Brian Ferris, Loyalty New Zealand’s CDAO and CTO, shares how he’s laid the foundations for AI adoption and moved the organization into the cloud over the past 12-24 months
What would you say have been your greatest professional achievements of the past 12-24 months, and why?
I have seen a lot of progress since joining Loyalty NZ two and a half years ago. Top of the achievements list has to be our cloud migration and strategic partnerships.
Firstly, we’re very happy with our cloud migration and in just a few weeks (March 2022), we’ll be completely out of our data centers and have no on-prem presence.
This has been a big journey. We’ve turned off a number of pretty clunky on-prem solutions in making the move and that opens up a whole range of opportunities for the next few years.
We have also introduced a totally different way of working with some of our key vendors, which is really bearing fruit. We’re investing in more meaningful, longer-term partnerships; I’m not a big fan of RFIs and RFPs and that real nickel and diming transactional approach to vendors.
I find people tend to get what they pay for and what they invest. So, we identified a number of key vendors that we wanted to commit to and build a strategic partnership with, and they’ve done the same. What we’re seeing is that they’re putting a lot of investment back into us. The longer-term benefits we’re getting from this approach are colossal, particularly in the cloud space.
What business challenges did you encounter while driving toward these goals? And how did you overcome them?
One of our biggest successes links directly to one of the challenges we faced. And it’s fair to say that what may be more obvious in hindsight can be tricky to identify upfront.
At Loyalty NZ, we’re all aligned under one strategy; focus on building NZ’s leading data-driven customer engagement business. We don’t do any tech for tech’s sake. The big challenge initially was that there was no widespread understanding of why we really needed to be cloud-based to advance. It was quite challenging initially to articulate the connection between needing to replace an aging, transactional server with something in the cloud to improve data-driven customer engagement.
Once we reframed everything in terms of ‘If we want to get this business outcome, and that’s the direction we’re moving in as a business, then this is what we need from a tech perspective to enable that’.
You’ve got to build those strategic linkages. Once they’re in place, there’s a shared understanding of the future vision and everyone can get on board with it. We’re not doing it ‘just because’, this is actually enabling where we want the business to go; it becomes a strategic priority.
Based on your observations in the region, how would you say the events of the past 24 months have affected business priorities in your industry?
In the past, a lot of organizations, and even us to a certain degree, have paid a little bit of lip service to analytics, because in ‘regular’ times, experienced leaders tended to be able to predict what was going to happen. A well-tuned gut feel was often enough to make pretty good calls.
Once the global pandemic hit, this rug was literally pulled out from under everyone and we could no longer rely on past experience as a predictor of the future. We needed to start looking much closer at what was going on and start saying, ‘OK well what’s the data saying in the last three months, what about the past month? Where are things tracking?’ The ability to do this provided invaluable input for decision-making.
At this point, if you were already cloud-enabled and had built a data and analytics team you could start leveraging it. And this is what Loyalty NZ was able to do. Organizations without data engineering capability or real analysts would have been way behind in their ability to examine the recent past and compare with previous years.
Organizations that hadn’t embraced the importance of all that foundational work, like data quality, data engineering and data platforms, are realizing the impact of their decisions and are rapidly racing now to catch up.
Those who had embraced it earlier and made the necessary step change and investment are likely looking to strengthen their data literacy programs at present.
What will your priorities be in 2022? And what are the key things you hope to achieve in the coming 12 months?
I’ve been talking a lot about unlocking machine learning and AI but again, not just for the sake of it. We want to do it in a way that actually improves outcomes for the organization. We’ve got a whole raft of potential right through the entire data value chain from data ingestion through to data insights.
We’re doing a proof-of-concept and trialing things. One of the challenges is that it’s a very fragmented market in terms of what solutions vendors are offering. Every man and his dog has a product or three. There are thousands of them. Many of the big players are trying to show that they’re a one-stop-shop by way of merger and acquisition. Some aspects of the resultant products are deeply brilliant and some are just really weak.
It’s very hard to figure out who’s good at what and where the value is. That will be a big focus for us, leaning into those areas without wasting too much time and then bringing those capabilities in so we can do way more with way less. It will allow us to have our technical people focusing less on the routine tasks and more on the highly technical problems, while our end users in the rest of the business can do more to slice, dice and mine the data the way they want.