Cars and Computers
Most of us look at a dashboard in our everyday lives, in the car. When looked at closely, the car dashboard provides a perfect model for a BI dashboard. Some information is updated in real time, for example, traveling speed and the engine speed (RPMs). Some information provides warnings, such as low fluids or worn brake pads. Some reflects the current state of something, like drive or park. Taken as a whole, the dashboard provides a quick and easily consumed overview of the state of a car. Some cars provide an additional level of detail, for example, a mileage range for the car based on the amount of fuel remaining. Behind this is a real-time display of MPG and an average MPG, which allows the user to drill down to gain more insight into the original piece of information, the range. By drilling down and looking at the data behind a number, a user can gain additional insight and answers to questions. A BI dashboard acts the same way: it provides a quick and easy way for the user to see the state of “the business” and may provide the ability to drill into the information to provide detail. To be successful, the dashboard must present the information in a straightforward fashion in the form of charts, traffic signals, gauges, dials and, in some situations, spreadsheets.
The BI dashboard converts numerical information to charts and gauges, or color-coded graphics, which can be efficiently perused and understood. For example, a business may have a key metric that needs to be within a range: between 1 to 10 is good, 11 to 25 is ok, and above 25 is bad. If the metrics displayed as a numerical, the range info must also be provided so the user can put the value in context. This takes up screen real estate and takes time to for the user to process the information. In contrast, a key performance indicator (KPI) in a BI dashboard for the same metric, a value of 1 to 10 is graphically displayed as a green graphic, 11 to 25 as yellow, and above 25 as red. The user does not need to know the range values; green means that value is where the business has defined it needs to be.
Key Advantages
Allowing a user to process information more efficiently is only one advantage of the BI dashboard. The benefits of these tools can have far-reaching, enterprise-wide effects. There are several reasons for investing in the design and construction of a BI dashboard. It maximizes the ROI on the BI analysis tools, it reduces decision-making time and increases business agility, helps the entire organization to focus on what the key metrics are for the business and, finally, can increase quality of information used to make decisions.
Speeding and Increasing the Efficiency of the Enterprise
In the past, the available data analysis tools required human effort to convert the analysis to charts and graphs. Once formatted, the analysis could be disseminated for decision-maker consumption. This time-consuming process restricted information flow, as it was generated quarterly, monthly or perhaps bi-weekly. Business performance measurements were therefore restricted to the same time frames. Consequently, not only were decisions made based on old data, but the reaction time of the business was measured in weeks, at best. By converting the human effort into “coded process” in the BI dashboard platform, the results of the analysis can be made available on demand, with the data being as up to date as the data sampling frequency - allowing the decision-maker to benefit from accurate on-demand data analysis.
Focus and Data Quality
A BI dashboard focuses its users on the key metrics that drive the organization forward to success. An organization can monitor the key metrics and react quickly to any changes, reducing the latency between an event and the appropriate response. The dashboard can then become the central point by which the organization or team can monitor its performance. Its creation can fundamentally change the nature of the information used to create it. If reports were created monthly, then the data was likely collected monthly. By allowing the data to be displayed on demand, users will naturally desire the data to be refreshed more frequently. This will soon reach equilibrium when the collection or sample rate reaches the optimum rate for the data source. By increasing the data-sampling rate, the result of the analysis can be improved by providing more data points for the analysis, for example, when averaging the temperature over the span of a month, versus sampling just one day.
Dashboard Design Variables
Dashboards are designed based on the requirements of the end users. The two basic forms of dashboards are business reporting and operational. End-user needs then determine how frequently the information is updated. The two modes of operation available in a BI dashboard are snapshot and real time.
Business reporting dashboards are typically used to show how the business is performing over a specific period of time. Reporting dashboard usually contain financial information, such as revenues, forecasts, projections and tracking information. They may break down sales by product or region. In some larger organizations, project rollup information is displayed for major strategic initiatives, providing senior management an enterprise-wide view.
For example, financial services companies build dashboards to display summary market information for global markets, displaying such things as GDP growth, population trends, employment demographics and economic data. These dashboards are maintained by analysts and are used by traders and other analysts within the organization. These kinds of dashboards tend to operate in a “snapshot” mode because the data does not change that frequently.
