Tag Archives: Halo Effect

Executive Presence: “Gravitas”, Communication…and Appearance?

Executive Presence is considered essential to achieve leadership roles and effectively perform in them.

Sylvia Ann Hewlett

Sylvia Ann Hewlett

Organizational advancement assumes measurable knowledge, skill, competence, coupled with less quantifiable “authenticity,” “cultural fit,” and “executive presence.”

To more clearly define these less tangible prerequisites of executive advancement, Sylvia Ann Hewlett, economist and CEO of Center for Talent Innovation, conducted 18 focus groups and 60 interviews to systematically investigate behavioral and attitudinal aspects of Executive Presence (EP).

Interviewees opined that Executive Presence accounts for more than a quarter of factors that determine a next promotion, and includes three distinct components:Executive Presence

Gravitas” – Authoritative Behavior

    • Confidence, composure,
    • Decisiveness,
    • Integrity,
    • Emotional Intelligence: self-awareness, self-regulation, interpersonal skills,
    • Clear personal “brand” reputation,
    • Vision for leadership

Communication

    • Strong speaking skills:  Voice tone, clear articulation, grammatical speech conveying competence, credibility,
    • Presence”, “bearing”,  “charisma” including assertiveness, humor, humility,
    • Ability to sense audience engagement, emotion, interests

Appearance

    • Attention to grooming, posture,
    • Physical attractiveness, normal weight,
    • Well-maintained, professional attire.

Harrison Monarth

Executive presence can be cultivated with Image Management, argued Harrison Monarth.

He advocated self-marketing tactics including:

– Creating and maintaining a compelling personal “brand” to influence others’ perceptions and willingness to collaborate,

– Managing online reputation, and recovering when communications go awry,

-Effectively persuading those who disagree, and gaining followers,

-Demonstrating “Emotional Intelligence” skills of self-awareness, awareness of others (empathic insight).

He focused less on appearance as a contributor to career advancement than Hewlett and Stanford Law School’s Deborah Rhode, who summarized extensive research on Halo Effect.
Rhode and Hewlett acknowledge the impact of appearance and non-verbal behavior on various life opportunities including career advancement.

Deborah Rhode

Rhode estimated that annual world-wide investment in appearance is close to $200 billion in 2010 USD currency, and she contended that bias based on appearance:

  • Is prevalent,
  • Infringes on individuals’ fundamental rights,
  • Compromises merit principles,
  • Reinforces negative stereotypes,
  • Compounds disadvantages facing members of non-dominant races, classes, and gender.

Executive Presence is widely recognized as a prerequisite for leadership roles, yet its components remained loosely-defined until Hewlett’s systematic investigation, Monarth’s consulting-based approach, and Rhode’s legal analysis.

-*Which elements seem most essential to Executive Presence?

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Attractive Appearance Helps Men – but not Women – Gain Business Funding

Laura Huang

Laura Huang

Entrepreneurs create jobs and contribute to economic growth with early investment by financial backers who trust the perceived business proposal’s viability and the founders’ previous experience.

Alison Wood Brooks

Alison Wood Brooks

Additional implicit criteria for new venture-funding include gender and physical attractiveness, asserted Harvard’s Alison Wood Brooks, Laura Huang of Wharton, MIT’s Sarah Wood Kearney and Fiona E. Murray.

Sarah Wood Kearney

Sarah Wood Kearney

Brooks and colleagues enlisted 60 experienced investors to:

  • Evaluate videos of 90 randomly-selected presentations by entrepreneurs at three pitch contests in the US,
  • Comment on presenters’ appearance and effectiveness.
Fiona E. Murray

Fiona E. Murray

Male presenters who were rated more attractive were 36% more likely to receive funding than men judged as less attractive, but there was no difference in funding rates for women based on attractiveness ratings.

In a separate study, investors evaluated identical pitches delivered by a man or a woman, and rated male-narrated pitches as more persuasive, logical and fact-based compared with the same presentation delivered by a woman.

These finding suggest that financial backers favor attractive male entrepreneurs, leaving women entrepreneurs – attractive or not – at a disadvantage in creating new businesses, jobs, and economic growth.

This finding underscores financial backers’ preference for male entrepreneurs’ proposals, based on attractive men’s greater perceived persuasiveness than women or less attractive men.

Edward Thorndike

Edward Thorndike

Previous blog posts have noted the “halo effect” of physical attractiveness leading to positive attributions of intelligence, competence, and likeability, originally described by Columbia’s Edward Thorndike.

Woods’ latest findings point to the double advantage enjoyed by attractive men seeking new venture funding.
Aspiring women entrepreneurs, on the other hand, continue to encounter significant unacknowledged disadvantages, not improved by physical attractiveness.

Eleanor Holly Buttner

Eleanor Holly Buttner

However, these findings were not confirmed by University of North Carolina’s E. Holly Buttner and Benson Rosen in their investigation of bank loan officers’ funding decisions.

