Telling the stories behind the numbers

Telling the stories behind the numbers

Older women prefer younger men. Making use of data analytics tools, dating specialists Lunch Actually found out that women generally want to date older men until they hit their mid 30s, when their preferences are reversed.

Men, on the other hand, prefer the company of younger women, regardless of how old the men are.

These insights were gleaned from the dating preferences of nearly 3,000 members in Singapore, Malaysia and Indonesia using Qlik Sense, a business analytics tool that helps small and medium-sized enterprises (SMEs), such as Lunch Actually, make sense of the growing glut of corporate data.

Personality-wise, both men and women prefer extroverts to introverts. Women, however, also want their ideal partners to be tidy, the intelligence software revealed.

Ms Violet Lim, chief executive officer of Lunch Actually, said while some of these insights are familiar to those in the matchmaking business, the company has never used business analytics to validate such findings till now.

"We've accumulated a lot of data over the years, so rather than look at the numbers superficially, we decided to crunch the data to see how we can use it to keep up with the changing preferences of our clients," she said.

Ms Lim plans to use the insights to moderate the expectations of her clients so that they can be more successful in their dating lives. "If a man in his 60s is looking to date a woman in her 30s, his success rate is not going to be very high," she said.

While it is unclear how many SMEs here are harnessing business analytics tools, industry analysts believe more organisations are becoming aware of the benefits of using such tools to make faster and more accurate decisions.

According to research firm IDC, the overall business analytics software market in the Asia-Pacific region, excluding Japan, last year was worth nearly US$3 billion (S$3.9 billion). This market is expected to grow at an average rate of 8 per cent per year from 2013 to 2018.

Self-service analytics

Part of this growth is fuelled by the emergence of tools such as Qlik Sense, which makes it easy for businesses to visualise data and glean business insights.

In the past, organisations had to hire specialists to extract, massage and load data into computer systems before it can be presented in a visual manner, but "self-service" business analytics tools can now do all of that, allowing firms to slice and dice data on their own.

To most SMEs, such tools are good entry points into the world of "big data", the latest technology buzzword that refers to the use of sophisticated algorithms to make sense of very large volumes of data in multiple formats.

Take Blackball, a restaurant chain which specialises in Taiwanese tea and desserts, and has 20 stores in Taiwan and more than 40 branches in Malaysia.

Each store used to send sales data to its headquarters, where managers manually entered the information into spreadsheets. The company also monitored other sources, such as social media, but it was difficult to connect disparate sources of information.

"Our main challenge involved reporting," said Mr Andrew Cheong, senior manager at Blackball. "There were a lot of questions that we were just unable to ask about customer behaviour."

Last year, Blackball started using a big data analytics service from Microsoft to integrate multiple data sources, which allowed it to manage its stock more efficiently and uncover new trends.

For example, the company previously thought people would order cold products in hot weather but, in certain outlets, it saw the opposite happening. It now makes sure those outlets have the right supplies to meet demand.

Companies such as Blackball are warming up to big data, said Mr Joey Tan, Microsoft Singapore's lead for cloud and enterprise, because information and its use are fast becoming the currency for business growth.

Indeed, based on Microsoft- commissioned research conducted by IDC, organisations in Singapore have an opportunity to realise a potential "data dividend" of $10 billion over the next four years, resulting in greater revenue, lower costs and improved productivity.

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