How merging data analytics and retail management can drive business value

Posted on
August 17, 2021

Data science is very powerful – but capturing real value from that capability is challenging, particularly if you’re not the biggest retailer in your market sector.By developing decisions based on sound, sustainable analytics-based information, multinational retail consultancy Scalene Group is positively impacting product ranging, category space allocation, store network development and even promotional pricing for retailers spanning three continents.

Thanks to their unique combination of extensive retail management, strategy development and data analytics experience, Scalene’s founders Mick Moore and Pushkar Kumar have in just three years built the company into a 12-strong team with offices in Melbourne, Sydney and London, serving customers in Australia, New Zealand, Hong Kong, Singapore, and the UK.

Scalene Group works across all retail sectors, its clients ranging from businesses turning over from $100 million into the 10s of billions of dollars. That roll call includes names like Marks & Spencer, McColl’s and WH Smith in the UK, Officeworks, Priceline and Coles in Australia; and Mannings, Giant, and Dairy Farm in Asia.

“Often we work with retailers who have historically taken a one-size-fits-all approach to decision making helping them adopt a more granular set of outcomes that can be deployed across their store networks or their various channels,” Moore tells Inside Retail.

Retailers, he says, need to think about how they can move beyond using analytics for applications like customer loyalty or customer insights – which is as far as many retailers have got to during the last few years – to using it for the broader swathe of decisions business leaders are making right across their business.

Among Scalene’s core services is helping a retailer determine the best range from its master assortment to optimise sales store by store.

“We help identify what products to keep and what to remove and how to evolve the range over time using combinations of commercial, transactional and customer data,” explains Moore.

“A lot of category managers tend to think about the range they have, but not the combination of range and store. They may not realise that what might work in a large store is not necessarily what is needed in a small store or the varying requirements across stores in different location types.”

Equally important to optimising a retailer’s return on range, is correctly allocating category space.

“Through taking a more dynamic approach to the allocation of space across a complex network of stores, there’s the potential to gain 5 to 7 per cent sales and margin uplift. When you translate that margin gain for a retailer that might currently be making a net profit of 2 or 3 per cent, it can translate into really substantial profit growth over a relatively short period of time,” says Moore.

During the Covid crisis, Scalene’s team has spent a lot of time advising retailers on ranging, and how space allocations, store sizes and store formats could evolve.

The company’s approach has helped property teams, for example, to use data analytics to determine the optimal size for new stores and where their brand’s footprint can be expanded, how formats can evolve for different markets, and how macro space can be allocated and optimised in a localised manner.

Scalene also helps retailers adopt a more sophisticated approach in pricing and promotions, right through to an even more sophisticated deployment of capital. “It really is that sort of spectrum from understanding what your customer needs in different locations, and working through the range and price proposition you want to put in front of those customers, through to how you supply productive inventory into those environments.

“A lot of retailers don’t necessarily fully optimise these aspects of their business. You sometimes hear retailers say retail is a simple game – that it’s about providing customers with a product they want, and engaging with them where they are. But it can get really complicated when you’re talking about hundreds of shops and tens or hundreds of categories, and thousands of products. We try to use data science to provide that bridge between that simple proposition of matching your product to a customer and delivering this at scale across a retail network.”

Scalene works with retailers as partners and its work with fast-growing Australian cosmetics chain Mecca – which has now opened more than 100 stores – is a great example of how that approach breeds success.

In the beauty space, suppliers tend to have many preferences around how their products are presented in-store, and which stores they want to prioritise being ranged in.

“Mecca has been on an amazing growth path during the past 20 years and is still rapidly evolving its store network, brand portfolio and customer offer. We’ve been working with Mecca across a number of different initiatives that focus on right-sizing its stores going forward, guiding the allocation of space across categories and how to ensure the best selection of brands is available in each store.”

Partnering with Officeworks, Scalene has been helping the company differentiate the range and proposition best suited to stores’ locations and customer catchment, right down to managing the macro space to balance the share of space in each store. Customers of a shop located in the middle of a CBD, for example, will have different needs to those of a shopper in a regional market or perhaps an outer suburban area popular with young families.

“So, essentially, the work we’re doing with Officeworks is to tailor the proposition to the needs of different communities of customers or businesses, track the outcomes and validate that it’s delivering the results they have been looking for.”

Moore says Scalene’s solutions allow leaders of large retail groups to better understand how advanced data science techniques, AI and machine learning can help their teams make better decisions, faster – and with greater tailoring to the needs of customers.

“So in those businesses, decision makers are making more informed choices – not ones based strictly on their experience or their perception of what a good answer looks like.”

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