Loan officers, who typically make funding decisions based on the business plan and interview with the entrepreneur, evaluated a:

  • Business plan or
  • Business plan plus a videotaped interview conducted by a loan officer with a male or female entrepreneur seeking a loan to start a business.
Benson Rosen

Benson Rosen

Bankers rated their likelihood of:

  • Recommending loan approval of the requested amount,
  • Making a counteroffer of a smaller amount, which they specified.

This study found no difference in funding decisions for male entrepreneurs compared with female entrepreneurs presenting the same business case.
In fact, loan officers made larger counteroffers to female entrepreneurs when considering both the business plan and the loan application interview.

Student volunteers’ loan funding decisions were compared with loan professionals, and the younger generation of lay people made larger counteroffers to the male entrepreneur instead of the female when they evaluated both the business plan and the loan interview,
Loan officers, in contrast, made significantly more cautious and conservative funding decisions than student participants.

Buttner and Benson recommended that female entrepreneurs ask to meet with loan officers to present their business proposals because this personal contact resulted in more successful funding of requested loans.

John Becker-Blease

John Becker-Blease

Another source of funding is “angel investors,” and Oregon State University’s John R. Becker-Blease and Jeffrey E. Sohl of University of New Hampshire found no difference in funding for male and female entrepreneurs.
They noted that women seek private investments substantially lower rates than men, but they are equally likely to receive investment.

However, when the “angels” are women, female entrepreneurs are more likely to seek financing and are as likely to receive the requested funding.

Jeffrey Sohl

Jeffrey Sohl

Women entrepreneurs may still face obstacles in starting new ventures,  a barrier shared with less attractive males.

-*How do you mitigate biases based on gender or attractiveness when asking for funding – for a business, initiative, or idea?

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Debiasing Decisions: Combat Confirmation Bias, Overconfidence Bias

Philip Meißner

Philip Meißner

Cognitive and behavioral biases can contribute to “blind spots” in decision-making, leading to less effective outcomes.
To improve decision outcomes, University of Marburg ’s Philip Meißner, Torsten Wulf of HHL Leipzig Graduate School of Management and HEC’s Olivier Sibony proposed a systematic checklist to identify potential decision derailment based on bias, along with rapid remedies.

Torsten Wulf

Torsten Wulf

They argues that two types of bias contribute to most decisions that lead to undesirable results:

  • Confirmation bias, the unconscious tendency to believe new information that is consistent with existing beliefs and recent experiences, and to discount contradictory data,
  • Overconfidence bias, the out-of-awareness likelihood to overestimate one’s skills, insights, and judgment.
    This leads to increased risk-taking based on illusory sureness of the decision and ability to mitigate adverse outcomes.
Olivier Sibony

Olivier Sibony

Previously, Lovallo and Sibony articulated four related decision biases:

  • Pattern-recognition biases, countered by changing the “angle of vision,”
  • Action-oriented biases, mitigated by recognizing uncertainty,
  • Interest biases, minimized by explicitly highlighting these interests,
  • Social biases, reduced by depersonalizing debate.

Debiasing techniques such as checklists, can limit the negative effects of biases in decision-making by offering a disciplined, comprehensive analysis of downside risks and by systematically considering multiple viewpoints.

Atul Gawande

Atul Gawande

However, effectively implementing checklists requires consistent discipline, noted Harvard’s Atul Gawande, who cited examples of partial adherence leading to costly oversights and failures.

One approach, suggested by Princeton’s Daniel Kahneman and Gary Klein of McKinsey, is a “premortem.”
Decision makers imagine that the decision has failed and analyze sources and reasons for adverse outcomes, to more thoroughly assess points of failure and possible mitigation strategies.
Formal scenario-planning is another way to expose assumptions underlying a plan, as well as a competitor’s priorities and potential strategy.

Massimo Garbuio

Massimo Garbuio

Using a variety of debiasing techniques significantly increased the Return on Investment (ROI) in a study by University of Sydney’s Massimo Garbuio and Dan Lovallo and Olivier Sibony of HEC.
As a result, Michael Birshan, Ishaan Nangia, and Felix Wenger of McKinsey, argued that debiasing techniques should be embedded in formal organizational decision-making processes, particularly for high-impact, repetitive decisions.

Michael Birshan

Michael Birshan

Decision biases may be out of awareness, or unconscious, so it’s more effective to evaluate the process of developing a proposal, rather than focusing only on the content and merits of a proposal.

Decision-making safeguards can be built into standard analysis processes by including questions to expose:

  • Multiple data sources,
  • Diverse opinions and perspectives,
  • Downside risk,
  • Potential negative outcomes for company, industry, and broader ecosystem.
Daniel Kahneman

Daniel Kahneman

Proposals are considered ready for a decision only when multiple perspectives are available to mitigate confirmation bias and risk analysis is available to reduce overconfidence bias.
Responses to decision checklist questions can be quantified to indicate one of four action steps, according to Daniel Kahneman:

