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Synergy is the promise of every M&A deal. But how do you find it? Our latest article shares a counter-intuitive strategy that puts data at the heart of integration, unlocking hidden opportunities and accelerating results.
Discover how a “Data First” mindset can transform acquisitions into true engines of growth.
Imagine this: Two companies, eager to combine forces after a successful acquisition. Excitement quickly turns to frustration as they slam headfirst into IT integration. The acquiring company insists on forcing its IT systems onto the acquired company. Data gets lost in translation. Teams resist the changes. Months drag on, budgets balloon, and the promised synergies remain elusive. Sounds familiar?
Too often, M&A integration starts with the wrong question: “How quickly can we integrate them into our systems?” This leads to costly, disruptive, and often unsuccessful projects, with sometimes a divestment a few years later. As systems from both parties are often not easy to integrate, here’s now a better way. A way that unlocks value faster, minimizes risk, and paves the way for a truly integrated future. That way is to focus first on data integration to realize the business case before working on system migration.
The Traditional Approach and Its Problems: A Recipe for Disaster
Traditional M&A integration is often a high-stakes game of IT tug-of-war. The acquiring company, often driven by a desire for standardization and control, or for regulatory requirements, attempts to force its systems onto the acquired company. This usually means ripping and replacing systems that have served the acquired company well for years, and destroying value for which the company was acquired:
The problems with this approach are legion:
- Lost opportunity: Differentiating capabilities brought by the acquired companies are lost, compromising the business cases for the acquisitions
- Frustration: This leads also to frustration among employees who have to learn new systems, unfit for their business. This leads to decreased productivity and increased errors.
- Capacity constraints: The acquiring business faces capacity constraint to run their business while transforming to integrate the systems
- Resistance to Change: Employees who are comfortable with their existing systems often resist change. This can lead to conflict and decreased morale.
- Costly and Time-Consuming: Full system integration is a complex and expensive undertaking. Projects often take longer and cost more than expected. The PMI period is always too short to succeed a diligent system integration.
- Missed Synergies: By force fitting IT systems into another one, companies often miss opportunities to identify and realize synergies.
Ultimately, the traditional approach often results in a clunky, inefficient IT environment that exceeds the PMI period without delivering the promised benefits of the acquisition.
The “Data Integration First” Approach: Building a Bridge, Not a Wall
The “data integration first” approach flips the traditional integration model on its head. Instead of focusing on migrating all systems, it prioritizes sharing data in a way that allows the two companies to “speak” to each other, wherever the systems are not a good fit, or when some capabilities are missing.
This involves several phases:
- Understand the value: Early on, during due diligence or shortly afterwards, understanding which data is needed to capture the value for which the business was acquired. It will of course differ whether it is a component of a solution, a market expansion, or a service matching existing capabilities.
- Focus on the value: Then, and as soon as the business/markets are ready, integrate this data to capture this value leveraging technologies such as Azure/AWS data lakes, or setting up APIs.
- Focus on Synergies and Productivity: In parallel to this phase, the acquiring company can decide, based on priority or availability of the capabilities, to migrate gradually the processes or to build missing capabilities. This effort can last possibly beyond the PMI period, but at a pace/prioritization in synch with enterprise IT development plans, until complete integration and decommissioning of non-compliant applications.
This approach offers several key advantages:
• Faster Time to Value: You can start realizing the benefits of the acquisition more quickly by focusing on data.
• Accelerated data reporting for the leaders: Getting actionable information to the executive leaders will speed up the transformation
• Reduced Risk: You minimize disruption to operations and reduce the risk of project failure.
• Increased Agility: You create a more flexible and adaptable IT environment.
• Improved Understanding of the Acquired Business: You gain deeper insights into the acquired company’s operations, customers, and products.
Building a share data layer: the options
Creating a shared data layer may seem daunting, but current technology now offers different options:
- Leveraging a data lake, a centralized repository that can store large amounts of raw data in its native format. Acquiring companies may alreadu have one in place, that can be use to store and analyze data from the acquired company, along with the existing company data
- Using API (Application Programming Interface) , which allows different IT systems to communicate and share data. This is the best option for data that requires real time access.
- More and more IT systems (like SAP, Oracle, Workday, Salesforce…) offer standard API that do not require custom programming.
- In addition to the standard APIs provided by ERP and CRM vendors, there are also low-code/no-code integration platforms that can be used to connect these systems with other applications. These platforms often provide pre-built connectors and templates for popular ERP and CRM systems, making it easier to set up integrations without extensive effort.
These options must be considered taking into
Benefits of the Data-Centric Approach: Unlock Synergies and Insights
The benefits of a data-centric approach to M&A integration extend far beyond basic system interoperability.
