Cloud adoption of BI tools lagging
By 2014, fewer than 30 percent of Business Intelligence (BI) initiatives will align analytics completely with enterprise business drivers, despite alignment being the foremost BI challenge, according to Gartner.
Cloud offerings will account for just three percent of BI revenue by 2013, despite every major BI platform vendor presenting one. In addition, Gartner analysts say that by 2013, BI initiatives will be based on an organizational model that strikes a balance between centralized and decentralized delivery.
“The immediate future of the BI landscape is one of disconnect between marketing hype about pressing challenges on the one hand and reality on the other,” said Andreas Bitterer, Research Vice President at Gartner. ”
He added that the need for analytics does not match most organizations’ skill requirements; vendor hype for cloud-based BI is not reflected in revenue and customer adoption, and there is a struggle between centralized and decentralized organizational models of BI delivery.
Gartner’s three central predictions for the BI market are:
By 2013, every major BI platform vendor will present a cloud offering, but these will account for just 3 per cent of total BI revenue.
Current adoption of cloud BI by user organizations lags far behind the expectations of vendors, which are busy creating and marketing new off-premises solutions. Organizations that have already invested in on-premises BI infrastructure are hesitating to identify a segment of their BI initiative for which data can be moved into the cloud and reports and dashboards received from a cloud provider. However, companies that have subscribed to a specific cloud application, such as customer relationship management, payroll or help desk service, are more inclined to use BI functionality delivered by their cloud provider, as they see it essentially as an extension of the cloud application.
By 2013, BI initiatives will be based on an organizational model that strikes a balance between centralized and decentralized delivery.
Many BI programs have departmental roots with analytical resources embedded in the business. This model has worked well in serving departmental needs, but it lacks consistency in terms of data definitions and measures across an entire organization. Often, the IT organization has solved this inconsistency problem by establishing a central team to deliver BI. However, such an overly centralized model lacks the agility and familiarity of the decentralized model. A hybrid delivery model enables greater consistency and economies of scale, more autonomy and faster turnaround times.
By 2014, fewer than 30 percent of BI initiatives will align analytic metrics completely with enterprise business drivers.
The foremost BI challenge is to align initiatives with corporate strategy and objectives, but less than one-third of organizations have a documented analytics, BI or performance management strategy. Organizations often develop and deploy hindsight-oriented reports and/or query applications focusing on metrics that users may find interesting, but they don’t represent the operational or strategic controls used to facilitate business performance.
With the increasing consumerization of BI, for example mobile BI, the growing volume and variety of available data, and the soaring speed of business, it can be challenging to establish appropriate guard rails for analytic implementations to ensure that the right data is presented to the right people and processes at the right time. These user/data growth factors also challenge the cohesion of metrics frameworks among lines of business, resulting in business functions that operate in conflict with one another; for example, one group may focus on profitability, while another concentrates on market share.
“Throughout 2012 and beyond, BI will remain subject to non technical challenges,” said Bitterer. “IT leaders should concentrate not only on the technological aspects of BI, but also on the severe lack of analytical skills. Second, they should use a ‘think global, act local’ approach in their BI programs to provide the right level of autonomy and agility to avoid the bottlenecks that overly centralized BI teams create.”
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