As senior vice president of research and development, his most recent role, Heuman was responsible for planning, scheduling and implementing data production and software programming with EA. Direct Marketing sat down with Heuman to chat about his new position and the path that led there.
Q: Congratulations on your promotion! Before we discuss your history with Environics Analytics, please tell me how this change will affect your day-to-day work and priorities?
A: This promotion is really focused around optimizing the company’s resources. We’ve recently integrated all of the custom services group—we’re all together now ‘under one roof.’ The data scientists who traditionally work on projects that use PRIZM5 and personify client-based profiles are together now with the statisticians and dana scientists. We are all geared toward data-driven execution and understanding the role of analytics, models and visualization tools so that we can better serve our customers.
Up until recently these groups have been focused on certain areas, doing their own thing and by bringing them together we hope to learn from one another, to consolidate the toolset, bring everyone to a certain level in terms of what the different software packages are that we have and to, of course, promote a one team kind of approach toward serving our customers.
Q: You have a master’s degree geography, you lead teams of programmers and data scientists and you’re an expert in market analytics and modelling. How would you summarize what it is you do?
A: That’s a hard one. I’m not a data scientist. I work with data and I can mine the data and I use the techniques to find things out. But I really see myself more as a problem solver—someone who can take the desired end goal of what clients will want from us and really try to think of the optimal route to get there. Sometimes its circuitous, of course there are always challenges along the way, and I see those more as challenges than obstacles—we can do it, it’s just a matter of doing something to overcome it. I’m a problem solver focused in market research, data analytics and identifying opportunities through data.
If I were to look at my career, it’s always been one of a practical approach to solving problems and using whatever tools you have in the moment to address the issue and find the best answer. If it means programming something because the tool doesn’t exist, that’s great, but if you have tools that are out there that can do it just as effectively and give you the same or a similar answer then do that too. Whatever it takes. I’ve always promoted that kind of can-do attitude—you’ve got the tools, just use what you have. There’s no reason to reinvent the wheel if there is already a serviceable wheel.
Q: How have you managed to balance complete emersion in all things EA with staying on the cutting edge of wider industry?
A: I think it’s investing your time in appropriate ways. There’s clearly a need to understand the methodologies, to find the best data sources and partnerships out there so that we can build the best data products. That all began in my days at Compusearch and understanding what the possibilities were. Being mentored by Dr. Tony Lea of course helped, having a lot of experience there, and so that’s on the data side, just understanding what you can do within reason and producing the best results that you can.
Now, at the same time, the world is always changing and the internet has been around now for what feels like forever but it’s probably only been 25 years. But the e-commerce side of things has clearly changed and shifted the retail landscape. The idea of social media and how its quickly taken over people’s lives is another big thing. And how all these things interact is just something that I feel we need to stay on top of. It’s a big part of marketing, it’s big part of understanding the consumer.
This is where you need to balance time between understanding the products and the marketplace and the needs of our customers and improving the methodologies and finding the best data sources with understanding the future and what’s to come and where are we heading. It’s that balance. It’s not an hour or two a day, you can’t put a number to it, but there’s many hours of the week where you’re just trying to catch up with what’s going on in the industry.
Q: What EA does is impacted not only by the fast-changing discipline of data analytics but also social trends—for instance, are neighbourhoods becoming more or less homoegenous? Are demographics becoming more or less important and which characteristics of people are particularly good indicators of how they will behave? These are not static values by any means. How does that factor into how you’re developing new products—the fact that social dynamics are by nature dynamic?
A: Things are always changing and to simplify that world we at EA take a snapshot in time. We’re not trying to keep up with monthly changes at the postal code level and the people who are moving in and out. We’re aware of privacy issues and so we don’t get down to the household level, we always deal with aggregate data. We essentially come up with annual estimates so the dynamic that’s being captured is overall of bigger trends as opposed to the minute details. That being said, it takes us about nine months to produce our estimates and projections data. This is the earliest we’ve ever started but we’ve already started our 2018 data processing for release in Q1 of 2018.
We’re trying to make our best estimates of what’s likely to happen in the 2018 year, starting today, and it’s hard. This is where the partnership data is very important because they do give us insight into the changing attitudes and the changing behavior and the changing landscape of Canadians—by region, by city, urban versus rural, young versus old, affluent versus poor, educated to uneducated. All of those things are things we consider and they all factor in at some level in terms of what we do and how we proceed with our understanding. It comes down to having a good comprehensive view of the landscape.
Q: What’s getting more challenging about your work?
A: What’s getting tougher is just clever ways to use the data. We invest a lot in technology and faster computers make it easier to process the data but you still need to have clever methods for how to take a sample of 30,000 respondents to a survey or a client base of 100,000 and you have to know what to do with it. A lot of the traditional techniques work but they don’t always work because customers are inherently erratic and unreliable.
Fifty, 60, 70 years ago brand awareness was critical and once you were a customer of that bank or jean or car, you tended to stick with that for years. You could count on that kind of behavior. People today are less loyal and that loyalty factor, that sticky factor isn’t there. So projecting what’s going to happen or being able to state with some reliable estimate of what’s likely to continue is very difficult because the introduction of a new website, the introduction of a new retailer, the introduction of a new technology can disrupt that. People overnight can shift their allegiance from one to another. Our customers, from a marketing perspective are trying to understand, how do we communicate with these people? What’s the most effective means? You can’t assume that what used to work will continue to work.
Q: You mentioned Dr. Tony Lea as a mentor of yours. As you embark on your tenure as chief analytics officers, what are your thoughts in terms of mentoring less senior professionals in this industry?
A: When I was started out the primary goal was about learning and understanding. It wasn’t about management style or communication, it was really about knowledge. How to best approach and tackle a problem and to do so in a creative way but also a practical, functional way and that’s something that I think Tony imparted.
We have a very loyal staff here, overall. The people that have worked with me and for me in some cases have been with us since day one. Overs have been with us for 10, 11, 12 years. I’ve never seen myself as a mentor. It’s probably happened over the years but I’ve never looked at that as I’m mentoring people, I’ve looked at it as I’m assisting people along the way so that they can learn what I know and hopefully adapt and change what I know to suit their needs. There’s no one way to approach the issues and challenges that we face, there’s always an alternative approach. I’ve tried to show people that the way I would do it is not necessarily the only way.