By Johan Steyn, 15 February 2022
Leaders in business today work in a world where their internal operations and, in particular, their digital connections with customers generate previously unimaginable volumes of data.
To keep track of their development and make future expansion plans, companies of all sizes and sorts are turning to data and analytics. Managers face a deluge of data they must sort through and make sense of.
Most business data is classified as unstructured, which means it does not have specified data types nor may be easily searched. Documents, emails, sensor data, and audio or video files are just a few of the examples. It is estimated that more than two-thirds of business data is unusable.
With the help of data analytics, it is possible to foresee a company’s future issues and opportunities and identify areas that are ripe for improvement. It is possible for businesses to predict the long-term consequences of current issues or future opportunities using machine learning and predictive analytics.
Many businesses continue to face data management challenges despite large long-term investments in data management. This is due to the fact data has rarely been viewed as a company asset, but rather as a mere component of technical initiatives. Data analysis enables leaders to make well-informed decisions that contribute to long-term success. Consider the following data variables: strategy, culture and ownership.
What is the definition of a data strategy? A data strategy, as defined by the Data Management Body of Knowledge (DMBoK), is a “high-level course of action to accomplish high-level goals”. This plan details the company’s objectives for exploiting data to gain a competitive edge and advance its aims. Among the benefits is the capacity to make judgments and take actions with data assets based on a predetermined path.
Due to the fact data is rarely used as the only foundation for decision-making, many businesses struggle to build a data-driven culture. The issue is not with the technology; rather, it is with the culture of the organisation. Data adoption as the lifeblood of an organisation’s operations begins at the top. By setting an example, senior executives must make data-driven decisions and help their workers on a data-driven path, early on demonstrating the importance of data science.
According to Gartner’s 2021 CEO and Senior Business Executives Survey, less than half of the world’s largest firms have a chief data officer (CDO) in control of their data strategy. When the C-suite is involved in and directed by the data strategy, firms are more likely to be innovative and particularly effective at creating commercial value.
Recently, PwC in SA released a thought-leadership article, “The role of the chief data officer”. It shows that global organisations that use data innovation correctly typically increase revenues by up to 8% with a net profit increase of circa 2%. “Repositioning the role of CDO is the key for an organisation to identify the value of their data, realise the value and sustain the value in key business areas.”
It is clear that data is vastly growing in importance as a business value driver. What is also clear is that the data strategy, the organisational culture and ownership is not a technology department role as such, but that business owners at the most senior levels should be intrinsically involved.
• Steyn is chair of the special interest group on artificial intelligence and robotics with the Institute of Information Technology Professionals of SA. He writes in his personal capacity.