Aussie satisfaction in big data lags behind global results: Accenture

Accenture Analytics' latest research into big data projects finds Australian organisations are actively engaging in activities, yet aren't as satisfied or as strategic as their global counterparts in its value

Australian organisations are overwhelmingly satisfied with their big data activities, yet are lagging behind international counterparts when it comes to seeing data as a significant source of value, a new report claims.

The Accenture Analytics Big Success with Big Data report found 78 per cent of Australian executives surveyed are either ‘very satisfied’ or ‘satisfied’ with their results from applying big data to their business, and 70 per cent rated big data as ‘very important’ or ‘important’ to their businesses’ digital transformation.

However, both of these lagged behind the global survey results of 92 per cent and 89 per cent, respectively, Accenture stated. In addition, 94 per cent of global respondents reported that their implementation is meeting their needs, and 94 per cent said big data is being used to identify new sources of revenue.

Among the top uses cases in Australia are identifying new sources of revenue (86 per cent), retaining and acquiring customers (80 per cent) and developing new products and services (80 per cent).

Related: Westpac taps into new big data streams for customer delivery

Yet only 58 per cent of Australians believed big data provided a significant source of value for their organisation, a far cry from the 82 per cent reported globally. And only 34 per cent of local organisations are likely to use big data to stay competitive. This contrasted with 58 per cent of global respondents.

While 36 per cent said c-suite and management extensively understood and supported big data initiatives, half said these executives only ‘moderately’ support such projects.

“There is a clear disconnect between the confidence Australian leaders have in big data solutions, and the value these solutions can deliver, particularly as organisations look to become more digital,” commented Accenture Analytics lead for Australia, Michael Pain.

“There is a direct correlation between leadership support and big data success. So for Australian organisations to drive real business outcomes, there needs to be alignment and investment in big data solutions both at a strategic and operational level.”

Related:Accenture Analytics: Don't drop leadership intuition for analytics
CMOs, CIOs increasingly see chief customer officer as relationship saviour, finds new Accenture survey

Over the next five years, two-thirds of Australian respondents said big data will have the biggest impact by ‘changing the way we organise operations’, indicating that many are still using big data primarily for efficiency and cost reduction or within siloed business functions. Sixty-two per cent said big data will benefit ‘customer relationships’, and 52 per cent saw it contributing to ‘product development’.

More than half of Australian respondents cited budget as impeding big data projects, followed by integration with existing systems (48 per cent), security (44 per cent) and a lack of talent to run big data and analytics on an ongoing basis (42 per cent).

Globally, security was the top challenge, followed by budget. Notably, 41 per cent also cited a lack of talent to implement big data, and 37 per cent lacked the talent to run big data and analytics on an ongoing basis.

What was interesting was that 95 per cent of global respondents are relying on external help to make sense of big data. Fifty-seven per cent are using consultants to help their big data installation, 45 per cent have contracted new employees, and 34 per cent are relying on technology vendor resources to do the job.

The Accenture report is based on companies from 19 countries that have completed at least one big data implementation. Of the 2600 organisations chosen globally, executives from 1007 were interviewed between February and April this year.

Sources of big data nominated by respondents included large data files, advanced analytics or analysis, data from visualisation tools or social networks, unstructured data and geospatial/location information.

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