– George Anderson, RetailWire
Few topics are as hyped up as omnichannel in Retail – or as difficult to execute successfully. Part of the problem depends on where you sit within the organization. Marketers view this as a consumer issue, in-store this is a merchandising and fulfillment issue, online this is a website design and e-commerce execution issue, and of course there is also a supply chain and fulfillment angle. Next is your IT department that views this as a complex data integration issue with huge ETL implications and a multimillion-dollar price tag to get started. More often than not your retail omnichannel strategy ultimately gets kicked to the curb! However, as indicated above, Nordstrom is doing things differently and is currently testing a store redesign that would make in-store pick up of merchandise easier to manage for consumers and the retailer.
Having a consistent view of and delivering a seamless experience to your customers across all touchpoints in-store, online, via kiosks, mobile, digital and social media is the original premise of omnichannel and it has become an even more important strategy in today’s competitive market. Consumers want to be treated as individuals and responded to consistently – regardless of channel. And, given how easy it is to compare pricing and fulfillment options online, lack of an omnichannel strategy would increase the chance that consumers may abandon their shopping carts mid-transaction and kick your brand to the curb.
So why does Omnichannel Fail? Three Major Challenges
Delivering on an omnichannel strategy requires linking consumer data with product and supply data, and delivering on a live transaction regardless of channel. You need a 360 view of the consumer, product and supply as well as the ability to manage live transactions that utilize heterogeneous data sources.
Let’s examine why this is so difficult:
To make omnichannel work, you must be able to link consumer data with product and supply data in real-time to enable operational transactions.
Unfortunately today’s retail systems and databases just weren’t built for this challenge. Most retail database systems run on rigid, inflexible relational database (RDBMS) models first developed in 1970. Data stored in RDBMS’s is framed into a rigid schemas consisting of rows and columns prior to analysis. It’s really difficult to make changes to these schemas so RDBMS does not work well for the unstructured and constantly changing heterogeneous data associated with omnichannel. Next are the challenges inherent to complex data integration across multiple legacy systems – many of which are the multimillion-dollar dream projects for systems integrators and ETL software vendors. Finally, we’re looking at making this operational or live if it needs to work.
So, how can a retailer achieve success at omnichannel?
NoSQL Represents a Revolutionary Solution for Omnichannel
Clearly traditional mainframe or RDBMS’s lack the flexibility and scalability to handle the data volume, velocity, and variability issues inherent to omnichannel retailing.
Trying to combine the vast scale of structured and un-structured consumer, product, and supply data for analysis into a relational database designed for structured “rows and columns” and then using SQL (Structured Query Language) to query it – just does not work. Part of the problem here results from the dominant position incumbent vendors like Oracle and IBM hold in Retail IT departments making a radical shift difficult even when the business value proposition is clear.
NoSQL (Not Only Structured Query Language) technology represents a transformational change in perspective. Instead of getting the schema just right before doing anything else, NoSQL advocates loading up the data first and then seeing where the problems lie. This problem-oriented approach focuses on how the data will be used (queried) rather than how the data must be structured to fit within a traditional RDBMS.
For omnichannel retail, the shift to NoSQL means you would not have to spend a year trying to figure out the right data model and perfect schema to analyze and store data on consumers, products, and supply. Instead, you can load the data, have it indexed automatically, and then search and query it for emerging trends and signals.
The retail industry has surprisingly lagged behind other industries like media, financial services, and even government when it comes to using NoSQL to solve the complex operational problems associated with Big Data. But with the growing importance of omnichannel it may finally be the retail industry’s chance to get it right.
Please be sure to read my other articles in this series:
1. Big Data, Little Insight: Challenges for the Retail and Consumer Industries
2. Removing Roadblocks to Omnichannel 360 in Retail
3. Consumer 360: Reaching Each Consumer With a One-in-a-Billion Message
4. Retailers: Are You Meeting the Needs of Digital Consumers
5. Why do Retailers Miss Out on E-Commerce Opportunities?
6. Reinventing Your Retail Loyalty Program to Win
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