Do Companies really need Analytic Translators?
Kudakwashe Mazhetese
On a mission to ignite the next movement of people across the continent for personal and economic growth. Imagine 1.5 Billion people traveling for Trade or to reconnect with the continent & even relocate.
Firstly what is an Analytics Translator?: Growth Tribe says Analytics translators bridge the gap between organisations technical expertise and operational expertise. They help to convey business goals to data professionals while ensuring data solutions provide insights that the business can use to inform decision making.
To understand more about what translators are, it’s important to first understand what they aren’t. Translators are neither data architects nor data engineers. They’re not even necessarily dedicated analytics professionals, and they don’t possess deep technical expertise in programming or modelling. (Source: McKinsey | HBR: Analytics Translator)
Instead, translators play a critical role in bridging the technical expertise of data engineers and data scientists with the operational expertise of marketing, supply chain, manufacturing, risk, and other frontline managers. In their role, translators help ensure that the deep insights generated through sophisticated analytics translate into impact at scale in an organization. By 2026, the McKinsey Global Institute estimates that demand for translators in the United States alone may reach two to four million. We estimate that in South Africa there is a current need for up to ten thousand of them.
You don’t have to be a data scientist to fill this must-have roll.
To widen the company’s aperture, decision-makers have to realise that success with ai and analytics does not just require data scientists but agile teams that are cross-functional and inclusive of technical and non-technical members - most importantly professionals who can translate business problems, customer and also technical jargon between the team and management. Therefore this places a demand to have an analytics translator.
What makes up the ideal Analytics Translator:
- Domain Knowledge
- Technical Fluency
- Project Management Skills
- And an Entrepreneurial Spirit
So now what is the Analytics Translator supposed to do exactly
Firstly they have to drive the successful implementation of A.I, this includes being able to identify and priorities problems that analytics is suited to solve. By using domain knowledge an Analytics translator can establish the key metrics for success per task and communicate how it affects the business in terms of profit, revenue, relations etc.
Companies are finding themselves hiring excellent data scientists, data engineers, and data architects but do not have the experience of managing them, or they find the hires to be less knowledgable about the industry. But for an Analytics translator, these are people already in the organisation. A Data product manager is the closet match. Data Iku defines that the Data product manager is the link between the analysts and the end-user.
Growth tribe suggests that a well trained T-shaped Growth Marketer is a perfect match for this career. I would suggest that this becomes industry-specific. Some industries could only have to upskill their product managers or project managers. The best way to find out is to consult Helplink Africa for full in-depth company analysis and free advice.
In terms of Personalities Traits Growth Tribe suggest that the person must be :
- Influential
- Open to experience
- Intellectual Openness
- Preference for non-routine tasks
- Need for cognition
- Enjoy difficult tasks
So we interested to know what you think about this new job role, do you think it can apply in your business case? Do you want to try it out with a company looking for these skills? Drop us a comment and let us engage further!