07 OCTOBER 2024
Transient advantage isn’t going away – how AI can help

by Rita Gunther Mcgrath: Associate professor at Columbia Business School.

The field of strategy has long been anchored to the idea that industries exist and that the normal state of things is in equilibrium. Maybe that was the way things were, but it certainly isn’t the way things work now. Instead, we need to be building systems capable of coping with transient advantage. Here are some ways AI can help.

Strategy had its intellectual roots in industrial economics. In that tradition, there are two truths that are taken for granted. The first is that the position within an industry occupied by a firm will determine its fate. The second is that the normal state of things is equilibrium. Change is considered a temporary state that punctuates the norm – hence “punctuated equilibrium.” Innovation is an aberration, not a core economic activity of a firm.

But we all know that today industries are colliding unexpectedly and that competitive advantages can come and go in the blink of an eye. What that means is that we need to figure out how to adapt our strategies to whatever is going on in the moment – I mean, even two months ago nobody was associating Brat Summer with national politics. Two months ago I didn’t even know what brat summer was!

Consider just a few major assumptions that were considered bedrock that are now going by the wayside:

Globalisation is a one-way street: the end game is going to be awesome! Well, maybe not. Our assumptions about globalisation haven’t met reality very well. We thought that the world was going to march merrily together in a pro-western, pro-democracy, pro-free-trade framework. Instead, geopolitics is perhaps at its most fraught point in decades. We’ve gone, as my colleague Mauricio Cardenas would say, from offshoring to nearshoring, and now with the advent of war in Europe, increasingly “friend-shoring!” Or as he put it in a recent lecture for my Genentech class “This time, the crises are different.”

In just three generations, women have taken astonishingly larger roles in commercial and political life, and by 2030 are predicted to control much of the world’s wealth. That shift is going to take whole industries (looking at you, financial services!) by surprise and will leave a lot of those who aren’t prepared in the dust.

There is such a thing as unambiguous truth. Well, we used to have mass markets for news and entertainment and there were few alternatives to those. Today, people can live in entirely self-constructed news bubbles. Traditional news organisations are reeling from a shift in consumer behaviour and underlying technologies.

Retirement? What retirement? Lifespans used to have retirement at the age of 65 make sense. Today, modern medicine has produced marvels in terms of longer lifetimes and treatment possibilities for previously incurable diseases, causing taken-for-granted assumptions about careers to be shaken. Seniors are hanging on to their jobs for longer, sometimes blocking younger people from moving into them – and sometimes careers are starting for the last third of life, which used to be unheard of.

A whole boatload of new risks are popping up, seemingly daily. JP Morgan Chase alone is spending $15 billion per year on protecting itself against cybercrime, a threat that perhaps 30 years ago was non-existent.

Change is the normal thing, now

Strategists today need to focus at least as much attention on periods of foment and change as they do on periods of stability. Further, our models and frameworks need to cover the whole life cycle of competitive advantages, from the earliest periods of remote possibilities, to the decline of past advantages that require an organisation either to transform, become irrelevant, or disappear altogether.

Questions of organisational form and design can no longer be considered independently from strategy. In a world that is fundamentally unpredictable, a huge part of strategy is designing a system (an organisation) that can engage appropriately with its environment. 
Here are some ideas on how AI can help:

Predictive Analytics: AI can analyse vast amounts of data to identify patterns and trends that might indicate emerging problems, such as declining market demand, shifts in consumer behaviour, or supply chain disruptions. For instance, AI has been helpful in identifying potential COVID hotspots by examining wastewater studies.

Early warning systems: At Valize, we use AI to help build early warning systems for companies. The idea is that you identify a “time zero” event that indicates an inflection point has arrived, then work backward to identify leading indicators that might suggest when it is more or less likely. With AI, monitoring those signals becomes a trivial exercise that you can actually build into an ongoing workstream.

Continuous monitoring: AI can continuously scan internal and external data sources, such as market data, social media, and news outlets, to detect signals of potential strategic issues. For instance, my colleague and collaborator Chandler T. Wilson was able to anticipate Europe’s divided response to the original Russian occupation of Crimea and how the whole system responded, leading to a more coherent response to the 2022 incursion of Ukraine.

Scenario analysis and simulations: One of the big problems with traditional scenario planning is that it is just so heavy, that busy executives don’t ever go back and look at the scenarios, which kind of misses the point. With AI, you can simulate what-if, impact, and possible futures quickly, immerse people in those futures and develop a far wider lens than you would otherwise apply to problems. Kes Sampanthar and I have a whole bunch of models for doing that. And a new project on the brink (shhh, it’s a little stealth at the moment).

Natural Language Processing (NLP): With natural language processing, you can analyse sentiments that appear as text such as customer feedback, social media posts, and news articles to gauge public sentiment and detect early signs of reputational risks or shifts in customer preferences. It can also keep track of text references and information put out by competitors. And you can use it for your own communication too – here’s a fun idea for creating your own “brat summer” meme from an AI creator. See what we did there?

Decision support systems: AI can provide actionable insights and recommendations based on data analysis, helping leaders make informed decisions quickly when strategic problems arise. For certain types of decisions, AI can automate the response process, ensuring that appropriate actions are taken without delay. For instance, AI might instruct a peaking plant in the energy business to come onstream when demand exceeds a certain level.

Adaptive learning: AI systems can learn from past decisions and outcomes, improving their ability to spot emerging problems and recommend effective responses over time. AI can help with constructing a post-mortem of an engagement, for example, or help you to improve your skill at interviewing by giving you feedback it would be hard to get any other way.

Collaboration and communication tools: AI can facilitate collaboration across teams by automatically routing information to relevant stakeholders, suggesting appropriate responses, and coordinating action plans. It can also summarise complex data into easily understandable formats, making it easier for decision-makers to quickly grasp the situation and respond.

Customer insights: AI can put together a picture of what might lead a customer to end your relationship and alert you if any of these indicators are present. It can also automatically take action to counteract any weaknesses.


Source: Rita McGrath works extensively with leadership teams in Global 1000 companies who wish to develop their capability to drive growth. Visit our web-site at: http://ritamcgrath.com.

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