Organisations are using data as a means to boost performance. Leadership must understand capabilities and desired outcomes to drive meaningful change.

Data is known to have been used to drive business performance since Taylor and Ford started measuring and optimising the output of assembly lines in the late 1800's. The importance of the analysis of data to support decision-making, referred to interchangeably as 'Business Analytics' or 'Data Analytics', has grown and continues to grow proportionally to our ability to store and process data.

The volume, velocity, and variety of data being processed in organisations has experienced a substantial increase. By one estimate 90 percent of the data that exists today has been produced over the last 2 years. This paradigm shift requires a fresh outlook.

Future success will depend on having the right business understanding and selecting the right technology to process and make sense of data as well as on meaningful usage of insights generated from it – with the amount of data available it makes no business nor economic sense to process everything.

Moving forward, all organisations will need a framework that helps shape data strategy, governance, data integration, architecture, and data quality. Modern tools enabling automated and intelligent data processing will also be crucial, removing the burden of repeated and non-value-adding tasks from people and letting them focus more on leveraging the data for their primary goals.

Companies need to understand their desired outcomes to select the right data. Then they need to know exactly where the data comes from, how it was collected and what it represents. That information is key to understanding the context of such data and building trust in the quality of the data being employed in strategy and planning.

This requires an understanding of the kind of analytics that is possible and how this can be used to support the organisation's goals. Analytics can be broadly categorised into four types: Descriptive Analytics; Diagnostic Analytics; Predictive Analytics; Prescriptive Analytics.

Fostering a data-driven culture then becomes essential to ensure that any technological advancement is embedded and leveraged in daily business processes, with information workers made aware of data-enabled possibilities and motivated to use and benefit from them. This will help organisations successfully integrate all aspects of a data-centered approach that will prepare them for the continued growth of the data economy whether it be data analytics, business intelligence, artificial intelligence or intelligent automation.

Having successfully completed a number of data analytics projects, and with the support of an international network of data professionals, KPMG in Malta is well on its way in its journey into this new paradigm, which many businesses are only just starting to traverse.

As we look to the future, KPMG intends to join the public forum in this area to stimulate discussion, offer expertise, and support businesses in their needs.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.