Learn about AI success from execs who are getting it right

Starbucks CEO Kevin Johnson - Photo: Starbucks
Sep 08, 2020

A characteristic of companies achieving the most value from investments in artificial intelligence are executives able to articulate the role of AI in their business.

Most organizations, on the other hand, pursue AI within silos. What they risk is failing and giving up and never recovering, which has severe consequences at a time when no business can afford to miss out on opportunities to improve.

Public statements by executives getting AI right highlights best practices that every company should consider.

Starbucks’ CEO Kevin Johnson, Oct. 2019:

AI investments are an important element of Starbucks’ digital strategy and work to grow digital customer relationships. Over the past year Starbucks has been “dialing up” its in-house capabilities and investments in AI through its “Deep Brew” initiative. Noted Mr. Johnson, “Deep Brew will increasingly power our personalization engine, optimize store labor allocations, and drive inventory management in our stores.”

Then P&G CIO and current Mondelez CIO Javier Polit, Nov. 2019:

“We focus on AI, starting with our data and making certain that data engineering and governance exist. We then look at ML on top of that to solve business problems. Today every company needs to be a data, analytics, and algorithmic company. If you don’t look at things from this perspective, you’re going to miss opportunities to help the business.”

Nestlé CIO Filippo Catalano, Nov. 2019:

“AI is really about experimentation and continuously improving what you do, versus the reality you need to master,” he explains. “I know it’s overused, but this idea of making it very ‘okay’ to encounter failure along the way is very important in AI, not just in general innovation.”

L’Oreal Canada Chief Digital Officer Robert Beredo, Sept. 2020:

The use of AI has been a “game changer,” helping the company differentiate service experiences with its brands, personalize consumer interactions, and remove friction from the shopping experience.

Walmart Chief Data Officer Bill Groves, Oct. 2019:

With a success rate of only 75 percent, Walmart is eager to lean into AI and machine-learning projects. One of Walmart’s standard evaluation procedures for high-tech initiatives includes answering three questions: “Why are you doing it?”, “Can you explain it?”, and “Can you implement it?”

“If the answer is ‘no’ to any of these three, we’ll typically put a stop to the project immediately, so that way we aren’t spending money that we shouldn’t spend,” Mr. Groves said.

DISCUSSION QUESTIONS: How would you prioritize developing an artificial intelligence strategy amid competing priorities in the current retailing environment? How do you think retail executives should set the tone for AI in their businesses?

Please practice The RetailWire Golden Rule when submitting your comments.
"The most important piece of AI is really thinking through the problem it will help solve."
"Personalized customer experiences, removing friction, etc. is not intelligence, rather a mapping of behaviors translated by non-intelligent systems of algorithms. "
"Most retailers never took the initial learning step – here’s what drives my business – and AI is not what they need."

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15 Comments on "Learn about AI success from execs who are getting it right"

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Dr. Stephen Needel

An AI strategy is important when you don’t know what you’re doing. Might AI uncover that great tactic or logistical issue? It might, but then again it might not. A lot of AI solutions are black boxes – you don’t quite know what goes into them or why it comes out the way it does. That might give you a great short term answer that blows up long term (or when an unforeseen event like a pandemic comes along). Most retailers never took the initial learning step – here’s what drives my business – and AI is not what they need.

Suresh Chaganti

Success depends on the culture of experimentation within the organization. Experimentation by definition leads to some failures, so the leadership has to understand that and encourage experimentation nevertheless. The related aspect is the culture of analytics. When experiments are done, they produce results. Understanding why such results came in, and attributing the right reasons, leads down the path of success.

Technology comes in rather late. Technology is also the place where most advances have been made – computing speed, availability of data processing, image processing, and more accurate algorithms. But technology alone doesn’t get results.

All these need two critical factors. 1.) Business leaders who understand the need for experimentation and a culture of analytics, and 2.) Vendors who get the business DNA and implement the solutions.

Rodger Buyvoets

Suresh is spot on. Technology should never be a retailer’s silver bullet. But to take a culture of experimentation further, retailers need to be able to approach the data that is generated with a critical, human eye, to glean actionable insights from it.

Without the human in data, business leaders can’t leverage AI to its full potential, and will encounter failure along the way. Walmart hits the nail on the head with the three questions they ask before implementing high-tech initiatives.

Richard Hernandez
Richard Hernandez
Merchant Director
2 years 8 months ago

I believe you have to be in it completely to see the real benefits of AI. That means having a solid infrastructure, clean and accurate data, and personnel to support the investment. As mentioned in earlier articles, I think the investment in AI is moving faster due to the pandemic so that companies can conduct business in an ever changing landscape. The companies must also be able to show the worth of the investment otherwise I believe buy-in will be a hard sell.

Zel Bianco

The most important piece of AI is really thinking through the problem it will help solve. What is the practical application of it? Many times AI is included for the wrong reasons and it ends up being a solution looking for a problem to solve.

