By Verghese V Joseph –
The banking sector in Southeast Asia faces skills gaps in areas where the line between business and technical skills is blurred. In sectors where the distinction between business and technical abilities is blurred, the Southeast Asian banking sector faces skills shortfalls. According to a research, 67 percent of Southeast Asian (SEA) banks are experiencing talent gaps in data analytics/data science, while 48 percent are experiencing skill gaps in business analysis. Closing the skills gap entails not only upskilling in technical areas, but also improving the usability of tools to benefit users throughout the organization.
Different responsibilities necessitate data intelligence to attain various work-related objectives. As a result, technologies must give benefits to users across the organization and be simple enough for employees with diverse backgrounds to use. When more business users have access to, share, and understand data, that data becomes more powerful and useful.
Rocket Software, a worldwide technology company that creates corporate software for some of the world’s major corporations, specializes in mainframe and I/Z system, application, and data modernization. In an interview with AsiaBizToday, Praveen Kumar, Vice President for Asia Pacific at Rocket Software, discusses democratized data in the banking sector and how it can supplement their upskilling efforts to close the skills gap.
ABT: What is data democratization and why is it important?
Praveen Kumar: Data democratisation refers to the process of making data accessible and usable to all individuals within an organisation, regardless of their technical background. It involves creating systems and adopting tools that allow employees to easily access, use, and discuss the data they need to make informed decisions. This shift is crucial as it enables companies to rely on data-driven decision-making, turning data into a strategic asset rather than just the output of specific individuals or departments.
Traditionally, the ability to analyse and act upon organisational data was limited to those with data science skills. Business users, from marketing professionals to CEOs, had to rely on data analysts to identify, transform, and present relevant data. This cumbersome process slowed down decision-making and put organisations at a disadvantage. Data democratisation eliminates these barriers by allowing users across the entire organisation to access, share, and interpret data.
One of the key requirements for successful data democratisation is user-friendliness. Data intelligence tools need to provide benefits to users with varying backgrounds, offering intuitive interfaces and clear visualisations. This empowers employees to leverage data in their specific roles and achieve their goals effectively.
In fact, IDC finds that the ability to synthesise information to learn and to apply the resulting insights at scale is a significant competitive edge. According to its findings, organisations with high levels of data intelligence outperform their counterparts with lower data intelligence by 40% in terms of financial performance and 20% in terms of operational success. These organisations also report a significant increase in data management metrics.
ABT: How is data democratization driving efficiency in financial services?
Praveen Kumar: Data democratisation is driving efficiency in financial services in several ways. Firstly, it allows for easier validation and proof of proper handling, redaction, and containment of sensitive personal data. In the past, when regulators requested this proof, it could take weeks or even months to deliver. However, by giving business users the ability to track the flow of data throughout the organisation, understanding what did and did not happen becomes a simple query. This saves time and reduces the risk of non-compliance.
Secondly, advanced data analytics enables financial institutions to predict trends, improve operations, deliver better offerings, enhance customer experiences, and reduce risks. For instance, PwC finds that Southeast Asian banks are hampered by a lack of appropriate skills and capabilities, particularly in the areas of data analytics/data science and business analysis. Here, data democratisation presents opportunities to reduce the reliance on a finite group of individuals or departments and harness the power of analytics to drive efficiency and make informed decisions.
Data democratisation also helps banks overcome issues that hinder a company’s capacity to meet customer expectations e.g., data silos, the inability to report on all pertinent data and obtain data from all required sources, as well as delayed access to data.
Customer-facing teams can deliver personalised experiences faster with complete access to data and insights on customer behaviour and preference. On the other hand, the same level of access for other teams can lead to better resolution of customer issues and even the creation of entirely new products, services and business models.
ABT. One challenge is that data can come from multiple sources, which requires users to go to many different places to find what they need. How does one address this challenge?
Praveen Kumar: Having an organisation’s data spread across multiple sources often requires users to navigate various platforms to find the specific information they need. Tackling this challenge rests on effective data intelligence tools that seamlessly integrate with different technological environments, allowing organisations to harness data across cloud, distributed, and mainframe infrastructures.
This ability to integrate and pull data from every and kind of data source is crucial. Indeed, 93% of organisations surveyed recently told Rocket Software that hybrid infrastructure spanning the mainframe to the cloud should be embraced. Meaning that to fully leverage their data assets, organisations require data intelligence tools that eliminate barriers and facilitate efficient data utilisation.
There is also a need to easily locate and access the right data, and solutions with an intuitive interface and clear visualisations can deliver that. This, then, increases trust in data quality, which fuels strategic decision-making. In addition, platforms that offer a variety of browsing customisations and search options allow users to tailor their data exploration based on their specific criteria and preferences for sharing information with others.
ABT: There’s so much more data today than there was in the past. Why has data growth skyrocketed?
Praveen Kumar: A significant contributing factor is the rise of the Internet of Things (IoT). Previously, data production was primarily driven by human activities. However, with the proliferation of IoT devices and the immense number of machine-generated and sensor-induced data, this machine-produced information now dominates the data landscape.
Moreover, significant contributions to data growth come from large enterprises, tech companies, e-commerce platforms, health and scientific industries, as well as governmental and non-governmental organisations. Tech companies, with their billions of connected devices and services worldwide, generate an immense volume of data. Therefore, effective technology for data life cycle management and manipulation is essential.
The potential for leveraging data from a business perspective also acts as a multiplier effect. Modern businesses utilise data to account for inventory, manage customers, optimise processes, and ultimately increase their profit margins. Thus, the scope of exploiting data from a business standpoint has propelled the growth of data.