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Look to data simplification and democracy for data-driven success

Andrew Martin
Andrew Martin • 6 min read
Look to data simplification and democracy for data-driven success
Data is only useful if it is understandable and actionable for everyone in the organisation. So how can we achieve that?
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It is now undeniable that transforming into a data-driven organisation is critical for driving meaningful business outcomes. As Southeast Asia’s technology hub, data is central to Singapore’s economy, with studies indicating that the data industry is said to contribute around S$1 billion to Singapore’s economy each year.

This priority has been further highlighted during last year’s Singapore FinTech Festival, where Singapore pledged further commitment to developing a vibrant ecosystem for sustained data innovation alongside research and development (R&D) in artificial intelligence (AI).

However, being empowered with the right data and AI skills to create business impact requires providing the right resources and more importantly, the evolution of current attitudes towards handling and sharing data.

Data needs to be simplified

Though it is almost imperative that all workers must understand how to gain insights from data at a general level, it is even more important to remember that there are different levels of technical expertise.

Even within a data team, there are various members, from data engineers, data scientists, machine learning engineers to business intelligence analysts. Each discipline works with data differently and requires varying levels of access and understanding as a result.

See also: Responsible AI starts with transparency

This same principle applies when the role of data expands across an organisation more broadly. Data doesn’t serve the same purpose for each employee, so the extent to which they need to access, interact, and understand it differs too.

These are the very needs fuelling the likes of the low-code/no-code movement, for example, with a boom in development platforms that can be used to build apps either completely without code or with just a few lines. The evolution of such codeless software development tools has also been identified by the Infocomm Media Development Authority (IMDA) of Singapore as one of the nine key technology trends that are making the greatest impact on the region’s digital economy.

No-code has seen a surge of interest in recent years, as a result of the growing push toward digitisation among businesses – a push that has been made more urgent by the Covid-19 pandemic. Enterprises are increasingly aware of the importance of going digital, and the value of being able to build applications that can benefit a business without going through the lengthy development process has been amplified.

See also: Mitigating the third-party identity threat

Ultimately, data has to be simplified to more users across all experience levels, to accelerate innovation and boost productivity.

Democratise data with easy, governed access for all

Still, making data more accessible – let alone simplified and visual – poses a cultural hurdle for many organisations. Too often in larger, data-rich enterprises, data can be isolated from many employees and only controlled by a select few – much to the organisation’s detriment.

Technology plays a key role in ensuring that all employees can better understand and utilise data, no matter the business requirements or the level of data literacy. Yet, technology is only part of the journey towards becoming a truly data-driven organisation.

Breaking down data silos and embracing the use of data in everyday decision-making is often a dramatic cultural shift that requires team engagement from across the organisation. Data needs to be accessible, easily contextualised and for people within a department to be able to interact with it at the granularity that is needed for their roles.

Let’s look at online-to-offline platform Grab, which needs a consistent view of millions of users across 351 cities in eight countries to accurately forecast consumer needs and preferences. With disparate data teams supporting different product functions and building different features based on different consumer segmentation, Grab used to struggle with having an inconsistent view of its data across teams.

To build a holistic understanding of its consumers across various product segments and functional teams, Grab needed to consolidate its data via a unified catalogue approach. Its in-house self-service consumer data solution, known as C360, now empowers Grab’s data-driven culture and serves as the single source of truth for thousands of consumer-centric attributes crowdsourced from different business and technology teams.

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Now, staff can securely access this democratised consumer data from anywhere to better learn about their consumers’ habits and needs and create an enhanced in-app experience for them.

Rather than employees having to pull out the necessary data for themselves or data being fragmented, organisations should be streamlining access to enable different groups to use data effectively and efficiently to gain the most value from it, and quickly.

The demand for data skills

While data may still be seen as a competitive advantage, it will soon be the foundation of all businesses. Data science and analytics expertise are quickly becoming 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. Singapore continues to strongly support talent development in this area, rolling out the Smart Nation Scholarship to students in information and communications technology (ICT) related disciplines such as computer science, information security, and mathematics.

Beyond this, the best data teams 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 testing data projects and experimenting with new software programmes through internal hackathons.

Importantly, before taking on any data reskilling efforts, organisations need to first understand what outcome they are driving towards and what skills are required. An employee self-assessment survey that focuses on necessary skills can help companies determine a customised curriculum and plan based on the existing skills gaps.

Consistent training of new technologies and certifications are an investment in shaping the workforce of the future to be more data-driven and will ultimately help to ensure that employees stay ahead of industry trends and business demands.

Data will be everyone’s business

A common thread that runs throughout these skills mentioned is making data understandable and actionable as the language of your organisation. 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.

As organisations continue to ensure employees’ data skills are being reinforced and upgraded, it is also important that businesses can drive immediate impact from data right now.

While every company’s data and AI capabilities may not be at the same level, it will be essential to ensure that simplifying and democratising data is at the core of everyone’s business.

Andrew Martin is the head of Databricks South Asia

Photo: Unsplash

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