This is the first in a three-part series.
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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.
