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A Philosophical Blueprint for Building the Executive Dashboard, Part 2

  • September 01 2002, 1:00am EDT

Last month I began a two-part discussion on the philosophical principles that should guide the implementation of an enterprise dashboard solution. I listed eight specific ideals or concepts that provide the theoretical underpinnings for top-notch enterprise dashboard solutions. This month I'm going to talk about the final two guiding principles – empowering the knowledge- worker and deploying the right technical architecture – that should drive the conception and design of the solution.

The ninth guiding principle is the concept of empowering organizational knowledge-workers. For this discussion, I'm going to break the broad concept of knowledge into three specific categories: potential knowledge, explicit knowledge and tacit knowledge.

Potential knowledge resides in all the data that companies have. It is not transformed into knowledge until it is extracted, summarized, analyzed and understood. Top-notch dashboard solutions help organizations tap into their potential knowledge by turning raw data into information and turning that information into knowledge. This transformation enables actionable insight into business problems by providing information to knowledge-workers at all levels of an organization in the right format, at the right time and place so they can take the proper action to solve even the most challenging business problems.

Explicit knowledge is knowledge that has been recorded in a document, e-mail, on a Web site or some other location. Executive dashboards empower knowledge-workers by making explicit knowledge available to employees who need it, when they need it. With a first-class dashboard solution, the organization's explicit knowledge is searchable; and it provides version controls, workflows for approval, etc. One practical benefit of exploiting explicit knowledge is attaching that knowledge to key metrics in order to better understand the behavior of those metrics.

Tacit knowledge is the knowledge that is resident in people's heads. Tacit knowledge represents the majority of knowledge in an organization. What people know is often more valuable than what's actually written down. Helping to create a connection between people who don't know and the people who do know is critical. The best dashboard solutions enable users to share tacit knowledge with each other via collaborative capabilities. Collaboration in the dashboard environment allows people to work as richly as possible with other people across teams, departments, enterprises or geographic areas.

The final guiding principle that should drive the construction of any enterprise dashboard solution is the commitment to build the system using an architecture that is straightforward, easy to use and rapidly deployable.

The right technology architecture requires several components:

1. A data integration tool that enables the extraction, transformation and loading (ETL) of data from sources in an organization including legacy systems, ERP systems and external data sources. In addition to the ETL capability, the tool must be able to distribute transformed data to department-specific applications, end-user specific requirements, etc.

2. A relational database that enables storage and integration of "one version of the truth" historical data.

3. An online analytical processing (OLAP) engine that provides end-user analysts with fast and easy access to data for optimal analysis capability.

4. Powerful portal software to enable deployment across the organization.

5. A GUI front-end tool which, in conjunction with the OLAP database, provides a user interface that is intuitive and easy to use. The tool must include a mechanism for proactively alerting knowledge workers on the status of user-defined key performance indicators (KPIs). In addition, the front-end tool – coupled with the portal software – must provide users with the ability to take appropriate action as required by the status of KPIs.

In the vast majority of cases, this does not mean that you have to completely restructure your organization's technical architecture. Many organizations already have a business intelligence architecture that will support these requirements. Typical contemporary architectures probably consist of a data warehouse (with several departmental data marts) along with a myriad of toolsets for data integration and front-end application support. Front-end applications usually include a series of Web-enabled applications that are key components for an enterprise dashboard environment.

The key is to use the technology you have in house and add new pieces when needed to build a technical architecture that is optimized for enterprise-wide analysis and knowledge management.

I've tried to provide a flexible user guide for the design and implementation of an enterprise dashboard solution. One caveat: the key word here is "flexible." Define what the terms I've used in these two columns mean to your organization. Use my advice as a general guide, not as a rigid procedure for building a rigid system. Like the guidelines I've provided, the system you build must be nimble, flexible and adaptive.

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