Getting to the Single View
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If not Master Data Management, what?
Enterprise Resource Planning (ERP) – the “back office” – has been around forever, and the “customer master” function in most ERPs is adequate, but due to acquisitions, many companies have more than one ERP system, and some companies let major business units build their own separate technology architecture.
Customer Relationship Management (CRM) – the “front office” – was supposed to be a “silver bullet”, bringing businesses closer to their customers, delivering 1-to-1 marketing, and increasing sales.
And data warehousing and business intelligence were supposed to deliver performance management and analytics, enabling better decision-making and deep analyses, but have sometimes proven to be difficult to deliver and extend.
But to varying extents, all of the technologies failed to deliver on all of their promises.
So circa 2004, along came Customer Data Integration (CDI) and Master Data Management (MDM). I call it the “hole in the donut”. MDM takes information from source systems like CRM and ERP, and eventually passes it on to downstream applications like data warehousing and business intelligence. But a lot of magic happens in that “hole in the donut”.
Information is consolidated into an MDM hub, usually using service-oriented architecture based integration technology. It’s cleansed using data quality software and completed or enriched with third party information. And it’s managed by a data governance organization. For more details on the end-to-end MDM process, see our earlier post on the “Five Essential Elements of MDM“.
So that would give you the Single View of the Customer (or Product, or Supplier, or whatever data domain you were mastering).
And from there, most companies would, in fact, flow the consolidated / cleansed / completed information into a data warehouse or business intelligence application.
But if your MDM hub is missing, and you don’t have the data governance organization or processes, all of the above is going to be much more difficult, if not impossible.
Organizations are waking up to this, realizing that they’ve got “the donut” i.e. key pieces of the puzzle (plenty of source systems, decent integration technology, tons of third party data) but no data quality tools and no central MDM hub.
If you want the Single View (the “whole donut”), you need to invest in those missing pieces.
“And data warehousing and business intelligence were supposed to deliver performance management and analytics, enabling better decision-making and deep analyses, but have sometimes proven to be difficult to deliver and extend.”
So like every other form of human endeavour, sometimes this is done well and sometimes it is done badly. This doesn’t seem like the best of arguments for writing off the entire area to me.
Thanks for your comment, Peter. I didn’t mean to write off data warehouses; they’re obviously a useful and important part of the enterprise technology landscape.
Most of the data warehousing and BI professionals I know have taken an interest in MDM and data governance. There’s a lot of wisdom out there about data and its management that can be shared between MDM and BI.
I agree – MDM can contribute strongly to BI and MDM has merits all of its own.