The pros and cons of self-service analytics
July 29, 2016 -- Data analytics (Aka big data) is a powerful tool for gaining insights into customer behaviours and trends, but traditionally it’s been the domain of experts – data scientists — who are one step removed from the ‘coal face’ of marketing, customer service and delivering the optimal customer experience. That's changing with the growth of self-service analytics.
Research firm Aberdeen Group calls it the “democratisation of analytics” and says more and more data and analytical functionality is being brought from behind the IT curtain into the line of business.
To get a handle on this trend it surveyed some 560 organisations on their business intelligence deployments, categorising the extent of self-service in their use of analytics as low (<20 percent of users), moderate (21-60 percent) and high (61-100 percent).
It found most organisations, large and small, to have fewer than 20 percent of self-service users of analytics, and about one third with moderate levels of self-service. It found SMEs somewhat more likely than large enterprises to have high levels of self-service because they often lack the IT resources needed to support robust analytical deployments. “This difference also speaks to the agility of smaller organisations and their ability to empower more users without having to navigate a web of corporate bureaucracy and politics,” Aberdeen said.
Aberdeen’s research found considerable benefits from the use of self-service analytics”:
High-self service organisations achieve desirable performance across a number of metrics demonstrating successful analytical engagement and user experience;
Self-service makes analytical tools more widely available throughout the business. High-self-service organisations can offer BI access to 65 percent of employees with a need or desire for analytical capabilities, compared to 50 percent for moderate self-service organisations and just 29 percent for low self-service ;
The more mature organisations become with self-service analytics, the more users they will be able to onboard;
Self-service analytics consume fewer IT resources and reduce project completion time and residual work. The time that IT no longer has to spend on mundane information delivery and technical support can be spent on new analytical projects and spreading data-driven decision-making throughout the organisation.
That’s all good, but Aberdeen’s findings come with a warning. “Before anybody gets carried away with the numerous benefits of self-service, it is important to talk about data governance. … Too many users are running wild and engaging data as they please.”
It says data governance will become more important as more and more users become self-sufficient across all company sizes. “Organisations need to be sure that users are not seeing data that they shouldn't. Poor data governance can result in serious regulatory and security infractions.
Self-service users can also be presented too much information that inhibits actionable insight. This may sound counter to the philosophy of analytical empowerment, but users can be paralysed by a glut of impertinent information. Data governance protects users from irrelevant or inappropriate data and guides them towards the right data.”
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