The CIO Challenge: Helping Build a Self-Driving Enterprise

By Nilantha Brito, Senior Director, Technology Cloud, Oracle ASEAN

Even in the light of the current challenging business environment, the global data sphere continues to expand exponentially at breakneck speed — growing by 5 times from 33 zettabytes in 2018 to 175 zettabytes by 2025 according to International Data Corp. (IDC), and it is unlikely to stop. This explosion of data and the value it creates, propelled by an increased focus on digital technologies, continues to ingrain itself into all lines of business, as processes transform across businesses of all sizes and in all industries.

However, managing all this information typically has not become much easier despite the growth in the number of tools available. It involves a highly complex interplay between robust data management policies and well-enforced data governance practices that span far beyond the realm of IT.

To tackle this challenge, and because of data’s boundary-crossing nature, the C-suite has united with chief marketing officers (CMOs), chief human resource officers (CHROs), and chief finance officers (CFOs), all having to consider the management and usage of the data they have come to possess. This gives their counterpart, the chief information officer (CIO), a huge opportunity to take the lead and provide them with direction, uniting the organization in a common mission to become data-driven.

Tomorrow’s Workplace: Humans and AI co-existing as colleagues

New Year, New Game for Business Data Management

But that is easier said than done.

Transforming toward a self-driving enterprise

Such activity should be treated as a journey.

To cope with the wide reserves of data produced in the current business environment, decision-makers need to reassess the way they collect, store, and subsequently analyze their data to achieve business goals.

They need to map out clearly how data flows throughout the organization. Starting from the very beginning, it is imperative that incoming data is stored in a manner that allows it to be seamlessly used in conjunction with all existing data.

Another aspect in this process is ensuring that the necessary data security measures are in place — the next hurdle that CIOs have to contend with when it comes to laying the foundations of being a data-driven enterprise.

The next step is then how organizations can capitalize on their data. This requires advanced analysis, ideally leveraging machine learning (ML), to empower the business with actionable insights so it can make better-informed decisions in a timely manner. The complexity involved in striking a balance between data scalability, security, and agility — all in real-time is a Herculean task. Yet, those who see through it can gain a key-differentiator, which can create a solid lead.

Altering our present to power our future

Implementing procedures and protocols on managing data across a whole organization, particularly as it scales, would typically see the volume of data quickly reaching levels that surpass human capabilities to manually manage and secure it effectively.

This means companies need a new approach. Rather than having valuable time taken up with all the manual, lower-value tasks that surround data management such as patching, updating, and so on, new cloud-based tools can leverage Artificial Intelligence (AI), ML, and other automation technologies to speed things up.

This automation of repetitive tasks enables data to be processed, analyzed, and subsequently used to provide real-time insights. It also removes human error and secures databases by autonomously detecting, preventing, and responding to threats both internally and externally.

Another new feature advancing through cloud data management is the ability to pool all types of data to form a data lake, where the data can later be drawn from and used by anyone in the required output format as if it was created originally for that purpose.

Investing in such modern architecture therefore means that data can be managed effectively throughout the organization, across departments and processes. It also gives business leaders the confidence that any company-owned data will contribute to better business decisions and can be used safely with the necessary safeguards in place.

Greater efficiencies across departments

Driving this transformation and facilitating the shift toward operating with greater control and oversight of data help CIOs provide invaluable support across the various lines of business.

For instance, using Oracle Autonomous Data Warehouse, Forth Smart, a payment services provider based in Thailand is storing large amounts of data securely and generating insights in minutes. Forth Smart can now target consumers strategically to offer them greater cost savings and provide an overall better user experience.

One company where the implementation of a cloud-based data model has benefited the business is AsiaPay, a digital payment gateway that processes payments for multiple currencies, languages, channels, and devices across 15 countries. Oracle Autonomous Data Warehouse is helping AsiaPay easily migrate data to the cloud, reduce administrative chores, and use machine learning to stop fraud in real-time.

A process outsourcing company in Japan, Outsourcing Business Service Inc., is using Oracle Autonomous Data Warehouse to strategically execute its corporate health and wellbeing initiative to approximately 35,000 employees. Through that, it aims to understand everyone’s situation and collaborate with them to find and create a work environment where they can maximize their potential and deliver highly reliable services to the organization’s clients.

For companies to stay resilient, it requires a powerful engine that is capable of refining data into the fuel that drives the organization forward. Technology such as the Oracle Autonomous Data Warehouse effectively manages and underpins the governance of data in the organization and perfectly encapsulates the role of this engine, helping CIOs with the data conversation. It also equips fellow key decision-makers with data-driven insights to help steer the enterprise toward a self-driving future enriched by its reservoirs of data seen in new, innovative ways.