Forbes46%

Why Fast Executive Teams Often Make The Most Expensive Decision 63%

By Janet M Harvey0%

7/10/2026, 6:01:19 AM

Keywords: Janet M Harvey

BS Summary: This article contains 31 faulty reasoning types, including Indoctrination, Negativity Bias, and Post Hoc (False Cause), with Appeal to Authority as the most egregious example at 19.4% saturation with 197 hits. Analysis detected 1,973 faulty-reasoning hits from 1,015 analyzed words, generating a BS Score of 57.6% and a BS Rank of 63% (8,286 of 21,887 articles). This article is worse (more manipulative) than 62.10% of the article peer group.

Why The Fastest Executive Teams Often Make The Most Expensive Decisions 
Forbes Councils Member. 
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Jul 10, 2026, 08:45am EDT 
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Janet M. 
Harvey, CEO and Founder of inviteCHANGE , advancing enterprise performance through Generative Wholeness leadership. 
​Last quarter, I sat with an executive team facing a 90-minute window to make a call on a business unit divestiture. 
They reached an agreement in 28 minutes. 
By the next morning, three of the seven members had emailed the CEO with reservations they had kept quiet in the room. 
Two weeks later, the decision was reopened, and the cost of that rework exceeded what the original decision was meant to save.​ 
Speed in decision-making is overvalued in many senior teams. 
Across 30 years of coaching executives on six continents, the most expensive pattern I see is premature resolution. 
Teams reach an agreement before the real question has surfaced, and the cost shows up later as rework, disengagement and second-order consequences nobody saw coming. 
Downstream rework is one of the clearest indicators that a decision process is breaking down at the front end.​​ 
Now, AI is accelerating the problem. 
Deloitte's "2026 Global Human Capital Trends" survey , which reached over 9,000 leaders across 89 countries, found that "60% of executives now regularly use AI to support their decisions." 
By 2027, Gartner projects that "half of business decisions will be augmented or automated by AI agents." 
And Oracle's 2023 "The Decision Dilemma" study of more than 14,000 professionals found that 72% say the volume of data has stopped them from making any decision at all, while 70% of leaders said they would prefer a robot to make decisions for them.​ 
The Generative Operating System we deploy with enterprise clients treats this as a measurable capability called "paradoxical capacity," which is the ability to hold two conflicting truths in view long enough for a better option to emerge. 
​Five Patterns To Assess 
Here are five patterns to assess whether an executive team has built that capacity or whether speed is quietly costing them quality. 
1. 
The room reaches agreement before the loudest dissenter has spoken. 
Quiet alignment is rarely real alignment. 
Harvard's Amy Edmondson has documented this: Absence of dissent is often suppression rather than agreement. 
The rework from forced resolution can cost organizations more than the original decision was meant to save. 
A useful protocol: Before any consequential decision closes, the most senior person in the room should ask, "What still needs to be said before we decide?" 
Then wait in silence for at least 30 seconds. 
The discomfort of that pause tells you the discipline is working. 
2. 
A binary frames the conversation, and no one challenges it. 
"Do we exit this market or double down?" 
"Restructure now or wait one more quarter?" 
I've found almost every binary in an executive room is a false choice waiting to be examined. 
The most useful contribution in a high-stakes meeting is often 15 seconds and a question: "Is this actually a choice between two things, or is there a third option we have stopped looking for?" 
Teams that build this habit often experience fewer decision reversals over a four-quarter cycle. 
The choice between A and B is rarely the real question. 
The constraint that makes it feel like A versus B almost always is. 
3. 
A senior leader uses 'let's just decide' to end discomfort. 
This phrase is one of the most reliable patterns I track. 
Discomfort in an executive room often signals that the real question has surfaced. 
Closing it down too fast forfeits the answer the room was about to find. 
When you hear "let's just decide" land in a senior team, ask, "What would you lose by giving this one more round?" 
The answer is almost always less than the room thinks. 
Decisions made out of fatigue or impatience tend to come back at the worst possible time. 
4. 
The CEO closes the conversation before everyone has spoken. 
In a healthy executive team, every senior voice contributes to every consequential decision. 
In an unhealthy one, the CEO speaks first, and the rest calibrate around the CEO's tone. 
The result is nodding heads and a CEO who genuinely believes the team is aligned. 
The fix is structural: Establish a norm that the CEO speaks third in any high-stakes decision conversation. 
Two more junior voices speak first. 
Track over a quarter how decision quality and durability shift. 
Many CEOs who run this experiment are surprised by how much intelligence the team had been holding back. 
