|Business intelligence (BI) capabilities that provide better analysis of and insights into operations will be essential if organizations are to achieve high performance, according to a recent Accenture study.
Shari Rogalski, a partner in Accenture's North American Business Intelligence practice, reports the study found that nine in 10 senior executives at Fortune 1000 companies place strong analytical and business intelligence capabilities at the top of their list in preparing them for their biggest challenge ahead.
The companies best prepared to thrive in an uncertain economic and political climate will be those that take advantage of their capabilities to collect and analyze internal and external data to improve their decision-making, financial management and customer service.
The survey, conducted by Wirthlin Worldwide on behalf of Accenture, surveyed 150 executives representing major US companies in the services, manufacturing and high tech industries.
Business intelligence is hardly a new concept. After all, companies have been capturing data for years. High performing companies are now focusing on how to extract and analyze data that can generate insight and value for the organization. This includes support of business processes and decision-making at the strategic, tactical and operational levels. Today, this data is acknowledged as a corporate asset, with C-level executives now viewing it from a business rather than technology perspective.
Through the use of data warehouses as the fundamental enabler, and the business analytics that leverage it, business intelligence offers a strategic, competitive advantage that examines trends and histories in order to predict the future as well as models scenarios and creates benchmarks to make the future.
Of course, not every organization and executive recognizes and chooses to invest in this. According to David Loshin in his book Business Intelligence: The Savvy Manager's Guide, "Instead of treating data as the raw material that fuels a 19th century-style assembly line masquerading as 21st century information processing, we must learn to think about a company's data as a corporation information asset, one that can be manipulated in different ways to corporate benefit."
Specifically, business intelligence helps organizations improve performance by:
- providing insights that can help pinpoint new revenue-generating opportunities.
- improving operational efficiencies and visibility across the organization.
- optimizing the return on such existing business and IT investments as customer relationship management and enterprise resource planning.
However, as Shari Rogalski notes, it is not simply a matter of accumulating mountains of data. Organizations today, in fact, are swamped with data, spending significant dollars on data management and security in order to comply with recent legislation like Sarbanes-Oxley, HIPAA and Basel II. Rather, the goal is the strategic collection and analysis of data that can provide an organization with insight.
It all begins with placing a premium on data quality. Not having accurate, complete or properly defined data will lead to a lack of data needed to generate insight or, even worse, result in the organization basing its insight on flawed information. Most business intelligence failures, in fact, are a result of companies focusing on identifying, extracting and loading data, rather than an issue of data quality. New regulations and corporate governance have increased the demand and attention for data quality attention. Unfortunately, too many organizations continue to take data quality for granted, as a required manual effort, or as something that only needs to be addressed when a specific problem or question surfaces.
With larger organizations, data may exist in hundreds of different platforms, applications and databases scattered across multiple business lines, functions and geographies. This can result in many 'siloed' business-unit or departmental-specific data interfaces that have been spun like spider webs throughout the organization, lacking any cohesive strategy for integration. To alleviate this, the organization needs to begin to standardize and optimize processes, methodologies, tools and capabilities, preferably from an enterprise perspective. Data can then be accessed and analyzed to derive insight useful for business decisions and, hopefully, a competitive advantage.
Today, in the business intelligence space, the talk no longer centers simply around data warehousing and reporting, but around insight and analytics (i.e., translating data into information and actually using it to make decisions and impact strategy), data governance (i.e., determining who owns the data and then defining data definitions, business rules, and calculations) and competency centers (i.e., pooling internal or external resources, physically or virtually, to focus on data and business intelligence activities).
Outsourcing and offshoring business intelligence capability is also floating to the top of the discussion topics. Data mapping is now frequently offshored, and the data management function is a likely candidate for outsourcing. A key question being debated today is whether or not the "thinking" and strategizing, the real value in business intelligence, can also be outsourced.
If applied holistically across the organization, business intelligence can positively influence decisions that affect every functional area from marketing to human resources, from supply chain to finance. Instead of being viewed as a technical solution, business intelligence must reinforce an organization's strategic imperatives and leverage existing systems and operations. It must include processes to guide the effective use of information and analysis and address the roles and responsibilities of those charged with making analysis-based decisions.
(extract of an article "Top Companies View Business Intelligence (BI) as Key to Future Growth" by Shari Rogalski, DM Direct Special Report, June 21, 2005. Copyright 2005 DM Review and SourceMedia, Inc.)