Redefining the Future of the Modern Big Data Economy

Here at Countdown Supermarkets, I lead a team of about 70 to 80 people with approximately 10 to 30 direct reports.

So this is probably one of the biggest data and analytics teams in New Zealand, and our remit has spread from data ethics, data excellence, and data governance to master data, personalization, data science, supply chain optimization and food. We support all aspects of the business with different types of analytical and data solutions. After being with Woolworths New Zealand for about 18 months now, I can say this has definitely been the hardest job that I have ever done due to the size of the opportunity and also the level of responsibility on our shoulders to deliver superior analytics every day for both operational purposes and strategic decision making as well.

Drawing insights from this incredible journey, what do you think are some of the major pain points prevailing in the market lately when it comes to data analytics and the technologies associated with it?

The central pain point at the moment is definitely around the speed of the data. We've got so many opportunities to collect data from many different places, and it can come at different points in time—at a lighting speed. Subsequently, managing all of that data in a way that makes it useful for people is really challenging. One of our biggest challenges internally is knowing where to go to get the data and gauging its quality and applicability. With such a vast analytics team that loves its data and analysis, it is a huge burden on the organization if it can't make sense of it quickly. So I think that's definitely a big challenge certainly in our organization around specifically managing big data.

From your perspective, what are some of the most promising technological trends emerging over the past few years that are helping tackle these pain points?

The most important trend is productivity tooling that democratizes data science to a broader group of data professionals. As a big fan of productivity tools, I think we can't continue to manage data and derive value from it in the same way we've always done it. It's too expensive to be able to handle data in the same way. And therefore, we have to lean on productivity tooling to enable us to manage data proficiently. In the data management space, we keep experimenting and implementing tools, which play a crucial role in showing the data lineage of the tools and how the data flows through the organization in an automated fashion. The next promising trend is data quality monitoring tools, which we've also been implementing. This helps us define the basic business rules of what makes data correct, useful, and usable because we want our leaders to be confident around the data they use for decision-making.

I think what follows after is that once you have built a model in weeks, as opposed to months or years, getting that model into production and then being able to monitor those models is going to be the next area where organizations are starting to experiment and push the boundaries. Taking stock of this important trend, we're exploring tools that would be able to support us in that space in the near future.

Finally, I'd like to know how you envision the future for the next couple of years with all these potential disruptions and transformations taking place?

I believe that the future is always about people. Our biggest challenge is providing an enjoyable workplace that makes it easy to bring out an employee's best work. Also, finding great employees is one thing, but retaining them is a different challenge altogether. Organizations worldwide are facing the challenge of attracting great talent and retaining them as people are becoming more motivated by the opportunity to be creative and innovative than just minting money. At this juncture, I feel we will rise to the challenge while innovating a much better working environment for people to grow and develop some essential products that drive value for our customers.