When an acquisition happens, the acquirer isn't just buying software. They're buying potential synergy – the ability to unlock value neither system could achieve alone. That synergy doesn't happen automatically. It needs to be engineered. You can save tons of effort by making your system easy to integrate with from the start.
TL;DR
Data synergy is engineered, not bought: Build integration-ready systems.
Good practices: Improve APIs, centralize data, enable phased migrations.
Bad practices: Avoid custom systems, data silos, outdated tech.
Readiness delivers value faster: Integrate in weeks, not months.
As Marek Gajda, the co-founder and COO at The Software House, put it:
You can buy the revenue, you can buy the market, you can buy the talent, but you cannot really buy the synergy."
You’ll soon find out that these words don’t apply only to companies that face mergers and acquisitions, but also to any systems that try to integrate in any way.
This guide covers the dos and don'ts that help achieve data synergy and readiness for integration.
The post-M&A webinar that sparked the conversation
Marek’s words come from the recent webinar: “How to Avoid the Biggest Pitfalls in Post-M&A Tech Transformation”.
The webinar featured more experts, including:
Bart van Muijen, CEO of Pro4all
Adam Ludera, Head of Engineering at Sogelink Nederlands
Eyass Shakrah, co-founder of Pet Media Group
Data synergy emerged as a critical factor in post-M&A transformation projects. Panelists shared stories where hard-to-integrate code or databases turned quick wins into months of work. Time meant for building features was lost to incompatible data schemas and undocumented systems.
Inspired by their stories, let’s talk about why integration readiness gives such a competitive advantage.
Why does data integration readiness matter?
Data integration readiness means your system is designed to enable others to easily connect with your data and services.
It's about.
clean, accessible data
clear documentation
standard interfaces
The benefits of data integration readiness
Not sure if it’s worth the effort? How about these benefits:
Lower financial risk
Poor data quality costs organizations $12.9 million annually on average. Integration-ready systems help you avoid these costly surprises during M&A.
Faster time to value
When you're prepared, you can deliver measurable business value immediately after the deal, instead of spending months on migration and refactoring.
Higher valuation perception
Acquirers see you as a low-risk, high-synergy opportunity, which can positively impact deal terms and your perceived value.
Data-driven insights
Clean, centralized data enables in-depth customer analysis and the ability to train AI models, both of which are increasingly critical for acquirers.
Seamless customer experience
Integration readiness enables common authentication, shared data exchange, and unified experiences across platforms without disrupting existing users.
Let’s review the do’s and dont’s of data integration readiness.
Do’s of data integration readiness
Here are the best practices to follow on an ongoing basis to make sure that the integration will be easy whenever it comes:
Establish a single source of truth (SSoT)
Create one central place for all data. This eliminates conflicting information from multiple systems and forces clarity on which data sets are truly accurate.
Build robust APIs
APIs enable fast data exchange between applications. Ensure yours are comprehensive and well-documented so that external parties can utilize them effectively.
This approach worked for Pension Lab. As noted in the case study, the client was able to improve development productivity through API upgrades: "Some of the earliest efforts involved extensive API optimization. Where possible, we made sure that third-party platforms could feed data into our platform. That way, they could do much of their work on their side."
Document everything comprehensively
Your systems, data flows, and processes need documentation. Without it, technical due diligence becomes incredibly difficult. Acquirers want facts, data, and metrics, including code and infrastructure details.
Even better, as pointed out by TSH’s Head of Development, Andrzej Wysoczański, for Effective Delivery, you can write code so clear that it documents itself.
Maintain a sandbox environment
Provide a non-production environment where partners can test integration with simulated data. This allows them to assess compatibility upfront in a risk-free way.
Ensure data consistency and quality
Eliminate conflicting information and redundancy across systems. Implement quality checks when data first enters them. Consider a data warehouse for efficient management.
Prioritize data governance
Treat data as a strategic asset with clear ownership and governance policies in place. Establish these before any transition.
