Creating a Customer Information Management Plan

Where is your customer data…and where should your customer data be? If you take a broad look across your organization, you are likely to find pools of such information scattered among departments and corporate hierarchies, and embedded in a variety of systems. You will also find it varies in quantity, quality, recency, precision and content.

This should be the case – but do you have the optimal distribution of data across your organization? For a great number of firms, the answer is unequivocally, and frustratingly, no.

A customer information management plan enables you to optimize the value of your customer data assets. It addresses:

– How to efficiently collect customer data. There are typically any number of data-collection options and practices that vary greatly in efficiency and effectiveness.

– How to transform data into meaningful, usable information. The data may need to be consolidated into monthly transaction summaries or linked to regional sales territories.

– How to readily distribute customer information throughout your organization. This could range from a point-of-service application to information in sales/service centers or to a decision support system.

Having a plan to address these issues is important, because:

– Customer data management can quickly become a very costly, ineffective and inefficient process.

– Sharing data hygiene, consolidation, maintenance, reporting or access tools across systems could provide significant cost reductions and efficiencies.

– Customer data sharing is a difficult, exacting process.

Developing a customer information management plan represents a big opportunity to realize cost efficiencies and increase effectiveness in managing customer relationships across your organization. Developing and implementing this plan, however, can prove challenging. You’ll likely face some of the following obstacles:

– Departmental and/or divisional boundaries. Within your organization, various groups may have different opinions on data ownership and value. And they might have dissimilar business goals that help or hinder data collection and maintenance.

– Deeply entrenched systems and processes that may be difficult to change. These might relate to existing technologies or business processes and practices.

– Time and money. An enterprisewide initiative such as this could be too big to handle.

Here’s an approach to devising a manageable plan:

1. Define where customer data is needed or could be utilized across your organization and why. You might be surprised at the diversity of data needs. Therefore, it’s important to differentiate “must-haves” from “nice-to-haves” – and prioritize.

2. Conduct a customer information audit, which defines where and how data is currently gathered; the quantity and quality of the data; and where, how and by whom this data is maintained. This documentation is crucial; it ensures that existing data resources are identified.

3. Based on findings in Steps 1 and 2, develop a specification document that details data, process, functionality and architecture requirements. At this stage, avoid identifying specific solutions; rather, focus on detailed business processes and support elements.

4. Conduct a gap analysis, identifying discontinuity between what you have and what you need.

5. Define a solution reflecting your current situation and prioritized requirements. It should take into account such “softer” organizational and situational issues as the interest levels and capabilities of the different departments that could benefit from the customer information.

Potential solutions include:

– Developing new processes and mechanisms for customer data collection.

– Creating data collection standards.

– Improving data processing capabilities.

– Constructing a conceptual model for an enterprisewide customer information system.

– Implementing a customer-centric data warehouse.

– Realigning internal data-sharing practices.

– Developing tools for common access to customer data.

– And, aligning customer information needs with internal data-warehouse plans.

Developing such a plan is only a start, but it should ensure that subsequent implementation efforts are in harmony with a broader strategy.