4 Things Your Competitors are Doing to Cultivate a Data Culture💡

Sep 24, 2021

Hello,

I just completed 10 years of my startup journey with Gramener🎉. We got started with a mission to solve the challenge of data consumption at organizations. Back then we were clueless if data analytics and visualization would resonate with clients and if the market was big enough. Little did we know about the coming tidal waves.

The best part of my journey so far? The flexibility to explore new disciplines within data analytics, set up greenfield teams, operate-stabilize, and transition before moving on to the next thing. I’ve set up 5 teams in the past 10 years and they are all an integral part of what we do at Gramener.

This newsletter will take you about 5 minutes to read.

I. Spotlight: 4 Things Your Competitors are Doing to Cultivate a Data Culture💡

What’s often considered nirvana for organizations that aspire to use data for decision-making? Data culture. But what does this term really mean?

It is often tossed around to explain away failures in delivering value from Artificial Intelligence (AI), or to describe vague goals with analytics.

Is data culture just another buzzword - just like big data, AI, and gazillions of other fancy terms in data science? (which is yet another buzzword😀)

(Photo by Susan Holt Simpson on Unsplash)

What really is data culture?

It is said that an organization’s culture is what employees do when no one is watching. Culture is the collection of shared values and practices that drive the actions of all team members. Similarly, data culture is the collective behavior and beliefs of people in how they use (or don’t use) data for decision-making.

“To make sense of data culture, we need to understand how it fits into the overall corporate culture,” said Katherine Tom, CDO at the Federal Reserve Board of Governors.

Data is often meaningless on its own. “The essence of data culture is in figuring out the real purpose of data,” she adds.

The four traits of organizations where a data-driven culture thrives

Peter Drucker famously said that culture eats strategy for breakfast. Bringing about a culture change is exhausting and time-consuming. But, it can be done.

Here are four key traits of organizations with a strong data culture:

1. Executive leadership owns and drives the use of data

Executives at data-leading organizations don’t just sponsor data and analytics initiatives: they own them. “If you don’t have leadership buy-in, then you don’t really stand a chance,” said Elizabeth Puchek, CDO of U.S. Citizenship & Immigration Services (USCIS).

“If a director looks at a dashboard or an analytics product frequently and uses that to ask questions of the operations, then the adoption of this product will easily get propagated down the chain,” she adds.

2. Data champions break silos between teams and promote collaboration

While leaders can start the fire, change agents carry the torches across the length and breadth of the organization. Identify people in departments whom you consider data-driven and make them data champions.

These champions evangelize the use of data among their groups. They turn into interpreters of data and help build bridges between teams.

3. Data is trusted, easily accessible, and freely shared

For people to use data for decisions, they must first trust it. Additionally, data and insights must be readily accessible to every employee within the organization. This is often called the democratization of data.

Contrary to conventional opinion, share data not just internally but also externally. Gartner found that sharing data externally generates three times more measurable economic benefits for organizations.

4. Data literacy is considered a critical skill for every role

Data-driven organizations see understanding and communicating with data as critical skills for every employee. They don’t relegate data literacy to just data and analytics teams.

With a common language for data, people across business and technology teams can freely exchange ideas in a manner that is enabling rather than inhibiting.

The benefits of building a data-driven company

Given the time, commitment, and resources needed to orchestrate such a change, what’s the payoff? IDC found a clear 46.2% improvement in financial, customer, and employee metrics at data-leading organizations.

Thus, the business benefits of data culture are tangible. However, the key thing is to not get intimidated by the magnitude of change. Start small, secure easy wins, and build momentum over time.

II. Industry Roundup:

1. AI Doesn’t Have to Be Too Complicated or Expensive for Your Business

7 minutes | HBR | Andrew Ng

When it comes to adoption and ROI from data science, there’s a big divide. How did consumer internet companies succeed with AI while those in industries such as manufacturing and healthcare fall behind? Companies in legacy industries have failed to adapt the AI playbook to their unique challenges, says Andrew Ng, an AI pioneer.

He explains why companies should focus on data rather than algorithms. He shares a 3-step approach to tackle small data, talent shortage, and non-scalable pilots.

-> Read the Article

2. How Home Depot uses AI to help customers improve their homes

22 minutes | MIT Sloan Management Review | Me, Myself, and AI

How can analytics help manage a portfolio of over 2 million product SKUs? Home Depot’s head of data science for E-commerce explains how they optimize search to ensure customers find the products they need. She shares how to productionize pilots and why cross-functional teams are crucial for complex technology projects.

-> Listen to the Podcast

III. From my Desk:

1. PennState’s AI-for-Good Challenge: Reviewing Startup MVPs

The annual Nittany AI challenge puts student teams through a rigorous 8-month process wherein they conceive ideas, build MVPs, and take them to the market. The $25,000 prize pool is awarded to help winning teams scale to the next level.

I was part of the industry board that reviewed the final submissions, last week. I was pleasantly surprised by the quality of ideas, the depth of execution, and the market potential. Some of the teams had achieved revenue run-rates and traction that even funded, early-stage startups struggle to achieve. Tune in for the results next week.

-> Register for the Expo & Final Results (September 28th, 6 PM ET)

Have you seen the hilarious Back-to-Office video 😆? I loved it.

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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