The world is transforming rapidly, driven by the growing importance of data in decision-making. As organizations navigate this landscape, they must adapt to extract valuable insights from large volumes of operational data using real-time analytics. The potential of real-time analytics lies in its ability to deliver hyper-personalized and immediate customer experiences that adapt to users’ changing circumstances.

Despite the benefits, only 17% of enterprises today have the ability to perform real-time analytics on large volumes of data. The Philippines is investing heavily in enhancing AI and analytic capabilities, with significant growth expected in the AI market. This is accompanied by an increasing adoption of real-time analytics across various sectors, as businesses recognize the value of immediate data insights for decision-making.

The Analytics Association of the Philippines estimates that by 2028, the country will require 500,000 analytics professionals, highlighting the growing demand for data analytics expertise. This surge in demand underscores the critical role of real-time analytics in driving business performance and competitiveness.

The Asian Institute of Management (AIM) has launched its Master in Data Analytics (MDA) program to address the skills gap of data analytics professionals. This move reflects the country’s positioning as an emerging hub for business analytics in Southeast Asia, with continuous growth expected over the next 5 to 10 years.

Why Real-Time Matters

The app economy is booming, with Apple’s App Store ecosystem generating a staggering $1.1 trillion in total billings and sales for developers in 2022. As users demand more relevant, personalized, and immediate experiences, attention has focused on real-time analytics as a critical stepping stone to success.

This is particularly true for dynamic apps that can adjust behavior and features in real-time based on factors such as user preferences, environmental conditions, data inputs, and changing circumstances.

A retail app with analytics and AI capabilities can offer businesses and advertisers the right products and services to the right target audience at the right time, while keeping track of inventory, delivery details, and more. Similarly, a booking app with adaptive functionality can be regularly updated based on real-time travel information, events, and user history to suggest personalized journeys and deals.

In the Philippines, banks and insurance companies are focusing on hyper-personalized, data-driven services by consolidating customer data and automating workflows to keep pace with rapidly evolving customer expectations.

The power of AI and real-time analytics offers numerous benefits, including enhanced predictive capabilities, personalized user experiences, improved operational efficiency, and the ability to respond to events in real-time.

Four Mistakes Organizations are Making with Real-Time Analytics

• Too much focus on speed over accuracy and data quality

  As their moniker suggests, timeliness is critical to these applications. However, speed shouldn’t come at any cost. The old adage “garbage in, garbage out” applies here. If a service draws on poor quality data, it will not deliver the intended outcomes. Outdated or incomplete datasets will only lead to inaccurate insights and erode customer trust in the application. Organizations should instead prioritize data validation checks and cleaning, as well as regular audits, to maintain data integrity and accurate results.

• Ignoring the importance of context

  Real-time data requires broader context and correlation to help derive accurate insights. That’s why organizations must dig deeper to uncover the true relationship between variables. For example, a sudden spike in sales of an item may be due to increased consumer demand, macroeconomic conditions, climate-related indicators, or perhaps promotional campaigns. Correlation does not imply causation.

• Choosing the wrong tools

  Not all analytics tools are created equal. It’s critical that organizations choose technologies tailored for real-time data processing and visualization, including a database that offers analytic, AI, AI agent development services, mobile and edge, operational, and vector search support on a unified platform. Failure to do so could lead to bottlenecks, latency, and accuracy issues.

• Failing to clearly define objectives

  Analytics projects will rarely reap the desired rewards without specific, measurable goals. Organizations must therefore define clear objectives, such as improving customer retention by a certain amount within a set timeframe. This will help guide data collection and analysis efforts. Without clear goals, it’s difficult to identify actionable insights or measure success.

Time for Real-Time Analytics

There are potentially serious business consequences to getting real-time analytics wrong in this context. Some 41% of enterprises claim they could go out of business within three years if their apps no longer meet user expectations. An even greater share (46%) believe they’ll lose out to the competition if this happens.

Yet, while these capabilities are already being used by a few mature businesses, the vast majority of organizations struggle to get hold of the right tools and know-how to leap barriers like siloed data systems.

Fortunately, modern developer data platforms can address these challenges if they are able to integrate both operational and analytical workloads in a unified environment. This avoids having to move data from databases to data warehouses, reduces the need for costly Extract-Transform-Load (ETL) processes in OLTP and OLAP systems, and minimizes latency.

Real-time analytics offer organizations a vital edge in meeting today’s dynamic customer needs. By overcoming common pitfalls and leveraging modern solutions, businesses in the Philippines can make timely, data-informed decisions that improve customer satisfaction in an increasingly competitive landscape.

The Philippines is poised to become a leading hub for business analytics in Southeast Asia, with continuous growth expected over the next 5 to 10 years. As the country invests in enhancing AI and analytic capabilities, businesses must prioritize the adoption of real-time analytics to stay ahead of the curve.

By understanding the challenges and benefits of real-time analytics, organizations can unlock the full potential of AI and data to drive growth, improve customer experiences, and stay competitive in today’s fast-paced business environment.

Definition of Real-Time Analytics

Benefits of Real-Time Analytics

Hyper-personalized and immediate customer experiences

Enhanced predictive capabilities

Personalized user experiences

Improved operational efficiency

Ability to respond to events in real-time

Challenges of Real-Time Analytics

Common mistakes

• Too much focus on speed over accuracy and data quality

  Ignoring the importance of context

  Choosing the wrong tools

  Failing to clearly define objectives

Conclusion

Real-time analytics offer organizations a vital edge in meeting today’s dynamic customer needs. By overcoming common pitfalls and leveraging modern solutions, businesses in the Philippines can make timely, data-informed decisions that improve customer satisfaction in an increasingly competitive landscape.

The country’s growing investment in AI and analytic capabilities positions it as a leading hub for business analytics in Southeast Asia.