Half of Aussie organisations fail big data quest

New Fifth Quadrant report into big data analytics across Australian organisations finds three-quarters are using big data analytics but half are finding their efforts unsuccessful

Big data analytics are being increasingly infiltrating Australian businesses but more than half claim their attempts to leverage such information to improve customer experience have failed, a new report claims.

Research consultant firm, Fifth Quadrant’s new Big data or big hype? research found three quarters of Australian organisations surveyed are using big data analytics to examine large volumes of data for a variety of reasons including better decision making and greater profitability. However just one in eight claimed such activities were ‘extremely successful’, while 53 per cent said their attempts were actually unsuccessful.

According to the research, 31 per cent of organisations actively use big data and analytics when forming strategic decisions or across a wide range of corporate activities, and the majority of respondents recognised how much impact big data can have. Despite this, less than three in 10 consider big data a core business initiative and less than a quarter use it to determine a product or project’s success.

The biggest users of big data analytics in the enterprise are customer service, sales and marketing, while the least prolific is the human resources department. Common objectives include forecasting, improving the customer experience, marketing and real-time decision-making. In a comparison of mature versus immature organisations, mature organisations were more commonly using big data in reducing operational overheads, development of new products, fraud prevention and detection, and contact channel optimisation.

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Major challenges were also identified by respondents and range from a lack of skills and appropriate technology solutions to poorly integrated IT systems, and insufficient internal resources. The report was based on surveys of 63 Australian organisations.

The Fifth Quadrant findings echo the views presented in a similar report on the big data challenge for marketers conducted by the Economist Intelligence Unit in the US. According to EIU’s research, 37 per cent of marketing executives see interpreting big data as the biggest challenge to crafting an effective marketing strategy. In addition, 45 per cent of respondents claimed to lack sufficient big data analytics capabilities, and just 24 use data analysis to develop actionable insights for their overall marketing strategy.

The Fifth Quadrant study also highlighted a link between the maturity of an organisation's big data analytics practices and business performance outcomes, with a particular focus on customer experience performance, revenue generation, employee engagement and operational efficiency.

Businesses that score highly in maturity are consistently more advanced in using analytics to determine return on investment (ROI) and to more effectively manage resources, the research stated. In terms of who is leading thought leadership regarding big data analytics, 41 per cent of mature organisations said the CEO, compared with 20 per cent of immature organisations.

The research also found less mature organisations usually have line-of-business or business unit manager leading the big data push.

Fifth Quadrant’s head of customer experience research, Chris Kirby, said Australian businesses are in little doubt about the potential value that big data analytics can deliver, especially when it comes to developing a better understanding of customer needs.

“We know big data analytics are being used by organisations to drive a range of positive performance outcomes but this study also shows work still needs to be done to leverage the analytics for greatest advantage,” he commented.

“The greatest success appears to come when organisations adopt an integrated customer analytics strategy that puts quality data in the hands of decision makers and leadership from executive teams is critical.”

Top 5 challenges experienced
  • Lack of skills – 47%
  • Lack of appropriate technology – 36%
  • Poorly integrated IT – 34%
  • Different needs of stakeholders – 34%
  • Lack of internal resources – 31%

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