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Companies assume ramping up analytics is a matter of hiring enough data scientists. Maybe that’s why demand for that role
is booming.
Blinded by science
Hire as many data scientists as you can find—you’ll still be lost without translators to connect analytics with real business value.
Lost in translation
In this edition:
Data scientist: A hot job that pays well
Indeed Hiring Lab
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Data scientist: A hot job that pays well
Analytics translator: The new must-have role
Analytics translator: The new must-have role
Article
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A quick briefing in five—
or a fifty-minute deeper dive
Ten red flags signaling your analytics program will fail
Ten red flags signaling your analytics program will fail
Article
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What they do
Companies need translators to bridge the gap between data scientists and frontline managers.
Discover more Five Fifties
Analytics translator: The new must-have role
Analytics translator: The new must-have role
Article
Ten red flags signaling your analytics program will fail
Ten red flags signaling your analytics program will fail
Article
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Data scientist: A hot job that pays well
Data scientist: A hot job that pays well
Dream team
But data scientists are only one of the roles needed in the age of AI and analytics.
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Need some
But are there enough translators to go around? The McKinsey Global Institute estimates that in the United States alone companies will need two million to four million of them in the next decade.
The age of analytics: Competing in a data-driven world
The age of analytics: Competing in a data-driven world
Report - McKinsey Global Institute
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The age of analytics: Competing in a data-driven world
The age of analytics: Competing in a data-driven world
Report - McKinsey Global Institute
Homegrown
Addressing the shortage won’t be easy and will require carefully customized in-house training programs.
How to train someone to translate business problems into analytics questions
How to train someone to translate business problems into analytics questions
Harvard Business Review
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256%
increase in job postings for data scientists since 2013
>$120,000
average annual salary for data scientists in the US
—Nicolaus Henke, Jordan Levine, Paul McInerney
Success with AI and analytics requires not just data scientists but also entire cross-functional, agile teams that include data engineers, data architects, data-visualization experts, and—perhaps most important—translators.”
“
—Oliver Fleming, Tim Fountaine, Nicolaus Henke, and Tamim Saleh
[Translators] help leaders identify high-impact analytics use cases and then ‘translate’ the business needs to data scientists, data engineers, and other tech experts so they can build an actionable analytics solution. Translators are also expected to be actively involved in scaling the solution across the organization and generating buy-in with business users.”
“
20–40%
must become translators to meet projected demand
10%
became translators
US graduates in business and STEM fields,
100% = ~9.5 million from 2016 to 2026
Note: STEM = science, technology, engineering, and mathematics.
—Louise Herring, Helen Mayhew, Akanksha Midha, Ankur Puri
Translators can only master their trade by observing seasoned colleagues at work and then working on actual problems with expert guidance. This progressive, real-world learning approach prepares translators to manage diverse teams of specialists, create replicable workflows, and apply business judgment while assessing trade-offs. None of these steps can be skipped if a company hopes to apply analytics widely and generate significant value.”
“
How to train someone to translate business problems into analytics questions
How to train someone to translate business problems into analytics questions
Harvard Business Review
