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Cross-integration of many system

MM: In fact, Mike—as we were doing the quick recap of the history of data warehouses… I think one of the things that had developed or emerged out of ERP and the data warehouses as they interact… A lot of the data that people need aren’t inside the organization. They’re outside the organization in suppliers and in trade partners.

MB: Well, that’s certainly the case. There’s information that’s down in the supply chain. But in fact, in the organizations we visit the systems that are facing the supply chains at customer sites are actually comprised of a variety of systems like warehouse management systems (WMS), transportation management systems (TMS), freight payment systems, customer relationship management systems (CRM), budgeting and financial planning systems, and so forth.

These systems provide functionality not found in ERP systems and therefore sit next to them—so companies always have many disparate, systems where important data resides and needs to be integrated for analysis and other purposes. There still needs to be some cross-system integration of this information. ERP systems in some sense have not quite lived up to their billing of consolidating all of this information. It remains important to be able to reach across different systems as well as across multiple ERP systems to be able to provide the visibility that companies need.

You mentioned the organizational barriers. Those are really quite significant as well. I’ll mention a couple of significant problems there. These are good examples for contrasting the way we approach these issues at Oco versus the way others in the industry have historically gone after these problems.

Historically, people will set out to put the data from their whole organization into the data warehouse. They’re trying to get data — all the data — in one place and also must cleanse that data—an enormous task. It’s an open-ended business intelligence activity that will enable the company to utilize the data warehouse…someday.

In other words, they’re building the data warehouse without already knowing exactly what they want to get out of it. They want to get whatever can come out of it.

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