are way more technical and savvy than I am.” Because when you reach those dizzy heights of leadership, you don’t always get to code or read all the technical blogs and it can feel that your team is just running rings around you. If you can give people a vision and harness that energy towards something more successful and give people those insights, then the leaders don’t feel quite as much on the back foot. It is hard to be vulnerable and be a leader at the same time. And I think that is a pressure.
That’s really a great point. You’ve obviously been incredibly successful in your career. Just thinking back to your earlier self and other folks who are just getting started, I’d be curious to know what some advice you have for folks, early on in their career might be.
A: I think you need to own everything you do, whether it’s small or big. If you don’t get the small things right, then you won’t get trusted with the bigger things. Earlier today I was looking over a PowerPoint deck for someone and I tightened it up, just tiny things. It looks better and it probably makes me sound really picky, but I thought to myself, “Well, how can I put myself in the perspective of the person viewing that? I don’t want them to be distracted by small formatting issues. Sometimes people are. I think if you own everything you do, whether it’s small or large, then you do get trusted to own the bigger things as well. And this is something that I do see with graduates, that I have employed or I have mentored in some way. Sometimes they expect to run before they can walk.
There’s almost a sense of entitlement, “Why am I not getting to do bigger things?” Then I have to get back and say, “Well, you know, you took half a day to do a PowerPoint deck slide. You know, you need to understand why that took so long, what the problem was and what you don’t understand. Asking for help is the second piece of advice and that is something that I have struggled with. You do get to the point where you are just too busy and you do need to delegate and you need to understand what’s your personal strengths and what’s not. And that can be quite soul searching. I think in some ways it can be easier to admit to yourself what you’re bad at and what you don’t like then as to say, “Well actually, I really did a good job of that.”
My third and final piece of advice would be to journal. I write a journal so that I can see patterns in my own behavior. I’m not always transparent when we move around each day. So it works for somebody that I had quite a few issues with on the team and I couldn’t understand their point of view. So I really started to journal. And then I started to think, “ I can see perhaps I was not good at asking for what I wanted and how I wanted it.” And I think it’s a good learning thing for me to do because instead of saying that a person never does it right, it was easier to look at a journal and say, “I should have made more of an effort to ask better questions” I think it’s about being humble enough to say, “Well, that was a growth thing. I can get back, apologize and we can have a reset and move forward from there.” And I noticed that just as a pattern, I might not have seen that unless I had journaled. So that would be my other point is to really have self honesty and to try to look at things through different lenses in the same way that we do with data and do it with ourselves.
The self awareness component is so important, I really liked that you brought that up. Just being able to be honest with who you are and understand what you’re good at and where your flaws are and then to strive to get better, but surround yourself with other people that can compliment you as well.
A: Yes. And it’s hard because it’s a good thing to do. I think it’s a growth thing and growth is always painful.
Thank you, Jen! If you’re interested in hearing more of these conversations through CHATSCALE, you can visit atscale.com or find us on SoundCloud. If you would like to hear more from Jen, please visit her website, datarelish.net as well as jenstirrup.com. You can also find her on Twitter, @jenstirrup.
Want to hear from more analytics leaders? Check out our past interviews: