Master data management should not be like a scavenger hunt — but for many organisations with diversified businesses, legacy systems, and complex infrastructure, it usually turns out that way.
As a result, any plans to improve customer experience or launch a new line of business are hampered by the lack of data governance.
During a panel discussion at Informatica’s virtual MDM & Data Governance Summit, several business leaders in Asia-Pacific shared their challenges with master data and the strategies they applied to resolve those issues.
Data chaos
For oil and gas company PTG Energy, data analytics was not delivering the desired business insights due to unstandardised systems and scattered master data.
The company, which has around 2,200 petrol stations across Thailand, has also ventured into other businesses, including a coffee shop with around 1,200 branches, convenience stores, and the master franchise of fast food brand Subway.
“It was chaotic at first, because there was lots of information coming from different businesses, and there were data silos,” noted Songpon Busparoek, Chief Information Officer, PTG Energy.
To get started on its master data management journey, the company began small — avoiding the massive end-customer data for the time being, and focusing instead on identifying the data they truly needed first.
Meanwhile, Indonesian property developer Sinar Mas Land, which has different customer segments based on various property types, wanted to tailor its communications to customers.
“We have data on people who buy our residential properties, rent office buildings, open food stalls on our land, or pay the bills in a house they don’t even own. All of them are our customers — no matter how big or small,” said Stefanus Mulianto, Chief Information Officer, Sinar Mas Land.
The goal for Sinar Mas Land is to give a good customer experience — whether someone opens a business on their land, buys a residential space, or visits their township.
“With all the data we have, our shareholders said we need to build a customer 360 (a unified view of each customer across all touchpoints). We need to understand our customers better so we can serve them better — and at the same time, promote our products more effectively. Without the proper information, we can’t send the right marketing campaign,” he remarked.
For engineering, architecture, and construction firm GHD Australia, data silos across jurisdictions remain a persistent challenge.
“The sources of data aren’t centralised. Discovering them can be difficult, as the data often sits in Excel spreadsheets. There’s a lack of governance and ownership — it’s unclear who’s actually responsible for the data and how it’s delivered. We’ve had some issues with defining what that structure should look like. How do we apply consents and permissions so we can share data more easily across the organisation? Then there’s the integration challenge too,” shared Pinder Bains Johal, Data Management Leader, GHD Australia.
Through its nearly 100-year history, GHD has acquired multiple companies — along with layers of technologies that have made its tech environment highly complex.
“To summarise: we have point-to-point data feeds, a complex data landscape, and we operate in equally complex markets. And those data needs can shift rapidly depending on what the client requires,” Johal said.
Data management
Sinar Mas Land, which recently migrated to a new ERP system, needed to simplify and standardise its customer data. This is where Informatica proved beneficial, helping them manage their master data and gain a holistic view of business partners.
According to Mulianto, the project began two years ago. Given the company has around 130 entities, it first went live with a group of pilot companies.
“We’re embarking on a journey that will take another two or three years. Beyond serving our existing customers, we also plan to use the data to market our properties internationally — to attract investors from Singapore or the UK. For example, if we want to entice a school to open on our property, we can share aggregated demographics — like the number of kids nearing university age or those going to primary school,” he said.
GHD, for its part, underscored the value of a data-driven strategy, especially when business operations suffer due to disorganised or inaccessible data.
“We’re still early in our journey with Informatica. We started in the client domain, focusing on data quality. We onboarded the platform and connected it to Salesforce, SAP S/4HANA — which we’re migrating to Microsoft Azure — and then all the way through to Power BI. That allowed us to show stakeholders how data quality holds up through all the hops, jumps, and transformations,” said Johal.
By focusing on Informatica’s client and opportunities dashboard, the company spotted data anomalies during profiling.
“We had to define which quality dimensions really matter if we want to make the right decisions for our clients. We were able to drill down to the granular level and demonstrate the value of what we’re trying to achieve,” he continued.
Johal also shared how Informatica helped them visualise the flow of data across systems.
“Through that process, we identified who owns the data and who’s responsible for stewarding it. We didn’t just want to locate a steward — we built a case to demonstrate discrepancies and show who should be owning the data,” he said.
Informatica’s platform also enabled non-technical users to build data quality rules using low-code or no-code tools.
“With just a click, you get a notification if a data attribute falls outside its threshold. That makes escalation and remediation within data governance much more streamlined,” Johal explained.
Data realisations
To avoid the kind of data chaos many organisations face, Busparoek emphasised the importance of placing data in the right structures and formats.
“The most important thing is making sure the business buys into what you’re doing — otherwise, you won’t get the support you need,” he suggested.
Likewise, setting a clear objective for the data journey, mapping out a roadmap, and establishing governance policies go a long way toward solving major data challenges, Mulianto noted.
For Johal, starting small is always better than diving headfirst into a large-scale data project without proper analysis.
“Pick something — especially when you’re implementing the platform for the first time — that can demonstrate the value of its components. Whether it’s lineage, data quality, or governance, find something that’s juicy, low-hanging fruit. Use that to showcase the capabilities, and build from there,” he concluded.
