Tech mergers tend to be flashy, attention-grabbing affairs — but more often than not, they simply don’t deliver. In fact, a 40-year analysis of roughly 40,000 merger and acquisition deals found that 70-75% of such deals fail.

While there are a variety of contributing factors that cause mergers in tech and other industries to fall short, Dr. D Sangeeta, founder and CEO of Gotara, believes that better data-driven integration can go a long way in addressing many of these challenges. By focusing on data during the integration process, merging tech companies can minimize disruptions and ensure that their union actually brings about the desired results.

Complex Challenges Hindering Tech Mergers

“A lot of tech mergers look good on paper, but the leaders involved don’t realize just how much work is involved after the deal is complete,” Dr. Sangeeta explains. “Without a clear roadmap for how systems, teams and data will be blended, the end result is often little more than a confusing mess. Full integration takes time, but without leadership to guide how this process will play out, the end result can negatively affect employees and customers alike.”

In the context of PMI, “data” refers to the operational, financial, customer, workforce and technology stack signals that reveal how each company truly functions beneath the surface. This includes everything from product usage telemetry, profitability by segment, customer health scores and support ticket patterns to engineering workflow data, integration bottlenecks, system redundancies and organizational performance metrics.

When this data is unified, normalized and analyzed early in the integration process, leaders gain a fact-based roadmap for how to combine operations, eliminate overlap, sequence technology decisions and standardize processes. 

Even among tech companies themselves, a lack of a clear plan often results in failure to dial in on the realities of technology integrations. McKinsey reports that “most IT issues are not fully addressed during due diligence or the early stages of post-merger planning,” usually because not all data is shared by the parties involved in an attempt to raise their valuation, even though as many as 60% of merger initiatives are closely related to IT in any industry merger.

As Dr. Sangeeta notes, “Tech mergers are often hindered by insufficient due diligence, unrealistic timelines that fail to account for the complexity of both sides’ tech and data operations, different methodologies and standards among the two organizations’ tech teams and poor, inconsistent or incomplete data sets. All of this can make the merger far more complex and costly than anticipated. Without directly accounting for these key areas, it can be hard for the merger to deliver true value.”

Of course, these tech-specific challenges come on top of other issues that can negatively impact a merger, such as cultural incompatibility between the organizations, service disruptions leading to customer attrition and even the loss of key talent as a result of the merger. An inability to share and collaborate on data can make organizations less efficient than they were previously, and a lack of quality data can contribute to poor decisions both during and after the merger.

While Dr. Sangeeta acknowledges these as critical issues that can derail any merger, she also believes that data-driven integration can be a powerful fix.

How Data-Driven Tech Integration Provides the Fix

Data-driven tech integration typically refers to the strategic use of data, analytics and modern technology systems to unify two organizations’ operations, processes and decision-making frameworks after a merger or acquisition. Instead of relying on assumptions or legacy workflows, this approach leverages real-time data, from customer behavior and product performance to operational efficiencies and workforce patterns, to guide integration priorities. 

“Using data to guide decisions helps remove bias from the two parties involved in a merger, which is perhaps the most important factor of all. When due diligence is performed prior to the merger and appropriate preparatory steps are taken, data can become the most powerful tool in fully integrating two organizations,” Dr. Sangeeta says. 

This requires that leaders come together before or right after the merger closes to develop a strategy tailored to the specific data platforms and metrics that they have been using. This helps leaders tackle big data challenges in advance, such as identifying incompatible systems and processes, or identifying who will need different data dashboards for their work. Evaluating each organization’s data maturity, beginning data integration early on and centralizing and harmonizing data assets is critical.”

With data-driven integration at the forefront of the merger, leaders can enjoy greater transparency regarding key metrics, and also ensure that other employees within the organization have access to the critical information they need to perform in their adjusted roles.

As Dr. Sangeeta explains, a data-driven approach also drives positive outcomes for what she describes as the three pillars of successful integration.

“The first pillar is business problem solving — rallying everyone with measurable outcomes, including goals for employee and customer satisfaction. Next is program management, which is designed to keep tasks on track with clear plans and timelines for each project. Quality data is key for minimizing disruptions and enabling accurate analyses for this pillar. Finally, data can support the pillar of culture and leadership integration by demonstrating whether business goals are being met and helping leaders identify areas for improvement.”

With data serving as the baseline for supporting these pillars, business leaders can achieve full integration in a shorter timeframe and with fewer major disruptions for employees and customers. Focusing on agreed-upon metrics and looking for ways to fully incorporate data at each level of the organization helps support alignment initiatives with quantifiable information.

A Smarter Approach to Tech Mergers

While data-driven integration won’t solve every problem (particularly when the organizations refuse to come together on cultural or strategic alignment), it can still go a long way in alleviating many of the issues that trip up these mergers in the first place.

Instead of integrating based on assumptions or legacy dynamics, executives can use real-time insights to determine which systems to consolidate first, where talent gaps or duplications exist, how customer experience will be impacted and which integration tasks will drive the greatest enterprise value fastest.

With data as the foundation, tech mergers can succeed with enhanced delivery of their products and services, more efficient operations and better data visibility to enable smarter decision-making. Data should never be an afterthought. It should be a front and center consideration in all aspects of the merger.