This vast rise in the ability of retail companies to collate and sift data for insights can be termed as algorithmic retail for its persistent use of big data analytics.  Algorithmic retail allows companies to manage their businesses in real time, seeing their products as they flow from suppliers to customers, optimize replenishment to have the right goods at the right store or delivered direct to the customer’s door, provide consistent and personalized customer service and engagement, optimize pricing, all while improving the bottom line!

Renowned management guru Ram Charan has asserted that companies that have algorithmic capabilities will enjoy an advantage over corporations that don’t, even ones that have been successful in the past. He calls these companies “Math Houses”, and specifically names Google, Facebook, and Amazon – all of whom were created as mathematical corporations. Even a traditional retailer such as Macy’s is using algorithmic methods to fuse the online and in-store experience. Mr. Charan further stressed that companies that cannot make the digital shift will be very vulnerable to their competitors. (Source: Fortune 2015)

And how vulnerable are companies that don’t innovate? A recent study from McKinsey found that unless corporations adapt, 40% of the S&P 500 will no longer exist in the next 10 years! Average corporate life expectancy has dropped a dramatic 70% from 61 years in 1958 to 18 years in 2011!

Now, what does this digital trend mean for retail?


Consistent Shopper Experience

First and foremost, that retailers need to adopt a “world without walls” attitude. Increasingly, retail sales are expected to come from non-store based engagements with their customers. In order to facilitate this, retail companies need to provide an enhanced and consistent experience across all devices in order to meet the needs of perpetually connected customers. Most importantly, companies need the technical skill to enable a consistent experience across devices, yet one that conveys that retailer’s message and engages with the customer.

To enable algorithmic retail the technical architecture must be in place to track every conceivable interaction with customers – browsing, inquiries, purchasing, and any positive or negative comments on social media. Only by knowing how the customer interacts with them can a retailer begin to build a full picture of that customer, and what actions drive them to sales (and to public comments).

Nimble Operations

Having given their customers the consistent shopping experience they desire, retailers need to fulfill the order!  To do this, retail corporations need to take into account the growth trends of the developed and emerging worlds, as well as the global nature of the materials markets. Most importantly, retailers need a networked supply chain that may need to become increasingly local or regional to meet customer demand, meaning retailers may need to consider sourcing closer to the final distribution point rather than across the ocean.

Turning the tables for a moment, a customer who is engaging with a connected, algorithmic, retailer wants transparency, with a real-time view into inventory, shipping times, and offers. Various aspects here include pinpointing the in-store inventory so customers have immediate feedback on what is available. For example, at a recent visit to a US retail store, I could not find an item I was looking for. When I asked the store manager if they had any more in the back, he turned to their in-store inventory screen that showed an in-stock quantity of three. As I became optimistic he said “We are probably out of the item. Any quantity under five is unreliable!” Retailers need to leverage technology to enable greater inventory precision, be it in-store or online. Perhaps more importantly, retailers need to enable “in-network” inventory tracking, allowing them to work with their supply chain network to enable up-to-date visibility of the “in-transit” and “store-network” inventory to better meet unexpected demand surges and logistic disruptions.

Loyalty & Segment of One

Basic human nature wants our needs understood and our desires catered for. When customers participate in loyalty programs to earn points, the awards must match the customer’s needs. Personalized offers, closely matching a customer segment of one, are most valued. Many customers are also moving towards digital receipt of both offers and redemption – email and text are expected, with paper coupons being a thing of the past. On the other hand, while customers expect this highly personalized engagement, they also expect their personal information to be protected, and any failure causes a loss of faith from the customer population.

The ability to present personalized offers is algorithmic retail exemplified. Creating an offer that matches the needs of the individual shopper implies collection and storage of direct data (transaction), indirect interactions (digital footprints on websites, mobile, social interactions), as well as third party data employing trending, anomalies, and predictive analytics. Such analytics yield offers based not just on a customer’s purchase history (the traditional approach) but offers that appeals to the broader self – related interests, likes, friends’ likes on Facebook, interest groups, hobbies etc.

The road ahead

Retailers today capture a wealth of data. With the adoption of sensors and RFID tagging retailers can acquire ever greater quantities of data around consumer behavior, in-store and in-transit inventory. Success, however, requires an algorithmic retailer culture and mindset – the ability and willingness of the company, at all levels, to sift through data to discern what the numbers really mean, and then translating those insights into actions to meet corporate KPIs. And they must be able to do this quickly, for the connected world does not abide slowness, expecting interaction and responses within seconds, if not milliseconds.

It is still early days! Kevin Plank, CEO of UnderArmour, mentioned in a recent interview that the math house idea, that ability to use data and analytics to drive the business, is something they very much care about.

That said, all retailers that survive the digital disruption will be “math houses” to a greater or lesser degree. Those who do it deeper and do it better, by augmenting their executive and middle managers with the necessary skills, mindset, and tools, will leverage the mathematical power of algorithmic retail and flourish as they do!

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