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Using Dashboard-Based Business Intelligence Systems
An approach to improving business performance

by Nancy Dodd, Academic Editor, Pepperdine UniversityFriday, September 14, 2007
Written by Owen P. Hall, Jr, PhD Generously submitted by Pepperdine University

User-friendly business intelligence systems help increase organizational participation as well as improve bottom line performance.

Business Intelligence Systems Defined

Business intelligence systems (BIS) are interactive computer-based structures and subsystems intended to help decision makers use communication technologies, data, documents, knowledge, and analytical models to identify and solve problems. The new generation of BIS offers the potential for significantly improving operational and strategic performance for organizations of various sizes and types.

During the 1990s, most large organizations engaged in enterprise data warehousing projects. The scope of these efforts ranged from combining multiple legacy systems to developing user interface tools for analysis and reporting. The data warehouse is the underlying structure that is used to generate a variety of reports and analyses. In the past, business intelligence amounted to a set of weekly or monthly reports that tended to be unconnected.

Two salient features of the new generation of BIS are integration and visualization. Typically, this information flow is presented to the manager via a graphics display called a Dashboard. A BIS Dashboard serves the same function as a car’s dashboard. Specifically, it reports key organizational performance data and options on a near real time and integrated basis. Some BIS industry pundits claim that Dashboards are simply “eye candy” for executive managers. This perspective suggests that these systems are merely a new fad being promoted by consultants and vendors. While these claims may have some merit, Dashboard based business intelligence systems do provide managers with access to powerful analytical systems and tools in a user friendly environment. Furthermore, they help support organization-wide analysis and integrated decision making.[1]

The first executive dashboards actually went into organizations around 1985. We called them executive information systems at the time. And they had limited success because they were executive systems -- the chairman of Merck would have it on his desk -- but then that was it. What we're seeing today are management dashboards, which have been pushed down through the organization, providing relevant information to a particular manager. At Southwest Airlines, they call them cockpits, and they're specialized, so that the guy in charge of putting peanuts on airplanes gets a different view than the guy who's in charge of purchasing jet fuel. But they all see what planes are flying where.

~ John Kopcke
Hyperion Solutions Corp.*

Typically, BIS can be categorized into two major types: model-driven and data-driven. Model-driven systems tend to utilize analytical constructs such as forecasting, optimization algorithms, simulations, decision trees, and rules engines. Data-driven systems deal with data warehouses, databases, and online analytical processing (OLAP) technology. A data warehouse is a database that is constructed to support the decision making process across an organization. There may be several databases or data marts that make up the data warehouse. OLAP is increasingly utilized by managers to help process and evaluate large-scale data warehouses and data marts.

In five years, 100 million people will be using information-visualization tools on a near daily basis. And products that have visualization as one of their top three features will earn $1 billion per year.

~ Ramana Rao, founder and chief technology officer,
Inxight Software Inc.*

Today, there is an ongoing requirement for more precise decision making because of increased global competition. Generally speaking, decision making should be based on an evaluation of current trends, historical performance metrics, and forecast planning. New and improved BIS continue to emerge to help meet these ongoing requirements.[2]

Within three years, users will begin demanding near-real-time analysis relating to their business -- in the same fashion as they monitor stock quotes online today. Monthly and even daily reports won't be good enough. Business intelligence will be more focused on vertical industries and feature more predictive modeling instead of ad hoc queries.

~ Thomas Chesbrough, executive vice president

BIS Developments

BIS vendors are offering a variety of new systems that provide necessary links and end user interface for managers to access and receive selective information such as competitor behavior, industry trends and current decision options. To increase organizational acceptance and use, these new systems feature distributed decision making, which helps leverage organizational visibility. Specific attention is being given to the user interface as highlighted by the following list of standard end user features:[3]

  • Filter, sort and analyze data.
  • Formulate ad hoc, predefined reports and templates.
  • Provide drag and drop capabilities.
  • Produce drillable charts and graphs.
  • Support multi-languages.
  • Generate alternative scenarios.


There are a number of approaches for linking decision making to organizational performance. For example, in the manufacturing industry, decisions may focus on resource allocation optimization and waste reduction, as supported by the Lean Manufacturing Methodology. From a decision maker’s perspective, the new BIS visualization tools such as Dashboards and Scorecards provide a useful way to view data and information. Outcomes displayed include single metrics, graphical trend analysis, capacity gauges, geographical maps, percentage share, stoplights, and variance comparisons. A “Dashboard” type user interface design allows presentation of complex relationships and performance metrics in a format that is easily understandable and digestible by time pressured managers. More specifically, such interface designs significantly shorten the learning curve and thus increase the likelihood of effective utilization. Figure 1 presents an example of a dashboard design.

Figure 1: Example of a Dashboard

Example of Digital Dashboard

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