Four Keys to Achieving Value Faster from BI and Analytics
Although technology advances are making a difference, organizations also need to improve practices and leadership to realize value from BI and analytics sooner.
- By David Stodder
- August 21, 2017
To be a smarter organization, knowledge workers at all levels need to be able to make data-informed decisions. That is, they need to formulate and answer business questions easily using relevant and accurate data, reports, visualizations, and analytics.
Over the years, our research has found that users have been dissatisfied with the time between identifying a need for business intelligence (BI) and analytics to receiving the appropriate application, report, or dashboard. Although technology advances are increasing self-service and driving democratization of BI and analytics, organizations still need to improve practices and leadership to realize value from BI and analytics at the pace necessary to become a data-driven organization.
TDWI has published a new Best Practices Report: Accelerating the Path to Value with Business Intelligence and Analytics, which addresses how organizations can move faster toward having data and analytics play a bigger role in decision making.
The new report examines results from an extensive TDWI survey of user organizations. It also includes insights from interviews with leaders from a variety of organizations about how they are overcoming barriers to achieve goals.
Four Recommendations from the Report
#1: Pay attention to project definition and scoping
Research survey participants cited this issue as the most common reason why they are not gaining anticipated value from BI and analytics projects and why return on investment (ROI) is falling short. One way that organizations can improve in this area is to ensure that business stakeholders, who usually play a role in initially defining questions to be answered and providing funding, stay involved as projects move forward.
One research participant told us that including business unit representatives along with technology and architecture team members is leading to "better agreement with the business units in the priorities....project funding has been better forecasted."
#2: Apply self-service to help with skill shortages
Having too few skilled personnel is a major reason why projects take too long. This deficiency becomes more glaring as organizations aim for data-driven operational decision making -- this requires continuous work on BI and analytics projects, not just occasional, episodic attention. Old and incomplete data or outmoded reporting can lead to poor decisions that negatively impact key areas such as customer and business partner satisfaction.
Self-service BI, analytics, and data preparation are maturing, enabling users to do more on their own and be less dependent on skilled IT personnel (or lack thereof). However, our research finds that without proper management and governance, self-service can lead to frustration.
Organizations should update governance policies to cover self-service environments and communicate rules and policies clearly. Governance should be part of a broader effort to nurture a culture that supports rising BI and analytics maturity through mentoring, stewardship, collaboration, and use of metrics to monitor milestones.
#3: Modernize data quality and integration management
Data-driven organizations depend on a steady flow of good data from multiple sources. Insufficient data quality, consistency, and completeness, as well as poor knowledge about the data's lineage, can slow down the realization of value. Organizations should evaluate newer technologies that could address data issues faster and more completely than older systems.
One innovator we profiled, St. Mary's Bank, is implementing BI dashboards to improve data quality; the dashboards enable business department managers to see what data they need to clean up as a precursor to doing true BI for managing sales goals and other business objectives. Additionally, our research found growing interest in new technologies for metadata management, data cataloging, semantic integration, and use of search engines to find and access relevant data faster.
#4: Take steps to reduce time to value
One of the chief ways to increase the impact of BI and analytics is by ensuring that capabilities are in users' hands at the right time to support decision making. Too often, organizations must wait so long for applications that they become less valuable -- the moment when they were most needed has passed.
TDWI research finds that there is room for improvement. Organizations should examine how to streamline development, align projects more closely with requirements (even as they change), and create a strategy to remove obstacles to completion and delivery. However, the urgency to reduce time to value should not displace efforts to provide users with more accurate, higher-quality data, which the majority of research participants indicated was a more important goal.
Treating BI and Analytics as Business Initiatives
Although not overwhelmingly common, our research finds that more than a few organizations are developing key performance indicators (KPIs) to monitor progress toward value with BI and analytics. One research participant said, "We use KPIs to measure before/after of our BI system implementations. We also make evidence-based decisions for any project or initiative that requires approval. BI is both a required cost of doing business and a value-driving tool."
To become a smarter, data-driven organization that can respond to shifting business conditions and stay on top of risk and regulations, firms need to view BI and analytics as more than just the latest technology trend. BI and analytics are critical ingredients of competitive organizations.
As self-service BI and analytics solutions spread across enterprises, organizations need to manage users' progress and commit resources to helping overcome their obstacles. Otherwise, frustration will grow -- not just with the lack of success with the technology, but more broadly with the organization's inability to support users who are trying to effect positive business change.
Read more recommendations in the full TDWI Best Practices Report: Accelerating the Path to Value with Business Intelligence and Analytics.
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 on mobile BI and customer analytics in the age of social media, as well as TDWI Checklist Reports on data discovery 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.