When I introduced the concept of algorithmic retailing two years ago my definition was simple. The application of big data through advanced analytics across an increasingly complex and detailed retail structure to deliver an efficient, flexible, yet unified customer experience.
In a recent blog post, Walmart announced Eden, a solution that “leverages sophisticated technologies such as machine learning, but we’ve made it simple enough for all of our associates to use. Eden’s suite of apps helps Walmart associates better monitor and care for fresh fruits and vegetables that are waiting to be shipped from distribution centers to stores. That could mean more efficiently ripening bananas, predicting the shelf life of tomatoes while they’re still on the vine, or prioritizing the flow of green grocery items from the back of the store to the shelf.”
This is a great illustration of how algorithmic retailing will enhance customer experiences and improve retailer performance. By enabling associates to extract knowledge from big data through machine learning via an algorithm, they are embracing the KISS method, Knowledge, that leads to Innovation and Strategy, at the Speed required to deliver results.
Walmart indicated that it has already prevented over $86 Million in waste and that it expects to save $2 Billion over five years. What a great example, made even better since it rose from ideas within the ranks of its associates. Gartner clients can read more on algorithmic retailing here:
Will People or Machines Rule Algorithmic Retailing?
Business leaders are understandably overwhelmed by artificial intelligence due to its complexity and disruptive workplace implications. Retail CIOs must take active leadership in setting the course for this critical technology as part of an overall retail digital business strategy.
Published: 21 Dec 2017
Using Algorithmic Retailing to Drive Competitive Advantage
Retailers gain competitive advantage through the application of algorithms that reduce costs and grow top-line revenue. CIOs can use this research to identify use cases that will improve business performance in the unified commerce retail marketplace.
Published: 21 Sep 2016
Algorithmic Retailing: Using AI to Drive Smart Automation
Retailers must use AI to automate and deliver better decisions and make it possible for associates to be customer experience differentiators. CIOs can use this research to identify opportunities to use AI to drive smart automation.
Published: 12 May 2017
Algorithmic Retailing: Merchandising Leads the Way
Leveraging algorithms is the only way that merchandising can meet the customer centricity challenges of digital business and the digitalization of retail. This research describes algorithmic merchandising and its impact on the business.
Published: 09 Mar 2016
Read Complimentary Relevant Research
High-Tech Manufacturing Supply Chainnovators 2016: Connecting, Collaborating and Capitalizing on Complexity
Gartner's Supply Chainnovators program recognizes unconventional, innovative and high-impact initiatives that high-tech manufacturing...
View Relevant Webinars
Hadoop and Spark: Understanding Open Source Opportunities and Risks
As companies build foundational data and analytics infrastructure with Spark and Hadoop, the market continues to shift and evolve in...
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.