Digital Transformation Happening In Vietnam

Duy Truong, Director, Head Of Data Engineering And Analytics, Ho Chi Minh City Securities Corporation (Hsc)

Duy Truong, Director, Head Of Data Engineering And Analytics, Ho Chi Minh City Securities Corporation (Hsc)

According to a survey by McKinsey, the COVID-19 crisis accidentally became the catalyst that accelerated digital transformation across companies around the globe, and Vietnam is not an exception. Even though we start at a later point compared to developed countries, the speed of digital transformation is shockingly fast. Recent research conducted by DBS indicated that companies in Vietnam were using digitalization to modernize their customer experience and engage their customer online at a higher rate than the global average.

Surfing on that inevitable trend, data and other digitalization pillars are playing a more important role than ever in Vietnamese organizations. This is due to the need to extract insights from the massive data generated from multiple touch points in the digital space to collect customer/consumer digital footprints. Furthermore, in the digital era, leaders see the need to make the right decisions fast in a rapidly changing world; thus, they start to learn to make more fact-based decisions rather than based solely on their experience.

This is no doubt an exciting time for those who work in the field of data like me; however, a reminder to fix our eyes on some tangible goals is advisable. This is crucial, especially if a company is still at the beginning of the journey, where there is little to be shown, and the initial investment cost can be eye-watering. Exciting to the new untapped potential as they may, the leader's patience has its limit. Chasing every new data technology claiming to give us cutting-edge advantages or change the playing field without solid proof can eventually exhaust us.

According to my experience, there are some typical ways that companies in Vietnam employ data to create advantages against competitors.

Even though it sounds boring and old age, I believe business intelligence and data governance won't be out of fashion soon. Playing this card right can give any organization an operational advantage.

Firstly, on the surface, this concept has existed for ages; new technologies like the cloud infrastructure, data lake house, and data catalogs did change our game. They allow us to bring down our data silos with less sweat and to work with our data more effectively. Secondly, by pumping data into each department at high quality and smoothing the data access process, we are one step closer to a data-driven company.

To fully utilize the power of big data, a customer data platform (CDP) can be the next safe bet. Knowing exactly who our customers' portrait is, what they are looking for, and how well we are serving them will give our organization a business advantage. If investment cost, partner locking, or data sharing risk is holding us back from investing in a full-functioning CDP platform, composable CDP may be our answer. A composable CDP can help lower the starting cost by allowing us to unlock the main functions of a complete CDP one by one and utilize each separate function without a one-time full investment. However, this approach would require a mid-size, capable data engineer team. If we don't have that luxury, a full-functioning CDP is a safe choice.

I cannot discuss big data without mentioning machine learning and AI (ML/AI). Wielding this right can give any company a product advantage or operational advantage. However, business leaders sometimes don’t know data scientists (DS) need infrastructure and business partners to unlock their full strength. Hence, as a data leader, we should advise our top leaders to invest first in the data platform. This would create a solid rocket platform for launching any ML/AI product. Finding the use cases and the right partners for our ML/AI seems to be the next reasonable approach. Or we may waste our DS time looking for where they should put their value effort.

In closing, I hope those initiatives inspire and excite us all as they did to me. There will be more depending on the industry, the market you are in, the business model, and the end customers. Exciting as it may be, it is worth mentioning other factors that would influence the success of any data project.

(a) Data strategy is a high-level master plan for any successful data journey. (1) Let’s press ourselves on what data initiatives would bring our company operational, business, or product advantages. (2) How well they align with company-wide business objectives. (3) What should be the right roadmap for each initiative and the investment cost? Once they are clear to us and aligned with our leaders' vision, it will become our Data Strategy.

Undoubtedly, People Are At The Center Of Your Data Journey

(b) Undoubtedly, people are at the center of your data journey. Knowing the data maturity of our organization and then recruiting the right roles will set us on the right path. Besides the skillset required by the role and the job, I tend to favor people with an open mindset. I found candidates who are looking for challenges and ready to be challenged would be highly valuable for any data team since that may be what you and the team need to surf above the rapidly changing waves of new technologies and new business requirements.

(c) And like any other pillar of digitalization, data analytics requires more than a single team effort. The success of any data project relies on cross-team work and well-defined processes; hence, don't shy away from dragging others from different functions to create a unit team to seize new business opportunities. Uncertainty and doubt can be raised at the beginning, yet I truly believe that consistency and early results would dispel those worries.