The Era of Big Data Is Ending: Time for Small Data to Transform Business with AI

Columnist29 Nov 2025 00:20 GMT+7

The era when organizations believed "the more data collected, the better" is coming to an end. A study byMIT Sloan Management 2023found that only 23% of companies truly believe Big Data aids decision-making, as most organizations get stuck in the situation of "having massive data but not knowing how to use it."

The reality is that Big Data is not the answer for every business.

A shocking fact is that over 70% ofthe data collected by organizations worldwide is never utilized.Moreover, it creates hidden costs often overlooked, such as storage fees, security expenses, and increasing PDPA risks.

Another problem seen in Thai SMEs is that most collect data in silos, each person recording separately without linking data across departments, resulting in an inability to analyze data holistically. There are also issues with data quality—being incomplete, inaccurate, or outdated.

. . .Gartneralso warns that poor-quality data can cost organizations at least $12.9 million annually. For example, the global case of Zillow, a home and apartment rental platform, which relied on incomplete data sets to predict housing prices,caused the company to lose$300 million in a single quarter (Q3 2021).

Small Data: A new approach that truly addresses Thai SME business needs.

The idea is that Thai businesses should adopt the “Small Data” approach—selecting and analyzing only essential, high-quality data that is ready for immediate analysis. This carefully chosen data suffices for AI application to create business advantages.

The truth is AI does not always require vast amounts of data; rather, it needs quality and relevant data, such as customer purchase behaviors, popular product types, or peak website visit times. Such data is suitable for training AI models to enable personalization.

Benefits of Small Data

Speed: Analyze a small amount of data but make decisions quickly.
Accuracy: Data containing only essentials reduces errors and bias risks.
Cost efficiency: Lowers storage, processing, and labor costs.
Reduced PDPA risk: Collect only what is necessary, minimizing risks.

Examples of Small Data use in SMEs

A small beauty salon uses an automated response system to send appointment reminders via LINE, reducing no-show rates by up to 25% without significant investment.
Retailers useRFM analysisto easily analyze customer behavior based on recent transactions, frequency, and total spending from Shopify data, segmenting customers and delivering targeted offers to boost repeat purchases.
Coca-Cola Amatilused just a few hundred shelf photos analyzed by AI to increase market share by 1.3% within five months.

Start with business questions, not technology.

A common misconception is that organizations often start by investing in technology first, then figuring out how to use it. The correct approach is to begin with business questions, such as

Where do we want to reduce costs?
Which customer group do we want to sell more to?
How do we want to improve customer satisfaction?

Then, determine what data best answers these questions. This approach helps businesses invest precisely and measure results clearly.

Strengths of Thai SMEs in the AI era

Although SMEs face budget and staffing limitations, they have the advantage of agility in adapting, a key strength in rapidly changing times.

"In the past, big fish ate small fish, but now fast fish eat slow fish."
"SMEs that dare to experiment and make quick data-driven decisions can outperform large companies."

AI tools SMEs can start using immediately

Chatbots and LINE Official Accounts – automatically answer customer queries 24/7.
Google Analytics + ChatGPT – analyze customer behavior and generate insights.
Automated customer management systems – segment customers and send targeted messages.
Content creation tools – assist in producing engaging images and text.

It is crucial for each organization to train employees on proper data management fundamentals first, such as collecting customer data following PDPA, cleaning data, and using analysis tools before moving on to more complex AI applications.

2026: A critical turning point for Thai businesses—quality data equals quality decisions.

The year 2026 will mark a significant shift as organizations begin prioritizing data quality over quantity and transition from investing in Big Data systems to investing in AI that operates on Small Data.

"Big Data means collecting everything without knowing its purpose, while Small Data means choosing to collect only what truly creates value."

Looloo Technology is ready to be a partner helping Thai SMEs enter the AI era correctly, without excessive investment but delivering measurable results. Implementing AI is not only for large companies; it is an opportunity every business can start today.