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M&A data storage integration challenges and how to tackle them

The need for efficiencies after mergers and acquisitions affects all IT operations. But data storage also raises issues around security, privacy and the reuse of data

Stephen Pritchard
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Published: 29 Jul 2025

To integrate operations as smoothly as possible following mergers and acquisitions (M&A) is always a challenge. Businesses want to keep revenues flowing and to cause as little disruption to customers as possible while they restructure behind the scenes.

When it comes to technology, this often means integrating a range of different and potentially incompatible systems. This carries risk. Alternatively, firms can keep separate IT systems running, but with higher costs and fewer efficiencies. Data storage is no exception.

To merge storage systems, however, offers the prospect of benefits beyond savings on hardware costs or cloud fees.

Integrating data is essential to efficient workflows across a merged business. And applications that include advanced analytics and artificial intelligence (AI) work better with access to larger pools of data. The challenge for CIOs and data architects is to achieve integration without disruption.

The approach taken by IT teams will depend as much on the business drivers behind the M&A as on the technical architecture of the organisation. Firms also need to comply with data protection laws and industry regulations, as well as any post-merger requirements set out by competition authorities.

Financial analysts typically split M&A into “scope” and “scale” deals. Scope acquisitions seek to broaden activity by entering new markets, bringing in new and often complementary products or technologies. Scale deals typically involve buying a direct competitor to increase market share.

Both types of deals offer the potential for IT integration. Scale acquisitions usually bring the most immediate push for efficiencies. If businesses sell a broadly similar product or service, there is likely to be more overlap between IT systems and business processes. In a scope acquisition, products, services and markets might be far enough apart to limit the drive for IT and storage integration, at least in the short term.

But in both cases, merging systems offers the chance to drive more value from company data, provided the process is planned and executed with care.

“M&A storage strategy boils down to one question: Are you integrating for agility or inheriting inertia?” says Darrel Kent, field chief technology officer (CTO) at analyst firm GigaOm. “Consolidation creates the opportunity for clarity – operationally, financially, and in risk posture.”

Some companies have become very effective at merging IT operations over multiple acquisitions, with data storage the final part of a complex integration puzzle. 

Increasingly, however, making integration work means establishing the value of data across both businesses, and understanding where data is held, whether in on-premise systems, co-located datacentres or the cloud.

Without that data picture, IT management teams cannot start to consolidate storage hardware or services. Skipping this step can put data integrity, accessibility and even security at risk, and increase the chance of disrupting business operations.

“What we often talk about as being a big challenge in organisations today, especially larger ones, is data management,” says Patrick Smith, field CTO at storage supplier Pure Storage.

“Do you understand what data you have got? Who owns it? Where does it sit? What business services does it support? And what are the dependencies?”

Integration risks

To save money, boards will likely want to integrate IT systems and remove excess capacity. For storage, this will mean decommissioning storage arrays and associated networking equipment, or, in the case of hyper-converged architectures, entire systems.

Organisations will need to ensure that doing so does not impact the performance and resilience of business systems, by removing redundancy, for example. They will also need to check the commercial terms for their storage systems, including maintenance and support.

It would not, for example, be worth switching off systems immediately and migrating data if there is a hosting, support or maintenance contract with years left to run and which cannot be cancelled.

To decommission storage in the cloud is easier, at least on paper. But again, CIOs need to look at the commercial aspects of cloud contracts. Moving data between cloud providers usually attracts egress fees, and cloud pricing might be based on a commitment to use a certain capacity.

Firms need to look at the details to ensure cost savings from spinning down capacity with one provider are not outweighed by higher charges elsewhere. For both cloud and on-premise storage, this “finops” work is vital.

Then there are risks that come with data migration, whether between cloud providers, from on-premise arrays to the cloud, or from cloud to the merged organisation’s on-premise storage.

“The integration period creates vulnerabilities,” warns David Boland, vice-president of cloud strategy at cloud data storage company Wasabi. “Employees from both organisations suddenly gain broader access to systems, data and intellectual property they’ve never seen or touched before.”

There are IT security risks, too, he suggests. “IT managers face a delicate balancing act between maintaining operational continuity while protecting valuable assets, including data, during organisational upheaval.”

AI opportunities

But while data storage integration brings risks, it also offers benefits. These are increasingly important as organisations seek to gain value from data via advanced analytics applications and to train AI models.

Only 10 years ago, organisations might have had little interest in keeping older data, such as archives or backups, after a merger or acquisition. The exception was where regulators required lengthy periods of data retention.

Now, though, the rush to train AI models has pushed organisations to look again at “cold” data and see whether it has commercial value.

“I think organisations are taking a more strategic view of their data strategy,” says Simon Robinson, principal analyst at Enterprise Strategy Group. 

“It doesn’t necessarily always come down to, where does the storage sit, and where does the data sit, and on whose system? There is a broader trend for organisations to take a more holistic view of their data assets and to ask whether they have the right foundations in place to optimise their data, wherever that might be,” he adds.

“When acquiring companies, do we have a consistent model to bring in data in, and to understand what data we have and where it is? In the past, there was a standard operating assumption that data had a value for a period of time and then we got rid of it. Now, I might pump that into an AI training model and get some value from it.”

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