A.I. Tools

Data Democratisation: 5 ‘Data For All’ Strategies Embraced by Large Companies | by Col Jung

It’s about data, skills, tools…and especially culture!

Col Jung
Towards Data Science
Image by Windows (Unsplash)

In 2006, Harvard Business Review published an article titled “Competing on Analytics”.

This influential piece by academics Thomas Davenport and Jeanne Harris sparked widespread discussion on the idea of leveraging analytics as a competitive business advantage.

Companies began investing in BI software, big data platforms, data science teams, and cutting-edge tools for AI and machine learning in the hopes of becoming a data-driven firm.

The results were underwhelming.

A Deloitte survey of American executives fourteen years later found that only 1 in 10 companies competed on analytical insights. Most firms could only lay claim to isolated silos of analytics excellence. And that the most popular tool for analytics was, drumroll…

…Microsoft Excel.

The truth is transforming into a data-driven organisation is way harder than it looks.

Where does your company sit? Image by author

Being able to harness data-driven insights at scale and integrate them into every day decision-making requires a high level of enterprise data maturity across multiple realms:

Data: If you don’t have good data, AI is over.Skills: Is your workforce as a whole data literate?Tools: Is your infrastructure set up for analytics at scale?Culture: This is the biggest impediment. Does your firm have a legacy culture resistant to data-driven insights? It’s a show-stopper.

My company, a ‘Big Four’ bank where I’ve worked as an engineer and data scientist for the past five years, is sitting at 2.5 out of 5 on the data maturity scale. We’re working hard to get to data-driven 4, putting us at the cusp of the industry-leading ‘digital native’ companies. (Go team!)

The average firm globally sits at around 2.2, according to the International Institute of Advanced Analytics.

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