5. 
Decisions made in the room get reopened by email afterward. 
If the same decisions keep coming back across meetings, or if reservations surface in emails after the room closes, the team is failing at the front end. 
Resolution was forced before the real question had been answered. 
Track decision rework over a four-quarter cycle. 
In my experience, healthy executive teams revisit consequential decisions less than 10% of the time. 
Teams that resolve tension too quickly revisit at around 20% to 30%. 
The gap is the cost of premature resolution, and it compounds. 
What These Patterns Add Up To 
Together, they describe a team that has confused decisiveness with quality. 
AI will not close that gap. 
The tools are scaling faster than the capacity to use them well, and that gap is accumulating what Deloitte calls cultural debt , the cost organizations absorb as AI scales faster than accountability structures can keep pace. 
Paradoxical capacity is not a software update. 
The leaders I trust most under pressure have learned that the discipline to stay with a hard question one more round is worth more than the comfort of closing it down. 
The room still decides.​ 
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Article reasoning-pattern comparisonThis article: 7.0%Janet M Harvey: 7.0%Forbes: 3.1%Confirmation Bias7.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 1.2%Anchoring Bias0.0%This article: 6.8%Janet M Harvey: 3.4%Forbes: 3.0%Availability Heuristic6.8%This article: 0.0%Janet M Harvey: 0.0%Forbes: 1.1%Representativeness Heuristic0.0%This article: 0.0%Janet M Harvey: 1.6%Forbes: 0.7%Hindsight Bias0.0%This article: 8.2%Janet M Harvey: 2.2%Forbes: 2.3%Overconfidence Bias8.2%This article: 1.7%Janet M Harvey: 2.0%Forbes: 5.8%Framing Effect1.7%This article: 1.4%Janet M Harvey: 0.3%Forbes: 0.4%Loss Aversion1.4%This article: 4.9%Janet M Harvey: 1.2%Forbes: 0.7%Status Quo Bias4.9%This article: 2.2%Janet M Harvey: 0.5%Forbes: 0.2%Sunk Cost Effect2.2%This article: 1.7%Janet M Harvey: 0.4%Forbes: 3.9%Optimism Bias1.7%This article: 5.9%Janet M Harvey: 2.7%Forbes: 1.3%Pessimism Bias5.9%This article: 17.2%Janet M Harvey: 4.8%Forbes: 5.4%Negativity Bias17.2%This article: 1.8%Janet M Harvey: 1.2%Forbes: 0.9%Self-Serving Bias1.8%This article: 3.3%Janet M Harvey: 0.8%Forbes: 0.6%Fundamental Attribution Error3.3%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.1%Actor-Observer Bias0.0%This article: 3.1%Janet M Harvey: 0.8%Forbes: 0.6%In-Group Bias3.1%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.1%Out-Group Homogeneity Bias0.0%This article: 5.1%Janet M Harvey: 1.3%Forbes: 3.2%Halo Effect5.1%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.0%Horn Effect0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.0%Dunning-Kruger Effect0.0%This article: 2.8%Janet M Harvey: 0.7%Forbes: 1.6%Recency Bias2.8%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.3%Primacy Effect0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.0%Blind-Spot Bias0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.1%Ad Hominem0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.1%Straw Man0.0%This article: 19.4%Janet M Harvey: 9.0%Forbes: 4.6%Appeal to Authority19.4%This article: 5.3%Janet M Harvey: 2.5%Forbes: 1.6%False Dilemma5.3%This article: 1.7%Janet M Harvey: 0.6%Forbes: 0.5%Slippery Slope1.7%This article: 5.8%Janet M Harvey: 1.7%Forbes: 0.2%Circular Reasoning5.8%This article: 14.7%Janet M Harvey: 9.5%Forbes: 5.7%Hasty Generalization14.7%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.1%Red Herring0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.7%Bandwagon0.0%This article: 10.7%Janet M Harvey: 2.7%Forbes: 3.8%Appeal to Emotion10.7%This article: 2.3%Janet M Harvey: 0.6%Forbes: 1.0%Begging the Question2.3%This article: 16.6%Janet M Harvey: 7.7%Forbes: 2.8%Post Hoc (False Cause)16.6%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.0%Tu Quoque0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.3%Burden of Proof0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.4%Appeal to Nature0.0%This article: 1.9%Janet M Harvey: 0.5%Forbes: 0.3%Composition/Division1.9%This article: 8.4%Janet M Harvey: 6.9%Forbes: 2.0%Anecdotal8.4%This article: 0.0%Janet M Harvey: 0.3%Forbes: 0.1%No True Scotsman0.0%This article: 1.3%Janet M Harvey: 0.3%Forbes: 1.8%Ambiguity (Equivocation)1.3%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.0%Gambler’s Fallacy0.0%This article: 3.3%Janet M Harvey: 0.8%Forbes: 0.1%Middle Ground3.3%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.0%Personal Incredulity0.0%This article: 5.3%Janet M Harvey: 1.3%Forbes: 0.2%Special Pleading5.3%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.1%Genetic Fallacy0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 1.1%Unattributed Quote0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.9%Quote-first Misdirection0.0%This article: 0.7%Janet M Harvey: 2.3%Forbes: 4.6%Biased Writer Voice0.7%This article: 17.7%Janet M Harvey: 8.5%Forbes: 2.5%Indoctrination17.7%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.4%Politically Left Leaning Bias0.0%This article: 0.0%Janet M Harvey: 0.0%Forbes: 0.2%Politically Right Leaning Bias0.0%This article: 6.3%Janet M Harvey: 5.2%Forbes: 5.1%Attempt to Sell a Product or S…6.3%

1015 words analyzed.

Speakers

7speakers19%attributed speech818writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 10 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageForbes Business Council • 3 words • 0.0% coverageForbes Business Council • 4 words • 0.0% coverageForbes Business Council • 8 words • 0.0% coverageWriter's voice • 7 words • 100.0% coverageForbes Business Council • 3 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 3 words • 100.0% coverageJanet M. Harvey, CEO and Founder of inviteCHANGE , advancing enterprise performance through Generative Wholeness leadership. • 2 words • 0.0% coverageJanet M. Harvey • 14 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageDeloitte • 29 words • 0.0% coverageGartner • 17 words • 0.0% coverageOracle • 44 words • 0.0% coverageWriter's voice • 37 words • 100.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 22 words • 100.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageAmy Edmondson • 15 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 26 words • 100.0% coverageWriter's voice • 9 words • 100.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 34 words • 100.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 22 words • 100.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 6 words • 100.0% coverageWriter's voice • 10 words • 100.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 27 words • 100.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 7 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageDeloitte • 37 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageForbes Business Council • 15 words • 100.0% coverageForbes Business Council • 3 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageForbes Business Council • 3 words • 100.0% coverage
Selected voice

Gartner

100%flagged-word coverage
17 attributed words8.6% of attributed speech90% writer coverage
0%12.5%25.0%Indoctrination-22.0 ptsWriter: 22.0%Gartner: 0.0%0.0%Attempt to Sell a Product -4.9 ptsWriter: 4.9%Gartner: 0.0%0.0%Biased Writer Voice-0.9 ptsWriter: 0.9%Gartner: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

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