Global management consulting firm AlixPartners has devised a self-assessment framework to help retailers and brands look before they leap into AI.
This is the second article in a two-part series. In the first article, AlixPartners shared a framework and approach to get on track with Generative AI and drive value for retailers and brands. This article explores the keys to impactful implementation of AI in retail.
It's tempting to jump on the buzzy Generative AI bandwagon amid fears of getting left behind, but in today's competitive fashion and retail climate, diving in without proper preparation can compromise a company's ability to effectively integrate the technology. New technical solutions often prove to be a waste of time and money due to flawed or misguided implementation, poor adoption, and/or the lack of integration with business processes.
Global management consulting firm AlixPartners has devised a self-assessment framework to help retailers and brands look before they leap into AI, however, accurately assessing needs and abilities is just the first step. Implementation is often the hardest part. Companies must begin with a well-defined strategy and clear objectives, actively measure AI's efficacy with KPIs, then quickly and constantly course-correct as needed. In other words, "fail fast and fail forward," according to Angela Zutavern, Partner and Managing Director and AI expert in AlixPartners' Digital Practice.
Here, we explore basic steps companies must take while applying AI into their workflows, all with the objectives to drive conversions, reduce costs and increase profits and as well as boost average customer value, acquire new customers and gain market share.
AI can be applied narrowly or broadly, but many companies make the mistake of putting the tech before their business concerns. "Experimentation is absolutely critical for any AI-generated initiative, because not all of them will work the first time. But initiatives must be goal-oriented," said Zutavern.
Companies must first have a clearly defined business case to know how the AI initiative can impact the business results. Once they have those financial metrics up front, they can pilot with a minimum viable product.
"If you expect a particular AI initiative to reduce customer churn or increase customer lifetime value, for example, you've got to be measuring that along the way," she said. "You need that historical baseline where you start and then you need to measure it throughout the pilot phase and the implementation phase, to make sure that you are making progress in those metrics that you've defined up front."
As part of its self-defined digital transformation, Spanish retail chain Mango identified a broad range of touchpoints across its value chain that could benefit from AI—from pricing to personalization—and since 2018, it rolled out 15 different platforms to address them. Midas, for example, is used for pricing policy and in store, while Gaudí recommends products online. Mindful of its massive international clientele, Mango programmed its AI customer service bot Iris to speak to customers in 20 languages in over 60 countries.
Dowload: 'Fail Fast and Fail Forward' When Implementing AI into Workflows – WWD
Originally published in WWD
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