The Real Cost of Data Illiteracy

The world is abuzz with technical jargon emerging, including the fourth industrial revolution, digitisation, digitalisation and digital transformation, and of course data. The truth is, while these terms represent the future of how humans will exist and operate, these elements are already firmly establishing themselves in our everyday lives.

 

Alarmingly, according to a study done by Qlik, only 24% of decision-makers are data literate. The pace at which changes are happening within personal and business lives, is faster than the pace at which people are able to keep up. And in business, this is one of the biggest threats to the sustainability and profitability of an organisation.

 

Data should be viewed as the lifeblood of a company as it empowers key decision-makers to derive meaningful insights and apply them in a manner that benefits the business.

 

Historically, data interpretation and analysis were limited to actuaries, who applied old-school algorithms to data to make a projection that determined the future existence of a business. Today, data literacy across the business is critical. All employees must embrace technology to maintain career success, plus the overall business’ sustainability, relevance and profitability.

 

COO of Natsure, Bernice van Leeuwen added, “Ignoring digital transformation in business, puts the business at risk of becoming redundant.” The specialist short-term insurance underwriting management agency intends to educate brokers on the need to embrace technology and encourage decision-makers to understand how to properly interpret and analyse data.

 

Tools, technology and the ability to think critically about data are key components to achieving data literacy, but it thrives in a culture in which data is valued by all as a primary vehicle for decision making. van Leeuwen reflected on four foundation traits that organisations need to build data literacy, as originally expressed by Doug Bordonaro on his blog, The Data Complex:

 

  1. Widespread Access to Data

Previously, data was only accessible to the C-suite, but in order to build data-literate organisations, all employees must have access without going through an intermediary. If, for instance, a sales consultant has to call the IT department to enquire about how many new customers were converted in the past month, then the system is failing that individual, and the company is not data-literate. Ideally, organisations should identify the sources of data that will be most useful to the broadest number of people, and ensure that they’re available via internal data services.

  1. Leadership by Example

Data literacy is a mindset and instilling a data-first attitude is half the battle. While opening up access is the first step, the leadership team must nurture a culture that moves away from making decisions based on experience and instinct, and rather encourage substantiation backed by data. Companies can foster this thinking by introducing a ‘data moment’, whereby employees describe how data informed a recent decision, or they could share data that reveals a change in customer habits.

 

  1. A Platform for Sharing

Excel tends to be a default platform tool for data capturing, however confining it to a desktop application is limiting and leads to inconsistencies as information will naturally become outdated. It’s essential that data is housed on a single source, common platform for viewing, analysing and sharing. When data is centrally stored and managed, it aids policy enforcement around security and governance.

 

  1. Critical Thinking

The ability to learn from data collected will hold valuable insights, which can be turned into action. Interpretation through knowledge, reasoning, and problem-solving is vital. In order to derive meaningful insights, employees must learn to think critically about appropriate use of the information they have access to. Confirmation bias, or the tendency to focus on results that support existing beliefs, is a common pitfall and a real danger. Training can prevent this.

 

“Natsure’s experience with data illiteracy has been a catalytic lesson. Some of the challenges relating to this resulted in delayed, reactive and ineffective decision making,” shared van Leeuwen. “However,” she continued, “through knowledge, understanding, and making data available throughout the organisation, data literacy became a game-changer for us. Currently, Natsure has four primary data sources, which adhere to a data sharing regulation, soon to be promulgated by the Financial Sector Conduct Authority, which requires us to store and share data down to the most granular level. This shift and adoption has lead to a better understanding of customers, and improved efficiencies.”

 

Based on her case study at a recent Qlik Ideas Lab seminar, van Leeuwen shared her advice to organisations embarking on the data analytics journey, which can be summarised into four key points:

 

  1. Get your data in order. Data that is manipulated or ‘manually cleaned’, but never corrected at the source, results in skewed trends and inaccurate results.
  2. Choose a cost-effective and intuitive data analytics tool that suits your business.
  3. Keep it simple. Don’t overcomplicate your analytics. Start with the basics and build models that will be meaningful.
  4. Define data filters and the model purpose. A key issue is not understanding what to analyse, why it’s being analysed and which filters have been applied.

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