Big-data analytics can serve as checks and balances

The ability of collecting and analyzing volumes of unstructured big data that can spot anomalies can serve to ensure the public sector is efficient and also transparent in its operations.
Written by Jamie Yap, Contributor

Singapore: The ability of big-data collection and analysis can serve as checks and balances on government bodies, ensuring agencies are both administratively efficient and transparent as public service providers to citizens.

An underlying force of big data is the move from structured to unstructured information such as social-media posts, photographs, and video clips. Unless social-media data is controlled or censored by the government, issues of national interest getting discussed and circulated on social networks can serve as checks and balances on a country's leaders, said David Menninger, head of business development and strategy at Greenplum, the big-data analytics provider owned by EMC.

"For example, say there's higher occurrence of a type of complaint [by users] about aging infrastructure, that creates a checks and balance for the authorities [in charge]," he said at an interview Thursday. Menninger, who is based in the US, was in Singapore to meet company executives and business partners.

Big-data analytics can make government agencies more efficient and also serve as checks to ensure transparency in their operations.

Gathering and analyzing all that data enables governments to better serve the people. They know what critical issues need immediate attention, where to concentrate their resources, and spend money where it is most needed to do the most good, he noted.

Going a step farther, big-data analytics can also be used to maintain transparency and fight potential graft in governments, Menninger pointed out.

In the area of procurement, for instance, analytics could spot a pattern of contract awards that is an anomaly, he said.

"The pattern is not necessarily obvious and could be several levels and layers of interactions among the people or groups involved. [With analytics], you might identify a connection between this group and contracts awarded to an organization.

"When you see a pattern like that, that in and of itself does not necessarily mean [there is] corruption, but it does suggest there's potentially an anomaly and at least prompts further investigation. Predictive analytics allows you to compare what you've identified are outside the norm with what is the 'average'. And it's unusual that, strictly by chance, something would be that far from the norm," Menninger said.

This level of analytical capability, according to the Greenplum executive, is "sophisticated" and cannot be achieved just by scanning data using traditional tools. "You really do need some additional skills to apply this type of analysis, and it's one of the biggest challenges in the industry right now,'' he said, pointing to the shortage of data-science talent.

Asked if governments in Asia would be receptive to the idea of big data being used to check on them, Menninger replied that it is not surprising people and organizations are not comfortable having themselves watched and monitored.

"Organizations that are more forward looking or in tuned with what their mission is, recognize that constructive criticism will make them better. It's really only those doing something wrong that have something to fear. Generally, closer scrutiny applied in a constructive way will help them be better agencies and provide better service. It's more of case of each individual organization's attitude, and not specific to governments or private enterprises."

As such, there needs to be a cultural shift in the way an organization thinks, and therefore those at the top need to recognize the value big-data collection and analytics brings, and help drive that change, he added.

The same applies to national leadership as well to spearhead that change through formal legislation and national policies, Menninger noted. The various public agencies may be reluctant to share their data with other agencies because they are unsure they may end up violating restrictions on what can or cannot be done with their data. "If you're worried about making sure you comply with laws and regulations, it's easier and safer to say I'm not gonna do anything, [even though] that's not necessarily the best outcome."

According to Melissa Ries, Asia-Pacific general manager of Greenplum, this links to a big challenge of cross-agency collaboration within the government sector. "For example, in Singapore, it's about how to get the Land Transport Authority [LTA], National Environment Agency [NEA], and traffic police all collaborate together with their data to help improve policies and efficiency of public transportation."

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