Ongoing reports of the “Retail Apocalypse” were fueled once again in 2019 with more than a dozen well-known retail brands closing their doors forever. On the flip side, a “Retail Renaissance” is well underway – and signs indicate that retail leaders that have already invested in their digital transformation journey will continue to reap rewards well into the future. Let’s talk about leveraging enterprise data as a competitive differentiator, as successful brick-and-mortars continue to widen the analytics capability gap.
They are winning because – unlike those who are struggling or who have already gone out of business – they’ve recognized that data is their most valuable asset and that the historical precedent of being extremely conservative when it comes to technology spend is no longer a sustainable strategy.
One thing Amazon has taught the industry – including other data-driven exemplar’s like Alibaba, JD.com and Ocado – is that new data types and advanced analytics are essential to understand and deliver what consumers want, while also helping to contain operational costs. They’ve been continuously innovating and investing in technologies by following three fundamental principles:
- Owning the competency – They’re adding people skills and implementing bold cultural change management initiatives, acquiring teams of data scientists, data engineers and software development teams who report directly to C-level executives.
- Owning the intellectual property – They’re infusing data analytics, in-house software development programs, machine-learning (ML) and artificial intelligence (AI) capabilities into existing business processes.
- Transitioning to agile and portable platforms – They’re moving to open-source data management platforms, cloud infrastructure and emerging IoT edge technologies to enable fast iteration of innovative analytics without the burden of costly or restrictive licensing requirements.
Looking beyond borders for retail industry pace-setters
A shining star among the global pace-setters belongs to Alibaba and its 100-plus in-store Hema supermarkets throughout China. Innovations in ML and AI are propelling Hema to set new standards in customer experience, engagement and overall satisfaction. This is the centerpiece of Alibaba’s “New Retail” initiative that has resulted in dramatic increases in average shopper spending and is considered to be the “locomotive” that’s leading the retail industry.
On the customer-facing front end, Hema (pronounced “Humma”) offers “Jetsons”-like features such as robot-enabled in-store restaurant services, speedy delivery, mobile-phone app-enabled ordering, self-checkouts and even facial recognition payments.
On the back end, Hema’s ML and AI predictive modeling capabilities analyze disparate data sets to digitize inventories and discern consumers’ buying and eating patterns. This also helps to reduce waste and quickly replace out-of-stock items.
Meanwhile, China’s No. 2 ecommerce player, JD.com (Jingdong Group), has zeroed in on elevating the customer experience as well as anyone. With fully robotic fulfillment centers and a fleet of bicycle- and motorcycle-riding couriers, they’re delivering groceries ordered online through the WeChat messaging system within 30 minutes.
In EMEA, online grocer Ocado incorporates ML and AI into fully automated fulfillment centers to reduce replenishment cycles and wastage far exceeding industry standards. The company is also providing lightning-fast delivery services in the U.K., with such a compelling business case that they are now taking their innovative technologies and services to other grocery retailers around the globe with great success.
Emerging practice: Leaders collaborating with other leaders
Another trend industry leaders have initiated is to collaborate with – and even invest in – retailers in other markets whose infrastructures and systems can be leveraged for rapid deployment and outcomes. For example:
- Walmart has invested heavily in JD.com after being unable to make inroads on its own in China, where its e-commerce offerings are now available on the Chinese company’s platform.
- Kroger has partnered with Ocado to build several automated, robot-driven warehouses in the U.S., similar to the JD.com-Walmart arrangement.
The industry has taken notice of what the leaders are doing: Retailers are expected to invest approximately $7.3 billion in AI technologies by 2023, according to Juniper Research.
Going all-in on analytics and in-house development
Nordstrom, Dick’s Sporting Goods, and Home Depot – which last year increased its technology headcount by approximately 1,000 employees – are among those in retail striving to become industry leaders.
Dick’s Sporting Goods recently wagered that demand forecasting software developed in-house can deliver a greater competitive advantage than third-party solutions alone. The point is that packaged point solutions across the spectrum of retail business processes can’t easily be tailored to a specific retailer’s needs, as rapidly as needed. Dick’s approach could quickly pay for itself with even a small improvement in demand forecast accuracy.
Nordstrom, meanwhile, has assembled a substantial team of data scientists who build analytics models and computer vision capabilities that can accurately measure and custom-fit online shoppers. Not coincidentally, Nordstrom announced $100 million in cost savings year over year in its Q2 financials reporting.
Data paves the road to the promised land
As more and more traditional retailers position themselves to survive and thrive by continued investment in data as a strategic asset, the future is bright. Unfortunately, for the few that may not recognize the value of data as a strategic asset, operating with a ‘business as usual’ funding of their IT shops, time is running out, and the gap between leaders and laggards is now widening at an accelerating rate.
Even for laggards, there’s still hope. By simply harvesting new insights from existing data can help close the widening gap through better understanding of customer tastes, preferences and shopping patterns. Building on that existing data with new data types such as mobile, social, video and call-centers requires neither significant technology investments nor a big initial cultural shift to get started. The tools and skill sets are readily available.
Without executive vision and courage from the top, though, the competitive gap between leaders and laggards will continue to widen, and more retailers will fall victim to the Apocalypse than enjoy the fruits of the Renaissance.
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