Getting the most out of your data analytics tools

July 20th, 2015 | by Aaron Tan
Getting the most out of your data analytics tools

While most enterprises today have embraced business intelligence or data analytics tools, some are benefitting more from the tools than others.

According to a new IDC survey commissioned by Tableau, it appears that strong management support and a data-driven culture are keys to unlocking the full potential of data analytics tools. The survey involved 207 respondents in Singapore, Japan, Australia and India.

“We found that top-performing organisations have cultures built around data-driven decision making,” IDC said in a report published in April 2015.

“These organisations provide employees with analytics tools that better suit their needs, see more frequent use of analytics among their employees, and are more likely to realise greater benefits in the form of cost reduction, revenue increases, productivity increases, and improved innovation rates,” it added.

In particular, organisations with a strong data-driven culture are more likely to use data analytics tools on a daily basis, leading to over 50 per cent improvement in business outcomes compared with less analytically-oriented ones.

And when managers are more involved in promoting the use of analytics, users report six times more frequently that their analysis needs are fully met.

As with any new technology initiative, there will be hurdles when implementing data analytics. Most will be organisational challenges that will require compromise and collaboration.

So, how can enterprises maximise their data analytics investments? IDC offers the following tips:

Deliver analytics tools that best support the business user: Users in the Asia-Pacific region often report shortcomings in ad-hoc analysis, visual analysis, and mobile access to information as inhibitors to more effective use of analytics. This can be addressed with tools that extend beyond commonly available enterprise reporting software.

Encourage the use of analytics in decision-making: Managers can lead by example and influence corporate policies. Management influence is key to driving pervasive analytics use across an organisation.

Have a team responsible for improving analytics capabilities: The team’s responsibilities should include establishing data governance policies, providing access to data sources, championing the analytics tools, and developing new analysis to share with users. The team should include members from both business and IT.

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