Data integration: M&A’s master data problem
When it comes to M&A, meeting extraordinary data management challenges can be viewed as the other side of the integration coin, because in addition to increasing the complexity of system environments, M&A increases the “big” in big data. The non-organic growth that creates so many integration issues around systems, applications and networking is itself catalyst for a dizzying array of critical data management challenges. Unchecked, and further exacerbated by a lack of alignment in data standards, the proliferation of bad and inconsistent master data will only slow down the M&A process, diverting vital resources and postponing M&A’s substantial business benefits by degrading or breaking existing business processes.
Admittedly, an organization doesn’t have to be undergoing M&A activity in order to produce bad and inconsistent master data. A lack of data governance—even in relatively, simple system environments—is still enough to generate redundant and inaccurate data.
But the sheer magnitude of M&A increases the scope of data challenges, requiring a faster pace of adaptive planning and new tool adoption. Master Data Management (MDM) is a key and proven solution to help standardize and reconcile the sudden influx of enterprise master data from multiple and disparate databases.
Disparate data creation in multiple ERP systems
M&A activity also creates a fertile breeding ground for highly disparate data models—the
initial and strategic key organizers of not only master data but also reference data/code sets, metadata—and their important (and oft times overlooked) hierarchical relationships.
Primary ERP systems of the past 10 years such as SAP, Oracle, Lawson,, JD Edwards™ and PeopleSoft might offer similar applications, but each one (due in large measure to their
different approaches to data modeling), guarantees a proprietary approach to the physical and structural creation of master data. When these data models attempt to coexist within the same enterprise landscape, odds are there is little to no organic basis for standardized data creation. Consequently, a single view of the customer is impossible.
Redundant or overlapping product catalogs might seem atypical in a less complex, more silioed environment. But confusion between product catalogs becomes inevitable in the following M&A scenario:
(See graphic at top). Fictional office supply/retailer Acme (the acquiring company) and fictional Penn Stationery Inc. (the target company) share the same manufacturer and/or distributor. The
conflicting product IDs (and representation of data attributes) ensure the duplicate appearances of the identical red cabinet and gray chair in both product catalogs and now systematically interprets them as four different products. As with multiple versions of customer, this product confusion will skew process integrity, undermine accurate sales reporting per product, and even paint a false picture for supply chain replenishment.
It may seem that an M&A has occurred once announced to the press. But in reality, the execution of legal terms is only the tip of the iceberg for the hard work ahead of merging IT assets, talent and standards. There may be many months ahead, in fact, as the acquired and acquiring companies implement strategies that will enable both to function as a single organization and as a Digital Enterprise.
But in most M&As, the IT integration and data management angles are still overlooked or
underplayed, delaying the success of the M&A—even to the point of degrading and making core processes less responsive to immediate business requirements.
The good news is that even while there are different types of integration challenges, there are also highly effective integration and data management strategies. Adopted in a timely manner, these strategies can strengthen the M&A initiative to overcome such challenges.
To read all of “An IT Manager’s Guide to M&A Planning, please click here.