In many instances, control is a prerequisite for sharing. Professionals who feel they lose control over their business contacts by contributing them to the centralised database will often decline participation. Accordingly, the more confidence they have in their ability to control what happens to their contacts within the CRM system, the greater likelihood that they will contribute and help build the firm's institutional knowledge.
Categorisation Categorisation represents another element of data change management. Not all changes will or should be submitted to a data steward for processing. Depending on the importance of a contact and the type of change, Klau says it is perfectly acceptable to allow certain changes to be completed and perform the data quality review later and en masse.
For instance, the 80-20 rule applies to most organisations - 80 per cent of the firm's business is derived from 20 per cent of its clients. It therefore follows that bad data on a top client can have a substantially more devastating impact on the firm's bottom line than bad data on a client for which the firm provides few and sporadic services. For example, Klau says in one case an Interface Software customer had invited its top client to an exclusive firm event. The client's name was misspelled on the invitation because someone had made an inadvertent error in the database. The outraged client argued that if its firm could not even manage to spell his name correctly on an invitation, what other mistakes might it be making? One seemingly minor error can have an enormous impact on relationships. Clearly this firm needed a CRM system that would allow it to monitor closely changes made to key contacts.
Given the frequency and volume of changes to contact and relationship information on an organisation-wide basis, even with data change management tools it could be an overwhelming task for data stewards to oversee all changes being made to firm data and ensure its accuracy. This could stall data quality efforts and negatively impact an implementation.
To prevent this data quality bottleneck from occurring, Klau says the system should facilitate the categorisation of contacts to enable data stewards to direct their efforts on changes that will have the greatest impact upon the organisation.
Data stewards can then apply some basic business rules to the data maintenance process. The organisation might require that all changes made to category one contacts have to be submitted to the data steward for verification prior to the changes being saved in the centralised knowledge base. All changes made to category ten contacts can be saved immediately in the database without verification.
From a data quality perspective, the ability to categorise clients within the CRM system and treat the various categories differently provides tremendous efficiencies. Data stewards are able to direct their time and attention to data changes that have the greatest potential impact on the organisation. Their resources will no longer be tied up managing contacts that are inconsequential to the firm's business.
Workflow A centralised database that allows everyone to contribute information is the optimum approach to keeping information current and maintaining high quality. When professionals are not allowed to make changes to existing information, they create duplicate copies. When they are not allowed to add new information, they find alternative storage mechanisms.
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