The COVID-19 pandemic has undoubtedly triggered an unprecedented demand for digital technology and, as organisations turn to data to inform their business activities, analytics and data science skills continue to be in high demand among the global workforce.
As one of the top emerging jobs in the region according to LinkedIn, data scientists are — unsurprisingly — in high demand in Singapore.
As Southeast Asia’s technology hub, data analytics is central to Singapore’s economy, with studies indicating that it contributes at least S$1 billion (US$730 million) each year. Meanwhile, the value of regional big data and business analytics services is projected to reach US$27 billion (SG$37 billion) by 2022.
The ability to communicate the analysis of data with precise acuity and brevity will become one of the most valuable skill sets moving forward, as Singapore accelerates its Smart Nation efforts, and as more companies turn to data to inform business recovery and future growth.
The pandemic only accelerated adoption of data-driven strategies across industries, especially in high-touch sectors like retail, healthcare, food and beverage that had to adjust to the changes brought about in their daily lives.
Other industries, like financial services, have drawn on data for years to inform business strategies and solve emerging challenges.
At the moment, data is seen as a competitive advantage. In the future, it will be the foundation of all businesses. Data science and analytics expertise will soon be commonplace skills throughout organisations, beyond just engineering or IT departments.
And with this need for greater data science capabilities, we can expect organisations to be equipped with a drive to secure the best talents in the field.
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To stay competitive, data scientists must focus on more than just perfecting the minutiae of data-related software and programs. They should invest in learning how to best translate their know-how into actionable insights and compelling stories that will resonate with stakeholders across their business.
These skills in particular will be critical to the success of future data scientists:
Go back to the basics: Communicating probability, statistics, mathematics and more
Data science is a complex field. A study by Accenture found that 75 per cent of employees read data, yet only 21 per cent “are confident with their data literacy skill.” While this widening gap in data literacy indicates the need to invest in data skills throughout an organisation, today’s data scientists should learn how to best communicate the fundamentals behind that data.
The ability to concisely explain different concepts like variance, standard deviation, and distributions will help data scientists give more insight into how data was collected, what the sample reveals about that data, and whether it appears valid.
These fundamentals enable you to easily explain the how or why behind a given data point and better address questions from executives or stakeholders on other teams.
The best data scientists value simplicity and build complexity only as needed. The same approach should be adopted for conversations on data.
During business discussions, it is best to avoid going too far into technicalities and instead focus on the value of that data by demonstrating the business impact or potential outcomes.
Be a data storyteller: Communicating data in an understandable way
Narrative storytelling has shown to enable a higher information retention rate. The ability to tell a story about data goes hand-in-hand with the ability to explain technicalities of data in the simplest way possible.
A study by Stanford Professor, Chip Heath on the analysis of participants’ memorability rate at a speaking conference detailed that only five per cent could remember a standalone statistic, whilst 63 per cent could remember stories.
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The best data scientists are also adept storytellers, providing the necessary context about data sets and explaining its importance in the larger picture. When sharing a new set of data or the result of a data project with a wider team, focus on crafting a narrative around the top three things the audience should walk away with.
Reiterate these points throughout the chosen medium — presentation, email, interactive report, data visualisation, etc. — to facilitate action amongst your audience.
Not only will data storytelling break down communication barriers between different stakeholders, but this also makes new information easily digestible and actionable.
Get creative: Visualising data to make an impact
Visual mediums are a great way to further enhance data communications. However, they are often undervalued. Consider the different types of graphs and charts examining various data sets related to the COVID-19 pandemic in Singapore.
From the Singapore COVID-19 Tracking Dashboard to the Collection of Worldwide pandemic-related graphs, data visualisation has proven to be an effective way to communicate data with precise acuity.
The best visual components explain and contextualise large volumes of data, allowing viewers (especially non-technical stakeholders) to quickly digest information and more easily spot key takeaways that may have otherwise been buried in the raw data.
Finally, stay curious: Balancing learning and teaching
Tomorrow’s best data scientists are those who believe in lifelong learning. It could be as simple as finding ways to build learning through everyday routines, reading the latest literature on data techniques and trends or even experimenting with new software programmes.
Not only can it bring new chances to showcase one’s value within an organisation, but it can also offer a helpful perspective: knowing how you approach information can improve the way of sharing insights with others.
A common thread that runs throughout these skills mentioned is — making data understandable and actionable as the language of your organisation.
Growing with the times is important, especially in today’s volatile climate. As more companies turn to data-driven insights to make smart business decisions, data scientists will increasingly take on more significant responsibilities within organisations.
Conducting cutting-edge data science is only half the battle; knowing how to explain the process and present findings in an engaging way will make tomorrow’s leading data scientists indispensable and ensure the organisation runs like a well-oiled machine.
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