First-Party Data’s Acquisition Problem

In my last post I talked about the challenges of acquiring quality data, particularly first-party data: that which a company collects from its sources. First-party data is the gold standard, costliest, and most challenging to acquire, keep, and maintain.?

First-party data is so challenging because right now, the industry standard tool for gathering, sifting, and applying data is people, and people are resource-intensive. They can also invalidate data by making errors, which, if undetected, can lead to downstream hallucinations and misguided decisions.

On top of that, every organization has its own tailored data needs, so unlike some other tech, you can’t necessarily acquire your way into first-party data that suits your needs.??

Why? First-party data is bespoke, and integrating data acquisitions into existing data adds complexity. A private equity Firm might have fifteen investments or acquisitions with different data needs. Returning to the water metaphor I referred to in an earlierlast post, they each need to drink from a separate spigot.

Financial Reporting and Accounting:

Imagine a private equity firm that has acquired fifteen businesses, each operating in a different industry. These businesses might have unique financial reporting systems, charts of accounts, and accounting practices. Integrating their financial data into the parent company's reporting framework could be like drinking from multiple spigots, where each faucet represents a different monetary system. Consolidating this data for accurate financial reporting would require substantial effort to map and standardize the data across diverse systems.

Customer Relationship Management (CRM):

Consider a scenario where the private equity firm acquires businesses in various sectors such as retail, healthcare, and technology services. Each business might use a different CRM platform to manage its customer data. Integrating these systems means dealing with differing other data structures, custom fields, and customer segmentation methods. Like drinking from distinct spigots, eExtracting and merging customer information from these various CRMs would involve a complex process to ensure a unified view of the customer base.

Supply Chain and Inventory Management:

Now, envision the private equity firm acquiring manufacturing, distribution, and e-commerce companies. Each of these businesses might have its supply chain and inventory management system tailored to its specific industry requirements. Integrating these systems into a cohesive supply chain operation for the entire portfolio would require aligning disparate processes, data formats, and inventory tracking methods. There are different neeeds This integration process can be likened to drinking from separate spigots for each type of product, and harmonizing themit involves streamlining processes and data flows.

Human Resources and Payroll:

Suppose the private equity firm acquires companies with varying employment structures, from traditional offices to remote freelance networks. Each company could use different HR and payroll systems, leading to diverse employee data formats and compensation structures. Just as each spigot provides a distinct water source, each HR system provides unique employee information. Merging this data requires defining standard data fields, pay scales, and benefits across the acquired companies.

Marketing and Sales Data:

The marketing and sales data would vary significantly when the private equity company acquires businesses ranging from B2B software providers to consumer goods retailers. Different industries might utilize distinct marketing automation platforms, sales CRM, and analytics tools. Integrating these data sources into a unified marketing and sales strategy could be compared to coordinating water flow from different faucets, ensuring that insights from each source contribute to an effective overall strategy.

Managing data acquisitions with different needs can be tricky, much like managing water sources from various spigots. Each source provides valuable information, but aligning and merging them requires careful planning, data transformation, and standardization to create coherent and insightful value for the entire organization.?

A cost-effective workaround would be to screen second and third-party data accurately enough to make it a viable alternative to the classic definition of “first party.” I’ll have more on this idea later.?

The bottom line is this: we can work to democratize software all we want, but until we can unblock data, we’ll never achieve proper integration.