Separate legacy data
When decommissioning systems, preserve historical data and context. Many acquirers spend significantly on maintaining old applications solely because data wasn't archived properly for regulatory purposes.
Prepare for phased migration
Build modular platforms that allow incremental migrations instead of painful "big bang" approaches. This removes many modernization risks and makes it easier to convince stakeholders to go through with it, as noted by our CTO, Adam Polak, in his interview on software modernization.
Embrace AI integration
Acquirers are increasingly relying on data to train AI models. Prepare your data for automatic ingestion and updates to enable advanced operational synergies.
Consider a GenAI Rapid Prototyping workshop to refine your AI strategy and acquire expertise in this area.
Don'ts of data integration readiness
There are also things that you should avoid if you want to make it easier for other systems to connect to it:
Don't build unsustainable in-house systems
Custom solutions, such as homegrown authentication systems, seem fine at a small scale but become major burdens at an enterprise scale.
As Adam Ludera explained during the post-M&A webinar:
"We also have to remember that, for example, changing the authentication of the software is not that easy, especially if it is a homegrown system. If it doesn't have an ORM and everything is in plain SQL queries, and the entire authentication system is actually stored in the database, then it's much more difficult to transition to an SSO-based approach. It's much better if the acquired system is already using a framework for it."
He adds that it is especially true for startups.
"A lot of it has to do with building too much in-house. Things that you wouldn't think of building in-house are built in-house. This may work for a startup, but if you are a large enterprise, this is no longer sustainable. I recall situations where you would see a startup's software without any frameworks because you can't build them on your own easily."
Given how typical it is for a startup to aim for an acquisition, their leaders should heed Adam’s advice!
Don't rely on custom systems too much
Beyond authentication, avoid custom ORMs, security protocols, or identity management. If quality SaaS solutions exist, use them. Acquirers will often replace your custom tools with industry standards anyway.
Don't let your tech stack become outdated
Old technology or unsupported systems inflate integration costs and extend tech transformations. What seemed maintainable internally may be a liability for acquirers.
Don't create data silos
Scattered information across isolated, incompatible sources makes it difficult for acquirers to drive insights and severely hinders migration.
Don't ignore data quality at capture
Bad data enters through human error or technical faults. Establish quality checks when data first enters your system, not after it's polluted your database.
Don't neglect security basics
Operating without multi-factor authentication or with unsupported systems exposes significant risk. Acquirers must establish baseline controls, increasing costs.
Don't forget compliance tracking
Track privacy policies and user consent agreements. Post-acquisition challenges multiply when there are no clear records of which users consented to specific data processing, especially in regulated environments.
Don't create customized forks for clients (unless you absolutely have to)
Small, customized application forks on outdated infrastructure create hidden maintenance burdens, often discovered only when they break.
Don't delay modernization indefinitely
Running old platforms in maintenance mode may seem cost-effective, but it creates risk. Acquirers attempting rebuilds can get stuck where old systems add features faster than new ones can be built, potentially scrapping projects after years.
Post-M&A data integration: Making synergy possible
As you can see, integration readiness may determine whether an acquisition creates or destroys value.
To achieve data integration readiness that creates business synergy between two software products, consider these ideas:
Preparation beats remediation: integration-ready systems are low-risk; technical debt means months of fixes.
Standards matter at scale: Clean data, documented APIs, and standard tech make you more valuable as an acquisition target as well as the acquirer.
Time equals money: Ready companies deliver value immediately; unprepared ones waste time on migration.
Quality compounds: Poor data quality costs millions and multiplies in M&A, where small errors become big problems.
Want to learn more about post-M&A tech transformation?
Watch “How to Avoid the Biggest Pitfalls in Post-M&A Tech Transformation".
Authors
Adrian Senecki
Copywriter and budding fiction writer, interested in (but not limited to) the business side of software development. Likes acquiring new skills and foretelling the future.