Chief: Research and Development
Professional Communications, Inc.
SUMMARY OF CURRENT FINDINGS
This study finds that women are poorly represented in engineering management. However, it does not appear to be due to gender selection bias. Rather the pool of women at the professional engineering level consists of substantial portions who are not well-aligned with culturally mandated demands of engineering leadership. The engineering culture has proven highly effective in meeting engineering goals. It is very unlikely that the this culture can be radically adjusted to accommodate women without damage to the core function. A rational strategy for increasing the management representation of women will involve attracting and retaining women whose information processing profile more closely reflects the role responsibilities of the various managerial levels.
PRIOR FINDINGS
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CURRENT RESEARCH
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Table 1
ENGINEERING
SAMPLE CHARACTERISTICS
SHORT-TERM DECISION MAKING
“I Opt” styles are used to measure the
probability that a person will choose a particular kind of response on the next
decision. The “I Opt” style” measures the kind of input a person seeks/accepts,
the probable character of the intended response and the mechanism for getting
from input to output. Information availability sets the range of behaviors that
a person can issue. (Footnote #5 for “style” explanation reference).
For example, attention to detail necessarily
limits the decision horizon since detail expands exponentially with time.
Focusing on general aspects (i.e., ignoring detail) lengthens the horizon at the cost of a loss of
precision. Obviously, different decision horizons can lead to markedly
different choices (e.g., long vs short term profit
maximization). A host of other behaviors can be accurately
predicted from style preferences (see
Footnote #6 for reference to a non-exhaustive listing of predictable
behaviors).
Table
2 shows the percent difference between men and women in their average “I Opt”
style strength as well as the probability that the difference is just random
variation (Footnote #7 for
explanation). It should be kept in mind that these are women actually
working in engineering and not women taking engineering degrees. The number
and “I Opt” style character of female engineers who have chosen not to enter or
to leave engineering is unknown. However, leaders are drawn from the pool of
working engineers and thus the number of working female engineers are what is
relevant to this study.
Table 2
MALE versus FEMALE STYLE DIFFERENCES BY
LEVEL
“I Opt” styles represent the first choice a person is
likely to make when confronting an unfamiliar situation. They set the initial
tone of a relationship. They are what get a person noticed (or ignored) by those making promotional decisions. Styles influence career advancement.
Table 2 shows that women differ significantly from men at
the professional level (see highlighted yellow boxes). This suggests that
a significant proportion of the women in these categories differ from men at a style
strength sufficient to move the averages. These women are more highly committed
to methodical action (i.e., LP style) and less attentive to more speculative idea generation (i.e., RI style). As noted in the study on Women in
Engineering (see Footnote #2) this
kind of difference can create an adverse environment.
The managerial levels of engineering show no significant difference between men and women in their approach to decision making. They share the same decision horizon, have roughly the same risk profile, favor the same character of response and so on. In other words, men and women are being promoted to higher levels based on the same decision making criteria.
The managerial levels of engineering show no significant difference between men and women in their approach to decision making. They share the same decision horizon, have roughly the same risk profile, favor the same character of response and so on. In other words, men and women are being promoted to higher levels based on the same decision making criteria.
This same kind of male-female decision making consistency
was found in an earlier Gender at the Executive Level study (Salton, 2006. See Footnote #8 for reference). The various levels of management appear to demand that
incumbents adopt an information processing perspective suited to the kind of
issues that the level typically addresses. In other words, no special
allowances are being made to increase managerial participation along this
dimension (See Footnote #9 for a cautionary footnote).
LONG-TERM
DECISION MAKING
No single information processing strategy applies to
every situation. When a favored strategy does not apply people shift to their
next most favored strategy. The specific
rank ordering of favored styles establishes a behavioral theme that readily
visible to all involved. “I Opt” terms
these characteristic long term behavioral themes as “patterns.”
Styles (short-term decision
strategies) characterize an individual among those who
have only occasional or intermittent exposure to their decision making. Patterns (long-term
decision strategies) temper these initial judgements among those
who are able to witness repeated decisions.
Since time is required to witness repeated exposures “I Opt” patterns
are deemed to be long-term strategies.
In
terms of hierarchical promotion, styles typically cause a person to be noticed
as adept in a particular function. Patterns are usually used to assess that
person’s likely performance in a particular role within that function. Table 3
shows the pattern differences between men and women at the various hierarchical
levels..
Table 3
MALE
versus FEMALE PATTERN DIFFERENCES BY LEVEL
At the managerial levels a majority of the categories
register an overall insignificant level of difference between men and women.
There are two instances where a marginal level of significant difference is
visible. Both of these differences can be questioned.
The Project Management difference in the “Performer” category (i.e., a short-term horizon focused on immediate results) rests on a sample size of only 20 women. On its own, sample size would not be a “killer.” However, the nature of the job is also highly variable. Project manager can involve responsibility for a billion dollar infrastructure project or the design of a critical component part. The combination of small size, widely discrepant job demands and marginal levels of significance call into question the “reality” of the difference found. Refined categorization and larger sample size could well cause the difference to disappear.
