In fact, more than three-quarters of UK businesses take a fortnight to complete this multi-step process, meaning by the time they get to the data it's outdated. This is a problem that is in dire need of rectification, particularly as in these uncertain times, businesses need quick access to data and insights in order to adapt to rapidly changing situations. Therefore, eliminating lengthy and time-consuming processes to be able to adopt a data-first approach to business is essential. The following three steps can help businesses in this endeavour, allowing them to put the processes and tools in place to turn data into actionable insights and deliver value back to not only their business, but also their customers. For many businesses, the focus tends to be on overarching organisational strategies as opposed to their top business priorities.

Many Australian enterprises have spent years trying to justify their investments in data analytics models. On average, only half of the analytic models built by organisations will ever make it to production. Clearly, organisations that operationalise and monetise their artificial intelligence (AI) and analytics capabilities are more likely to succeed with their customer engagements. Tech execs gathered at a virtual roundtable recently to discuss the challenges they face when moving their AI and data analytics programs from an experiment inside their business to one that is a key part of their core operations. The conversation was sponsored by SAS.