DDF #23: 🛡️There's a new insurance policy to protect your data projects from failure!
DDF #23: 🛡️There's a new insurance policy to protect your data projects from failure!
Hello!
This newsletter will take you about 5 minutes to read.
I. Spotlight: 🛡️There's a new insurance policy to protect your data projects from failure!
A few years ago, a French company was working on a new deal. The client planned a meeting in their Paris headquarters and brought in some of their employees from other locations.
The sales team didn’t realize that the client’s overseas employees couldn’t speak French. At the end of the day, the deal couldn’t be closed because the people in the room couldn’t communicate.
Imagine losing a big deal due to a language issue.
“It was a shocking wake-up call for the leadership,” writes Tsedal Neeley, Professor at the Harvard Business School, in her article for HBR. “Adopting a common mode of speech isn’t just a good idea; it’s a must,” she adds.
It’s easy to understand why language literacy is crucial for successful communication - you must be able to read, write, and converse with people. However, we don’t give the same importance to communicating with data.
Today, data is the new currency of businesses. If you can’t read, write, and converse with data, it hurts your business and personal effectiveness.
(Photo by Sharon McCutcheon on Unsplash)
Data is the fuel of the digital economy
Let’s say a COO makes a strong case for market expansion to grow company revenues and tackle competitive threats. He presents a compelling pitch with statistical summaries and lots of charts. If other executives in the room can’t grasp the data insights or their implications, they won’t reach the right decision.
Quite like how the French company lost their sales deal.
Data literacy is the ability to understand, create, and communicate data as information. It’s NOT so much about interpreting data architectures, building machine learning models, or creating visualization dashboards.
You must have the comfort to work with spreadsheets of data, identify basic insights, read charts, and interpret their business implications. It’s as simple as that. This skill is critical not just for executives but for every single individual in an organization.
When data is the new currency, you must empower all your employees to exchange it freely. How will this new skill help your teams?
There are three ways your data literacy investment can payback:
Pick right projects: Stakeholders who can communicate using data understand how it helps the business. They ask the right questions and help pick the most impactful data projects to execute.
Collaborate better: Most data initiatives suffer due to a communication breakdown between technology & business teams. Better data literacy leads to a sense of shared understanding and collaboration.
Improve adoption: Poor usage of data solutions is a roadblock that stumps data leaders. Data literate users tend to adopt ML solutions readily and embrace data-driven decisions rapidly.
Improving data literacy is a transformation initiative that takes time. It needs coordination across the entire organization and strong leadership support. However, it is well worth the effort.
Valerie Logan, CEO of The Data Lodge, sums it up well - “Data literacy is an insurance policy for your past, current, and future data analytics & AI investments.” It is your key to unlock value from the millions of dollars you spend on your data initiatives.
II. Industry Roundup:
1. Culture is no longer the top challenge for AI adoption, says O’Reilly
20 minutes | O’Reilly | Mike Loukides
O’Reilly runs an annual survey on ‘AI adoption in the Enterprise.’ "Culture," which was the top roadblock for several years, is now down to #4. “Identifying use cases” dropped to #3. This year, the top two challenges are "Talent shortage" and "Data quality." This order change surprised me since I see many organizations continue to struggle with ‘culture’ and ‘use cases.’
2. The Global AI Index ranks 62 countries on seven key pillars
5 minutes | Tortoise Media
We don’t have many indices that benchmark nations on their level of investment, innovation, and implementation of artificial intelligence. I loved that this Global AI Index uses a lot of public data such as Github activity, digital skills, patents, MOOCs, and broadband speeds to arrive at 143 indicators. With this, they analyze how 62 countries around the world are making sense of AI.
3. Podcast: Less Algorithm, More Application: Lyft’s Craig Martell
20 minutes | MIT Sloan Management Review | Sam Ransbotham
Today, when organizations depend more on technology-driven solutions to solve business problems, algorithms themselves are less important, says Craig Martell. What’s more important is how they fit into the overall product roadmap. He shares what this shift means for cross-functional collaboration in organizations.
III. From my Desk:
1. Upcoming Talk: 5 Steps to transform into a data-driven organization
Organizations struggle to get value from data despite big-ticket investments. There's one factor that influences the outcomes of all your data initiatives. This webinar will show what it is and lay down 5-steps to help you become data-driven.
-> Register for the Webinar (May 27th)
2. Free tool to assess your data science maturity
Do you want to find out your organization’s data science maturity? Here’s a 5-minute survey that we’ve built at Gramener that assesses your capabilities and sends a personalized report on email.
-> Get your Free Maturity Score
Have you seen Google’s latest tech that renders hyper-real 3D videos to get you closer to your loved ones😲? Here’s a preview of Project Starline.
Thank you for subscribing and reading the newsletter. I appreciate your attention,
Ganes.
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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.
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