Putting Data to Work: Winning Approaches to BI, Analytics and Reporting

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Sustainable success for BI and analytics implementations, Gupta said,“requires strict adherence to security, access, and quality rules as well as training and broad communication across a wide spectrum of functions and hierarchies that touch the data in various stages of ingest through insight.”

Change Your Thinking

What types of skills are required for the emerging data-savvy organization? Experts concur that the growing ease of use with tools and platforms means that additional training requirements may be minimal. Rather, new ways of thinking are more important.

With a shift of this magnitude, change management skills are the most needed, said Greg Simpson, chief technology officer of Synchrony Financial. “It takes conscious effort and communication to bring the organization along. The good news is that the organization is hungry for insight. The IT teams and the specialized analytics functions need to work together to move the culture forward, and demystify analytics.”

“Start with architecture, said Don DeLoach, CEO and president of Infobright. “Separating the creation of data from the consumption of data enables you to leverage the utility value of that data. This way, the underlying data assets can be exposed for greatest leverage. Pre-processing the data makes sense to filter out inconsequential data from the master store.”

In addition, the overall design should contemplate the fundamental organizational objectives, DeLoach continued. “Keeping everything is a bad idea. First, while the price of computing and storage continues to drop, in most cases the data is growing at a faster rate than the corresponding costs of computational accommodation are  dropping. That  said, there is certainly a role for the visionary who understands the various component technologies and that the volume of data kept will likely grow, but can craft the architecture with a deliberate eye on the value of the data to the organization.”

As BI and analytics proliferate, training needs to be rethought, said Patel. Training on specific tools or capabilities is necessary, but so is training on how policies related to managing data, promoting insights, and understanding how BI and analytics will fit into business processes and operations, he noted.

What is needed now is not simply the right skills but analytics leadership qualities as well, Villacís agreed. Some of these qualities, he said, include the practice of asking more thought-provoking questions, considering more data than peers, running many experiments with the data, making more data available to the front lines of  users, having a plan for building analytics competencies, and a commitment to treating data as an asset.

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