The volume of data companies deal with has increased 14 fold over the last five years and half of them are struggling with “data reliability”, according to a new report from the Melbourne Business School that warns of the need to invest in data ecosystems.

The study suggests emerging technology like AI is widely popular but only the companies with strong data fundamentals are gaining significant value from it.

For its Analytics Impact Index 2020 the University of Melbourne’s business school, along with consultancy Kearney, surveyed 300 global companies with a median revenue of USD$330 million across 33 industries, respondents from participating companies were primarily from the C-Suite and Director levels. 

The companies reported continued rapid growth in data velocity – the speed at which data is generated – and data volume – the size of data that is collected and processed. 

On average data volume has increased 14 fold over the last five years, according to the report. The rate increases more for businesses that are more advanced in analytics. For example, the volume of data analytics “leaders” collect increased 20x in five years.

Increasingly, the report says, wrangling that data is becoming a competitive differentiator.

“In the challenging times that we currently face, organisations can leverage their data assets to compete, but the extent to which they can compete is limited by the reliability of their data assets,” said Professor Ujwal Kayande, Director of the Centre for Business Analytics at Melbourne Business School.

 “The increase in data volume is not so surprising as more organisations and customers connect into the internet of things and high-speed networks. Moreover, moving data into the cloud has removed the barriers that organisations previously faced in terms of being able to access and store data.

More data ≠ more insights

Kayande said while data is increasing quickly across the board, more data does not necessarily mean better insights because data reliability remains a major issue.

“Organisations face challenges in being able to aggregate data across legacy systems that don’t always talk with each other. To be able to integrate and leverage data across systems requires a strong sense of the purpose of the data. Once that is addressed, organisations find it easier to integrate and leverage data, thereby resolving reliability issues.”

According to the report, More analytically mature businesses spent 20 per cent of their total data ecosystem budget on improving data reliability and 83 per cent met their data accuracy and reliability objectives. Analytics laggards, however, invested just five per cent of their total budget on improving data reliability and only 14 per cent met their objectives.

Leaders leverage AI

The study also looked at investment levels in AI. While AI investment levels were similar across organisations it was mainly those with more mature analytics capabilities extracting value from them.

“What we found was that whilst the investment in AI was similar between the two groups, only the Leaders and Explorers were reaping true value from their AI pilots. This implies that you simply can’t expect superior results just by injecting more capital into your AI program and expecting it to be successful,” said Kearney Partner Enrico Rizzon.

 “Companies need to be highly aware of other influencing factors and work on enhancing them. As an example, we found that AI pilots were successful for Leaders because of their culture of experimentation and other differentiating factors such as having leadership and buy-in from the C-suite.”

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