Gene Detroyer

“Many times AI is included for the wrong reasons and it ends up being a solution looking for a problem to solve.” Great comment, Zel! That comment can be made for so many technology initiatives that retailers institute.

Ralph Jacobson

Not all business challenges need AI to be solved. The pressure put upon decision makers quite often drives investment in newer technologies prior to the establishment of a clear objective. We must define what our problem is, create a vision of the desired end state, and determine the most effective way to to get there — with or without AI, blockchain, etc.

Andrew Blatherwick

If a company cannot articulate what they are using AI for or what they are trying to achieve, then they deserve to fail. That would be the same for any software they purchase. Why is AI seen as a mysterious thing that when deployed by a company will solve all of its problems? Let’s get real here, AI is a tool like any other — if you do not have a direction the tool is not going to help you find it.

Brent Biddulph

First of all, recognizing data and analytics as an enterprise asset and competitive necessity is essential – perhaps obvious, but far too many have yet to embrace this reality.

In my experience, successful prioritization of AI projects takes into consideration a blend (value v. effort) of tackling low-hanging fruit (aka quick wins) to sustain momentum, incremental improvement of enterprise business processes to ensure cross-LOB engagement and fleshing out data governance improvement opportunities, and a few “moon shots” to test new hypotheses and drive innovation.

Gene Detroyer

AI is a holistic approach to problem solving. Think about a self-driving car. The AI involved cannot separately consider the operation of the car in technical silos. It can’t consider the operation of the car without anticipating the driver’s reactions and behavior. It can’t safely go on the road without anticipating every other car and its behavior — and more. Not one action can be programmed in isolation.

It is the same for retail. AI is not an analytical approach. It is a systems approach. The difference between information systems and technology and AI is that proper AI sees everything and understands how EVERYTHING interacts and affects everything else.

How should an executive prioritize AI strategy? It depends on the time frames. If the executive’s focus is five to 10 years for the company, prioritize it #1, because it will take care of everything else. If the executive’s focus is next year, don’t even start.

Karen S. Herman

AI cuts through the noise in today’s retailing environment. Developing an artificial intelligence strategy is essential to every business, large or small. There are plenty of ways to get started with existing platforms. Google Analytics uses machine learning algorithms and is easy to access. Facebook and Instagram offer features enhanced with machine learning algorithms. For big companies, there are many new platforms available to run pilot programs. For example, I am excited to see Mastercard’s Shop Anywhere pilot with Circle K, Dunkin’ and White Castle. The answer is to make AI a priority and find the right platform to get started. Period.

Kim DeCarlis

AI can best be used as an enabling technology to help retail businesses accelerate previous people-centric analysis and resulting decision-making. Retail executives should prioritize AI as part of their continuing digital transformation efforts, not in lieu of them. And these should be balanced against all of the other efforts required to run and grow the business – rather than overtake them.

Cynthia Holcomb
AI based prediction, which is a judgement of an individual customer based upon a myriad of algorithms interacting to find the “correct” answer as determined by an individual programmer, is ripe for bias. At this point in time, the retailers who have invested time in grasping AI are focused on the rudimentary steps of a one-size-fits-all solution. Personalized customer experiences, removing friction, etc. is not intelligence, rather a mapping of behaviors translated by non-intelligent systems of algorithms. Those retailers crossing into the realm of prediction/judgment of an individual human customer outcome on the behest of their internal AI models must prepare themselves for the unintended consequences of the inherent bias of AI models designed as a one-size-fits-all solution. AI diversity is not an option if retailers are sincere. “Playing” in AI has the ability to create hidden landmines, waiting to be exposed in heretofore unimagined human scenarios. Retail executives, to truly lead in AI, should take a deep dive into the documented groundswell of the across-the-board AI gender bias hidden in plain sight. In time,… Read more »
Peter Charness

AI can provide new options for solving old (largely unsolvable) problems. As others have pointed out though, the right path is not to take AI and find a problem worth solving, rather it’s revisiting existing roadblocks and determining if new tools can provide new approaches. Without a well defined use case, AI will be no more successful than any other prior attempt.

Casey Craig

As the coronavirus intensifies the need for digital and online retail strategies, retailers have a stronger reason than ever before to invest in AI solutions. That’s because data-driven AI technology can help retailers learn who their customers are and craft shopping experiences tailored to their online customers’ wants and needs. AI can power the personalized and data-efficient marketing strategies that will drive online sales.

That said, an AI strategy should definitely be downstream from a broader digital strategy. Communicating the need for a convenient, streamlined, and enjoyable online experience should remain the top priority for retail executives in today’s market. AI can certainly empower and enrich your digital offerings, but it can’t fix a broken online experience. Customers want the benefits of AI from retailers, but they need a strong digital presence first and foremost.

"The most important piece of AI is really thinking through the problem it will help solve."
"Personalized customer experiences, removing friction, etc. is not intelligence, rather a mapping of behaviors translated by non-intelligent systems of algorithms. "
"Most retailers never took the initial learning step – here’s what drives my business – and AI is not what they need."

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