Monday Apr 27, 2015

Insights from OIC: Nordstrom’s New Canada Stores Become Testing Grounds for Enterprise IT Initiative

Last month our customer shared some fantastic experiences at Oracle Industry Connect 2015. Here is a glimpse of what you missed from the sessions....

Among its other accomplishments, Nordstrom has been a retailing technology pioneer, beating its competitors to market with customer-focused offerings including save-the-sale and endless aisle capabilities, buy online/pick up in-store, and coordinating returns between multiple stores and channels.

From 2001 until 2013, the Oracle Retail Merchandising System (RMS) served as a technology backbone for Nordstrom’s increasingly complex operations, but this required more and more customization as time progressed. When the retailer realized it was reaching the limits of customization, it initiated the Nordstrom Next Generation (NGEN) initiative, a six-plus-year program to support the company’s growth by replacing its current enterprise foundation solutions with new Oracle Retail systems offering advanced capabilities and scalability.

Nordstrom’s recent expansion into Canada is doubling as the first phase/pilot for NGEN, according to Nordstrom Director of Supply Chain and Fulfillment Brenda Glasgow, who spoke in late March at Oracle Industry Connect in Washington DC. The retailer has already opened two of a planned 10 full-line stores in Canada, with the next opening planned for fall 2015, and also plans to open its off-price Nordstrom Rack stores beginning in 2017.

The Canada expansion “gives us a chance to test, learn, and adjust with our business partners and technologists,” said Glasgow. “It’s allowing us to socialize the ‘vanilla’ implementations of Oracle solutions, and giving us practice managing the scope of these implementations.”

Nordstrom is still relying heavily on Oracle solutions, particularly in merchandising with Oracle Retail Merchandise Operations Management (MOM). This system is supporting international requirements around currencies and import/export issues, and Nordstrom is also taking advantage of new trade management and invoice matching modules that supplant older legacy applications for these functions.

Glasgow and Deby Hansen, Director of Program Management and Architecture for Nordstrom, identified key learnings from the Canada opportunity that include leveraging best practices identified in the Oracle Retail Reference Library, and using a process-led design approach that makes extensive use of personas and job roles. “By painting a full picture of a job’s process flow, it’s been easier to work through what’s been different from one system to the next,” said Glasgow. “We need to balance respecting our people’s business requirements with our motivation to stay ‘vanilla’ with these implementations.”

Nordstrom will apply these learnings as NGEN progresses, supporting long-term corporate goals that include sustaining the company’s growth, supporting its Nordstrom Rack stores becoming more of a separate entity, and “keeping us on an upgrade path that leverages our research and development investments,” said Hansen.

Congratulations to Nordstrom for their hard work and success. Nordstrom continues to impress the industry with their approach to the enterprise transformation. Read the press release or check out the presentation in the RACK to dive a little deeper. 


Friday Oct 26, 2012

Analytics in an Omni-Channel World

Retail has been around ever since mankind started bartering.  The earliest transactions were very specific to the individuals buying and selling, then someone had the bright idea to open a store.  Those transactions were a little more generic, but the store owner still knew his customers and what they wanted.  As the chains rolled out, customer intimacy was sacrificed for scale, and retailers began to rely on segments and clusters.  But thanks to the widespread availability of data and the technology to convert said data into information, retailers are getting back to details.

The retail industry is following a maturity model for analytics that is has progressed through five stages, each delivering more value than the previous.

Store Analytics

Brick-and-mortar retailers (and pure-play catalogers as well) that collect anonymous basket-level data are able to get some sense of demand to help with allocation decisions.  Promotions and foot-traffic can be measured to understand marketing effectiveness and perhaps focus groups can help test ideas.  But decisions are influenced by the majority, using faceless customer segments and aggregated industry data points.  Loyalty programs help a little, but in many cases the cost outweighs the benefits.

Web Analytics

The Web made it much easier to collect data on specific, yet still anonymous consumers using cookies to track visits. Clickstreams and product searches are analyzed to understand the purchase journey, gauge demand, and better understand up-selling opportunities.  Personalization begins to allow retailers target market consumers with recommendations.

Cross-Channel Analytics

This phase is a minor one, but where most retailers probably sit today.  They are able to use information from one channel to bolster activities in another. However, there are technical challenges combining data silos so its not an easy task.  But for those retailers that are able to perform analytics on both sources of data, the pay-off is pretty nice.  Revenue per customer begins to go up as customers have a better brand experience.

Mobile & Social Analytics

Big data technologies are enabling a 360-degree view of the customer by incorporating psychographic data from social sites alongside traditional demographic data.  Retailers can track individual preferences, opinions, hobbies, etc. in order to understand a consumer's motivations.  Using mobile devices, consumers can interact with brands anywhere, anytime, accessing deep product information and reviews.  Mobile, combined with a loyalty program, presents an opportunity to put shopping into geographic context, understanding paths to the store, patterns within the store, and be an always-on advertising conduit.

Omni-Channel Analytics

All this data along with the proper technology represents a new paradigm in which the clock is turned back and retail becomes very personal once again.  Rich, individualized data better illuminates demand, allows for highly localized assortments, and helps tailor up-selling.  Interactions with all channels help build an accurate profile of each consumer, and allows retailers to tailor the retail experience to meet the heightened expectations of today's sophisticated shopper.  And of course this culminates in greater customer satisfaction and business profitability.

About


David Dorf, Sr Director Technology Strategy for Oracle Retail, shares news and ideas about the retail industry with a focus on innovation and emerging technologies.


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