Is AI needed to cure this existential business crisis? (Part 2)
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Kohl’s, Walmart and Trader Joe’s stories add more perspective and depth to my earlier analysis of how BestBuy survived the Amazon threat. None of these four success stories could be described as AI strategies even though many aspects of some of these firms’ business strategies benefitted from the use of AI technology.
Before analyzing the business strategies and uses of AI, let’s look at the problem through the eyes of CEOs.
CEOs are not blinded by the AI light. They’ve not approved significant investments in AI. Only one US CEO out of twenty, 5% percent overall, say AI initiatives are either fundamental to their organization’s operations or present on a wide scale across the organization.
They’re not totally ignoring AI either. Forty percent say their firms have introduced AI initiatives for limited use. Those uses consist of pilots, prototypes, experiments and tool refinements, not strategic imperatives in service of significant new business strategies.
Fear of competition from apex internet predators takes precedence over AI. That’s a pretty rational approach. The internet predators are a clear and present danger. They are clearly capable of taking away lots of business from many players in a broad range of industries.
AI? Sure, go build some prototypes and run some pilots and demonstrate real business impact. Come back when you have something substantial.
Particularly in the US, there’s already been a lot of technology investment in various enterprise systems, more so than in other geographies. That’s a handicap under some conditions. Consider some of the roadblocks enterprises face:
- Too many unintegrated systems. They have a jumble of disparate enterprise application systems already, driven by acquisitions as well as technology purchases by line-of-business managers for “their own businesses.”
- Data confusion. Your enterprise data is obscured in silos. They are owned by different EVPs and labeled, cleaned and stored in dissimilar ways. This complicates efforts to use all the enterprise’s data coherently.
- Too much pain, too little gain. Major vendors and consulting firms pitch large scale projects to consolidate enterprise systems, applications and data. Too many CEOs know of significant integration projects that disrupt enterprises for years, consume vast amounts of resources and fail to deliver the promised strategic results.
- The clear and present threat of Amazonization. If it’s not Amazon that’s feared the most, then maybe it’s Walmart or Alibaba or some other similar apex predator.
- Where are the strategic business outcomes from AI? The largest enterprise AI investment area right now, chatbots, might reduce call center costs, raise caller satisfaction or increase upselling. But, so what? Those results aren’t bad, but they don’t feel adequate to stave off the Internet interlopers, the apex predators.
How does your enterprise do on these five roadblocks?
In my previous post, I considered the position of BestBuy. In 2012, they seemed to face an existential crisis versus Amazon and other dominant Internet merchants. I offered several strategic alternatives that might have made sense for BestBuy to protect itself from the apex internet predator threat.
The surprise was that BestBuy has done better than anyone expected back in 2012, but their primary focus was on smart business moves, not technology driven strategies. (Technology plays some role in almost everything — let’s not get sidetracked.)
BestBuy is not alone.
Kohl’s has protected itself from being Amazonized by partnering with Amazon. Last year, they started a pilot in the Chicago area, involving 100 of over 1100 Kohl’s stores, nationwide. In the pilot, they handled merchandise returns for Amazon, making it easier for Amazon’s customers to return goods to Amazon while walking through Kohl’s stores. They experienced a net increase of 8% in overall foot traffic and a net 5% gain in revenue.
Kohl’s announced on 23 April 2019 that it will expand its handling of Amazon returns to all its US stores. It is also converting excess retail space to partnerships with other firms (Aldi, the discount grocery chain, and WW — formerly known as Weight Watchers.) These moves are very similar to some of BestBuy’s.
Examples of Kohl’s uses of AI include customer-facing chatbots, personalizing search results and empowering customers to search for products based on pictures they submit.
Walmart’s strategic initiatives to hold off Amazon’s threat to Walmart’s business include:
- Exploiting a logistical advantage. They use their dense network of stores as fulfillment centers for orders placed on the internet.
- Delivering orders placed through Walmart’s app direct to customers’ cars at the curb
- Partnering with Google (voice-based ordering) and other AI-intensive firms such as Tencent and JD.
Examples of Walmart’s uses of AI include it’s just unveiled AI-powered store of the future with in-store vision-enabled robots and drones to take inventory and identify items placed on the wrong shelves, other robots with vision systems to clean floors and e-commerce systems that better engage customers online.