  • Decide, based on inclusion of robust safeguards against both confirmation bias and overconfidence bias,
  • Screening MatrixReach out, suggesting the need for gathering additional perspectives, opinions, and perspectives to prevent narrow assumptions to reduce confirmation bias.
    The Vanishing-Options Test, proposed by Stanford’s Chip Heath and Dan Heath of Duke University, can generate new ideas by imagining that none of the current proposals are available.
  • Stress-test, by conducting a pre-mortem or analysis by external devil’s advocate or provocateur to reduce overconfidence risk by.
  • Reconsider when both more perspectives and risk analysis are required to reduce both overconfidence bias and confirmation bias.
    This screening matrix helps reduce related decision-making biases:
  1. Self-interest Bias
    -To what extent is the proposal motivated by self-interest?
Ishaan Nangia

Ishaan Nangia

Recommendation
-Assess for over-optimism

  1. Affect Heuristic
    -How strong is the team’s emotional attachment to a specific proposal?
    -To what extent were risks and costs fully considered for both preferred and non-preferred options?

Recommendations
-Assess for strongly-preferred outcomes
-Reintroduce analysis of all options

  1. Groupthink
    -How many dissenting opinions were analyzed?
    -How adequately were all options explored?
    -Was dissent discouraged? 
Felix Wenger

Felix Wenger

Recommendations
-Encourage substantive disagreements as a valuable part of the decision process
-Solicit dissenting views from members of the recommending team, through private meetings

4. Saliency Bias
     -To what extent are decisions made based on a potentially incomparable, but memorable success?
     -What about the proposed analogy is comparable to the current situation?
     -What are relevant examples from less successful companies? What happened in those cases?

Decision Making QuestionsRecommendation
-Carefully scrutinize analogies’ similarity to the current decision situation
Solicit additional analogies using reference class forecasting:

.Select reference class,
.Assess distribution of outcomes,
.Intuitively estimate project’s position in distribution,
.Assess estimate’s reliability,
.Correct intuitive estimate.

  1. Confirmation Bias
    -What viable alternatives were included with the preferred recommendation?
    -At what stage in the decision analysis were alternatives discarded?
    -What efforts were undertaken to seek information to disconfirm the main assumptions and hypotheses?

Recommendation
-Request two additional alternatives to the main recommendation, including analysis of benefits and drawbacks
-Acknowledge unknowns, risks

  1. Availability Bias

    Max Bazerman

    Max Bazerman

    If you had more time to gather date, what information would you seek?, asked Harvard’s Max Bazerman
    -How can you access similar data now?

Recommendation
-Use checklists to ensure comprehensive analysis of data required for each decision type

  1. Anchoring Bias
    -What data sources are used to analyze decision?
    -Which data are estimates? By whom? If so, from which data were estimates extrapolated?
    -To what extent could there be:
  • Unsubstantiated numbers?
  • Extrapolation from non-equivalent previous situations?
  • Attraction to specific anchors?

Recommendations
-Present data from other sources, benchmarks, or models
-Request new analysis

8. Halo Effect
     -To what extent does the analysis team expect that a person, organization, or approach previously successful in one context will be equally effective in different situation?

Phil Rosenzweig

Phil Rosenzweig

Recommendations
-Question potentially inaccurate inferences
-Solicit additional comparable examples
-Question attributions of success and failure to leaders’ personalities instead of chance factors, advised IMD’s Phil Rosenzweig.

9. Sunk-Cost Fallacy, Endowment Effect
     -To what extent are recommenders attached to past decisions?

Recommendation
Disregard past expenditures when considering future costs and revenues

  1. Overconfidence, Planning Fallacy, Optimistic Biases, Competitor Neglect
    -To what extent is the comparison case unwarrantedly optimistic?

Recommendation
-Adopt an outside view by using relevant simulations or war games

  1. Disaster Neglect
    -To what extent is the worst case scenario realistically and sufficiently negative?
    -How was the worst case generated?
    -To what extent does the worst case consider competitors’ likely responses?
    -What other scenarios could occur?

Recommendation
-Conduct a premortem, suggested by Gary Klein of Applied Research Associates:  Imagine the worst case scenario occurred, then propose likely causes, mitigations   

  1. Loss Aversion
    -To what extent is the evaluation and decision team risk averse?

Recommendation
-Realign incentives to share responsibility for the risk or to reduce risk

  1. Planning Fallacy focuses only on the current case while ignoring similar projects’ history and statistical generalization from related cases.
    -To what extent does the analysis rely on “top-down, outside-view” comparisons to similar projects?
    -Did the evaluators use a “bottom-up, inside-view” to estimate time required for each step?

Recommendation
-Statistically analyze a broad range of similar cases to avoid over-estimates from “top-down, outside-view” approaches and underestimates from “bottom-up, inside-view”
-Differentiate accurate forecasts from ambitious targets

  1. Loss aversion
    -To what extent are evaluators more concerned with avoiding loss than achieving gains?
    – How concerned are evaluators with being held responsible for a failed project?
    -To what extent has the organization specified acceptable risk levels?

Recommendation
-Seek risk tolerance guidelines from organizational leaders.

Decision-making tools like checklists can significantly reduce unconscious biases, provided that they are consistently and systematically applied.

-*What strategies have you found most helpful in reducing biases in decision-making?

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