Why Everyone Should Think Data?

Chiang Yoke Fun

Senior Vice President / Head, Data Analytics & Artificial Intelligence, ST Engineering


A Covid-19 cluster has emerged at a building. Immediately, its occupants are forced to evacuate and quarantine themselves as the entire campus is placed under lockdown, which severely affects business operations and productivity.

This scenario is happening around the world. But the power to mitigate such a situation could well lie in our pockets – through a smartphone Bluetooth contact tracing system. I take pride and am heartened that this is one of the solutions developed by a team of dedicated and earnest individuals in ST Engineering.

By harnessing Artificial Intelligence (AI) and drawing critical insights from data analytics and 3D visualisations, authorities can accurately identify the degree of contact with affected individuals expeditiously – such as where each individual travelled to within the building and his sphere of influence. This allows for the quick isolation of infected individuals before the premises become a bigger cluster. Business continuity is also ensured as a full office closure can be avoided.

This is just one of the many ways data can save lives and sustain operations during this pandemic.

Today, AI and data analytics are driving the future of virtually every industry as we head towards a new normal. But rather than be guided by cold and structured technology hardware , humans and AI can join forces for the greater good through sensemaking and collaborative intelligence.

Knowing the unknown to engage, grow and secure

The power of AI is boundless in inspecting data and highlighting meaningful information.

Going a step further, sensemaking capabilities facilitate quicker and more incisive decision-making through actionable intelligence drawn from datasets.

But while many acknowledge the potential of analysing data, 6 in 10 key decision-makers still consider managing complex data a top challenge, as highlighted in our Sensemaking Maturity Index study by Forrester. If data is not integrated quickly to distil insights, it will be very hard to harness the power of the people, technology and capabilities to deliver and act on the insights.

When we leverage the power of AI and data, everyone is a winner.

For businesses, data analytics not only help to boost personalised engagement, sales and drive down costs, but also to identify and understand existing and undiscovered risks – such as exposing potential fraudulent activities with AI.

In the areas of governance, we developed a system which automatically analysed 50,000 emails for a client. With the insights drawn, we were able to flag potential misconduct in individuals and associates. We succeeded in fighting white-collar crime and ensuring continued good governance through data augmentation, timeline analysis, topic modelling and unsupervised machine learning capabilities – which worked together to circle in on potentially fraudulent activities.

Building a sustainable analytics organisation

Many companies have small teams that specialise in data analytics. They guide everything from gathering data to help in decision-making processes to working on various projects. But this is not enough. The benefits will be manifold when everyone leverages data insights in their daily work and transforms processes at every level.

To facilitate the adoption of organisation-wide analytics, we must be clear on our returns when investing in data and sensemaking. Here are three things to work on: First, think of ways to accelerate the speed-to-market in your projects. One important aspect is to create a collaborative environment within the team – from business users to data scientists and technology providers.

Begin with the end in mind by embedding and linking every project with analytics to harness the power of data to the fullest. And when it comes to conceiving ideas, think and analyse on the ground with agility to deliver the fastest output in every project.

Next, we need data champions who can ideate and find solutions by visualising how data can solve problems for business users. To do that, we need to think of everyone as a data scientist and build a data culture across the entire organisation.

Data science skills should not be limited to a small group – anyone who adopts an analytical mindset to find the problem statement and discover novel ideas can be a data expert.

Take a leap with user-centric platforms

Organisations then need to transform data into actionable insights, augmenting decision making as they accelerate and enhance their thinking processes.

The Forrester study revealed that a staggering 75% of leaders do not have the right data dashboards and visibility. It is essential for organisations to identify and uncover hidden, meaningful insights in real-time to deliver personalised data-driven experiences for the end users.

We must continue to bridge the execution gap by involving everyone across all levels to create user-centric platforms, as different types of users accelerate the process and find the unknown.

It is only when humans and technology work in tandem, we can then develop and adopt solutions that empower lives and bring out the value of data to any organisation. So, are you ready to adopt the right mindset to build sustainable analytics in your organisation?

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