Since the pandemic, organisations across the globe have scrambled to accelerate their digital transformation plans in pursuit of establishing business resilience. To successfully execute these plans, data and analytics play a pivotal role in informing business leaders with the necessary key insights on which strategies would deliver the most value.
According to McKinsey, digital adoption has taken a quantum leap at both the organisational and industry levels, forcing organisations to digitally transform and use data analytics to remain competitive.
“We previously saw many business activities focused around analysing data, from visualisations of past quarterly profit margins, to predictive analytics – customers are expected to churn or use as a response to a campaign,” said Nick Lim, General Manager, APJ at TIBCO.
“Increasingly, now we see more use of artificial intelligence and machine learning, using analytics to calculate things that humans were previously unable to even imagine.
“Customers and consumers now use digital services as the norm. As a result, we see organisations adjust to this uptake and utilise data analytics as a way to create a hyper-personalised approach, particularly in the banking and financial sectors where the competitive landscape has changed dramatically.
Challenges faced with harnessing big data
Lim reveals the following challenges faced by organisations when gathering insights from the collected data:
- Lack of the right analytics tools
Companies are having difficulties managing the massive volume of data coming from multiple sources both inside and outside the organisation. Together with the increased usage of digital services in the market and across industries, it has resulted in the data ending up in silos.
Without the necessary analytics tools, data scientists and business leaders are unable to analyse the large volumes of data in their organisation.
- Effective use of data
When the data is not used effectively to meet a meaningful purpose, the insights gathered would not necessarily provide decision makers with the right information to do their jobs effectively or to take the next best actions based on discoveries on customer trends or market conditions.
An intelligence platform that provides the data needed to deliver a good customer experience, drive innovation, and optimise operations would be needed to circumvent this issue.
- Data privacy
Safeguarding data privacy is turning out to be a major challenge as more laws mandating the protection of personally identifiable information (PII) are passed around the world.
Companies also have internal rules limiting who has access to certain data and what people should do with it, meaning you have to be extraordinarily vigilant about data access rights.
This requires a balancing act as companies cannot simply lock down all the data or allow open access to everything. Organisations need to ensure they govern their data and have a unified data infrastructure in place to comply with regulations around data management.
“The challenge goes back to having visibility of data across your organisation,” adds Lim. “As data is commonly located in different silos within the organisation, companies need to have a robust master data management platform that provides a single source of truth for their most critical data assets.”
APAC’s diversity creates greater need for data analytics
In Asia, given its diverse nature and the rapidly evolving markets, organisations are faced with a unique set of challenges as customer needs and expectations are constantly changing – making it critical for companies to be agile with how they respond and adapt.
“As more organisations move toward using cloud platforms to drive more value from their data, it is important to look at cloud from both sides,” shares Lim.
“On one side, there are many benefits, such as unburdening the organisation, data processing scalability and performance, and flexible fee structures. However, there is something of a misconception that cloud helps eliminate your data silos.
“The truth is that cloud adoption introduces even more silos. As a result, rather than reducing your data integration workload, moving to the cloud actually increases your data integration requirements. The important thing is to have a solution that allows organisations to break down the silo walls between departments and have the ability to connect, unify, and predict their organisational data.”