The difference in Mid-Level management’s “Perfector” category (i.e., longer-term horizon focused on complete understanding of new items) is different. It has a more substantial sample size of 84 women. Categorization remains an issue. Mid-Level management consists of jobs with a wide range of responsibility. For example, if just the General Manager (n=17 all males) were removed from the comparison the probability of no male-female difference would jump from 1.4 to 3.2 out of 100. Shifting seventeen people can more than double the uncertainty.
A detailed examination of the data underlying the pattern calculation was conducted. A significant “Perfector” difference persisted even when the comparison was confined to managers or directors. The mid-level manager difference appears to be real. The difference is likely attributable to the information processing strategies used by the pool of women from which mid-level managers are drawn—the Professional Level.
Table 3 indicates that Professional level women and men differ on all four “I Opt” patterns. In 3 of the 4 patterns that difference reaches “highly significant” levels. This reinforces the position that the raw number of women engineers dramatically overstates the number actually available for promotion. Many of the professional level women engineers do not have the information processing patterns that match the culturally prescribed patterns suitable for higher levels.
The result of this condition is that it will appear that women are being systematically discriminated against in promotional opportunities. In reality, those women who use strategies compatible with the demands of these higher level positions are being promoted and “fit in” with some precision (see footnote #10 for an analysis of the mid-level manager anomaly).
This analysis points to at least some of the causes underlying the issues on condition of women in engineering. The women electing to stay in engineering after graduation are systematically different than their male counterparts. In addition to stereotype exposures (see “Women in Engineering” study) this difference methodically disadvantages them in career advancement. The cause (i.e., information processing election) is invisible. Women considering engineering are likely to attribute this to gender bias. This discourages others from entering the field. The raw number of women in the field is further reduced. It is a bit of a vicious circle.
ASSESSMENT
The Project Management difference in the “Performer” category (i.e., a short-term horizon focused on immediate results) rests on a sample size of only 20 women. On its own, sample size would not be a “killer.” However, the nature of the job is also highly variable. Project manager can involve responsibility for a billion dollar infrastructure project or the design of a critical component part. The combination of small size, widely discrepant job demands and marginal levels of significance call into question the “reality” of the difference found. Refined categorization and larger sample size could well cause the difference to disappear.
The difference in Mid-Level management’s “Perfector” category (i.e., longer-term horizon focused on complete understanding of new items) is different. It has a more substantial sample size of 84 women. Categorization remains an issue. Mid-Level management consists of jobs with a wide range of responsibility. For example, if just the General Manager (n=17 all males) were removed from the comparison the probability of no male-female difference would jump from 1.4 to 3.2 out of 100. Shifting seventeen people can more than double the uncertainty.
A detailed examination of the data underlying the pattern calculation was conducted. A significant “Perfector” difference persisted even when the comparison was confined to managers or directors. The mid-level manager difference appears to be real. The difference is likely attributable to the information processing strategies used by the pool of women from which mid-level managers are drawn—the Professional Level.
Table 3 indicates that Professional level women and men differ on all four “I Opt” patterns. In 3 of the 4 patterns that difference reaches “highly significant” levels. This reinforces the position that the raw number of women engineers dramatically overstates the number actually available for promotion. Many of the professional level women engineers do not have the information processing patterns that match the culturally prescribed patterns suitable for higher levels.
The result of this condition is that it will appear that women are being systematically discriminated against in promotional opportunities. In reality, those women who use strategies compatible with the demands of these higher level positions are being promoted and “fit in” with some precision (see footnote #10 for an analysis of the mid-level manager anomaly).
This analysis points to at least some of the causes underlying the issues on condition of women in engineering. The women electing to stay in engineering after graduation are systematically different than their male counterparts. In addition to stereotype exposures (see “Women in Engineering” study) this difference methodically disadvantages them in career advancement. The cause (i.e., information processing election) is invisible. Women considering engineering are likely to attribute this to gender bias. This discourages others from entering the field. The raw number of women in the field is further reduced. It is a bit of a vicious circle.
ASSESSMENT
The Bureau
of Labor Statistics registered 7.6% female managers in Architecture and
Engineering while they made up 15.4% of the workforce. In contrast women made
up 38.6% of management versus a total workforce of 43.7% across other professional occupations (Bureau of Labor Statistics, 2014; see Footnote #4 for reference). There
appears to be a serious shortfall of women engineering managers whether
considered in absolute or relative terms.
This analysis indicates that the managerial shortfall has two interrelated causes. The first is due to the relatively few women who choose to enter and stay in engineering. This can be addressed in a variety of ways. The study of Women in Engineering (footnote #2) suggested that things like the compensation structure could be adjusted to better recognize the role responsibilities of women while still retaining gender equity. Attention to the physical work environment might also be adjusted to lessen the exposure to potentially gender hostile occurrences. These kinds of things in combination with the current promotional efforts would do much to attract and retain women engineers.
