Pick up the business section of The New York Times, The Wall Street Journal, or USA Today and what do you see? It’s hard to go more than a day without spotting a news item about a company merger, acquisition, or business unit divestiture. All three are typically viewed as favorable strategies for achieving growth and improved profitability, but in today’s age of big data, executives have a lot more to worry about than final regulatory approval.
Managing the transfer of intellectual property (IP), where much of the value of a deal may be derived, has always been a concern. Now, with the ubiquity of big data and the rise in cloud computing, this concern is greater than ever. Each business transaction carries its own challenges and requirements to meet the desired outcome, but there are important steps that can be taken for mergers, acquisitions, and divestitures that will help to ensure that the big data changing hands does not turn in to a big problem.
Divesting a Business Unit
When an organization divests a business unit, a constant challenge that must be addressed across all scenarios is the protection of corporate IP. Just imagine the potential for damage if a product roadmap, confidential vendor list, sensitive customer identifying information, secret recipe, or private pricing analysis were exposed during the process.
Identifying, analyzing, and scrubbing data to separate the data to be transferred to the new company from the other data takes a significant amount of time, effort, and resources. Any data that will not be transferred must be segregated and purged prior to handover. Then data that will be handed over must be presented in a format compatible with the new entity. Making matters more complicated, the timeline to complete this is usually very short.
Technology is able to play a role in this process, but it takes more than simple software to solve this problem. To make a divestiture as smooth as possible, the company should take a strategic approach to managing data. Start with an archiving initiative. Archiving will allow the company to separate data according to its business value. High-priority data should be kept in the live database for frequent use, while other data can be archived and kept either in near-line storage for quick, occasional use or in an archive repository for long-term storage of data required for regulatory purposes.
Once all the relevant data is sorted and archived, any data that has reached the end of its lifecycle can be destroyed. This process makes isolating the target data for a business divestiture much simpler.
At this point, a data carve-out can be completed quickly and more efficiently. Properly archived data will allow for faster system transfer or data migration, and teams will be able to more easily identify and separate the high-priority data that is not part of the divestiture. Another added benefit of starting with archiving is that any data that must be retained for regulatory purposes can be locked down to avoid tampering.
Mergers and Acquisitions
During mergers and acquisitions, several problems can arise involving the integration of big data from two entities to one organization. Most importantly, the entities must consolidate systems. This often involves the need to migrate data to a new system or modernize existing systems, as one or both entities may be operating older, legacy systems. Similar to divesting a business unit, an archiving initiative can play an important role in this process, as it will make data more easily portable when legacy systems are decommissioned.
Another problem that develops is a clash in business processes. For example, every finance department is different, and most have evolved to develop an approach to meet the unique needs of their business. Many are manually driven and labor intensive, spreadsheet dependent, and woefully inefficient, but they get the job done. For this reason, change is hard to instill. Mix in two entities that must now perform as one, and issues are bound to arise.
Many organizations still don’t treat these areas with an eye toward big data, but an M and A scenario is the perfect time to start. Technology, coupled with process innovation, can make the finance department data-driven. Instead of manually handling invoices, invoices are captured in the system and, through the establishment of business rules, can actually be routed through the system without manual approvals. Analytics and reporting can then be applied to track performance, determine where the bottlenecks remain, and capture early pay discounts. An added benefit of being data-driven instead of manual is the ability to flexibly scale and adapt to new processes. This is important, as the goal of M and A usually is to stimulate additional business growth.
Ready for Anything
Corporate transformations are not limited to divestitures or M and A activity. Think about the process of moving from a traditional ERP database to cloud-based operations. Many of the above lessons would apply to this situation as well. A company could shift to a shared services model or decide to implement new business models that would require the integration of a previously non-existent division. The introduction of ecommerce and online stores is a perfect example, as this requires organizations to seamlessly adapt to new business models.
The only constant in today’s always changing business environment is that anything can happen, which is why it’s important for an organization to be ready for anything when developing a big data management strategy.
Dr. Werner Hopf is Dolphin’s CEO and Archiving Principal. He has more than 20 years of experience in the information technology industry and specializes in SAP Data Volume Management initiatives. Founded in 1995, Dolphin works exclusively within the SAP ecosystem. As the one partner that manages both data and processes, it leads the way in business performance improvement.
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