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In an ERP System, the core functionality has been well defined since the 90's. Some companies might need a different distribution module or a fancier scheduler algorithm, but MRP is pretty much MRP. An accounting system? You'd better not have a lot of creative requirements.

CRM Definition and Solutions

But a CRM system is used by those right-brained types who bring you revenue, and there is significant variation in functional requirements from company to company. Even the precise definition of "CRM" can be debated if you get enough consultants in the room. So it's all too common to have wide-ranging discussions about marketing automation, call center features, SFA, forecasting, order entry, e-commerce, customer support, and customer portals. This makes for a very long feature list to be evaluated, ranked, and budgeted for.

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While these discussions about requirements are important, they also distract management from the issues that matter. Take a look at why.

Secret #1: Features are less important than User Adoption

A CRM system without users is just a database schema with a user interface. So getting users to get on the system early is a key success factor: user activity is what starts the virtuous cycle of CRM (more users mean more relevant information which makes it easier to attract more users). Of course functionality (and, let's face it, some cool bells and whistles) will help attract users. But the early adopters won't need that much functionality to get going.

As I've written endlessly in this column, deploying features in a "big bang" release is not the right approach for CRM projects. Agile techniques and incremental deliveries let you optimize for ease of adoption and early business value. So instead of focusing on one feature list, work the problem as a series of small but coherent feature sets that each solve a contained business problem for the users.

Secret #2: Features are less important than Data Credibility

A CRM system is only as good as the data asset it holds. The credibility of CRM data comes from its business relevance (timeliness), accuracy (cleanness), and scope (number of users and systems feeding the database). Yes, functionality contributes to the data credibility, but it's far less important than:

• The care taken in doing data migration and imports
• The quality of the external system integrations (watch out for systems that corrupt fields, or worse, create duplicate records)
• The tightness and consistency of semantics for key fields (such as "sales stage" or "case resolution")
• The precision and realism of business process definitions surrounding the system.

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