Data Vault 2.0 – A Decisive Advantage For Successful Mergers & Acquisitions

The simple act of one firm buying the assets or stock of another firm is no longer a boardroom transaction hidden away from public attention. We need look no further than the play-by-play storyline reported in the popular press about the Elon Musk – Twitter sweepstakes to witness how the contest plays out in a largely public arena. And like a dramatic, competitive sporting event, we can’t take our eye off the action. We choose sides, speculate the moves, and predict winners and losers in the same sort of way we watch any other match.

Why the fascination? Because these transactions, categorically referred to as Mergers & Acquisitions (M&A), can change the landscape of a market in one click of a DocuSign autograph. Wealth changes hands in an instant, competitive advantages are won and lost, and customers are asked, usually without their permission, to adapt to new paradigms for buying and seeking services and support.

And M&A activity is more prolific than you might imagine. In the US alone, Statista reports that over 20,000 transactions closed in 2021, up from about 15,000 in 2020. Some are huge. 675 acquisitions were valued at over $1B in ’21, more than double the count from ’20.

Data, as it turns out, and our ability to manage it, is vitally important to the endeavor. The phenomenon is most acute during the due diligence phase of the acquisition process, and again shows its face during the integration phase, just after closing. Let’s look at each, one by one.

 

The Importance of Data In Due Diligence

Once a firm takes an active interest in another, and drafts a term sheet specifying high-level transactional expectations, it’s time to dig in. Due diligence (DD), an exercise that can last anywhere from a few weeks to several months, strives to confirm the statement, “If this is what we think it is, and find no surprises, we commit to move forward and close the deal.” Finding hidden surprises, then, becomes the not-so-subtle agenda for the acquirer. “Show me everything you’ve got,” rings like a Gregorian chant through the halls. The mood is tense. The demands are relentless. The stakes are high.

“Everything” includes, well,…seemingly everything: P&L statements, balance sheets, leases, distribution agreements, tax filings, pending and potential lawsuits, employee contracts, customer contracts, warranties, and other legal documents. A lot of it is largely mechanical, check-the-box sort of stuff.

But the bombshells are often found in the way a to-be-acquired entity represents their management reports to the acquirer. The stories are often rosy, perhaps even inflated, in characterizing growth, margins, employee productivity, market share, etc. After all, these stories are what attracted the potential acquirer to the party to begin with. In the cost accounting and BI systems that embed business rules, data of all sorts is curated, transformed, aggregated, analyzed, and presented.  It is in the interest of the acquirer to penetrate narratives laced in excessive optimism, marketing spin, and outright propaganda. While, on the other side of the table, it is in the interest of the to-be-acquired party to defend their data, their analysis, and their stories about their business. All this, while the clock is ticking. Time is of the essence to validate, substantiate, and build confidence in the transaction before anyone signs the dotted line. No surprises.

Auditability and Access To History Data

Data Vaults, in this scenario, are invaluable. In fact, they are nothing short of godsends. Scraping away to validate data can only be done expeditiously if said data is well organized and defensible to attack. “How did you get that result?,” must be answered with a concise description of metadata and data lineage, rooted in rigorous methodology that put the data there in the first place. Data Vaults, by definition, provide this grounding. History data? No problem. Compare and contrast exercises based on variables such as time, product line category, customer demographic, and more, are all there for the taking.

The acquirer, then, still not satisfied and smelling a rat, asks, “But the rules for how you measure employee productivity are different now than they were 5 years ago. What would the graph look like if you re-ran the numbers using the old rules?”

Data Vaults, here again, are most resilient to the inquisition. Version control for business rules are inherently embedded in the methodology. “Knock yourself out, acquirer. We can run it all again with whatever business rules you want. We can show old data with new rules, or new data with old rules. Either way, you’re going to see that our data hangs together, and our narrative is sound.”

Validating data under different rule-based conditions, often retroactively, can be one of the most difficult of activities during DD to fulfill for firms that don’t have a Data Vault installed. Product lines change. Organizations change. Accounting practices even change. One can imagine the what-if game turning into a nightmare if the forensic minded acquirer smells blood in the water after the first, or second, busted storyline because data couldn’t hold up to the desired context in time travel. It could be a deal breaker.

