Best practices for business-driven BI and analytics

New, easy-to-use BI tools are allowing business users to bypass IT, but there are pitfalls.

By David Stodder, TDWI

One of the chief goals of nearly all organizations today is to enable data-driven decisions and actions. Firms want to achieve the “right data, for the right user, at the right time” objective that has characterized business intelligence (BI) and data warehousing since their beginnings.

They also want to enable users to push beyond canned reports and limited spreadsheet views to take advantage of more advanced data visualization and analytics; then, users can accelerate exploration and discovery of valuable insights and apply them for business advantage.

It is becoming more important to avoid 'technology for technology's sake' and to define the benefits of technology deployment in terms of business advantages ...

Only in recent years have BI tools, as well as those in the newer categories of data discovery and software as a service (SaaS), become easy enough for business users to deploy and implement without considerable handholding by IT developers and data analysts. Analytic database platforms that are specifically designed to support data discovery and advanced analytics are also now easier to deploy, load with data, and use. Offering flexible data visualization, dashboard-based information views, analytics, and more, the latest BI tools, analytic platforms, and SaaS offerings are spurring users in business functions and lines of business to venture beyond the boundaries of IT management and obtain technologies themselves.

This trend toward “business-driven,” rather than IT-driven BI and analytics, is riding the momentum created by technology change and strong interest, if not CEO-driven mandates, to infuse data into all decisions and actions. This TDWI Best Practices Report explores key drivers behind this trend and examines how organizations are both taking advantage of it and realigning business-IT collaboration to avoid pitfalls. Organizations need this collaboration to allocate resources effectively and adhere to data governance policies.

Our research finds that, overall, IT still plays a major, if not dominant, role in BI and analytics implementations. As they have historically, IT and corporate-level leadership still head up sponsorship of most BI and analytics projects. However, it is becoming more important to avoid “technology for technology’s sake” and to define the benefits of technology deployment in terms of business advantages, such as smarter financial management, more effective marketing, or more efficient operational processes. Business-side leadership and IT leadership need to align business and technology objectives so that projects can succeed in satisfying users.

One way that some organizations have effectively brought together business and IT leadership is by establishing a BI and analytics center of excellence (CoE) or competency center. Such an institution can bring the sides together to share best practices, identify training needs, tighten alignment between BI and analytics and business processes, manage data governance, and more. Currently, however, our research finds that business-side participation in CoEs and competency centers is low.

If business-driven BI and analytics are to be sustained with less direct IT involvement, business-side leadership must step up to ensure that chaos does not reign and to provide direction for the adoption of new technologies and practices for the betterment of the enterprise as a whole. Otherwise, organizations could invite data confusion and unnecessarily waste precious budget and resources.

David Stodder

DAVID STODDER is director of TDWI Research for business intelligence. He focuses on providing research-based insight and best practices for organizations implementing BI, analytics, performance management, data discovery, data visualization, and related technologies and methods. He is the author of TDWI Best Practices Reports and Checklist Reports on data discovery, data visualization, customer analytics in the age of social media, BI/DW agility, mobile BI, and information management. He has chaired TDWI conferences on BI agility and big data analytics. Stodder has provided thought leadership on BI, information management, and IT management for over two decades. He has served as vice president and research director with Ventana Research, and he was the founding chief editor of Intelligent Enterprise, where he served as editorial director for nine years.

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