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The ‘Analytics Translator’ – Turning big data into better business

by Ami Jayakrishnan October 03, 2018
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Previously, I shared some thoughts on what the current ‘digital skill-set’ looks like and the steps that businesses and consultants can take to ensure that they are plugging this skills-gap in the most efficient way. I touched on the concept of a ‘translator’ i.e. an individual who has excellent strategic decision-making experience, either through their strategy consulting or corporate strategy background, combined with a strong understanding of Big Data, AI, Predictive Analytics and technology. This blog will explore what is a Translator, what skills they have and how they are useful to modern day businesses.

What is a Translator?

Since 2015, Data Analytics, AI, Machine Learning and Predictive Analytics etc. are concepts that have seen the rapid uptake. This has created the need for individuals who can think logically and understand how to use analytics to create tangible value in day to day businesses. Essentially, a translator bridges the gap between data scientists and corporate decision makers – they have the fluency in analytics, can understand large data sets and manage quantitative colleagues.

Translators are NOT data scientists or data engineers or data architects – perhaps a more apt term would be ‘Data Strategists’. As Daniel Newman, Principal Analyst at Futurum Research says, ‘translators are the Switzerland of the data debate. They look at the numbers, the goals and help both sides understand the best way to move forward’.

What do they do?

Translators will play a key role in identifying and prioritising business problems. They will typically lead projects with analytics components which will include articulating a problem statement, identifying and collecting data, applying modelling techniques, leveraging the model to influence decision making and capturing the value for better decisions.

They will know which datasets to focus on and will point data scientists in the right direction. They do not need to build complex models, but they will have a strong knowledge of which models exist and their application. They will also have a good idea of technology / digital tools too in order to help clients integrate the data model through the appropriate technology the suits the business operating model.

What skills do they need?

  • Industry knowledge 

  • Tech fluency 

  • Project management 

  • Entrepreneurial 

Where you can find them?

There are three key ways in which organisations are trying to bring this translator skill-set in-house.

  • External consultants – by using either a specialist consultancy focused in this space or freelance consultants who showcase this expertise, companies are able to bring in a quick injection of this skill-set where necessary. This can be a great solution where projects or problems are business-critical and can prove to be cost-effective.

  • Grow capabilities internally 

  • Dedicated teams/hiring programmes – companies are also creating Data Analytics teams and hiring Data Strategists to be the main bridge between the numbers and the decision-making. Roles like Chief Analytics Officer or Chief Data Officer are being increasingly sought after, and these individuals can help departments determine what type of data to collect to make important business decisions as well as manage teams effectively.

Data is everywhere in businesses at the moment – we are in a world where customer experience is of utmost importance and terms like IoT, AI and analytics are changing businesses with data as the key driver. Businesses that identify individuals with strong data skills and commercial ability to close the gap between human and machine interaction will find themselves staying ahead of the competition. 

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