8 steps to success with self-service analytics
Self-service analytics are growing in popularity because of the benefits that inquisitive clinicians can achieve. Self-service analytics tools can be easily deployed by non-technical users. Consider the following checklist for an effective and comprehensive self-service analytics strategy.
Self-service analytics—a checklist for critical components
Through the use of self-service analytics, “organizations have the opportunity to dig deeper to uncover significant indicators and metrics, explore information and discover its potential, interact with real-time data, automate the scheduling and delivery of vital information and use the resulting insights to drive better business outcomes,” says Rado Kotorov, chief innovation officer at Information Builders. “Analytical insights are no longer reserved for data scientists and other elite groups.” Kotorov’s keys to success include the following.
“Provide a powerful, comprehensive and accessible way to share and operationalize insights by offering an intuitive interface that influences people to use any app, even an analytical one,” Kotorov advises. “This leads to new heights of adoption and increases return on investment.”
To avoid increasing hardware and maintenance costs, “utilize a scalable underlying architecture that will effectively support a growing user base,” Kotorov says. “This will hold true even when the number of users reach into the hundreds and thousands.”
“Ensuring the integrity of confidential information is always critical in BI and analytics initiatives,” Kotorov notes. “When data is shared among outside user groups, like customers and partners, this becomes even more critical. Make sure you invest efforts in data security as part of your self-service strategy.”
Contemplate data services and integrations
Use data services and integration to enable IT to expand the data environment and open up all information, Kotorov says. “This includes all internal systems such as CRM, ERP and legacy applications, as well as social, cloud, mobile and other sources.”
Address the unique needs of end users by delivering a single integrated platform with a broad range of capabilities, Kotorov stresses.
Drive up performance
“Users will quickly abandon a self-service initiative if performance isn’t up to speed, and they aren’t inclined to cut you any slack due to large volumes of data or a high number of queries,” Kotorov says.
Keep it personal
“Give users full control over what they see and how they see it,” Kotorov says. “This will deliver greater levels of BI pervasiveness, because information is only truly relevant when users can shape it to their own specific needs.”
Check your integrity
“Ensure your BI and analytics initiative is supported by an underlying data quality platform,” Kotorov says. “This will guarantee that all data is timely, trusted and available for self-service access and ensure the data accuracy, consistency and completeness that is essential when information is shared with a broad user base.”