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Planning Your Data Estate Post-Acquisition

One truth about technology-focused roles is that mergers and acquisitions will never stop. Companies see value in purchasing proven companies, technology and teams to accelerate growth and break into new markets. As you gain more responsibility in your organization, you will likely be asked to participate in these transactions.

A virtual assurance when you work as the Chief Data Officer, Chief Architect or Head of Product is that you’ll be tasked with planning the integration of an acquired company. You will work as part of a large team, each focusing on HR, marketing, sales, facilities and technology integration. Your focus will be maximizing the value of the acquired company’s data assets.

The executive team will look to you for detailed analysis and supporting plans for the value of the data the acquired company brings to the new, larger organization. They will expect detailed plans for integration, specifics on how to accelerate the process and maximize the value of the acquisition, zero disruption to existing revenue streams and what amplifying aspects come from the value of the new company’s combined data assets. This plan must include costs for integration and different options with tradeoffs for speed, compliance, capability and market conditions.

Your First Steps Post-Acquisition

As you engage in this discovery and planning process, you will need to identify multiple workstreams, identify supporting resources, and identify target timelines.
  • Data Discovery – This work track focuses on inventorying all data assets in the newly combined company, identifying regulatory requirements governing each and identifying the subject matter expert or data owner. This discovery supports later evaluation stages where teams will dig deeper into the datasets’ quality, completeness and current places of creation, enrichment and consumption.
  • Value Modeling – Acquisitions are justified on the additive value of the newly combined company. Data assets are part of this value, and the datasets identified above need to be measured by their reach, depth, completeness and measured value. In addition to value, the risk of the dataset for loss or compromise can be identified to feed the investment strategy post-acquisition.
  • Journey Documentation – To fully understand our data assets, we document usage and where value-added processes can be automated or data science predictions can be applied. We document the journeys of our customers and employees and where the stages of data value consumption and creation occur. Identifying and documenting key journeys allows us to better understand where to collect additional data for value-add capabilities and where to inject data products for enhanced experiences.
  • Systems Analysis – Our assessment should include our data assets and the systems that store, process, protect and transform our data. This inventory enables the functional teams to identify duplicate functionality deployed in the newly integrated organization.
  • Future State – The culmination of the above information and our business objectives becomes the future state data estate plan. This plan incorporates critical decisions about dataset retention, data integration, systems and technology roadmaps, and organizational enablement plans. These plans collectively become our transformation plan to maximize the value of the combined entity. The anchor for our future state plans is our target state journeys for customers and employees and what data is needed at each stage to be highly effective and impactful.


Post-Acquisition Planning

As we assemble our future state plans, we have many options for planning the disposition of the data and systems we have identified. Each option brings a different balance for speed, retention, and transition costs that must be balanced with the acquisition goals and complexity of systems and datasets. Our planning unit will be the datasets we identified earlier, but we will have a close relationship with the systems when planning the disposition post-acquisition.

  • Maintain – The maintain disposition identifies that a given dataset and its record systems will be left in place post-integration. They will be maintained and invested in based on their usage in the organization and the business criticality. This is often the lowest-cost approach during an acquisition with varied long-term costs associated with the system’s age and complexity.
  • Integrate – Often times in acquisitions, duplicate functionality will be identified. In these cases, a decision is often made to integrate the redundant systems, pulling the best-of-breed technology into a single platform for the new integrated business to consume. This approach will cost more than a maintained disposition but will often provide lower long-term costs by rationalizing and retiring unneeded technology capacity.
  • Modernize – Modernize goes beyond the integration of duplicate systems and enhances functionality. We will pull capabilities from both companies’ technology portfolios but additionally make investments in bringing the capabilities onto modern platforms, using modern programming techniques and adding advanced capabilities. This will often be the most expensive upfront cost for an integration, but it will provide the highest level of functionality to the business. This approach allows the newly integrated organization to ensure that technology meets the goals and objectives of the newly integrated organization.
  • Retire fast – For systems with compliance risks or high operation costs, it’s common to develop plans to retire the systems, retrain users on the new business processes and archive the data for required legal hold or later use. This can often be the lowest upfront cost and allow for a move toward zero operations costs. This decision can be made for functionality and data no longer needed or a duplicative set that does not warrant integration or modernization investment.
  • Retire slow – For functionality that the business requires longer or additional time to retrain staff on new processes, there is the alternative to retire the system and data over a longer period. The operations cost for this approach can be higher but will eventually approach zero as the system is eliminated.

The decision to keep data post-acquisition has several components. The usability and value of the data are first and will drive our level of investment for the protection, analysis and exposure of the data. But often, legal requirements for legal hold or other retention policies will drive a need to retain data, even if it’s in a way that takes significant time to access due to the low number of access requests.

Tech debt is often a consideration for post-acquisition plans for systems and datasets. Usually, the integrated company will have duplicate functionality. Teams must determine how best to utilize the most modern capability, retiring the older systems and moving all data into the newly integrated system. This elimination of tech debt can provide lower long-term costs and better acceleration with a more straightforward addition of new functionality and features.

The most significant risk to any acquisition is the cultural transition. Two distinct cultures must come together, make decisions about a unified direction and manifest that through journeys, data, systems and processes. This data discovery and future state planning is only part of the more extensive integration planning that must occur but is a crucial component to ensuring revenue streams are protected and enabled to grow in the newly integrated organization. Every acquisition is hard, but with thoughtful planning, methodical analysis and singular goals and objectives, you can ensure acquisitions you participate in are successful.

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