Measure the success of a merger by the quality of your data

Follow these 4 steps to ensure you use best practices and emerge from a merger or acquisition with a trusted version of your data.

“Once you understand the acquired companies’ data assets, you’ll want to migrate that data over to your company. Make sure you clean up that data as much as possible, so it’s not ‘garbage in, garbage out’.”

—David Rye, senior vice president of Corporate Development at Informatica

When two companies merge, data is often the last asset considered by stakeholders. However, data integration in a merger or acquisition (M&A) is always more complicated and time consuming than the business expects.

Converting data from an acquired company is a complex process that involves many layers of business rules and enterprise-wide systems. Data conversion must occur as quickly as possible once the contracts have been signed. This ensures a single, trusted, complete version of all of key data in time to meet your M&A financial reporting deadlines.

Of course, if you don’t currently have solid data governance overseeing your own company‘s data before an acquisition, rushing new systems integration will only make a bad situation worse. David Rye, senior vice president of Corporate Development at Informatica, recommends adopting data governance for your existing systems as soon as possible.

“You need to set up a data governance process before merging systems. If you don‘t have the expertise, leverage that expertise from outside software or services vendors. Look for best practices and software that will help establish governance for your own systems, but that can also be expanded to the acquired company’s systems. Look for as much automation as possible. That way, you don‘t have to throw a lot of programming resources at it,” says Rye.

With solid data governance in motion, you’re ready to tackle the four steps that every information leader must follow to integrate data in an acquisition:

  1. Discover all of the acquired company‘s systems and processes.
  2. Conduct data profiling to identify what the data is, where it is stored, and its current condition.
  3. Use data quality software to cleanse and enrich the data as much as possible.
  4. Standardize data from the acquired systems to match the existing systems. Master data management software can help to ensure the data remains in sync across these systems.

“Once you understand the acquired companies’ data assets, you‘ll want to migrate that data over to your company. Make sure you clean up that data as much as possible, so it’s not ‘garbage in, garbage out.’ Standardize customer data so it’s not in five different formats. Update addresses so you don‘t have old, outdated contact information. Attempt to fill in any critical fields that are missing,” recommends Rye.

It‘s rare that both the acquired company and the acquiring company have perfectly matching data fields in their systems or have even collected the same types of data. Automated software can help you fill in the blanks if you‘re working with incomplete data. For example, you can use address validation and enrichment software to get customers’ full addresses if the street number and names are missing from Salesforce.com.

Rye cautions that there is no interim solution immediately after an acquisition is finalized—you simply must run both sets of systems and their processes until you and your IT staff can discover, profile, clean, and standardize the data from the acquired company.

“The problems that companies run into stem from saying, ‘We‘re going to integrate by X date,’ and they don‘t budget sufficient time and resources to run both systems in parallel,” says Rye. “Ultimately, you can decommission one set of systems, but you’ll need to run both systems in parallel for a period of time.” Only once the data is trusted and standardized can you consider a plan to reduce costs and improve efficiencies by consolidating the combined systems.

Then, with clean, combined data governed by standardized policies, you can be confident that you‘ve created a single view of data that better integrates with the processes and operations of the combined businesses.

For advice on how to pitch a data governance initiative, read “Whatever you do, don’t lead with the data. Or the governance.”

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