BBQ Guys and Lowe’s discuss best practices for implementing AI tech




Bryan Wassel, Associate Editor, Retail TouchPoints
Through a special arrangement, presented here for discussion is a summary of a current article from the Retail TouchPoints website.
Fine-tuning data science solutions to optimize results has been, relatively speaking, the easy part. Preparing people throughout the retail organization to take advantage of the new insights is the more complicated task, IT executives indicated on a panel at the 2019 Retail Innovation Conference.
“Executives like to believe that 99 percent of your time is spent on building the algorithms involved — but actually that’s the smallest part,” said Doug Jennings, VP of data and analytics at Lowe’s.
Teams across the organization must be educated on how these solutions will affect their jobs and have reasonable expectations about how much things will change. “We have to show some sort of roadmap of where we want to go,” said Jason Stutes, director of analytics & design at BBQ Guys.
One key ingredient is making a dashboard that is able to go through insights piece by piece, enabling marketers to understand the popularity of items beyond just how many were sold. A carefully built machine learning tool helps Lowe’s pull apart historical sales at a very granular level to see just what shoppers are looking for in any given category. Taking into account activities at nearby competing retailers can be invaluable.
Lowe’s created a team of “analytics translators” to serve as middlemen between the data science team and other departments, ensuring that everyone involved understands both what is happening and what is possible.
BBQ Guys sends out a data driven operating model (DDOM) every morning that gives employees outside of the data science team the opportunity to see what is being worked on without getting lost in technical jargon. Employees are encouraged to ask questions they might not otherwise bring up.
“They start asking how you build this and what it’s for, and that’s when we and the executives can all meet and say ‘We’re going to tie conversion rate to this’ or ‘We’re going to use linear attribution for this channel,’” said Mr. Stutes. “Before this I was having a meeting about the numbers, and how we were getting the numbers was going over everybody’s head. This kind of changed the game for us.”
DISCUSSION QUESTIONS: How can retailers reduce the learning curve around machine learning or AI tools for marketing, merchandising and other departments? What are the best routines for translating insights for department managers and employees?
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7 Comments on "BBQ Guys and Lowe’s discuss best practices for implementing AI tech"
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Chief Executive Officer, The TSi Company
Senior Vice President Marketing, PDI
This is so cool! It is brilliant that Lowe’s and BBQ Guys have AI translators who focus on helping their internal teams understand what the AI data means to them and how it directly relates to their specific roles. The approach that they’re investing resources into translation and team communication is spot-on and it will give them a competitive edge, because their team will know what to do with the potentially extremely valuable information. Knowledge and information are power, but only if you know how to use it. Lowe’s and BBQ Guys are training their teams on how to use it.
Global Industry Architect, Microsoft Retail
Change management can be a huge issue for such initiatives — getting people to “believe” in the results is critical. Before this can happen you have to convince the individual that this can help them do their job and make their life easier. Do this and then show them the value they can add by providing their insights that improves the result and helps them.
Retail Strategy - UST Global
I get the role of “translators” during the development cycle to ensure that the data scientists have the right context surrounding what they are looking at/building. But what happened to self explanatory analytics that are well-targeted/simple to understand and relevant to the person’s role?
Vice President, Research at IDC
This is all about communication. Anything that rocket/data scientists do must still be translated into concepts that are easier to understand. More importantly, these must be shown to positively impact the business and customer.
However, AI/ML is very much a black box scenario. Not everything is visible and in many cases, data scientists are testing out variations to their algorithms and training with different sets of data. It’s great to inform and outline the “Why are we doing AI?” question to departments, but giving them a say in what to test and improve is better still.
Lowe’s newsletter is a scalable idea that is a good starting point. But it can’t end there. When improving business ops, employees must be involved and understand what’s happening, which means “Data Science Training 101.”
SVP Sales & Business Development, Theatro
I’ll echo Peter’s comments. Additionally, you can have the best AI insights ever, however, they need to be turned into very clear and specific action to be taken, sent to the right person at the right time to take the action, and then have the ability to confirm and measure the results to validate the value of that specific AI insight — did it result in a net increase to business value?
Marketing Strategy Lead - Retail, Travel & Distribution, Verizon
As with any new technology, training on the tool and change management are imperative for success. This is especially true for AI, which many feel is a magical “black box” that is difficult for people to understand and oftentimes hard to accept and trust. In some cases, the AI may be taking the place of work that some employees traditionally do and this could feel threatening to those employees. Training these employees on how AI will improve their processes and decisions is critical for success.