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Algorithmic retail: powering intelligent enterprises

Algorithmic retail: powering intelligent enterprises
(Image credit: Shutterstock.com)

The paradigm shift in retailing means that customers are more informed, have more choices and are more price savvy. Life in lockdown has amplified and accelerated this shift, with consumer shopping habits further transforming over the last few months and with long-lasting impacts. New purchase behaviors and consumer expectations have driven retail businesses to explore new avenues and drive innovation at scale.

The recent disruption brought new opportunities, but it also exposed significant gaps in retailers’ capabilities to balance demand and availability, while ensuring safe and contactless shopping. Several retailers struggled to cope with the surge in online demand, inventory shortages due to skewed demand patterns, and workforce imbalance to fulfil customer services and orders. While the immediate focus is on employee welfare, costs and capital optimization, in the long term we see our retail customers preparing to become more resilient and adapt to such changes and challenges.

Planning omnichannel assortment, maintaining inventory visibility, managing orders, delivering on the last mile, integrating channels, and ensuring supply chain resilience have now become top priorities. Retailers who can orchestrate all of these, while rolling out new business value propositions, will be best placed for the future. 

In order to tackle these challenges effectively, it’s time to integrate data and insights across the value chain to solve pressing problems and uncover exponential value through algorithmic interventions.

The journey of algorithmic retailing requires:

  • Taking a unified enterprise approach towards building a robust organization, based on a foundation of data insights;
  • Creating a unified value chain that cuts across organizational silos and clearly shows where and how to use algorithmic interventions within the value chain; and
  • Having a flexible operating model that can leverage ecosystems i.e. unified ecosystem

Unified Enterprise beyond channels for algorithmic retailing

In order to thrive, businesses need a single view of the customer, regardless of the channel they are using. This requires a seamless integration of enterprise systems to consistently deliver customer satisfaction. Transforming the organization by using a machine-first approach across the business will enable greater agility in responding to customer needs.

A core part of this will be investing in an omnichannel shopping experience, which will benefit customers and retail staff alike. Enabling a single basket, single order, single wish list across all online and offline channels is now a possibility through various unified ecommerce platforms that are now available. The global basket feature helps customers seamlessly switch their shopping journeys between devices - from online or mobile app to kiosk; from store associate app to checkout. Enabling tech like this can support retail staff too. For example, a store assistant can look up items not available in store and add them to the customer’s digital basket, allowing them to continue making the sale. An omnichannel approach is essential to maintaining a strong customer base as we enter a post-COVID retail space.

A machine-first approach across the business enables retailers to keep up with evolving customer expectations and business landscapes. At a time when safety has become paramount, machine first empowers retailers to deliver seamless contactless shopping and best-in-class customer experiences.

Unified value chain: shifting from silos to value chain optimization

AI is not new to retail; however, big gains await those who can identify how to create the most value from algorithmic interventions. Customers expect a unified experience and data analytics and insights can no longer operate in a silo. The power of algorithmic retailing can be realized only through pooling data and insights to optimize business processes at scale. By leveraging AI to gain a cross-channel view of pricing, assortment, promotions, and last mile delivery, retailers can use AI-powered retail optimization solutions to respond in real time by harnessing insights, getting recommendations on next best actions, and redefining customer experiences.

For example, for companies having issues with fulfilment costs and truck utilization, a neural AI-based replenishment solution can transform the supply chain. Through multidimensional, concurrent modeling and optimization in near real time across stores, distribution centers and transportation, companies can better improve availability and customer experience while reducing waste and cost to serve. For retailers looking to enhance the lifetime value of every customer, gathering data across the omnichannel journey is a necessity. To enable hyper-personalization at scale across channels, retailers need to orchestrate customer journeys through intent-based, AI powered solutions that algorithmically architect the entire chain of recommendation systems in real time.

Even as retailers continue to contend with fundamental issues such as shrinkage, wastage, inventory accuracy, and labor productivity, they are being pulled in all directions by macro environment changes that are forcing a big reset. These include redefining the role of stores, recalibrating the store cost structure, exploring new business models, and preparing the workforce to adapt to the new normal. AI powered store optimization solutions empower retailers to reimagine end-to-end store operations and optimize operational costs, improve productivity, and enhance the customer experience by reimagining store operations through digitalization and cognitive automation.

Unified ecosystem: moving from being product-led to purpose-led

Shifting consumer preferences and the growth of marketplaces requires enterprises to rethink retail and reinvent customer experiences. Retailers are shifting strategies from being product-led to becoming purpose-led. The relationship between retailer and customer is transforming from being transactional to becoming a more holistic solutions-provider. Retailers are creating and leveraging ecosystems that often transcend the traditional boundaries of partners and stakeholders to fulfil the purpose behind customer’s needs.

Forward-looking retailers are adopting an enterprise-wide collaboration strategy and working with new ecosystem partners to become the custodian of the customer’s experience. Networks can no longer be restricted to static longstanding partners; a new generation of dynamic and short-term partners will also need to co-exist. Retailers also need to plan for ‘what ifs’. For instance, smart network modelling powered by algorithms that allow retailers to dynamically switch suppliers in case of supply chain delays or disruptions.

By embracing this customer-centric approach, enterprises can completely reinvent their business model, and create a unique market proposition to get ahead of their competitors. Leveraging ecosystems this way, retailers can improve their sales, increase their online revenue and boost their digital traffic with higher average order and conversion.

It’s time for bold moves. Retailers need to identify space for algorithmic interventions in their value chain. A holistic overview that’s AI-powered and purpose-led, and combines data encompassing the business, its customers, and suppliers, will help them in creating competitive advantage. Such algorithmic retailers stand the best chance of navigating today and tomorrow’s challenges and building new market opportunities.