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Business Intelligence: Five Tips for Managing Data

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Tony Kontzer
Tony Kontzer
May 6, 2011

The way Jeanne Harris sees it, most companies haven’t put
enough thought into how they extract insight from the increasingly
massive pools of data they’re collecting. Harris ought to know. As
executive research fellow and director of research for Accenture’s
Institute for High Performance, Harris is co-author of two
well-regarded books on data analytics: Competing on Analytics: The New
Science of Winning
(Harvard Business School Press, 2007), and Analytics
at Work: Smarter Decisions, Better Results
(Harvard Business School
Press, 2010).

One of the consistent messages of the books is that organizations have
to think systemically about data–meaning that merely establishing a
data warehouse isn’t enough.

“It’s just a place to store stuff until you need it. It doesn’t create
value for anyone; it creates the potential for value,” says Harris.
“Many companies dump data in a data warehouse. The problem with that
is, now you don’t have a data warehouse; you have a data dump.”

Instead, companies need to work toward a data strategy that combines a
data warehouse with the ability to synthesize and organize data, get
that data into the applications where it’s needed, and apply data
visualization capabilities. For more on this topic, read the article "Business Intelligence: Meet the Data Wranglers."

To help organizations on this path, Harris and
co-author Thomas Davenport, a professor of IT and management at Babson
College, recommend a five-step model they’ve created that is
represented by the acronym DELTA. Addressing these areas, says Harris,
will give an organization a good start toward an effective data
strategy:

D: Data–Every good data strategy starts with clean, consistent data
culled from across the organization. Ask yourself: What data is most
important, and what do I have available?

E: Enterprisewide perspective–Look at your IT infrastructures and
assess how you either enable or inhibit efforts to achieve a single
360-degree view of the customer.

L: Leadership–Companies need analytical leaders who can set an example
in terms of making good decisions with data. Harris points to a quote
attributed to legendary statistician W. Edwards Deming: “In God we
trust; all others better bring data.”

T: Target–It’s critical to identify the areas of the business where
analytical decision making will have the biggest impact, and focus on
those. “Pick your spots,” says Harris. “You can’t apply analytics to
everything.”

A: Analytical people–Analytical skills are needed at every stage of an
organization’s data-analysis environment, as evidenced by the huge
demand for analytical and statistical skills on the job-listing site
Monster.com.

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