Although accountants have used physical spreadsheets for hundreds of years, the revolution of computerised self-service tools has been on the rise since the “Tale of VisiCalc”, an interactive visible calculator invention by Daniel Bricklin and Bob Frankston in the late 70s.
VisiCalc laid the foundation for Lotus 1-2-3, which established itself as a data presentation package as well as a complex calculation tool that integrated charting, plotting and database capabilities. It was also the first spreadsheet vendor to introduce naming cells, cell ranges and spreadsheet macros in the early 80s. Microsoft Excel was the next milestone in response to computerised self-services tools in the mid-80s. Self-service analytics as a need is in fact no stranger.
Most aspects of people’s lives are inundated with self-service alternatives. Companies are more frequently offering alternatives to “do it yourself”. Examples include airline check-in, automated teller machines for banking, public vending machines for a quick snack, as well as kiosks for settling shopping mall parking fees – all of which have enjoyed high adoption around the globe. Their success in adoption has been attributed to the ease-of-use of the self-service terminals and portals. Many companies have seen greater cost savings in their support costs, as well as improved service delivery due to these self-service alternatives.
Defining the self
Gartner’s IT glossary defines self-service analytics as a form of business intelligence (BI) in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with nominal IT support.
It is often characterised by simple-to-use BI tools with basic analytic capabilities and an underlying data model that has been simplified or scaled down for ease of understanding and straightforward data access. This promotes the notion of a shift from IT-led enterprise reporting to business-led self-service analytics in which business users are encouraged to “feed themselves”. The definition also supports the approach in which a semantic layer is prebuilt and a BI tool that is easy to use is presented to access the data.
Ideally, training should be provided to help users understand what data is available and how that information can be exploited to make data-driven decisions to solve business problems. However, once the skilled IT professionals set up the data warehouse/marts that support the business needs, users should be able to query the data and create personalised reports with very little effort. Slow adoption in self-service culture is mostly attributed to computer tools that required specialised knowledge to operate.
Until recently, existing self-service BI tools were mostly for specialists – they were hard to operate and required a knowledge level similar to that of data scientists. Front-line business managers who desired BI-style insights had to send query requests to BI specialists working in the BI department, and had to wait for unbearable turnaround times to get reports that were difficult to change or influence. All this is changing, due to advances in database and query technology, as well as redesigned front-end tools to make it easier for any user to interact with the data.
Self-service BI attempts to generate new insights through shared responsibilities.
The concept behind self-service is that front-line business executives and managers should be able to quickly get up and running with these tools, without having a data analysis background and without requiring a BI specialist as a middleman. Generally, these self-service BI tools should be as easy to use as the typical spreadsheet enabling a user to query data, analyse the answers, and create some kind of visual representation of this data that is suitable for presentation or sharing with other non-technical personnel.
Self-service BI in no way overthrows traditional database management or data scientists. The insights provided by these professionals are complex in nature and remain invaluable. Instead, self-service BI attempts to generate new insights through shared responsibilities, realising new value from hard-won data through more informal, ad hoc analysis.
The business need for self-service tools has always been around and has not changed much over time. What has changed, and continues to change, is the technology used, the data available, and the culture/expertise of information use. New technology possibilities are nurturing the self-service culture in recent times.
The increasing adoption is confirmed by the exponential growth in annual revenue for the three “leaders” in Gartner’s 2014 Magic Quadrant for Business Intelligence and Analytics Platforms (Tableau, Microstrategy and Qlik).
I concur with CEO of Clarity Solution Group Mike Lamble’s opinion: “In the self-service paradigm, ‘power users’ triumph over portal users. Tools are analytic-centric rather than reporting-centric. Business discovery supersedes information delivery. Semantic layer-free data exploration and rapid prototyping are where the action is.”