It's an age old question:  Which came first:  the data or the process?  Okay, not an age old question, but an interesting one to ponder nonetheless!  Of course the answer depends on who you ask.   Ask most Business Process pros and the reply:  "Process existed even before computers. In fact I saw on The Discovery Channel where they found a process map in King Tut's tomb. No joke..."  Ask a Data Management pro and you're likely to hear: "Data was invented by the Pharaohs - you ever hear of a little thing called 'numbers'?"  
In upcoming research we tackle this vexing question and conclude that process and data are of course inseparable (shocking we know).  Unfortunately, most Business Process pros, Data Management pros, and vendors we interviewed couldn't see the forest for the trees.  In fact, in our recent MDM Survey, only 11% of respondents said that their MDM and BPM initiatives share the same cost center and team members that work together on a daily basis to develop solutions for the business.
In many ways, master data management (MDM) and business process management (BPM) represent two different sides of the same coin when it comes to business optimization and transformation.  So, why is there so little collaboration and interaction between Business Process and Data Management professionals?  There's plenty of blame to go around:
Business Process pros don't find data sexy. While most process improvement initiatives pay lip service to data quality, only a small handful take data seriously and incorporate data modeling and data mapping into upfront discovery efforts. BPM teams typically focus on process first, user experience second, and data is an afterthought - no one ever asks if the data is clean until it’s too late!
Data Management pros value clean data over process context.  "If we create clean data, then they will come" is often the mantra of Data Management pros. Unfortunately, the person coming is the CFO - asking "why are we spending so much money on something when we can’t articulate its business impact?"  In other words, Data Management pros often fail to provide cross-enterprise context for MDM.
BPM Suite vendors conveniently MIA on the issue.  Some argue that SOA is the silver bullet to bridge the gap between MDM and BPM initiatives.  While SOA can definitely address reusability and architecture issues, many BPM teams come to realize the importance of master data too late into their initiatives.  While BPM suite vendors provide basic tools to define process variables, only a few (Lombardi/Siperian, Appian, and Polymita) accept some responsibility for keeping process data in sync with master data sources. MDM vendors focused on data governance and stewardship only.  The good news is these MDM vendors do in fact recognize that business process plays a major role in their success. The bad news is they are only actively addressing one side of the problem: the business processes and stewardship roles that govern the administrative workflows within the MDM tools themselves. The MDM vendors are not actively influencing the business processes that consume and depend upon the master data these vendors provide. 

Although process and data professionals may not see it, like your brain and your heart, BPM and MDM are interconnected and one cannot survive for long without the other.  Our upcoming research, "Warning: Don't Assume Your Business Processes Use Master Data," highlights the fact that process improvement initiatives face a vicious cycle of deterioration and decline if master data issues are not addressed from the outset. And MDM initiatives face an uphill battle and certain extinction if they're not connected to cross-cutting business processes that feed and consume master data from different upstream and downstream activities.
Earlier this year, Forrester highlighted the emergence of "process data management" in our BPM Tech Radar report.  This new category in the business process landscape organically merges BPM and MDM disciplines and capabilities to provide the enterprise with one version of "process and data truth".  
Over the next several months, we will publish a body of research that scopes the process data management challenge, provides best practice for combining process improvement and data management initiatives, and presents case studies highlighting teams that have successfully integrated these two critical capabilities.

Why It Matters?


Call it what you like, the consolidation of process improvement and data improvement is inevitable.  Organizations looking to minimize operational risk and boost adoption on BPM initiatives must incorporate data modeling and data management activities for cross-functional process improvement projects.  Additionally, organizations looking to increase the visibility and importance of master data must identify and harness the most critical business processes that generate and consume mater data.  These are just starting points for bringing process and data closer together.  Most importantly, senior management must foster collaboration and provide cross-training between these two siloed disciplines to begin this long overdue paradigm shift.

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