• Enhanced Reporting and Analytics: Combine data from both companies to gain a more comprehensive view of the business. Identify trends, patterns, and opportunities that would be impossible to see with siloed data, like sales, funnel, manufacturing quality….
• Improved Decision-Making: Provide management with the data they need to make informed decisions. For example, sales data can be combined with marketing data to optimize marketing campaigns.
• Increased Efficiency: Automate data sharing and reporting processes. Reduce the need for manual data entry and reconciliation, especially at a time when leaders track closely the synergies from the acquisition.
• Data-Driven Synergies: Identify opportunities for synergy based on data analysis. For example, you might discover that the acquired company has a more efficient supply chain or a more effective sales process.
The ERP Transformation Angle: A Life-Saver During Change
The “data integration first” approach is especially valuable when the acquiring company is undergoing a major IT transformation, such as an ERP implementation. In this scenario, the data layer can serve as a staging area for data migration to the new ERP system.
The acquired company can continue operating on its existing systems while the ERP transformation is underway. This minimizes disruption to their business. This also reduces the risk of data loss or corruption during the ERP migration process, as the data has already been extracted, transformed, and validated in the data lake.
Integrating Larger Companies:
Even when acquiring larger companies, the “data integration first” mindset is crucial. The data layer becomes a neutral platform, enabling you to understand the acquired entity’s processes and data landscape without imposing immediate system overhauls or while the acquiring entity is building missing capabilities.
Examples: Learning from Success
A large multinational (let’s call it Alpha), historically selling high end hardware acquired a young agile digital company (let’s name it Beta). Both sides could see the value of the deal, in terms of product portfolio expansion for Alpha and in terms of customer reach and brand reputation for Beta.
At that time, Alpha insisted that all systems would be migrated within a few months to their landscape, and all other systems decommissioned as it seemed the only way for the company to stay compliant in its heavily regulated environment. It seemed reasonable as both companies were using systems like SAP and Salesforce.
Result after a few months into Post Merger Integration:
Some success:
Salesforce was indeed integrated, and enhanced by several standard capabilities that had not been used yet by Alpha.
A Big Challenge:
On the ERP front, it was a different story. Alpha’s ERP was heavily customised to its legacy business, and after quite some development work, significant training of the super users, and significant resistance, the deployment was blocked: it turned out that a critical capability couldn’t be deployed in Alpha’s current ERP, without months of further customisation on a system that was already end of life.
Data integration as a solution:
Data integration using APIs allowed Beta to keep using this capability, and continue to offer a good customer and employee experience, while being fully connected to Alpha’s ERP and downstream financial systems.
In parallel, Alpha’s ensured that this critical capability would be deployed in the next ERP version, without troubling this massive cross company deployment. Once the new ERP would be in place, with the capability, Beta would then be integrated.
Learning: This data integration allowed to capture right away the value from the integration, while staging the system integration. This minimized the impact on the business while allowing the product portfolio to be combined.
Tools and Technologies: Building Your Data Integration Arsenal
A variety of tools and technologies can be used to implement a data integration strategy:
• Data Lakes: Amazon S3, Azure Data Lake Storage, Google Cloud Storage.
• API: standard API offered by ERP and CRM vendors, MuleSoft Anypoint Platform, Dell Boomi, Zapier…
The choice of tools will depend on the specific requirements of the organization, the pace of integrations, and the business value to be captured from the acquisition.
Overcoming Challenges: Be Prepared for Obstacles
A data integration approach is not without its challenges.
• Data Quality Issues: Data quality is often a major concern in M&A. It’s important to establish data quality standards and implement processes to clean and validate data.
• Incompatible Data Formats: The two companies may use different data formats. ETL tools can be used to transform data into a common format.
• Lack of Data Governance: Data governance is essential for ensuring data accuracy and consistency. It’s important to establish data governance policies and assign data stewards to oversee data quality.
• Resistance to Change: Employees may resist the change to a data-centric approach. It’s important to communicate the benefits of this approach and provide training and support.
Conclusion: A Smarter Path to Integration
The “data integration first” approach offers a smarter, more effective way to integrate acquired companies. By focusing on data, you can unlock value faster, minimize risk, and pave the way for a truly integrated future. So, before you launch your next M&A integration project, ask yourself: Are you building a bridge, or a wall? The answer could make or break your success.
However, before embarking on even a data-centric integration, a critical prerequisite is crystal clarity on the shared vision for the integrated entity. Define the target business model, the go-forward operating model, and the strategies to achieve this “North Star” vision. Data integration should enable that shared vision, not drive it. Without this guiding star, even the most elegant data integration strategy can lead to a well-connected, but ultimately misdirected, organization. One of the key strategy is the data integration first for success. The common vision should be based on clear objectives which have measurable goals.
