BI dashboards usually contain data summarized to a high level to enable users to quickly understand the larger trends affecting the organization, with the ability to "drill down" to greater levels of detail as required. It's important that the dashboard display information in a clear, concise, and intuitive manner and that the information display can be customized to a user's particular requirements.
BI dashboards are typically used for displaying metrics defined by the organization, such as products sold by region, defects per thousand shipped, or student grades by faculty. Typically, these metrics are expressed as key performance indicators (KPIs), and a typical dashboard brings several KPIs together across aspects of the business.
BI dashboards are typically used for displaying metrics defined by the organization, such as products sold by region, defects per thousand shipped, or student grades by faculty. Typically, these metrics are expressed as key performance indicators (KPIs), and a typical dashboard brings several KPIs together across aspects of the business.
Business Intelligence Systems
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.
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. 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.
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.
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. Business intelligence will be more focused on vertical industries and feature more predictive modeling instead of ad hoc queries.
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:
* 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.
Dashboards
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 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
Scorecards
A “scorecard” is a custom user interface that helps optimize an organization's performance by linking inputs and outputs both internally and externally. The scorecard must link into the organization’s vision. Over the years the differences between dashboards and scorecards will become increasing blurred as these interface structures become fully integrated. Figure 2 illustrates the current adoption of BIS throughout the organization.
Figure 2: BIS Adoptions by Management Area
Figure below illustrates the basic structure of how the Dashboard fits into the decision making process. The Dashboard integrates the data warehouses and analytical models directly into the decision making process. This is a continuous process based on ongoing environmental scanning and feedback from current performance metrics, e.g., inventory turns. Behind the graphical interface lie the supportive analytical systems such as statistical analysis for data validation, combined forecasting algorithms, and expert systems for decision options analysis and recommendations.
Figure 3: The Dashboard Interface Structure
ApplicationsHighlighted below are some specific examples in which dashboards have been successfully applied to improve organizational performance.
* Hospital Bed Management – The current crisis in the nation’s health care system has triggered an intensified focus on increasing productivity and reducing costs. Two primary goals of a hospital bed management dashboard system are to optimize bed resources and reduce emergency department wait times. The system consists of a number of modules, which include both bed placement and data mining models. Specific displays include real time bed availability forecasts and capacity alerts. In many respects this BI system is like an air traffic controller for hospital beds. For example, it both schedules patient bed assignments as well as facilitates the transfer of patients from other departments.
* Conflict of Interest Assessment – Prior to taking on a new client, many law firms routinely check throughout the organization to determine the potential for a conflict of interest. Historically, this has required many man hours of effort with the possibility of errors that could significantly affect operating performance. This dashboard based system, which connects attorneys and staff, automatically checks organizational records and results in reduced operating expenses and improved worker productivity. Specifically, the system has reduced the time to conduct conflict checks by 75%.
* Product Development Management – Historically, measuring the performance of ongoing product/service development (PD) has been a hit or miss proposition. This inconsistency has often led to significant overruns and in some cases, total failure. Estimating product development cycle time is key to any effective assessment process. A typical PD dashboard system is designed to report results to date as well as to indicate the potential for continuing success/failure. Project compliance is one key dashboard PD metric. A gauge reports the fraction of new product launches that occurred on schedule and budget. Another standard dashboard metric is the fraction of products/services that has received a favorable trade journal review. Additionally, the dashboard should have the capability of identifying new product/service opportunities.
* Financial Management – Many financial and investment organizations have concluded that it is essential to have real time updates of key performance metrics such as revenues and profits in order to remain competitive in today’s marketplace. Traditionally, many organizations have relied on quarterly reports to support the decision making process, a practice which has often led to uneven performance. A financial dashboard provides an integrated and real time overview of performance that can be directly correlated to the business model. Specific metrics include balance sheets, income statements and competitor performance. Additionally, the dashboard can display alerts identifying negative trends that require immediate attention.
Building the Business Intelligence Strategy
Developing an effective business intelligence strategy is predicated on three key drivers: perceived value, organizational utilization and a cost effective solution. The development of a BIS strategy should be tied to specific organizational performance goals and operational objectives. The latter include increasing customer retention and reducing turnover of key personnel. The proposed solution must be adaptable, scaleable and maintainable. Often a phased schedule in implementing the BIS is best since it tends to minimize risk as well as increase organizational acceptance. Such an approach allows elements of the system to be checked out prior to full system deployment.
Major steps involved in developing an effective BIS strategy:
* Establish BIS objectives. (Specifically, what do you want the system to do?)
* Evaluate the current in-house support capability, including the present system’s architecture
* Perform a gap analysis on existing data systems, including response time
* Identify alternative technical solutions
* Formulate an implementation timeline
* Conduct organizational “Town Hall” meetings to solicit ideas and to enhance the cultural climate for change
* Determine the need for outsourcing support
BIS Vendors
* Cognos Inc.
* Hyperion
* Information Builders Inc
* Microsoft
* Microstrategy
* SAS
Good Dashboard Implemenatations
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