Poor Data Management Leads To Merger Failures

by Dan Rotelli

Here are five data processing tasks that drive better outcomes.

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Mergers and acquisitions present unpredictable and unique challenges. While there’s a wealth of business advice available, there isn’t as much advice on one of the most important aspects: data. Analyzing information for due diligence is one thing, but integrating IT infrastructure, data and systems is a big project. And it seems like there’s never enough time allocated for it.

Adding to the stress is the fact that most mergers fail. The reason? Not poor financial decisions or a faulty audit. Studies show that broken business processes are the culprit.

No Two Organizations Use Data the Same Way

Chances are, the companies joining forces have completely different enterprise data systems, policies and processes. In many cases, at least one company brings a lot of paper to the table. Add in vastly different data standardization practices, email and productivity systems, archives and cloud solutions – and it’s clear to see why migrating data is such a significant undertaking.

Vendors have solutions for migrating data, right?

They do. Sort of. There are tools for migrating one system to another. For example, if you need to migrate basic content from SharePoint to Office 365, Microsoft has tools and support for that. However, if you are migrating content to an ECM, like Documentum or Alfresco, or you are using SharePoint as an ECM, the migration task becomes incredibly intricate.

Business workflows hinge on accurate and thorough data. Merging data that has already been interpreted by two enterprises requires a deep understanding of processes and data sources.

It’s no wonder why data management is the crux of a successful merger.

Performing these five data processing tasks during data migration will ensure that information for the combined enterprise is managed in ways that are consistent, efficient and secure.

1. Indexing

If paper or basic file stores are involved, indexing all documents before migration is a must. Accurate document indexing fuels precise data extraction and reduces the risk of losing data during migration. The best scenario is a migration solution that includes automated indexing.

Your organization may depend on very detailed HR information for compliance and workflows, while the other organization may only have paper files or a simple file share. By indexing before the migration, you will be able to capture the data you need from both entities regardless of how it was previously stored or identified.

Plan to re-index all document types across all storage locations – onsite/offsite, SharePoint, Documentum, Alfresco, Ariba, Dropbox, file servers, etc. You’ll save an immense amount of time and human labor by automatically indexing documentation during migration.

2. Validation

Validating data during a migration is another opportunity to reduce future workload and limit the chances of process failures. Vendor migration tools can’t perform validations on data you will be migrating. Perform validations on data like account numbers, addresses, phone numbers, financial calculations, etc. Create workflows to flag any errors for manual review.

The best time to discover data errors and omissions is before your go-live date.

Critical operations related to billing and customer support can stay fully functional by merging accurate data. You don’t want to discover that you aren’t billing for something you should be, or that you’re unable to support new customers because you can’t find them in the system.

Accuracy inspires trust. If your merger creates new employee and customer relationships, make sure you are getting off to a great start with accurate and reliable information.

3. Capture and Extraction

Even if there is very little physical paper involved, you still need to plan on extracting data from digital sources. Most prior migrations include file stores containing scanned document images, though searching for data on these documents can produce inconsistent results. The original documents may have been scanned using an older OCR technology or no OCR at all. You can unlock valuable data by re-OCRing these scanned images with a modern capture tool.

Other common sources of digital data that will need to be extracted include:

  • Basic content services – SharePoint, Box, wikis, etc.
  • Cloud storage – Dropbox, OneDrive, Drive, etc.
  • Email systems – G Suite, Exchange, Outlook, etc.
  • Archives and backups – tape drives, optical discs, fixed disc arrays, film, fiche, etc.

You may have business processes that are dependent on data that was never collected by the other company. Ensure the stability of your processes by identifying and extracting 100 percent of the data you need across both organizations. And if your goal is to collect information from disparate systems, use a solution designed to capture and extract data from multiple sources.

4. Standardization

Standardizing file formats makes it easier to quickly retrieve, read and annotate documents. Consider standardizing (or normalizing) to PDF format. Every modern enterprise data system works with PDFs. Original file formats can also be migrated to retain access, if necessary.

Converting to PDF saves money on licensing costs and makes documents accessible for years to come. When staff members need to search through documents to locate specific information, documents converted to PDF will be extremely easy to view in any information system.

5. Security and Permissions

Every company has their own methodology for managing security. Since you will be adding new data and possibly new staff, access to data and files will need to be scrutinized and harmonized.

To keep compliance initiatives intact, plan to identify protected data and route it appropriately during the migration. Use a migration tool that provides flexibility. For example, you may need to extract and redact protected data, but retain both redacted and original versions.

Dan Rotelli is the CEO of BIS and creator of Grooper.