Your Next Decision Could Change Lives: Why We Need Data Skills and Analytics

June 12th, 2020

This article is by Geoff Thomas and originally appeared on the Qlik Blog here:


The year was 1993. The place, a little town in Sweden. A serial killer was on the loose. He randomly shot at people standing at bus stops or sitting in their cars, killing one and wounding many others. The residents of Malmö lived in fear. Window blinds were shut, playgrounds were deserted. The police didn’t know where to start.

The breakthrough came when the police force used data analytics technology that was capable of analyzing 10 years’ worth of crime records—or two million files—and cross-referencing those with the tips submitted by citizens. With the use of a powerful business intelligence solution at the time, they managed to visualize crime data from multiple sources containing information such as reported behaviour, and locations and time of these incidents. In the end, with the big data insights they gathered, they finally identified the killer, putting an end to this high-profile crime case which lasted for more than a year. This proved that the power of investigating and understanding data can keep communities safe and directly impact lives.

We can extend this approach of using data, artificial intelligence (AI) and analytics to other aspects of life. In hospitals, doctors analyze patients’ data to fight chronic diseases and provide better treatment. Sydney Local Health District has utilized data to find trends and information through their award-winning STARS Back Pain App, all in a bid to enable healthcare professionals to confidently treat lower back pain by delivering better care, with greater visibility into the patients’ medical situation.

At the time of the COVID-19 crisis, one challenge that many hospitals faced is the dire need of provisioning medical resources, including personal protective equipment (PPE), such as masks, in areas of current and projected shortage. In the APAC region, Malaysia is left with only two weeks’ worth of personal protective equipment and Australia is facing similar shortages.

This is squarely at the heart of the mission of Direct Relief and their work both in the U.S. and internationally to equip doctors and nurses with life-saving medical resources to care for the world's most vulnerable people. We have used data and our business intelligence platform to develop a supply chain app to provide the organization with valuable insight into regions, counties, and individual health care systems where there is the greatest need for the deployment of masks, gloves, gowns, ICU medicines and more.

The UN is also bringing the power of data analytics to global humanitarian efforts, to impact efficiency and efficacy. With the use of data, systems and tools, the UN Climate Change department can integrate, process and visualize greenhouse gas emissions data, driving change towards reducing emissions and implementing “climate positive” strategies globally.

It is easy to believe that we are comfortable enough with the current data systems we have in place—AI-powered algorithms, machine learning and even data analytics platforms, which often run in the background while we do our work. However, the reality is quite different. Our recent “The Human Impact of Data Literacy” report found that six in ten employees (61 percent) feel data-overload has contributed to workplace stress, leading to billions lost in productivity each year. This brings up the issue of the lack of data literacy – a person’s ability to read, work with, analyze and argue with data.

More To Be Done To Become Data Literate

We all need to act in concert if we want to change this situation and enable more workers to turn data into decisions.

Championing data literacy should not be the work of just a single entity—everyone from all walks of life must be involved, be it individuals, the public or private sector. For instance, the University of Oakland has been integrating the use of data analytics into various courses it offers, from management information systems to statistics, business and manufacturing engineering.

Nanyang Technology University in Singapore has even introduced an innovative undergraduate degree program in Data Science and AI last year to prepare students for the new digital economy. However, it will take time for these programs to bear fruit. Even at the workplace, our Human Impact of Data Literacy survey shows that only 21 percent of the global workforce are data literate. As organizations from all sectors become increasingly data-informed, that’s not enough to secure the future of these businesses.

On a global scale, governments and organizations will have to play a bigger role in championing greater data literacy for the benefit of their people. Some governments have started to develop national upskilling programs and trainings to transform and improve lives.

Forrester predicts that this year, 40 percent of firms will launch a data literacy lifeline and create formal programs to promote greater data literacy across all roles in their organization to ensure survival. Hence, it is good to see governments and organizations alike recognizing the importance data literacy plays in society and developing learning programs with certifications, so that participants can measure the progress they make.

Data Is For Machines, Decisions Are For Humans

As data continues to permeate every aspect of our lives—at home, work or school—the power of data-informed decisions will only increase. And while the technology for collecting and analyzing said data will become more widespread, there is one thing that remains, which cannot be automated: our human ability to instil sense into what we see on our screens.

Starting today, we should ask more questions and interrogate the facts and numbers that we are provided with. We must be more curious and ask ourselves what the next steps are? How can we benefit from this information? In what way can it change our lives?

Going back to the Swedish town of Malmö—analytics might have helped to speed up the analysis of criminal records which would have taken one officer 43 years to complete, but ultimately it was the police officer behind the machine who made sense of the data and tracked down the serial killer. This is aligned to a Gartner study which states that AI-human partnerships is advantageous due to the power we can draw from the combined human and AI capabilities to deliver the best results.

There was a time when reading and writing skills were exclusive to scholars and the learned community. Just as these skills moved beyond scholars, data literacy will become an important and common skill, and those without it will be limited in what they can accomplish.