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The Center of Excellence in the Era of Self-Service Analytics

Once, the responsibility of the IT department was to provide business analysis tools, models, and reports. But this was back when mainframe computers and 2-pound cell phones were cutting-edge technology.

Nowadays, the analytics pendulum has swung toward business self-service capabilities. This means it takes less time to deploy analytics tools, put them in the hands of businesspeople, and start getting visibility into business performance. However, there are obstacles: siloed data, high cost perceptions, security concerns, and more. 

In this era, the role of an analytics center of excellence (COE) can provide considerable value to an organization, but it may require rethinking and reorganizing the business structure and operating principles.

In a recent Forrester research study, researchers explained the need for a new balance between IT and business. In the report, "Balance Self-Service Analytics and Governance to Achieve Business Success," Forrester points out that powerful analytics tools have become visual, accessible, and user friendly, forcing a change in the traditional IT role as technology provider. Additionally, the role of the analytics COE, also known as the business intelligence competency center, needs to adapt to this new balance to remain valuable to the organization.

It's important that we clearly define these roles. Self-service analytics and data discovery have been embraced by businesspeople in all functions as a way of quickly and effectively driving greater insight into business performance. Cloud or hybrid cloud deployment makes it easier to start small and scale, and increases flexibility. Businesspeople no longer need to rely on IT to provide analytic capability.

This new era of self-service, however, has risks, mainly in the lack of governance. Part of this risk is the unintended creation of a new set of analytic silos where individuals cannot align or communicate effectively with each other and across departments. The lack of data models and standards, no oversight of data quality, and no management of data security, legal=or regulatory compliance can reduce the effectiveness of data-driven decisions, inhibit economies of scale, and result in higher overall costs of operation. In the Forrester study, data security and privacy, data quality, and user training ranked at the top of the list of concerns.

Enabling self-service analytics without providing for compliance and cross-functional alignment is risky. Organizations must minimize the threats of operational drag and myopic perspective caused by self-service silos. What's needed is a rebalancing of the traditional relationship between business and IT where, as Forrester says, "…IT mostly governs and curates data while business users are empowered to drive insights mostly on their own without delay.

This balanced approach also requires new thinking about the role of the analytics COE. As an enterprise resource, the center can be "a team of people established to promote collaboration and the application of standards and best practices across the organization," according to Forrester.

But as organizations become more data-led, we must recognize that business is more likely to drive the acquisition of analytics tools and put them into use quickly, while IT has a more critical role in governance to reduce risk and inefficiency by defining standards for data models, quality, and compliance. A best-practice COE can empower the business with speed and self-sufficiency while providing necessary, effective controls.

Here are some examples of how the COE can adapt to the new world:

  • Companies that have an existing COE can review their framework to determine how to recast the COE charter in the self-service era. Business will select and acquire analytics tools while IT leaders ensure that business users have the tools they need for self-service analytics and freeform discovery while remaining monitored and controlled," as Forrester puts it, to allow data-driven insight and compliance.
  • Businesspeople are creating their own visual and predictive analyses without waiting for IT to build reports or models for them. Here the opportunity is to create an internal community where best-practice visualizations and models are shared among users.
  • The learning curve for self-service solutions is dramatically reduced, but there may still be a place for training on startup and best practices.
  • The concept of the service-level agreement takes on new meaning in the cloud era. Uptime becomes the responsibility of the platform-as-a-service or software-as-a-service provider, whether public or private cloud. IT's role in providing data quality and security becomes more critical.

While the analytics COE needs to adapt to the cloud and self-service, it can still provide structure, collaboration, and value.

For more information about Oracle's COE, review our white paper, From Specification to Exploration: Data Discovery and the Transformation of Business Analysis.

You should also check out Oracle's webcast with Forrester Research VP and Principal Analyst Boris Evelson and Oracle Analytics Senior Group Director Jose Villacis discussing the report.

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