No Silver Bullet for Data Success

Mark: Welcome everyone to a great interview with Gladwin Mendez, who is the Chief Data Officer at Fisher Funds. Gladwin, it's great to be with you today. Why don't you go ahead and share just a little bit about your background, how you came to be the chief data and analytics officer at Fisher.

Gladwin: I'm the data and technology operations officer at Fisher Funds, the fifth largest superannuation and investment firm in New Zealand. I ended up here through my 15-plus years working across consulting organizations — Deloitte, KPMG, PWC — building analytics teams. All those things have culminated with me landing up at Fisher Funds. I have a strong analytics-technology-risk background. Did an engineering degree and sort of got involved quite a bit with presenting to universities on analytics to cultivate that grassroots level, and also top-down involvement, in everything from data analytics to technology.

Mark: I understand that you're going to be participating in the CDAO Deep Dive, Asian Online Data Innovation panel coming up soon. What are some of the differences you think about between the community in New Zealand and the Asian data communities in terms of challenges and ongoing issues, and how can each region learn from each other's success?

Gladwin: I think the big one that I see between the regions and New Zealand and the Asian region as a whole would definitely be two things: the Asian regions generally have better access to people and better access to technology and cloud infrastructure.

Whereas New Zealand is kind of tucked far away, sometimes, we don't even get included on maps. In a nutshell, what can we learn? Us Kiwis and data leaders should take a step back and then take a more mature approach to data instead of always, constantly, Band-Aiding and fixing things.

Learn to leverage global expertise through global conferences. Everything's digital and no longer do you have to fly over. You can just jump online and leverage that great global expertise.

What others can learn from us Kiwis is definitely how to better MacGyver a solution and be more agile, breaking down silos and working on what I would call collective excellence.

Mark: The panel you're going to participate in is “Positioning Data at the Forefront of Business to Drive Consumer Engagement.” If you could share a little bit with us about what you see are the top three drivers of data monetization that you're going to share on the panel and that you think will have a positive influence on data application and usage in 2022.

Gladwin: The first one I'll start off with is the foundations of new innovation. It's interesting that was a resounding theme across all the leaders on the panel. Ensuring you have strong foundations around your strategy, people, process, technology, and data will be key. It was a pleasant surprise that everyone on the panel unanimously agreed. I'll use the analogy of walking up stairs. Think of your left foot as innovation and the right foot as foundational work. How do you walk upstairs? You take a step for innovation, then you take a step with foundation. That's how you deliver value quickly and learn to monetize your data.

The second point, if your data isn't clean and you don't have a data quality program in place, no one's going to pay you for bad quality data. If you're paying for a Ferrari and you get a banged-up old car, you're going to be mad and you're not going to pay for that.

And finally, as people get more mature. They'll look at not just the data monetization but bundling up predictive machine learning algorithms and AI models, and so on, and looking at monetizing those. For example, did you know that the Netflix recommendation engine is worth $1 billion a year, according to Business Insider?

So, it's not just monetizing data, it's monetizing everything around it. But as always, the same rule applies to data quality. The model has to be robust and good before you can sell it.

Mark: What are some of the data innovation strategies that you've heard about at the event on data innovation? What are some of the top strategies that are out there in the Asian Pacific?

Gladwin: It's how can you deliver value quickly? That's the key theme I'm seeing across the conference this year, you know, things like low-code data approaches to machine learning and AI, to the machine learning - AI experts out there.

How can we leverage off these low-code, simpler platforms to up-skill our data people more quickly and efficiently, and leverage the learning of the technologies, algorithms, and models to deliver value quickly? That's what I'm thinking about for my business, but again, with a big people focus.

Mark: Without giving away too much here, are there some exciting technologies or solutions that you have your eye on? I don't want you to share all the insights, but just a few. Can you give us a little bit around what you're going to share as you discuss the various topics at the CAO Deep Dive, Asian Online Data Innovation event?

Gladwin: There's no silver bullet to data success. I've had that strong people focus throughout this interview, and its people that implement change in tech.  It's not like you put out a technology and then you can maybe have the change management across data culture.

