#76: Can you read minds with data science?🧠
Hello,
This newsletter will take you about 4 minutes to read.
I. Spotlight: Can you read minds with data science?🧠
“Our market share declined sharply by 10% last quarter.” screams the headlines of an executive briefing.
As the CMO scrambles to find answers to this challenge, she turns to you, a data leader, for support. What do you think is critical to help plan the CMO’s decisions?
No, it's not the data that you can collect about the market or your competitors.
It's not the analytics techniques you can apply to model the scenarios.
It's not even the storytelling techniques you can use to drive understanding.
Then, what’s most important? Let’s find out by talking about a fun game show.
Mind reading on prime time
Have you heard of the popular game show ‘Twenty Questions’? It was a hit when it was launched on Radio. It ran for over 20 years and sparked many variants across countries.
In this game, a panel of hosts was challenged to identify an object in the listener’s mind by asking 20 questions or less. Each of the questions was answered with a simple ‘yes’ or ‘no.’
It was a classic parlor game of deduction.
What made the show stand out? The panel shocked audiences by guessing people, places, or items, often with just 6 or 7 questions.
One time, the panel did the unthinkable by guessing ‘Brooklyn’ correctly before asking a single question! (They got this by studying the reactions of the studio audience😀)
The key to winning this game is to ask the most optimized set of questions. It’s an accelerated journey of discovery with deductive reasoning.
You navigate with precision using carefully chosen questions. As you narrow down from the general to the specific, you sharply converge on the answer.
Things aren’t very different when it comes to solving business problems using data science.
What’s the most important thing in data science
Deep at the root of every business problem lie hidden insights. You must pursue a similar journey of discovery to uncover these nuggets of insights.
The first and most crucial step is to ask the right questions to understand the problem. Then, you choose a series of probing questions to keep narrowing down at every step as you apply the data, analytics, and storytelling techniques.
Here’s how it plays out, in sequence:
The questions will determine the data you must collect.
The data will dictate the analytics techniques you must apply.
The analytics findings will influence the visual stories you must create.
The visual stories will, in turn, drive the business decisions you should make.
Ignore #1 above, and your teams will get onto a wild goose chase. They will spend lots of time and money coming up with predictive models and fancy visuals, but these insights will be useless for decision-making.
Less Than Half of Data and Analytics Teams Effectively Provide Value to the Organization - Gartner
So, that’s how we must help our CMO solve the challenge of the declining market share. Start by questioning what caused the decline. Was it a product failing in one geography? Follow-up with questions on which competitor took away the business.
Continue this line of questioning until you get to the treasure trove of insights. Then, the business decisions to be made will jump out at you.
II. Industry Roundup:
1. Article: 5 Forces That Will Drive the Adoption of GenAI
22 minutes | HBR | Alexander Bant, Helen Poitevin, Nicole Greene, and Erick Brethenoux
Over a year post-launch, 45% of organizations are piloting generative AI, with 10% already live. Despite initial enthusiasm, Gartner predicts a slowdown but maintains that long-term benefits outweigh the risks. Executive leaders face pressures from multiple stakeholders to integrate AI strategically. This pivotal moment demands navigating risks while leveraging AI to drive efficiency, innovation, and competitive advantage. The authors advise how to manage these 5 forces by tackling expectations from boards, customers, employees, regulators, and investors.
2. Article: 7 Tips For Implementing Generative AI In Your Organization
06 minutes | Forbes | Bernard Marr
Adopting generative AI demands thoughtful implementation, focusing on enhancing human work, not replacing it. Cultivating a culture of curiosity and adaptability, investing in AI skills, and appointing a Chief AI Officer are crucial. Prioritize a strategic data approach and ensure your technology foundation supports AI integration securely. Find out how thoughtful, strategic adoption can help you leverage generative AI to revolutionize work efficiently and ethically.
III. From my Desk:
1. Article: How AI is transforming Agriculture
With a rising global population, the need to produce more with less is more important than ever. How is AI transforming the future of farming? In my latest for Forbes, I share how the critical challenges of pests, soil quality, irrigation, and weeds impact agriculture globally. With industry examples, the article highlights how AI-powered solutions are making a difference.
2. Podcast: B2B Startup Spectrum
I'm excited to announce my recent participation in the B2B Startup Spectrum podcast hosted by Pushpavalli Annamalai, discussing "Data, Analytics, and the Future of AI." I shared insights on leveraging data for transformative decision-making and the need for ethical use of AI. We also explored the power of data storytelling and the importance of embracing change, curiosity, and continuous learning in the rapidly evolving field of AI.
Thank you for subscribing and reading the newsletter. I appreciate your attention,
Ganes.
PS: Did someone forward this to you? You can subscribe here.
My Website | LinkedIn | Twitter | YouTube
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.
Recent Issues: