The Hidden Risk of Institutional Knowledge in Entity Management

Every governance team has one person who knows where entity documents are, remembers why a subsidiary was created ten years ago and can explain an unusual ownership structure without opening a single file. 

For a long time, that wasn’t a problem. Governance has always been relationship-driven, so when information was difficult to find, teams built networks of trusted experts across legal, finance and tax. As organizations grew, that reliance on personal knowledge became the default, even as the work grew messier and more laborious. 

Today, however, that model is breaking down.

The enterprise operating model has changed

Entity management has changed significantly over the last decade. What was once treated as an administrative function now underpins restructurings, acquisitions, regulatory compliance and financial reporting across increasingly complex organizations.

The scale of that complexity is easy to underestimate. EY’s research on entity management found that large organizations typically manage between 100 and 500 legal entities, yet 76 percent of legal departments have five or fewer people dedicated to the work. The number of entities has grown, but the teams responsible for them have not.

That mismatch becomes hardest to ignore during a live transaction. A due diligence request lands, and instead of pulling together subsidiary schedules, ownership chains and board resolutions in an afternoon, the team spends days chasing them down.

Gartner found that the average time to close an M&A deal has grown by more than 30 percent over the past decade, with roughly 22 percent of that slippage attributed to inadequate technology supporting due diligence rather than the deal itself.

Knowledge concentrated in one person is a liability

Georgia Venetsanakos, VP of Corporate and Legal Strategy at Hitachi Digital, has lived this reality. "My nickname is ‘the vault’," she says. 

Before Hitachi Digital centralized entity management, information was scattered across spreadsheets and computers globally, and every time someone needed information, it turned into what she describes as "this huge drive to find that information, cross-check to make sure it was accurate."

Over time, she became the person everyone called. "The dial friend network would bubble up to me... I'd remember it from whatever year, go to this person or see if I could find it in my records. It's just not scalable. It's not workable."

Her experience isn't unusual. It's the same pattern playing out across governance teams everywhere, where experienced professionals spend less time applying judgment and more time retrieving information, validating data and answering routine requests. 

Turning expertise into governance infrastructure

The organizations making progress aren't documenting institutional knowledge. They're moving it out of inboxes, spreadsheets and memory into shared systems that authorized users can access directly, without routing through one person.

At Hitachi Digital, that shift changed how governance worked day to day. A sales operations team negotiating a contract could confirm the right entity and signing authority in minutes instead of routing the question through legal. 

Finance, tax, sales operations and legal could all access what they needed through role-based permissions, rather than relying on personal networks or the memory of a few people, and the results showed up quickly. 

"It has been a huge game changer not only for our daily operations but for our big corporate projects, our M&A, post-M&A integration. The productivity gains have been enormous,” Georgia describes.

‍Governance maturity is measured by resilience

Institutional knowledge will always be one of governance's greatest assets. Experienced professionals bring judgment, context and strategic insight that no system can replace. 

That's what maturity actually looks like: not one person who knows everything, but systems where the knowledge survives promotions, reorganizations, acquisitions and retirements long after any one person has moved on. 

It's also the foundation for whatever comes next. AI and workflow automation don't create structure, they depend on it: a model can only reason over entity data that is easy to find. 

The organizations best positioned for what's ahead won't necessarily be the ones with the most experienced governance teams. They'll be the ones that turned what a few people knew into something the whole organization can rely on.