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The Data Daily

Forget Data Scientists And Hire A Data Translator Instead?

Last updated: 03-13-2018

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Forget Data Scientists And Hire A Data Translator Instead?

McKinsey survey. Due to this reality, some organizations have opted to add a data translator to help bridge the gap.

I have recently been approached by two separate clients about data translators, one wanted me to fulfil the role as part-time chief data translator and the other wanted my help in recruiting and training internal data translators. Given this sudden interest in this new role I thought it would be a good idea to explore what a data translator is and whether your organization needs one.

A data translator is a conduit between data scientists and executive decision-makers. They are specifically skilled at understanding the business needs of an organization and are data savvy enough to be able to talk tech and distil it to others in the organization in an easy-to-understand manner.

This professional must be someone who can “talk the talk” of both the executives and the data scientists. They are adept at extracting the business meaning and applications from the information they are provided by the data scientists. They not only respect the functions of the data scientists, but also understand the needs of decision-makers; therefore, successful data translators are typically respected by those entities in return.

How can data translators help organizations?

Data translators bridge the communication divide that often develops within an organization between data scientists and executive decision-makers. They are able to communicate with language that a decision-maker understands.

Data scientists often prefer the independence of assessing data rather than explaining to non-tech people the implications of the data, how it can help support or solve business issues, or being pulled into executive meetings to defend the data insights or why data should be trusted.

Executives can be dismissive of the data which can impact those that are responsible for it within the organization. Decision-makers usually like to know they are in control, but when faced with data they often don’t fully understand, it can make them uncomfortable.

You can invest in data technologies and collect all the data you can possibly imagine, but it’s worthless if it’s not analyzed or communicated to decision-makers so that action can be taken from the insights. Some organizations attempt to communicate data findings across departments of an organization, but something typically gets lost in translation as it makes it way from the data scientists to the executive decision-makers. This issue is so prevalent that only 18% of companies believe they can gather and use data insights effectively, according to aMcKinsey survey. Due to this reality, some organizations have opted to add a data translator to help bridge the gap.

I have recently been approached by two separate clients about data translators, one wanted me to fulfil the role as part-time chief data translator and the other wanted my help in recruiting and training internal data translators. Given this sudden interest in this new role I thought it would be a good idea to explore what a data translator is and whether your organization needs one.

A data translator is a conduit between data scientists and executive decision-makers. They are specifically skilled at understanding the business needs of an organization and are data savvy enough to be able to talk tech and distil it to others in the organization in an easy-to-understand manner.

This professional must be someone who can “talk the talk” of both the executives and the data scientists. They are adept at extracting the business meaning and applications from the information they are provided by the data scientists. They not only respect the functions of the data scientists, but also understand the needs of decision-makers; therefore, successful data translators are typically respected by those entities in return.

How can data translators help organizations?

Data translators bridge the communication divide that often develops within an organization between data scientists and executive decision-makers. They are able to communicate with language that a decision-maker understands.

Data scientists often prefer the independence of assessing data rather than explaining to non-tech people the implications of the data, how it can help support or solve business issues, or being pulled into executive meetings to defend the data insights or why data should be trusted.

Executives can be dismissive of the data which can impact those that are responsible for it within the organization. Decision-makers usually like to know they are in control, but when faced with data they often don’t fully understand, it can make them uncomfortable.


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