June 28, 2011, 10:24 AM — Offshoring IT work to India, China, Eastern Europe, and even South America has been a staple of IT cost reduction. And by definition the Cloud means location independence. Generally speaking, they're practically made for each other.
But in CRM and related systems, there are good reasons to keep the work in-country, or even in your building. This isn't just a matter of costs, but of business value and risk containment.
Why? It's all about the data. Compared to all other enterprise systems, CRM data has the highest chances of data quality problems. For example, in an accounting system, you'd never tolerate a duplicate invoice or a journal entry from an unknown source. In CRM, it happens all the time. Most of the data in a CRM system is entered by hand, by people who don't really care about consistent, coherent data. For many, CRM data quality is just not their job: they're sales reps trying to close a deal, or partners trying to register a lead, or customers filling out a registration form. They'll spell their name right, but even the e-mail address they enter may be fake.
Even when data is regularly cleansed and deduped, CRM systems have a never-ending problem with duplicate and phantom records being created by external system integrations and industry data imports. All too frequently, there's no DUNS number for the company or other reliable indicator of who's who. The more CRM and related customer-facing systems you have, the bigger this problem gets. I know of one large IT vendor that creates 100 new duplicate accounts in their system every day, and that's after they've applied all their deduping tools.
Despite all these negatives, the CRM holds the best information you've got about your existing customer relationships, current pipeline, and future prospects. By every possible measure, that data is worth far more than the system it resides in.
So keeping that data in as good shape as possible is a cornerstone to CRM success. Even though the cloud lets you move data around the world in a heartbeat, it's very hard to communicate the nuance of how to make the data more valuable and meaningful to your organization. Further, the tiny details of how to improve the data are likely to change over time — they seem to evolve as part of your information culture. None of this is easily documented or formalized, so it doesn't communicate well outside of your buildings.