Data Vaults, and the data they contain, accelerate an understanding and ultimately can provide a validation of narratives that are essential to the due diligence process. The DD process goes faster, more reliably, and with more accurate outcomes when the data lives in a Data Vault.

Data Vaults Ease The Burden In The Integration Stage

Once the deal closes, any CDO or COO of tenure will tell you, “Now is when the fun starts.” While the executives are busy popping Champagne, it is the folks responsible for “integration” that begin to feel the heat. How do we make sense of all these systems they-have with the systems we-have? Invariably, the newly acquired firm runs their business, including their analytics environment, on completely different systems. Some, like payroll systems, present an immediate challenge after the deal closes. People want to get paid and maintain near-zero patience for delays and errors. Good luck to those responsible for sorting it out.

Countless other operational systems, “source systems” in the analytics sense, are also undoubtedly running in alien environments in the acquired firm. CRM, ERP and L-M-N-O-P all have to be integrated. We use Salesforce. They use HubSpot. We use Oracle Financials. They use NetSuite. On and on it goes. In many cases, the new systems are left in place for a good while, perhaps indefinitely, just to keep the business operating.

Consider the impact of all this on analytics and BI. Existing BI reports and analytics applications operate based on current source data, utilizing some chosen set of business facing tools, such as Tableau and Alteryx, for example. BI and analytics applications in the newly acquired firm pull their data from different systems and use a completely different set of business facing tools, perhaps Power BI and the Microsoft stack.

Integrating the front-end tools, though not trivial, is not the hard problem. We can, through training and corporate policy, positively affect employee behavior so they productively utilize new and different tools. Though tools differ in their look, feel, and capability, practitioners are generally resilient to the switch. They learn what they have to learn, and move on.

The much harder problem, usually, resides in the back end. How do we integrate new sources of data into our existing data infrastructure? Data has to be reloaded, remodeled, and re-jiggered for downstream processing. The prefix, “re,” is derived from Latin and represents what linguists define as “meaning again-and-again.” Think about all the tables in our environment that must be redone (literally re-engineered). Staging tables, derived tables, aggregate tables… Oh no, it sounds like a lot of work. And indeed, for many firms, it is. It can take years to redevelop the environment.

However, if the firm doing the acquiring has a Data Vault installed, the daunting problem of integration is tamed. As Data Vault enthusiasts know, adding new source systems to a Data Vault is a cornerstone payoff of the architecture. We deploy Data Vaults because we expect to add significant amounts of new source data over time. The key term here is “add,” not “redo.” The Data Vault approach is iterative, rather than build-rebuild-rebuild-some-more.

The result? Organizations with Data Vaults installed integrate new source data more rapidly, more rationally, and more accurately than those deploying other data management methodologies. Business analysts gain more immediate results from richer, more complete data. Managers and executives enjoy the fruits of integrated reports. It all happens faster, and more reliably, when a Data Vault is in the mix.

And as a bonus, if a newly acquired firm also has a Data Vault deployed, the work is even less burdensome. It’s not just a matter of due diligence going more smoothly, but the integration post-close is also simpler. Taxonomy, ontology, and semantics are transparent and instantly leverageable. And for the acquiring firm that has corporate governance as a consideration, bringing on a firm that has intrinsic data governance embedded in their Data Vault environment is, well, a gift. The whole thing is that much easier to cope with.

So, on the subject of mergers and acquisitions, the case for Data Vaults is as intelligible as it is compelling. Too many deals fall over in the due diligence phase because narratives, seemingly attractive, become indefensible or are left ambiguous when it comes to the critical data required to prop them up. And once a deal closes, too many organizations are saddled with excessive costs, delays, and ultimately, manufactured excuses to explain away the lack of responsiveness, perpetuating a compromised status quo.

Are you working for a firm that hopes to offer an exit for your investors? Or do you work for a company more inclined to pursue acquisitions as part of their growth strategy? Either way, you owe it to them to present the facts. Choosing to implement a Data Vault is not just some random decision, only to be debated by data architects and engineers based on fleeting or esoteric logic. Your business’ chosen methodology for their analytics foundation is critical to their resiliency. The choice matters.

 

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