Trader Joe’s doesn’t sell products over the Internet, has no loyalty programs and runs no sales. But they:
- Sell twice as much per square foot as Whole Foods
- Are highest rated of 287 brands on customer experience
- Minimize the consumer confusion of too many choices
- Refuse to carry goods that aren’t at least competitive priced (simplifying their supply chain)
They’re also heavily private-label — much more so than the grocery majors — positively influencing their bottom line.
I’ve had a hard time finding information on Trader Joe’s use of AI. Forbes noted
In an era when “data is king” … and retailers use all sorts of technology such as beacons, RFID, and artificial intelligence to better understand their customers and optimize their customer experiences, it’s quite unbelievable that Trader Joe’s doesn’t use data, analytics, customer relationship management or any other means to target, segment, or track its customers.
Instead, it seems the company relies on its people to facilitate the kind of customer intimacy that enables it to have the products and deliver the experiences that customers want. Employees regularly interact with customers to get their input and feedback. Even CEO Bane often works in the stores as a bagger, as one of the podcast stories revealed.
- All in all, not the strongest recommendation for a technology-based offensive against Amazon! More to the point, CEOs want and need to drive business initiatives. When technology can assist (efficiency or competitive impact) with minimal disruption, do it.
- The most significant bottleneck preventing firms from making full use of new digital technologies like AI? These new technologies lack genius! They lack creativity, insight, judgment and common sense. Humans are still required. Ignore fictional nonsense.
- Neither AI nor other analytics would have driven Hilton Hotels to create an Airbnb before Airbnb was formed (August 2008.)
- Nor would AI (or other analytics approaches) tell your CEO how to deal with the threat from an apex internet predator like Amazon or Alibaba.
AI Action Plan
- Educate yourselves and then others. There is no genie in this technology bottle. The intelligence lies in the heads of the developers who built the system. It doesn’t train itself or learn by itself. It’s programmed to do that! (And the programming consists of models, parameters, data and code.) From a business strategy point of view, the intelligence lies in the heads of the executives and their advisors. Not in the AI.
- Disabuse people of the commonly held but fictional and fanciful attributes of AI. Focus on potential business outcomes that can be enabled by advanced technology. Business reality should be the center of gravity, not technology. People have been talking about (and working on) AI for almost 10,000 years. The state of the AI art is better than it ever has been before, but it’s still likely centuries away from delivering on the vision people have pursued for 10 millennia.
- Create an AI center of technical expertise (AI-CTE). Every enterprise needs a small AI-CTE on the state of AI science and engineering, typically staffed with 2 to 3 people (max several) because some AI is seeping into everything and management needs local experts to turn to. The AI-CTE should: (a) Vet various pilots, prototypes and simple, tactical projects around the enterprise. They’re good to have. Don’t over-invest. (b) Establish enterprise norms, policies and governance (including ethics, social and regulatory affairs.) (c) The AI-CTE should report to the CTO.
- Take simple, practical steps that make a whole lot of sense. For example, see Does Machine Translation Affect International Trade? Evidence from a Large Digital Platform for an example of a low-difficulty, low-complexity, minimum-disruption business initiative that involves an off-the-shelf “AI” technical capability.
- Embrace tactical opportunities as they appear. For example, look at AI Data Tooling to semi-autonomously clean and integrate data from multiple, disparate, internal and external sources. Two relevant providers are Datalogue.io and r4.ai.
- Where possible, buy instead of build. Minimize custom requirements on external providers (typically unavoidable.)
- Do not try to compete with the giants of AI (Alibaba, Amazon, Baidu, Facebook, Google, IBM, Microsoft and OpenAI) unless you are in their business.
- Avoid extended blackout periods (and moonshots in general). Projects should follow a quarterly cadence: MVP in one quarter, next revision in one more quarter and so on.
Homework: What do you know of your enterprise’s strategic initiatives? What is your CEO going to be measured (and compensated) on? How can you apply this blog post to the facts on the ground in your organization?
This post represents my opinion. I wrote it myself.
Previous posts this post builds upon:
Is AI needed to cure this existential business crisis?
Apex internet predators will devour you
CEOs are seeking major business initiatives, not AI or other tech giblets
Only 5% of US enterprises are investing in serious AI-based business projects