Digital Transformation in Retail
Retail is in the middle of a technology revolution. In the last two years alone, large, high visibility companies such as Walmart, Lowe’s, and Kroger have made noteworthy changes in their technology to improve their businesses. While these retailers get a lot of attention when they make these announcements numerous less visible retailers here and abroad have been and continue to use new technology to enhance their customers’ experience, improve internal processes, and work better and more closely with their business partners.
Retailers have been transforming their IT functions to work more like a Silicon Valley start-up than a traditional IT department by implementing DevOps practices, cloud-based microservice architectures, and embedding machine learning wherever possible. These three initiatives provide a wide array of benefits for retailers. Key are:
• Flexibility – Ability to adapt, change, and grow services quickly
• Automation – Removing human intervention for repetitive tasks
As a leader in an IT organization, it is often frustrating when someone adds or changes a requirement late in a project. Likewise, it’s always a challenge when there is a business need to make a significant change to one feature of an application. For example, when Apple launches a new iPhone feature that customers love, it’s difficult to respond to customer demand quickly and effectively.
By leveraging these new technologies, savvy retail companies are able to swap out one microservice for a better one without impacting the entire solution. New features can be spun up quickly without impacting the rest of the environment and without a large coordinated project and implementation plan. In addition, as a result, there are insights to help everyone know which features are working correctly and which aren’t minimizing disagreements and misunderstanding within your company.
How can technology help with the addition of a new payment system on your web site? Let’s use the simple example of a customer buying a shirt and a pair of jeans using a new payment solution from PayPal. For this example, the following questions are asked at different steps of the process:
1. “How many units of this shirt and pairs of jeans should I make available on the website?”
2. “Which jeans would look the best with this shirt?”
3. “How can I ensure that adding this new PayPal feature will not cause a major issue elsewhere in the system?”
For the first question, machine learning can be applied that predicts the demand of that shirt and pair of jeans and automatically allocates the product to the eCommerce fulfillment channel without taking any actions.
To answer the second question, machine learning can be embedded in a “My Look” service on your website to show the customer what he/she would look like in that shirt and the two or three pairs of jeans most likely to fit them best. Your customers would not need to search through your site to make this determination on their own.
Finally, with DevOps strategies, your developers/engineers can run automated scripts to regression test all of the other features of the website. This provides assurance to the organization that adding the new payment method will not have unintended consequences.
There are many advantages for the retailers implementing DevOps, cloud-based microservice architecture and machine learning including system scalability, security, and availability, but the benefits of automation and flexibility alone are enough to start driving retailers to change how they operate. Retailers and retail vendors that don’t adapt new technologies now to enhance their customers’ experience, improve internal processes and work better and more closely with their business partners will be left irretrievably behind during the current technology revolution.