Building a Successful Data Ecosystem in Southeast Asia
As major Southeast Asia economies continue to navigate the path to recovery, an increasing number of enterprises are embracing digital transformation as consumer behavior and spending drastically change. With up to eight in ten consumers in the Southeast Asia region being digital consumers, businesses in Southeast Asia have to adjust to their preferences or be left lagging behind.
Unfortunately, digital consumer growth has not been proportionate to digital adoption in the region. While the Philippines and Malaysia top the World Economic Forum list in e-commerce retail growth, it was Singapore that drove 70 percent of businesses to adopt business technologies such as data analytics and visualization to become the leading digital driver in Southeast Asia.
In this new normal, enterprises that seek to level the playing field need to harness their data and harvest meaningful and actionable programs that benefit business performance. Data is the backbone of modern day organisations and building the right data ecosystem can be a daunting task. Organisations with different subsystems may require unique models and components before any real value can be extracted to benefit the enterprise.
Data ecosystems are not just the environment on which infrastructures, applications and services sit. The way data is captured, stored, analyzed and leveraged into insightful information must be properly defined before businesses can utilize data to improve customer experiences, operations, employee management and marketing.
Data components and archetypes
The Harvard Business School divides data ecosystems into five different components. The first component, sensing data, is the process of identifying and assessing the value of data sources and evaluating the data in terms of accuracy, completion, novelty and trustworthiness.
The most common data sources are from internal spreadsheets, databases and Customer Relationship Management (CRM) systems or from external websites or third-party aggregators. After data sources are identified, data collection is automated through codes or APIs, or done manually through feedback forms or surveys. Here, enterprises need to consider how data managers can leverage available tools to ensure a seamless collection process.
Next, the raw data collected will require wrangling, or data structuring. Raw data from multiple datasets may require merging, and any data gaps addressed accordingly. This results in clean and transformed data that can be easily understood and analyzed.
The structured data then undergoes data analysis, often with automated tools that leverage artificial intelligence or known statistical models to provide the insights for businesses to inform and make data-driven decisions.
The final component, data storage, is about keeping your data secure and accessible either in the cloud, on-site, or in hybrid models throughout the lifecycle of the data. The exact medium of use for storage depends on the data governance and digital policies of the enterprise.
Each of these components can be used by businesses to develop their very own archetype. There are five ecosystem archetypes according to McKinsey. They are:
- Data utilities that aggregate data sets and provide services,
- Vertically-integrated operation centres that provide efficiency and optimization across the supply chain,
- End-to-end cross-sectorial platforms that integrate partner data and offer services through a single platform,
- Marketplace platforms that act as an intermediary between buyer and sellers and
- B2B infrastructures that are technology platforms where other enterprises establish their ecosystem business.
Aligning data ecosystems with business goals
Regardless of component or archetype, the ultimate mission of enterprise data is to empower businesses to support customers and partners. The right data ecosystem can go beyond and deliver various added benefits to the enterprise. For example, data can be used to improve communication, increase operational performance, or even tackle process inefficiencies.
Enterprises will also be surprised to know how data can help them innovate through predictive modeling and deliver products and services that meet needs of which the customer is not even aware. As a result, businesses know their customers better and can mould the right experiences to achieve success with them and increase revenue growth. The right ecosystem is also about business control, and how enterprises can scale to need, without compromising on user access or data security.
Ultimately, the company needs to decide and define its own place in the digital world. As there is no single ecosystem to fit all of them, companies need to consider the digital transformation a journey and not a destination. Enterprises in Southeast Asia need to keep an open mind and start their data journey or risk being unable to compete in the digital future.
Sandie Overtveld is the vice president and general manager for APAC at WalkMe. The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends.
Image credit: iStockphoto/BrianAJackson
