Last month we began the discussion of how an effective vision for a new DSS plays a role in keeping expectations and delivery realities aligned. The first three key elements of an effective vision were examined (decision process integration, end user enablement and decision support infrastructure), and this month we'll complete the discussion by looking at the remaining three key elements.

Deployment Strategy

An effective deployment strategy describes more than the planned build out and roll out of the DSS. Implementation of an enterprise decision support capability constitutes a major change initiative, and the corresponding vision statement must contemplate the numerous change management issues likely to be encountered. In planning the implementation time line, packaging and sequencing, consider how successfully the organization has conducted past change initiatives. This will assist you in identifying lessons learned and common organizational pitfalls, and it will allow you to build on past successes. This valuable insight will aid you in mapping out your entry point for introducing the new capability. Also, create a change program portfolio that analyzes other initiatives that are proposed or currently underway. By doing this, you can determine possible capacity constraints, resource and mission conflicts and potential conflicting demands on stakeholder commitment. Keep in mind, the more concrete the vision statement, the more powerful it will be in guiding the process. Examples of how to make deployment aspects of the vision more real for the organization include:

  • Describe which systems will go away, and when, as the vision is built. This provides clarity of what's changing and gives users a tangible point of reference.
  • Be specific about the separation of roles and responsibilities between the business units and IT, particularly around training, meta data administration and maintenance, audit controls processing, etc.
  • Anticipate opposition and resistance when articulating the vision. Include specific initiatives which are designed to diffuse potential naysayers.
  • Describe source system quality improvements which will be tackled. Key users know the potholes and integrity issues of the current systems and realize the limitations which result. Keep credibility by outlining in the vision what quality issues will be fixed and when.

Figure 1: DSS Vision Elements

The vision should express the range of rigor and alignment for the information to be delivered by the DSS. For instance, analytical applications may be defined and designed which incorporate important business rules and algorithms, such as credit scoring and customer profitability. On the other hand, content may be organized as logical groupings of key performance indicators which support a discrete decision processes, such as channel management or promotion planning. An issue related to how the information will be structured and delivered is that too often a DSS provides the organization with technically accurate information which has limited value to improve key decision processes. Challenge your vision to address the following inhibitors to success:

  1. Organizations implement conflicting decision support systems that compete for management attention. In the absence of a common set of reference data, decision support systems deployed in isolation or without linkages to other initiatives, or one another, yield few insights. Worse yet, the result may be divergent guidance.
  2. Decision support systems fail to meet the requirements of the different levels of decision making in a complex organization. It's a simple point, but one that's often overlooked ­ all decisions are not equal.
  3. Inherent feedback mechanisms are not instrumented into the decision support system. Underlying business assumptions, economics and business rules that underpin the DSS must be constantly tested and refined to keep pace with changing business priorities, market dynamics and competitive pressures.

Figure 2: Information Delivery Architecture

An information delivery architecture governs the transformation of data from its origin to the point where value is created ­ its use within a decisioning process. Many data warehouse architectures don't explicitly envision the decisioning application layer, although this is where the payoff is. It's the specific decision processes which will be improved ­ or created ­ which bring the potential of the data warehouse to life. Ensure the DSS vision defines an information delivery architecture which describes the distinct role of each component in achieving this objective. The warehouse layer will be designed for optimized data acquisition, consolidation and storage, but not user access paths. Its structures will tend to be stable over time, representing only the core dimensions of the business. Conversely, the data mart layer will directly reflect the current operating model of the business, with measures and dimensions around aspects of the business which flex with time, such as sales channels, lines of business, organizational structures and user navigation requirements. Also, an information delivery architecture suggests expanding the view of meta data to one of enterprise reference data. With an enterprise reference data approach, not only are the "wheres" and "hows" of using the data maintained, but the need for corporate governance in managing the creation of the common business lexicon which will be used by all information delivery systems is recognized.

The DSS vision must be revisited and refreshed as the business changes. Remember that listening improves vision. Listen to your organization, observe and respond to shifting priorities and allow this to reshape the vision over time.

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