This article will focus on collecting and defining metrics and key performance indicators for executive and operational dashboards. While the techniques discussed here can be used across many different business intelligence requirements gathering efforts, the focus will be collecting and organizing business data into a format for effective dashboard design.
With the explosion of dashboard tools and technologies in the business intelligence market, many people have different understandings of what a dashboard, metric, and key performance indicator (KPI) consist of. In an effort to create a common vocabulary for the scope of this article, we will define a set of terms that will form the basis of our discussion. While the definitions below might seem onerous and require a second pass to fully understand them, once you have grasped the concepts you will have a powerful set of tools for creating dashboards with effective and meaningful metrics and KPIs.
Metrics & Key Performance Indicators
Metrics and KPIs are the building blocks of many dashboard visualizations; as they are the most effective means of alerting users as to where they are in relationship to their objectives. The definitions below form the basic building blocks for dashboard information design and they build upon themselves so it is important that you fully understand each definition and the concepts discussed before moving on to the next definition.
When we use the term metric we are referring to a direct numerical measure that represents a piece of business data in the relationship of one or more dimensions. An example would be: “gross sales by week.” In this case, the measure would be dollars (gross sales) and the dimension would be time (week.) For a given measure, you may also want to see the values across different hierarchies within a dimension. For instance, seeing gross sales by day, week, or month would show you the measure dollars (gross sales) by different hierarchies (day, week, and month) within the time dimension. Making the association of a measure with a specific hierarchal level within a dimension refers to the overall grain of the metric.
Looking at a measure across more than one dimension such as gross sales by territory and time is called multi-dimensional analysis. Most dashboards will only leverage multi-dimensional analysis in a limited and static way versus some of the more dynamic “slice-and-dice” tools that exist in the BI market. This is important to note, because if in your requirements gathering process you uncover a significant need for this type of analysis, you may consider supplementing your dashboards with some type of multi-dimensional analysis tool.
Key Performance Indicators (KPI)
A KPI is simply a metric that is tied to a target. Most often a KPI represents how far a metric is above or below a pre-determined target. KPI’s usually are shown as a ratio of actual to target and are designed to instantly let a business user know if they are on or off their plan without the end user having to consciously focus on the metrics being represented. For instance, we might decide that in order to hit our quarterly sales target we need to be selling $10,000 of widgets per week. The metric would be widget sales per week; the target would be $10,000. If we used a percentage gauge visualization to represent this KPI and we had sold $8,000 in widgets by Wednesday, the user would instantly see that they were at 80% of their goal. When selecting targets for your KPI’s you need to remember that a target will have to exist for every grain you want to view within a metric. Having a dashboard that displays a KPI for gross sales by day, week, and month will require that you have identified targets for each of these associated grains.
Scorecards, Dashboards, and Reports
The difference between a scorecard, dashboard, and report can be one of fine distinctions. Each of these tools can combine elements of the other, but at a high level they all target distinct and separate levels of the business decision making process.
Starting at the highest, most strategic level of the business decision making spectrum, we have scorecards. Scorecards are primarily used to help align operational execution with business strategy. The goal of a scorecard is to keep the business focused on a common strategic plan by monitoring real world execution and mapping the results of that execution back to a specific strategy. The primary measurement used in a scorecard is the key performance indicator. These key performance indicators are often a composite of several metrics or other KPIs that measure the organizations ability to execute a strategic objective. An example of a scorecard KPI would be an indicator named “Profitable Sales Growth” that combines several weighted measures such as: new customer acquisition, sales volume, and gross profitability into one final score.
A dashboard falls one level down in the business decision making process from a scorecard; as it is less focused on a strategic objective and more tied to specific operational goals. An operational goal may directly contribute to one or more higher level strategic objectives. Within a dashboard, execution of the operational goal itself becomes the focus, not the higher level strategy. The purpose of a dashboard is to provide the user with actionable business information in a format that is both intuitive and insightful. Dashboards leverage operational data primarily in the form of metrics and KPIs.
Probably the most prevalent BI tool seen in business today is the traditional report. Reports can be very simple and static in nature, such as a list of sales transaction for a given time period, to more sophisticated cross-tab reports with nested grouping, rolling summaries, and dynamic drill-through or linking. Reports are best used when the user needs to look at raw data in an easy to read format. When combined with scorecards and dashboards, reports offer a tremendous way to allow users to analyze the specific data underlying their metrics and key performance indicators.
Gathering KPI and Metric Requirements for a Dashboard
Traditional BI projects will often use a bottom-up approach in determining requirements, where the focus is on the domain of data and the relationships that exist within that data. When collecting metrics and KPIs for your dashboard project you will want to take a top-down approach. A top-down approach starts with the business decisions that need to be made first and then works its way down into the data needed to support those decisions. In order to take a top down approach you MUST involve the actual business users who will be utilizing these dashboards, as these are the only people who can determine the relevancy of specific business data to their decision making process.
When interviewing business users or stakeholders, the goal is to uncover the metrics and KPI’s that lead the user to a specific decision or action. Sometimes users will have a very detailed understanding of what data is important to them, and sometimes they will only have a high level set of goals. By following the practices outlined below, you will be able to distill the information provided to you by the user into a specific set of KPIs and metrics for your dashboards.