I don't think it's going to be a surprise when there's that focus on positioning data with “people” written all over it. It's going to be the people driving and enforcing that, trying to create the data culture, and increasing adoption within the business.

Mark: That's a really key point I'd like you to elaborate on. There's been a big move around the world on this whole idea of data literacy and creating a data language within the business in terms of their ability to understand and assimilate various states of data quality — might be the availability of data, the formulaic algorithms that derive key performance indicators, etc. Can you talk a little bit about what you're seeing around the whole data literacy, formalization movement down in your region?

Gladwin: It's got massive focus. I think people have tried to implement the technology and adoption has not been great. There are organizations that have chucked millions of dollars into an analytics program to just end up with a single spreadsheet at the end of it and very low adoption.

So, it's thinking of how can you take people on the journey? More importantly, how can you deliver value quickly with these analytics programs? The people who are going on the journey, understanding the challenges behind what you're delivering, and the value.

So, it's literally taking people on that journey. That's one of the key focuses: How do you educate top-down (the execs, the board)? Because the dashboards that they look at are based on data literacy.

Also, bottom-up — how do you educate people, move them more to self-service, and how do you create that closed-loop program? If they're identifying issues, they know who to go to, to help solve their problems. 

Mark: What would you say is the secret sauce in that landscape for an organization to kind of get it right and make it effective, because you dropped out the key word that everybody is really looking for, this holy grail of adoption.

But there's a lot of implications because I'm not going to adopt something that I don't understand, and not going to adopt something that I don't trust, that I believe is not secure. So, when you think about adoption in this whole equation, what is the secret sauce in your mind to achieve data adoption?

Gladwin: If you're not going to educate your organization on data and the art of what's possible, you're not going to get adoption. Within my team, my data manager used to do an amazing job of running lunchtime sessions. It's only an hour out of people's lives. You'd run it over lunch. People could just join in and listen to the presentation. She would genuinely just talk about some of the work she was doing, some of the insights, and the amazing questions we got out of that. She was so passionate. Find the right people within your team who have that passion and tag-team with them. Get the feedback, adapt, pivot to what works, and so on. When I update my data strategy, I'll be presenting that to the executives with full transparency so that they understand the overall company strategy.

This is how the data strategy sits there: I use a statement, “If you can show people what's in it for we, not what's in it for me, you get a lot better adoption.” If I help you with this, it will save you X amount of time later on in your monthly reporting and your finance or month-end reporting … you'll get way more adoption.

And then, you tackle that people challenge and opportunity. 

Mark: You sort of summed it up really well. The carrot leads better than the stick. As we wrap up the discussion, and I know the event's coming up on November 23rd and 24th, what are you looking for? What are the key points of discussion that you look forward to? And maybe these will inform some other folks that are going to tune in to the event for what might be of interest to them.

Gladwin: The conferences do an amazing job of getting real-life use cases and stories shared. I really enjoy the real-life outcomes and how people went on that journey and how they overcame the various challenges from people, technology, data, and strategy.

So, that's what I often look for rather than theoretical “Hey, if you implement X, Y, Z technology, you'll be able to do this” against “We've actually implemented this technology and this is the journey we went on, and these were the learnings”. That's really what I look forward to with these conferences.

Mark: That's amazing. Let's just assume that you're speaking to a CEO and a CFO in an organization. What message would you like to deliver to those folks as a pearl of wisdom from this discussion?

Gladwin: I will use a Maori proverb that sums it up perfectly. It goes like this: What is the most important thing in the world? He Tangata. He Tangata. He Tangata. Which translates to, “It is the people. It is the people. It is the people.” Having that alignment throughout the business and its people, processes, technology, and data is critical. That's how we're going to do better than our competitors.

You know, everyone's heard of the common culture eating strategy for breakfast.  I really believe that. If you don't have the people behind you, you're not going to get there. It’s the hardest but the most rewarding challenge and opportunity to leverage and overcome.

Mark: That's a great note to end on for everyone who has been with me here today speaking with Gladwin Mendez, who's with Fisher Funds. We've had a great conversation, I’m looking forward to staying in touch with him and learning from the innovations that he's bringing down in Kiwi land, as he likes to call it. Mark Johnson here, Editorial Board Chair for CDO magazine.