George W. Bush would famously boast of being a “gut player,” like Gary Cooper in the Western movie High Noon.

This style of ‘cowboy’ leadership may be valuable in politics, but it can lead to reckless decisions or a failure to spot big problems. After the Iraq War and the subprime crisis, the world has moved on.

Data is now sought by leaders before all big decisions, from fighting crises to modernising workforces. “All these subjective phrases and terms are no longer being used,” says Alvin Pang, Head of Enterprise, Singapore at Tableau.

GovInsider discussed three key case studies with executives at Tableau, an expert in data analytics.

Areas of application

First, let’s look at transportation. The year is 2016 and commuters are stranded on the subway platforms where the rail network has suffered a major breakdown. The GovTech agency of Singapore sprung into action by using a limited data set comprising time, location, routes, and trains to find what was causing the problem. Through data analytics, they were able to spot a rogue train that was causing electrical shorting on the entire network – allowing action that got people back home to their families.

Second, we can see examples from hospitals, which use data to improve patient safety. Pang says that data from falls in hospitals can be plotted against their causes, timings, and locations to help healthcare workers understand if these are isolated incidents, or if the layout of the hospital needs to be changed. “Is it a pattern that is recurring? And from there, you’re able to provide better countermeasures to prevent such accidents from happening,” he continues.

Third, let’s look at how workplaces can reform their people management. A multinational company was able to use Tableau find out where headcount is needed most, and how much it costs to operate each headcount in every country, recounts Leslie Ong, Country Manager, South East Asia. It did this by standardising values like currency and giving them “a single pane of truth,” he says.

Enter smart tech in data

Data analytics lowers the barrier when it comes to gleaning valuable insights, allowing anyone to use data effectively. This empowers even workers with a basic understanding of data to manipulate “information in a much better way so that they can take that and make decisions,” says Ong.

Automated data prep is also changing the game for data experts. Data analysts spend 80 percent of their time cleaning up data sets, and 20 percent of their time analysing, says Pang. Machine learning in data analysis can flip the equation around, leaving them with more time to mine insights, rather than numbers.

Tableau is incorporating natural language programming into its software. ‘Ask Data’ allows people to type in a question, and have the software present them with answers in the form of interactive tables and graphs.

No longer do people have to trust their gut. And to see the data, it isn’t essential to hire a cohort of data scientists to trawl through it first. Let the computer do the work, take the decisions, then take the credit too. Mission accomplished.

Image by Tableau Software Facebook page.