Biases and approach
It’s well known that humans tend to fear the unknown, and are more comfortable with things or situations we understand and are familiar with. This phenomenon was reinforced when Zpryme and Asha Labs surveyed over 1000 consumers to understand customer sentiment on Artificial Intelligence (AI). We asked consumers between the ages of 18–65 whether they knew about Artificial Intelligence (the theory and development of computer systems able to perform tasks that normally require human intelligence) and what impact they believe AI will have on their lives or on society. 20% of the respondents did not know what AI is. Amongst the 80% who did know, there was an even split between those who believe AI will have a positive impact and those who believe it will have a negative impact on society. It gets interesting when we assess how respondents believe AI will impact individuals personally. Surprisingly, the majority of those familiar with AI do not think AI will impact them.
What does this have to do with the utility or energy industries and employees? Let’s start with three short stories on where AI and data science are today to illustrate the potential that innovative thinking has to transform our industry.
Stories of AI in real-life
- Story 1: In 2016, Google’s DeepMind built AlphaGo, AI that could play the board game, Go. Go is considered the world’s most complex game with 361 legal moves for every player turn and 10^(5.3 × 10¹⁷⁰) total moves, i.e. a whole lot of moves. The DeepMind team trained AlphaGo by having it ingest all the historical data on all moves made in every recorded game of Go and provided by experts. AlphaGo defeated the world champion 4–1. AlphaGo played moves that ‘did not make sense to human minds.’ Even the greatest Go players in the world. This feat seemed incredibly impressive at the time. Impressive enough that National Grid signed a partnership with DeepMind to use AI in optimizing data center energy usage, this after DeepMind had performed the same feat of resource usage optimization in Google’s data centers. Just a few months later, the DeepMind team announced that they had built AI (AlphaGo Zero), AI that was only provided with the rules of the game and a Goban (the board on which the game is played). AlphaGo Zero trounced AlphaGo 100–0.
- Story 2: Amazon changes product prices 2.5M times per day. That amounts to a price change for an average product of about every 10 minutes. No two customers see the same price. The price changes are based on customer shopping patterns, demand/supply, competitors’ prices, profit margins, inventory and hundreds of other factors. Using data science (and some claim AI), Amazon can predict what products users will buy and, in a feat of impressive operational efficiency, pre-deliver it to a location close to the user. This enables same-day delivery.
- Story 3: The Alibaba group’s grocery store, HEMA, displays the prices of products (in their physical locations) on wi-fi enabled price tags. The prices are determined by online and offline supply/demand, product freshness, the location of the store and proximity to different customer taste profiles etc. Customers shop in the store using their mobile phone with the Alipay app. Two shoppers who walk past the same product within a few seconds will see and pay different prices for the product. All based on hundreds of factors, including shoppers’ buying history and propensity to buy. Should a customer choose the delivery option when ordering online, the same models are used to optimize price and delivery..
What does this mean for incumbent companies?
In assessing new technologies and ideas, our minds rely on old models of understanding. When it comes to AI possibilities (intelligence at a level we cannot truly understand), we model AI as a potential extension of the things we already know (data analysis getting more powerful and not impacting us as individuals that much). Respondents to the survey believe that AI (or data science) will not impact their lives, but AI is already enabling companies to harness optimal levels of operational efficiency that create unbelievably personalized experiences and, consequently, generate margins and revenues that we couldn’t fathom just a few years ago (Trillion Dollar market cap companies!?!!). Most customers don’t even realize this is happening in real-time, because it is that seamless. Where is the equivalent of this in the utility or energy industry?
Honing In On Utility Industry CX
For customers to truly feel the impact of AI, utilities will have to make an investment in forward looking employees that are open to embracing change. To build the technologies that will enable utilities to compete with companies like Amazon in delighting customers (or at least stealing some mindshare), utilities need employees who truly understand these technologies. The industry will need to attract employees who can build AI to create a future utility platform that optimizes for resources and prices with no historical info, like AlphaGo Zero. An employee driven culture of innovation will enable the technological revolution that personalizes pricing for the customer, all the while improving the operational efficiency of delivering reliable, safe, and cost effective power. These new employees, and their perception and consequent interests, will cut across the traditional demographic profiles.
The capital requirements and asset base of the current electric grid model prohibits upstarts from from totally dis-intermediating utilities soon. This is one reason the industry is complacent, and it has lead to a dearth of talent to compete in a future where technology will provide experiences/value unlike what we’ve ever experienced. Ultimately, it will amount (and is amounting) to a spiral of lost opportunity in a time when 50% of the industry, the ones who got us to where we are, will retire in the next few years. Now is the time to refresh the pool with the right talent for the industry’s future. The survey data sheds some light on sentiment across taste profiles, gender and even traditional demographics that require some deeper analysis.
Over the last few months I’ve spoken to or heard about talent leaving the utility industry on both ends; mature talent retiring after having served the industry so well and newer talent leaving the industry to transition into other sectors due to the ‘lack of exciting or innovative opportunities‘ in the utility industry. To stay vital, every organism sheds skin and replaces it with new skin. The utility industry is shedding skin but not adequately replacing it with the new talent necessary to create these futures-we-want™. Hiring as usual won’t cut it. How can we attract the talent that makes the utility industry exciting again? Talent that moves the industry from chasing to leading the customer empowerment revolution?
The answer is in speaking the language that younger creatives and new age workers (who won’t have the 15yrs of experience in the traditional industry) speak. These new workers will come from outside our traditional recruitment approaches. We’re not suggesting that the industry declare itself to be AI first, like Google. But, we do need to bring in employees with the technical understanding and strategic vision to see where the possibilities lie for the future of this industry. Employees who speak the language.
The real question then is, what is that language?
More to come…
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