THANK YOU FOR SUBSCRIBING

How Big Data Analytics Guided our Decision - Making Through a Year Like no other
Michael Coatsworth, Principal Architect and Mazen Kassis, Head Of Data And Analytics At Foodstuffs North Island


Michael Coatsworth, Principal Architect and Mazen Kassis, Head Of Data And Analytics At Foodstuffs North Island
Firstly, a little context. Foodstuffs North Island operates supermarkets, liquor, and wholesale stores and has an award-winning suite of private label brands. New Zealand owned and operated, Foodstuffs North Island is a co-operative and one of New Zealand’s longest-standing businesses. But at our heart, we are grocers, with an unerring passion for delivering for New Zealanders.
Like most industries, grocery retail is fundamentally about matching supply with demand as efficiently and effectively as possible. This has been the cornerstone of Foodstuffs North Island’s business ethos for almost 100 years; aligning what we do and sell with what our customers want.
Also like many industries, we have increasingly sought to enhance customer experience and satisfaction through the meaningful use of data. Our SAP implementation has given us an all-important real-time view of demand and sales data, so rather than retrospectively address performance issues, we can now use data to predict and cater for future customer behaviour. In essence, putting us on the front foot, not the back foot.
A great example of this is in how we manage product affinity and store layout. Whereas conventional logic would encourage us to range different sizes of the same product together for labour efficiency, data analysis often reveals that we can increase customer convenience (and sales) by placing products of different sizes next to other products that they are typically purchased with and potentially even within different departments of the store.
But just having the data at our fingertips is only part of the story. While data can indicate which items sell more on a sunny or rainy day, or which flavours of a particular product are the most popular, so will an experienced grocer. And that’s because retail grocery is both art and science.
Many of our store owners can lean on considerable experience and are already confident making decisions based on well-honed instincts. The role of data analytics in our business is therefore not to replace human experience and knowledge, rather it is to augment it through validating or enhancing decision-making – all with the end goal of creating a better outcome and experience for our customers.
As such, the data is both everything and nothing. Everything, in that it provides a real-time view of performance and pain points; but this counts for nothing if the company using it doesn’t have the organisational maturity or culture to trust in it. In this regard, 2020 was quite the benchmark year for us: Firstly, as we embraced the responsibility and privilege of providing essential service to the nation during multiple lockdowns; and then as we delivered our most successful customer loyalty marketing campaign ever for our New World brand, our SMEG knives promotion.
Using data in our COVID response
Just over 12 months ago now we, like businesses around the world, pivoted from front to back foot by the immediate impact of the pandemic. As we all were adapting to social distancing requirements and significantly increased demand for grocery essentials, coincidentally we were also rolling out a new reporting and analytics tool across our coop. This allowed us to leverage our previous investment in SAP, which had enhanced our ability to collect real-time operational data, to create actionable insights where our customers needed it most.
Listening to our customers, it soon became clear that our COVID response would be best served by providing immediate answers to two key customer questions: “which store near me is the least busy? ”and “does it have the items I want?”
We responded by launching a digital queuing system for our customers, which we made available through both our New World brand’s website and app. Providing real-time queuing data and subsequent trend analyses also enabled our teams to understand times of greatest demand and resource accordingly, supporting our staff and ultimately providing a better experience for our customers at a time of great stress and anxiety.
Supporting our Christmas loyalty marketing campaign
As New Zealand emerged from lockdown and returned to traditional shopping habits quicker than most, we were able to proceed with our annual Christmas loyalty marketing campaign for our New World brand whereby customers could redeem collected points (stickers) for quality giftware. This year, the giveaway was for premium SMEG knives.
In 2019, when we ran a similar marketing campaign over the same period with Spiegelau glassware, we experienced challenges in certain areas matching supply with demand. Our efforts to enhance the customer experience at that time led to us conducting quasi-experimental causation analyses to estimate the impact of the campaign on customer activity.
To do this we took our New World data (e.g., sales, baskets, etc.) and cross-referenced this with similar data from our other supermarket banners, PAK’nSAVE and Four Square, to work out what impact the campaign and its purchasing incentives were having on customer behaviours. This enabled us to glean an enhanced view of customer behaviours over the period of the campaign and use these insights to better plan for 2020’s campaign.
The success of this effort as a means of aligning supply and demand not only benefitted the efficacy of the promotion but reaffirmed to the business the centrality of data to our customer-driven future. Augmenting art with science, it was the wisdom that we extracted from the data that allowed us to tailor our collective response to customer demand for the free, premium giftware.
Our Aspiration to Become one of The Most Customerdriven Retailers in The World is Dependent upon us Keeping the Dial Moving in Two Key Areas – Constantly Maturing the Organisational Culture, Underpinned by a Commensurate Maturity of Data Capabilities
Our data-driven future is also our customer-driven future
Most of us who work in the field of data and analytics would recognise that we’re no longer working in a world where we’re waiting for the technology to catch up with what we want it to do. Rather we need to catch up our organisations to the point we collectively understand and trust what the technology can provide.
Our aspiration to become one of the most customer-driven retailers in the world is dependent upon us keeping the dial moving in two key areas – constantly maturing the organisational culture, underpinned by a commensurate maturity of data capabilities. This means that the better the alignment between those primarily working to drive culture change and those primarily working on maturing data and analytics capabilities, the better the outcomes for all involved will be.
What we experienced through 2020 was a laser-like focus on responding to challenges that galvanised teams right across the business to improve customer experiences. Predictive analysis and machine learning will undoubtedly play an ever-increasing role in our future, but a priority for us at this stage of our data and analytics journey is not simply using more data, but on making the data use more meaningful for better customer experiences.
Weekly Brief
I agree We use cookies on this website to enhance your user experience. By clicking any link on this page you are giving your consent for us to set cookies. More info
Read Also
New Hr Capabilities To Face Evolving Technologies
Strengthening The Compliance Fortress In The Banking Sector
Navigating Legal Challenges By Adapting To Technological Shifts
Compliance In The Medtech Industry
How Can The American Trade Finance Companies Manage Present (And Future?) Chinese Mineral Export Control Measures?
Optimizing Customer Experiences Through Data-Driven Strategies
Customer-Oriented And Compliance Mindsets In Claims Management
Optimizing Business Efficiency with a Multi-Disciplinary Legal Operations Team
