The COVID-19 pandemic demonstrated how data analytics can be a great help to the government and healthcare sectors, as well as businesses and individuals. But data literacy is critical for data to be useful.

The current pandemic has brought about an explosion of data. As countries across the globe struggle to tackle COVID-19, more organizations are also stepping up by offering data visualization dashboards to help examine the outbreak.

But there’s the rub. How much of this data is accurately interpreted and understood? The answer, it seems, is little – according to recent headlines that have reported major discrepancies and confusion in pandemic data released by organizations.

With the pandemic carrying a massive impact on our jobs and livelihoods, organizations need to critically examine pandemic data to avoid falling prey to inaccurate representations. This means learning to become data literate – to understand the data, ask the right questions, then form meaningful, actionable insights.

DigiconAsia talks to Jordan Morrow, Global Head of Data Literacy, Qlik, about the importance of data literacy for Asia Pacific employers and employees in the digital economy:

DigiconAsia: How has data and analytics helped in the fight against the COVID-19 pandemic in Asia Pacific?

Jordan: Data and analytics have proven pivotal around the world with COVID-19, lending itself as an essential navigation tool for all. Governments and healthcare sectors are leveraging real-time pandemic data to keep communities abreast of the evolving situation and to gain insight into preventative measures that can help curb the virus’ spread.

In Asia Pacific, I understand that the Singapore government has recently developed a data analytics tool to help uncover links between COVID-19 cases and identify new clusters, allowing healthcare workers to conduct enhanced screening to prevent infections from snowballing into the wider population. Other countries like Taiwan are also tapping on data like travel history and health symptoms to classify an individual’s infectious risk, aiding in case identification and containment.

We are also seeing organizations stepping up by offering solutions like COVID-19 data visualization dashboards to help. Some have used “iteration” in the process – revising models as more data comes in. One of our customers, Asian Development Bank, responded with their own Qlik application that not only provides real-time data to track the virus’ spread globally, but also forecasts demands and losses in the economy to help countries plan their financial resources strategically to jump-start Asia’s economy post-COVID-19.

DigiconAsia: How has the COVID-19 pandemic amplified the need for data literacy across organizations?

Jordan: COVID-19 became a catalyst for data and digital transformation.

The lockdown period showed how unprepared some organizations were in using data to make smart decisions quickly. Recent news headlines have also sparked a debate on the accuracy and understanding around some of the COVID-19 data released, causing unnecessary worry and confusion amongst the public, and in some cases, led to delayed mitigation efforts in the region.

Inaccurate representation and interpretation of COVID-19 data has therefore amplified the need for data literacy across organizations. Despite data and analytics being known for its problem-solving and predictive capabilities, organizations must first become data-literate to reap its full capabilities. This means learning how to read, work with, analyze, and communicate with data to form accurate, meaningful, and actionable insights.

DigiconAsia: What are some steps that organizations can take to achieve a data-literate workforce and succeed during the pandemic and beyond? Please provide some examples of Qlik customers – global or regional – that have successfully achieved this.

Jordan: There are four key steps that organizations must follow to achieve a data-literate workforce.

  1. Set clear data goals. Consider what you want your data to do and where it can deliver value. By outlining clear and identifiable goals, organizations can define how different roles will need to work with data to achieve them.
  2. Develop a strong data and analytics strategy to achieve your data goals. Organizations need to have a holistic approach to data and analytics to ensure that data can be leveraged across various job functions and divisions. This can be achieved by assessing the current state of data literacy within your organization, like evaluating each employee’s level of data literacy, defining the data that employees need to access, or preparing the right data tools to support each employee. This will provide you with a clear view of what investments are needed to empower your employees.
  3. Empower your workforce with the right culture and learning. In addition to equipping employees with the right tools to use data, organizations need to establish training programs to help employees capitalize on data and act from insights.

    For example, the arm of the United Kingdom’s leading healthcare organization, NHS Foundation Trust, runs a Quality Champions program to teach all employees – from domestic staff cleaners to nurses and analysts – on how to turn data into actionable insights. Since 2012, the program has helped initiate more than 200 data projects to improve operational performance and patient care.

    Thanks to their early groundwork, employees have been able to find new ways to provide safe and timely patient care amid the COVID-19 pandemic through data. Together with Qlik, NHS Foundation Trust developed an application offering insights into COVID-19 risks that incoming patients travelling via ambulance may carry and real-time information on patient movements to help reduce delays in patient care and support patient flow. There are also plans to look at population health analytics to help identify vulnerable cohorts of patients and improve virus containment.
  4. Create a culture of co-evolution. Data literacy training should not be a tick-box exercise. Once in place, organizations should regularly reassess their data tools and make data literacy a compulsory part of employees’ learning and development programs. This practice of continued upskilling will also help organizations stay relevant in an evolving market.

    We are proud to be working closely with education sectors like Singapore Management University (SMU), to help foster a culture of strong data literacy. To date, SMU has trained hundreds of staff members through Qlik’s platform and courses. The university has also formed a culture of co-evolution by providing a platform for staff members to reach out to SMU data analytics experts at any given time. Nearly three quarters of SMU staff members now use Qlik for data requirements, which has saved 400 man-hours per year and created better work and learning experiences for students.

DigiconAsia: Looking ahead, what can organizations do more with data to thrive in the digital economy?

Jordan: For starters, continually find ways to leverage data-driven solutions like AI or machine learning to automate tasks within your organization. This will not only help streamline operations but also direct employee focus to more meaningful and challenging work that can spur business growth.

Next, regularly assess the value of your data. As data ages, its value can wane. Organizations should take advantage of the vast amounts of available data and identify opportunities to access new data to increase business value. When in doubt, always go back to your data roadmap to see the data you require to help you achieve your goals.

Above all, organizations trying to modernize their approach to data and analytics should understand that technology is not their biggest hurdle, but change management, culture, and leadership. Leaders need to understand that data and analytics are there to help empower and enable, but this only works if their employees are comfortable with it.

Not everyone needs to turn into a data scientist, we just need to empower them to have confidence with data. If leaders can adopt this mindset, I am confident that they will be able to execute a successful data literacy strategy to empower employees with the right data capabilities to make smarter decisions and optimize performance to help their organization thrive.