How to discover, interpret, and influence the real power structure inside complex buying groups

Why the org chart no longer explains decisions

In modern B2B buying, formal titles are weak predictors of how choices actually get made. Buying committees are large and cross‑functional—on average ~13 stakeholders participate and 89% of purchases involve multiple departments—so authority is distributed and influence is negotiated in motion, not fixed on a chart. That dynamic helps explain why 86% of purchases stall at some point despite apparent “sponsorship.” These are not one‑person decisions but network decisions. Forrester, The State of Business Buying, 2024 [forrester.com]

At the same time, buyers move across about ten interaction channels—email, Slack/Teams, portals, virtual demos, marketplaces, and more—and more than half say they will switch suppliers if the experience across those channels is clumsy. That omnichannel sprawl multiplies stakeholders and amplifies the role of invisible influencers who shape perceptions between meetings. McKinsey B2B Pulse 2024 [mckinsey.com]

Bottom line: If you rely on a title‑driven map, you will misread power, overestimate alignment, and underestimate the people who can quietly block a deal.

Power blindness creates false alignment

Sales teams frequently anchor on the most senior person in the room and assume alignment will cascade. But organizational research shows that the informal network—the web of who seeks advice from whom—predicts outcomes at least as well as the hierarchy. In a well‑cited study of 68 change programs in the UK’s National Health Service, network position (e.g., bridging disconnected groups) beat formal rank in forecasting who actually moved big initiatives. Harvard Business Review, “The Network Secrets of Great Change Agents” [hbr.org]

Consulting evidence echoes that leaders commonly misidentify their own influencers. At one large retailer, managers overlooked almost two‑thirds of the employees peers named as influential—and missed three of the top five in their stores. Hidden power is real, and most leadership teams are blind to it. McKinsey, “Tapping the Power of Hidden Influencers” (2014) [mckinsey.com]

Influence follows risk, not rank

Across complex deals, the people with the biggest downside often hold the biggest de facto veto. That includes operations leaders accountable for rollout, finance partners on the hook for variance, security/privacy owners facing regulatory exposure, and long‑tenured “go‑to” experts whose judgments carry weight. Organizational network analysis (ONA) is the formal practice of mapping these flows of advice, trust, and access that determine what actually happens. It routinely surfaces influencers who do not sit atop the org chart. Deloitte, “Harnessing organization network analysis (ONA)” (2024) [deloitte.com]

The Center for Creative Leadership similarly shows how informal networks—not just formal management teams—shape strategy development and execution, especially through the “strategic leadership system” spanning upper‑ and middle‑management. Center for Creative Leadership (white paper, 2020) [cclinnovation.org]

Practical rule: map who can safely say “no” (because they own the risk) before you chase only the person who can formally say “yes.”

How hidden hierarchies form inside buying groups

1) Operational dependence. People who control systems, data, and workflows—even with modest titles—become gatekeepers because execution is impossible without them. ONA consistently identifies these “connectors” and “brokers.” Harvard Business Review (2013); Deloitte ONA (2024) [hbr.org] [deloitte.com]

2) Reputational trust. Long‑standing experts and well‑regarded problem‑solvers become default advisors. In McKinsey’s hidden‑influencer work, peer‑named influencers rarely matched management’s guesses—credibility is earned socially, not conferred by title. McKinsey (2014) [mckinsey.com]

3) Political proximity. Advisors who brief executives informally, or who manage sensitive cross‑functional work, shape outcomes behind the scenes—especially in matrix organizations where employees serve on multiple teams. (McKinsey/Gallup research shows most employees are “matrixed” to some extent, which raises collaboration but also ambiguity.) McKinsey, Revisiting the Matrix Organization [mckinsey.com]

Signals that reveal real influence (even when titles don’t)

• Post‑meeting consultations: Who gets pinged after the meeting? People everyone double‑checks with often hold latent veto power. ONA work repeatedly finds bridges between groups are critical change agents. HBR (2013) [hbr.org]

• Objection gravity: Whose concerns trigger documentation or redesign, versus whose are parked? The former are your practical power holders. McKinsey (2014) [mckinsey.com]

• Resource gates: Who controls access to data, pilots, sandboxes, or integration teams? In omnichannel buying with ten channels in play, these people decide what evidence the group sees. McKinsey B2B Pulse 2024 [mckinsey.com]

• Language flags: “We should check with…” or “They’ll need to be comfortable” are breadcrumbs toward the real center of gravity. HBR’s network research shows central, trusted nodes set the tone of change conversations. HBR (2013) [hbr.org]

How to map influence without triggering defensiveness

Directly asking “who has power here?” can feel political. Use impact‑framed prompts that surface influence safely:

• “Who would be most impacted if this went wrong?” → points toward high‑risk owners (ops, finance, security). (In buying groups with ~13 people, risk owners often aren’t the nominal “deciders.”) Forrester 2024 [forrester.com]

• “Who tends to raise concerns when day‑to‑day operations change?” → surfaces trusted operators and connectors. Deloitte ONA (2024) [deloitte.com]

• “Whose support makes initiatives easier internally?” → reveals reputational influence that formal charts miss. CCL (2020) [cclinnovation.org]

• “Who usually weighs in when priorities conflict?” → identifies political proximity to execs within matrix teams. McKinsey Matrix [mckinsey.com]

If you can, encourage your sponsor to run a lightweight ONA (survey or “snowball sampling”) to map the informal network. McKinsey shows quick snowball surveys often reveal the true influencers in 3–4 rounds, and leaders’ guesses routinely miss them. McKinsey (2014) [mckinsey.com]