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Successful Frameworks for Scaling Data Maturity

Ganes, talks about scaling data maturity, building an effective data science roadmap, navigating the skills and people components of data maturity and more.

Nov 2022
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Key Quotes

When everyone in an organization understands how data and analytics is going to help, where the organization can go with data, and the business benefits are made obvious, there is much less resistance Leaders have a important role to play here in explaining why data and analytics is required. How it'll enable the business codes, who should get involved and what is expected of each stakeholders. So, the why, how, who, and what: communicating all four aspects clearly is the leader’s responsibility, and when leaders do a great job of storytelling and communicating this, then alignment is much easier.

What is important is looking at three aspects. One you reflect on the organizational strategy and the role of data. As part of that in the current state where the organization is. And number two, talk to people. Talk to the technology team, talk to the business team and understand what are their priorities? Where do they see the gaps with the data practices and how much data is able to support their business priorities. There's a second aspect talking to people and, and running surveys and figuring it out. And a third aspect, which is often missed out is you'll have to. Inspect the assets. You can't go with what people say again, each person has their own bias and blind spots.

Key Takeaways

1

The way you communicate with data can be the biggest inhibitor to shifting mindsets. When talking about data, speak as plainly as possible and refrain from using too much technical jargon.

2

When choosing projects, select two to three projects in adjacent areas of high impact to deliver a strong ROI as a combination of all of them. The more split your efforts are, the less ROI you will be able to deliver.

3

When everyone within an organization understands how data and analytics will help, where the organization can go with data, and the business benefits are communicated clearly, then there will be much less resistance to utilizing data in decision-making

About Ganes Kesari


Photo of Ganes Kesari
Guest
Ganes Kesari

Ganes Kesari is Co-Founder and Chief Decision Scientist at Gramener, which helps companies make data-driven decisions through powerful data stories and analytics. He is an expert in data, analytics, organizational strategy and hands-on execution. Throughout his 20-year career, Ganes has become an internationally-renowned speaker and has been published in Forbes, Entrepreneur, and has become a thought leader in Data Science.


Photo of Adel Nehme
Host
Adel Nehme

Adel is a Data Science educator, speaker, and Evangelist at DataCamp where he has released various courses and live training on data analysis, machine learning, and data engineering. He is passionate about spreading data skills and data literacy throughout organizations and the intersection of technology and society. He has an MSc in Data Science and Business Analytics. In his free time, you can find him hanging out with his cat Louis.

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