One of the critical factors that determines how quickly newly merged companies can begin to operate successfully as a single entity is the ability of the acquirer and the acquired business to seamlessly integrate their operations, processes and procedures. It is one of the main reasons why many mergers can often take longer than planned to settle down, possibly a symptom that not enough due diligence has gone into the target company’s IT and data management systems prior to the acquisition.

In a world in which increasing numbers of companies are adopting digital transformation strategies it is widely accepted that a structured data management strategy is a fundamental requirement needed to drive every aspect of the business operation from finance, HR and logistics, through to customer relationship management and sales. This means that when organisations merge, they are not just acquiring all the expected tangible and intangible assets, people and buildings but also the crucial and important data needed to make informed decisions to keep the business moving forward.

When mergers struggle to get off the ground it is often because the acquirers had not only failed to consider these data resources as a highly valuable asset but consequently, have also failed to put a quality data management plan in place for the post-acquisition stage.

In order to ensure a successful merger, companies need to include a data management plan as a central element of the due diligence phase and if possible, involve a CIO or data manager at an early stage in the process. He or she will be able to assess and advise on any weaknesses in the target organisation’s systems that present potential integration problems further down the line.


For any business or public sector body that is in the merger process here are a few questions that executives could usefully consider when assessing their own and their new partner organisation’s approach to quality data management.

#1 Is there a centralised data management system in place?

Many businesses operate with siloed departmental models with little or no sharing of data across the organisation. This can lead to not just multiple issues such as duplication, incomplete or inaccurate records but can also be costly in terms of time and resources wasted on activities arising from operational decisions based on bad data. Any time that can be focussed on developing a post-merger plan that creates a consistent, top-down data management system for the entire organisation will be time well spent to help ensure the ultimate success of the merger.

#2 How good is the actual data?

It is arguable that poor quality, unreliable data is worse than having no data at all. Data is the bedrock of all important business decisions and if it cannot be trusted or analysed with any certainty companies are basically operating blindfolded and trusting to luck. The challenge is knowing if the data is any good or not. But there are no real off-the-shelf tools that can be deployed to find out other to thoroughly test a randomised sample of the records. If this exercise reveals a high proportion of outdated and inaccurate data a decision needs to be made as to whether it should be retained at all. Merging good and bad data is never a recommended strategy and it is a good idea to remember the old adage “Garbage in – Garbage out” before finalising any plans to integrate legacy systems.

#3 Does your data management policy meet the latest Governance Standards?

Today any organisation that stores or processes personal data on their systems faces the prospect of significant financial penalties if any data is lost or compromised that is not properly managed and protected under the European General Data Protection Rules (GDPR). To comply, businesses need to be able to produce a written data management document that provides details of the policies and procedures put in place to govern where data is stored, who has access, how it is shared and what cyber security systems are deployed to protect it. This is something that cannot be left to the post-merger stage without creating the potential for major problems for the new organisation. Before moving forward to merge the business operations it is critically important to have a highly detailed data integration roadmap that can be shared and understood by all stakeholders and employees of both organisations.


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Your Data Quality Primer: Everything you need to know

Welcome to your Data Quality Primer from the iData Quality Academy – in this useful guide you’ll find everything you need to know to improve your understanding of data quality, assorted into useful categories for you. You don’t have to read through it in order, you can jump right to the section you’re interested in!

Your Data Quality Primer: Everything you need to know

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