It’s time to think about business processes.

In a recent post, I defined a business process as “the complete response that a business makes to an event”. Because this is such an important topic for data warehousing, I thought I’d share some additional thoughts.

Business processes include such activities as accounts receivable, orders, sales, and inventory management. Each process has a specific event (or goal) that defines the process and in many cases allows us to gauge the health of that process. For example, an order is an event within the orders business process. Inventory movement is an event within the inventory management process. And so on.

For a few years now, there has been a significant push — mainly by service oriented (SOA) and data warehousing architects — to get businesses to think more about business processes and not about departments, applications, and technologies. Traditionally, most organizations have structured IT around specific software purchases and departmental needs. Integrating these disparate systems later becomes a significant challenge for business intelligence, performance management, and master data initiatives.

James Gibson, in his research piece “A Research Strategy for Investigating Business Process Management Approaches”, wrote that it’s time to start thinking about process and process processing rather than data and data processing (I had to read that more than once too!). The key is that the business process — which is tied to a specific event — is a driver that can lead all other initiatives along. Actionable insights (typically what you hope to derive from your Business Intelligence and Performance Management initiatives) are only useful if they’re tied to a process that can be improved.

Thinking more about business processes, and developing architectures to support them, leads to a more integrated enterprise

Data Warehousing with dimensional modeling is solely focused on the business process. In fact, you cannot develop a true dimensional model without modeling it around some business event. And it should be clear that a single business event can span multiple source systems and departments. The dimensional model pulls all this together.

On the transactional and operational side of the fence, SOA is the right approach to take. Essentially, SOA provides a standard way to access myriad resources across a network through RPC, Web Services, and APIs (among other techniques). One application can communicate with another in real-time.

Developing an SOA and a Data Warehouse one-process-at-a-time is smart. I will talk more about this in a future posting, but the idea is simple: start with a single business process that will make the most impact and is most feasible. Then, in an iterative way, expand into additional processes. This allows development to quickly turn over key functionality while leaving room to resolve business process volatility issues and political ramblings. If you are lucky enough to be starting both data warehousing and SOA programs simultaneously, it makes most sense for the same business process to be the subject for both!

Master Data Management is about data governance and forms a core part of the integrated enterprise. Through SOA, applications can access master copies of shared entities, such as Customer and Product. Master data might be derived partly from a data warehouse using ETL and partly by operational applications in a transactional environment through SOA. When it is time to embark on an MDM initiative, it makes a lot of sense to start thinking about business processes, conformed dimensions, and how to maintain this critical data.

So imagine for a moment an enterprise with dozens of departments all using different tools and software solutions to manage their day-to-day operations. Through SOA, these applications can all talk to each other so that when a customer checks on an order, the clerk can also see who took the order, where the product currently is in transit, the customer’s order history and much more. The data is not integrated, but the processes are. At the end of the day, when the regional salespeople need their numbers, the data warehouse — which has integrated data arranged around various business events — provides the results quickly giving all subscribers a complete and integrated view of all relevant business processes.

Adopt architectures that facilitate business’ natural orientation towards the business process. Business Intelligence, Performance Management, Business Process Reengineering, and Master Data Management initiatives will benefit tremendously. I’ve been saddled by the department-oriented mentality by business for too long. Better IT/Business alignment in this area will create more opportunities for defining clear business processes which in turn will lead to a better integrated organization.

Tags: BI, MDM, SOA