What’s common to women during the World War and AI adoption at organizations👩🔧?
Hello,
I’m a productivity junkie😳 For example, I pair up all of my physical, non-thinking tasks with those that need mental attention - listening to audiobooks while I walk/drive or getting more out of Zoom calls by pairing them with household chores.
While some of these are useful, I often go overboard and optimize my entire day. I realized my folly when I read Digital Minimalism. Cal Newport highlights the value of solitude - not just time alone in a remote cabin, but time alone anywhere with zero external inputs.
“Regular doses of solitude are crucial for the effective and resilient functioning of your brain,” Newport adds. This is when your mind processes complex emotions, makes critical connections across domains, and paves the way for ‘Eureka moments.’ I’ve started giving myself at least 30 to 60 minutes of solitude every day - while driving, pressing the clothes, or in those breaks between calls. I’ll share how it goes.
This newsletter will take you about 5 minutes to read.
I. Spotlight: What’s common to women during the World War and AI adoption at organizations👩🔧?
As parts of the world open up, people are eager to slip back into the old normal. After all, the familiar comforts of the physical world are too tempting.
Take the example of university education. Most institutions have switched back to in-person classes with compulsory residential programs.
“It’s as if the Covid-forced changes were a temporary nuisance that can now be conveniently forgotten,” says Vijay Govindarajan, Coxe Distinguished Professor at the Tuck School of Business at Dartmouth.
Today’s big question is whether the pandemic-driven innovations will be sustained and built upon long after masks and booster shots are gone.
Looking back at history, we can find our answers. Govindarajan shares the example of World War II, another black swan event.
The revolutionary change birthed by World War II
(Photo by Library of Congress on Unsplash)
With American men drafted into military service, the factories suddenly didn’t have enough workers. So, they reluctantly recruited women, something they had resisted until that point. Not only did women do these jobs, but they also excelled at them.
However, this revolutionary change didn’t last after the final shot was fired in the war. As men returned, women were promptly retrenched from their jobs.
It took a few years for factories to re-embrace the idea of women as part of the mainstream workforce, working alongside men. However, this shift did happen, and the women's movement has never looked back.
Isn’t this similar to what’s happening now during the pandemic?
Once any crisis or urgency passes, the human tendency is to go back to business as usual. “I call it dominant logic,” says Govindarajan. “This makes people say, ‘That nuisance is over, so let’s all go back to our face-to-face classrooms.’”
This is the equivalent of factories firing women once men became available for recruitment after the war.
The longer a practice or entity has been in operation and the more successful it has become, the tougher it is to shake off dominant logic.
Dominant logic and AI-driven transformations
What’s the biggest roadblock reported by Chief Data Officers for the adoption of AI? It’s organizational culture. The inertial force that’s at play here is dominant logic.
How can organizations tackle it to get over this cultural resistance?
To learn a new behavior, organizations must first forget old ones - those that hold you back. “If you can’t forget, you can’t learn,” says Govindarajan. He shares a blueprint for forgetting organizations in his strategy framework, called The Three Box Solution.
Drawing lessons from this framework, there are two ways to fight dominant logic:
Role of leadership: Leaders shape organizational culture, consciously and subconsciously. When habits become dysfunctional, it’s the leaders’ responsibility to intervene - through ongoing messaging, incentivization, and hard decisions.
Continuous re-evaluation: To weed out non-constructive behavior, you must first identify it. Set up mechanisms to continuously evaluate the relevance of established ideas and prune out unhealthy ones. Organizations must create a conducive environment of trust and openness to enable this.
Once you tackle dominant logic, opportunities open up for creating the business of the future with AI.
Curious to know more about the three-box framework and how it can help build an AI-powered organization? Check out my interview with Professor Govindarajan.
II. Industry Roundup:
1. Article: Why humans inject the most uncertainty into AI-based decision-making
9 minutes | MIT SMR | Philip Meissner, Christoph Keding
How executives interact with AI puzzles researchers. Individuals make entirely different choices when presented with identical recommendations from AI. Research categorizes human response into 3 types: from skeptics who don’t trust AI to delegators who shift not just decision-making but responsibility as well to AI. How to balance these extremes and integrate AI into decision-making? Check out the suggestions.
2. Article: How Midsize Companies Can Compete in Data Science
7 minutes | HBR | Yannick Bammens, Paul Hünermund
Two classes of companies seem to share most of the spoils of AI’s capabilities: startups and multi-billion-dollar giants. Midsize companies are often left out. In a survey of 6,000 firms, only 15% had successfully adopted AI. To compete in the data-fueled economy, mid-sized companies must forge joint AI ventures. The authors share approaches, likely challenges, and resolutions.
III. From my Desk:
1. Article: The 3 steps to building an AI-powered organization
10 minutes | Forbes
Today, there is great awareness about the potential of AI. But, building an organization with AI at its core is extremely tough. This article is based on my chat with Professor Vijay Govindarajan, and it shares recommendations for putting data analytics at the heart of your organization.
2. Podcast: The 4 key indicators of a thriving data culture
46 minutes | Narrative Science
What really is Data Culture, and what makes it thrive at a workplace? Why is mindset more crucial than skillset for data-driven decisions? Check out answers to these questions and my confession on why data science is overvalued today.
3. Upcoming Talk: Cognitive biases in decision making
40 minutes | 500 Startups
What are the most common cognitive biases that impact leaders? How can early-stage startups lay a foundation for data-driven decisions? In this fireside chat, I will be addressing startup founders on how to champion good data stewardship, embed it in product development, and ensure organizational ROI from data.
-> Register for the free talk (10th November)
Have a dirty backyard? Clean it up by training birds with this nifty bird feeder that exchanges bird treats for bottle caps!
Thank you for subscribing and reading the newsletter. I appreciate your attention,
Ganes.
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I’m Ganes Kesari. I publish ‘Data-Driven Future’ to help understand how data shapes our world, explore key trends, and explain what they mean for you today. I speak and write to demystify data science for decision-makers and organizations.
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