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Governance Dashboards
An article by William Laurent

by William Laurent, William Laurent, Inc.Wednesday, September 26, 2007

Corporate governance has become a leading topic of attention for senior management, company board members, and shareholders of businesses worldwide. It comes as no surprise then that business intelligence (BI) dashboards are beginning to tackle the complex field of corporate governance from both proactive and reactive perspectives.

These dashboards must be designed so that they can support the policies and procedures of corporate governance by promoting best practices and measuring performance for maximum accountability and transparency among the various tiers of management. Through measurement and accountability these dashboards will help drive corporate strategy and serve as catalysts for both operational enhancements and the reengineering of mission critical business processes. Unless effective performance management mechanisms are built into the BI dashboard, true support of corporate governance will be elusive and difficult to achieve. Without proper performance management, it will be impossible for management to truly understand or communicate strategic and tactical strengths and weaknesses across the enterprise. Although corporate performance management and score carding is regarded by executives as more of a management process than a technology solution, a robust governance dashboard represents a primary means of delivering governance intelligence so that the business can both forecast and react to the numerous and ever changing challenges of the marketplace in a collaborative fashion.

Unfortunately, most governance dashboards exhibit limitations in performance management functionality (knowing what needs to be measured, when to measure it, and how to quantify and respond to the measurements). Some common problems that plague governance dashboards are:

  • Unacceptable Latency in Mission-Critical Data
  • Flawed Indicators and Thresholds of Performance
  • Slow Data Retrieval and Slice/Dice
  • Poor Codification of Semantics
  • Poor Intelligence (Cause and Effect) Traversal

While savvy data architects understand that these sorts of shortcomings usually point squarely at problems in data integration, less knowledgeable IT executives oftentimes think that their business intelligence issues will disappear simply by procuring BI software. The then neglect to budget for the real heavy lifting that enables dashboard solutions to function optimally — the robust and well thought out integration of enterprise data. While nobody really likes to get their hands dirty with data integration and data warehousing, data strategy is paramount to BI success and the choice of dashboard vendor or front end is always secondary. It is not unusual for the root cause of failed dashboard projects to be somewhat hidden in a tangle of data dependencies that are poorly understood, let alone properly integrated.

By default, the integration shortcomings associated with dashboard projects can be greatly reduced by closely adhering at all times to an enterprise data governance agenda which lays out procedures on data dictionaries, metadata repositories, and other mechanisms so that the ontology (i.e. the “true nature”) of all data is lucidly understood. If your organization is constantly pursuing a path of “data forensics”, how can viable dashboard solutions come to fruition? More and more IT auditors are focusing not only on control processes, but examining lower-level data processes in order to understand the web of data dependencies. They conduct complete mapping exercises—involving the relationships of data, business processes, and hardware—so that companies better understand data ontology and know what each piece of atomic data represents in business terms. Once data ontology is fully understood (with the support of semantic standardization, a metadata repository, distribution matrixes, etc.) business rules can be fully supported and better captured by rules engines and service oriented functions.

One way organizations temporarily avoid large integration dilemmas is to implement governance BI projects in distinct phases—performing siloed data integration, with compartmentalized and modular data access and roles, by deploying intelligence and performance management to satisfy a single area of the business. Companies often tackle their core financials first (with support from any common industry standard XML models if available) because the biggest key component of governance and performance is financial management. After all, there is nothing that can undermine shareholder confidence in an organization more than failure to correctly assess and report on core financial data such as profit and loss, debt, equity, and various high-profile fiscal liabilities and assets. Eventually other business areas can be brought online one at a time and tied together along premium “governance domains”, such as regulatory and compliance performance, fiscal, legal, etc. In this way you can better achieve visible ROI sooner, rather than waiting for large monolithic data stores to be ready before any results (no matter how vertical) are available.

Yet, there are other ways to deal with the pains of dashboard data integration. For instance, there is increasing clamor for “federated” models of data sourcing and integration to support governance dashboards. Although more easily conceptualized than achieved, this dynamic paradigm of data sourcing and integration is quickly becoming more mature, thanks to best practices in service oriented architecture (SOA) so that data can be sourced, transformed, and integrated “just in time”. In addition, business rules and other functions that operate on sourced/queried data can be wrapped for easy execution, reuse, and cataloging. SOA data calls can query different distributed databases on the fly, extensively shortcutting a host of integration problems.

Being able to seed the dashboard with data immediately, will give credence to how well IT can support real time corporate governance by delivering financial answers and measurements without waiting for nightly batches to prepare and massage the data that the dashboard desperately needs. These federated dashboards will eventually be served by entire SOBA (Service Oriented Business) platforms. A SOBA is a collection of cataloged and well-governed SOA software services that are packaged into macro business processes and rules which can then be executed from many different applications (dashboards) or systems, regardless of environment or platform.

Stakeholders in corporate governance are many. They expect that any dashboard solution be accountable for delivering many timely dimensions of governance that will drive continued compliance and innovation. Mutating regulatory requirements and factors of risk necessitate that the governance dashboard be able to scale and “roll with the punches” of an ever-changing global economic landscape. Only with a robust data strategy (based on a codified data governance policy) will you be able to ensure that your dashboard solution will be effective in measuring corporate performance.

For more information on William Laurent please visit www.williamlaurent.com

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