Self-service is commonly identified as a growing trend in the business intelligence (BI) and analytics fields. Many analytics and BI solutions are now starting to tout their self-serve capabilities as the “next generation” in business intelligence and analytics. (At times I may use the terms “business intelligence” and “analytics” interchangeably throughout this article, with the recognition that they are in fact distinct disciplines.)
Generally, what self-serve means (in the world of analytics and BI) is to provide end-users will the capability to extract their own data, create their own dashboards, generate their own visualizations, and conduct their own analyses. In healthcare, this would empower hospital executives, department managers, and other leaders to have exactly the information they need (in the format they desire) to aid them in their decision making.
In the past, there was just not the capacity for self-serve analytics. Data extractions typically required complex database queries, specialized programming was required for even modest statistical analyses, and data visualization tools typically were limited to spreadsheet (or presentation software) graphics. Users are now much more computer-savvy and analytically aware, and the available BI and analytics tools have become easier to use, more numerous (meaning more choice!), and less cost-prohibitive.
One-size-fits-all reports never were really an ideal solution, and now there simply is just no excuse for them! Customizable self-serve BI and analytics tools will allow decision makers to have immediate and interactive access to the accurate and timely information they need. In addition, self-service will mean that analytics (and BI) professionals will be freed up from building one-off solutions (essentially being a report factory) and will be available for more challenging, innovate work.
I must admit, in the organization I work, we are a long way from true “self-serve” analytics. It is a goal of mine to advance self-serve BI and analytics within my organization. In doing so, I will be exploring new tools, resources, and approaches to make self-serve analytics a reality. These experiments will be documented here on HealthcareAnalytics.info as we continue to innovate in this area – and I’ll do my best to share with you what works for us, what might work for you, and what doesn’t work (period). I’d be very interested to hear of your own experiences (including questions, issues, and concerns) in implementing self-serve analytics within a healthcare environment!
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