Right-Time Retail Part 1

This is the first in a three-part series.

Right-Time Revolution

Technology enables some amazing feats in retail. I can order flowers for my wife while flying 30,000 feet in the air. I can order my groceries in the subway and have them delivered later that day. I can even see how clothes look on me without setting foot in a store. Who knew that a TV, diamond necklace, or even a car would someday be as easy to purchase as a candy bar? Can technology make a mattress an impulse item? Wake-up and your back is hurting, so you rollover and grab your iPad, then a new mattress is delivered the next day.

Behind the scenes the many processes are being choreographed to make the sale happen. This includes moving data between systems with the least amount for friction, which in some cases is near real-time. But real-time isn’t appropriate for all the integrations. Think about what a completely real-time retailer would look like. A consumer grabs toothpaste off the shelf, and all systems are immediately notified so that the backroom clerk comes running out and pushes the consumer aside so he can replace the toothpaste on the shelf. Such a system is not only cost prohibitive, but it’s also very inefficient and ineffectual. Retailers must balance the realities of people, processes, and systems to find the right speed of execution. That’ what “right-time retail” means.

Retailers used to sell during the day and count the money and restock at night, but global expansion and the Web have complicated that simplistic viewpoint. Our 24hr society demands not only access but also speed, which constantly pushes the boundaries of our IT systems. In the last twenty years, there have been three major technology advancements that have moved us closer to real-time systems.

Networking is the first technology that drove the real-time trend. As systems became connected, it became easier to move data between them. In retail we no longer had to mail the daily business report back to corporate each day as the dial-up modem could transfer the data. That was soon replaced with trickle-polling, when sale transactions were occasionally sent from stores to corporate throughout the day, often through VSAT. Then we got terrestrial networks like DSL and Ethernet that allowed the constant stream of data between stores and corporate.

When corporate could see the sales transactions coming from stores, it could better plan for replenishment and promotions. That drove the need for speed into the supply chain and merchandising, but for many years those systems were stymied by the huge volumes of data. Nordstrom has 150 million SKU/Store combinations when planning (RPAS); The Gap generates 110 million price changes during end-of-season (RPM); Argos does 1.78 billion calculations executed each day for replenishment planning (AIP).

These areas are now being alleviated by the second technology, storage. The typical laptop disk drive runs at 5,400rpm with PCs stepping up to 7,200rpm and servers hitting 15,000rpm. But the platters can only spin so fast, so to squeeze more performance we’ve had to rely on things like disk striping. Then solid state drives (SSDs) were introduced and prices continue to drop. (Augmenting your harddrive with a SSD is the single best PC upgrade these days.) RAM continues to be expensive, but compressing data in memory has allowed more efficient use.

So a few years back, Oracle decided to build a box that incorporated all these advancements to move us closer to real-time. This family of products, often categorized as engineered systems, combines the hardware and software so that they work together to provide better performance. How much better? If Exadata powered a 747, you’d go from New York to Paris in 42 minutes, and it would carry 5,000 passengers. If Exadata powered baseball, games would last only 18 minutes and Boston’s Fenway would hold 370,000 fans. The Exa-family enables processing more data in less time.

So with faster networks and storage, that brings us to the third and final ingredient. If we continue to process data in traditional ways, we won’t be able to take advantage of the faster networks and storage. Enter what Harvard calls “The Sexiest Job of the 21st Century” – the data scientist. New technologies like the Hadoop-powered Oracle Big Data Appliance, Oracle Advanced Analytics, and Oracle Endeca Information Discovery change the way in which we organize data. These technologies allow us to extract actionable information from raw data at incredible speeds, often ad-hoc.

So the foundation to support the real-time enterprise exists, but how does a retailer begin to take advantage? The most visible way is through real-time marketing, but I’ll save that for part 3 and instead begin with improved integrations for the assets you already have in part 2.


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