The potential business returns of effective big data analysis have been well documented across a wide variety of industries from manufacturing to marketing.
But gaining a 360-degree view of a customer, successfully predicting sales in a new market or predicting when machinery will fail – all possible effective big data analysis outcomes – can’t happen if business users opt not to use the tools.
Increasingly, front-line workers likely won’t use big data analytics tools unless those tools are intuitive and easy to use in current work processes, according to recent research.
For example, the best performing companies “drive strong analytical activity in more than six times the percentage of their workforce compared to all other companies,” notes Aberdeen Group.
Furthermore, in the highest performing companies, 76% of users are actively engaged in analytics, compared to 28% at industry average companies and 11% in the lowest performing companies.
Additionally, Aberdeen notes:
- 66% of the highest performing companies are “satisfied or very satisfied” with the ease of use of their analytical tools compared with 29% of average performing companies and 8% of the lowest performing companies.
- In the highest performing companies analytical projects are much more likely to derive from business needs raised by business users.
- Top performing companies are four times as likely as the lowest performing companies to have processes in place to convey user needs and requirements for analytics.
- Best-in-class companies are almost three times more likely than all others to consistently track and measure the use of analytics.
“Going beyond simple deployment of the tools to implant analytics in the most important daily activities is a powerful way of building greater analytical adoption and ultimately improving performance,” the report notes. “Tools that resonate are specific to the needs of a given type of user or business area and provide intuitive views of metrics that closely align to that person.”
Bolstering user adoption of analytics tools is key to allowing companies to make the paradigm shift from using business intelligence tools to review historical data to using analytics tools to more proactively make decisions based on predicted outcomes, says Soumendra Mohanty, Accenture’s senior executive.
“The gulf – moving from report browsing to finding patterns, correlation between events and subsequent implications, etc. – needs to be bridged with navigational guidance, automated alerts and what-if scenarios,” Mohanty notes. “Guided analysis provides timeliness in dealing with anomalies and allowing the workforce to spend time performing quality work and managing greater workloads without any reduction in efficiency. If the effort in analyzing data to see if a problem is present can be reduced, more effort can be expended to remedy problems that have already been identified.”
Mohanty adds that guided analytics can help businesses achieve actionable insight by:
- Customizing display layouts and content relevance to users based on their profiles
- Defining alerts based on certain business conditions
- Embedding predefined analytics executables into business processes, reports and dashboards to direct the decision-making process.
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