This analysis indicates that the managerial shortfall has two interrelated causes. The first is due to the relatively few women who choose to enter and stay in engineering. This can be addressed in a variety of ways. The study of Women in Engineering (footnote #2) suggested that things like the compensation structure could be adjusted to better recognize the role responsibilities of women while still retaining gender equity. Attention to the physical work environment might also be adjusted to lessen the exposure to potentially gender hostile occurrences. These kinds of things in combination with the current promotional efforts would do much to attract and retain women engineers.
The second issue involves the kind of the
women being attracted and retained. Information processing styles and patterns
are strategies used continuously in all areas of life. While strategies for
temporarily adjusting them can be taught (see
footnote #12 for reference and explanation) they tend
to be very “sticky” and difficult to change. This means that attracting and
retaining women with information processing strategy aligned with engineering
management needs is key. The numbers tell us that engineering will promote
women who meet its cultural mandates. Engineering is not likely to sacrifice its
mission objectives or cultural mandates to meet abstract societal concepts of
gender equality.
What is needed is to attract a mix of women
engineers whose way of viewing the world matched the demands of the profession.
All styles should be welcomed—there is a role for everyone within engineering. However,
a bit extra effort focused on women with strong analytical (i.e., HA) and idea generating (i.e., RI) capacities would help fill that portion of
the pool from which management is drawn. This will probably require efforts by
all involved—academicians, professional associations and current engineering management.
The Engineering Insights (see footnote #3) study argued that engineering’s cultural
norms are near ideal and rooted in the demands of the profession. That means
adjusting cultural norms and standards is probably ill-advised. Rather
strategies have to be devised that attract, retain and develop women with the
requisite characteristics. These
strategies are not likely to come from the management structure of Chief
Engineer on down. These levels all share a common information processing
structure. This creates a common view and limits the range strategies which
might be deployed.
The Engineering Insights study does
offer a potential avenue for remedying the condition. The Vice Presidential
level is populated by individuals with a strong Relational Innovator (i.e., RI) component.
These people have the predisposition to generate options and ideas which can
create a favorable environment while maintaining the highly successful core engineering
culture.
The strategy suggested by this research is
for the Vice Presidential level to reach down and adopt the development of Professional
Level talent as a major responsibility. This is likely to be a stretch for the
VP. Their natural interactions will be with the various levels of engineering
management. Adopting this responsibility will require them to extend that
interaction down to a far more populous professional level (see
footnote #13 for elaboration).
The
delegation of this responsibility to the VP makes sense. In addition to the
ideas and options, the VP also has the authority and resources to actually
effect the changes that they deem warranted. The specific strategies are likely
to be unique to each organization. A “cookbook” prescription is
probably not needed. The strong idea-generating RI capacities of the
engineering VP found in the Engineering Insights study suggest that
there will be no shortage of potential remedies.
FOOTNOTES AND BIBLIOGRAPHY
<1> Salton, Gary
(April 2014). “The Engineering Personality.”
A textual version can be found in our research blog at:
http://garysalton.blogspot.com/2012/10/organizational-rank-and-strategic-styles_22.html
A video describing the research can be found on YouTube at
http://www.youtube.com/watch?v=sqeGLvjU2Oc&feature=youtu.be.
http://garysalton.blogspot.com/2012/10/organizational-rank-and-strategic-styles_22.html
A video describing the research can be found on YouTube at
http://www.youtube.com/watch?v=sqeGLvjU2Oc&feature=youtu.be.
It is also available in the Coffee Break
Videos section of
www.iopt.com.
www.iopt.com.
<2> Salton, Gary
(January 2015). “Women in Engineering.”
A textual version can be found on our
Research Blog at
http://garysalton.blogspot.com/2015/01/women-in-engineering.html
A video describing the research can be found on YouTube at
http://www.youtube.com/watch?v=sqeGLvjU2Oc&feature=youtu.be.
http://garysalton.blogspot.com/2015/01/women-in-engineering.html
A video describing the research can be found on YouTube at
http://www.youtube.com/watch?v=sqeGLvjU2Oc&feature=youtu.be.
It is also available in the Coffee Break
Videos section of
www.iopt.com.
www.iopt.com.
<3> Salton, Gary
(July 2015). “Engineering Insights.”
A textual version can be found on our
Research Blog at
http://garysalton.blogspot.com/2015/07/engineering-insights.html
A video
describing the research can be found on YouTube at
https://www.youtube.com/watch?v=40cZB_ngGSQ
It is also available in the Coffee Break
Videos section of
www.iopt.com.
www.iopt.com.
<4> The
Student’s-t test was used to estimate significance.
Technically there is no minimum sample size when using
this statistic. The primary effect of low sample size is the
loss of statistical power. Power is the probability of saying
that there is no effect when one is actually present (i.e., a Type II error).
The low sample size among senior Engineering Executive (n=9)
and 1st Level Executives (n=6) suggests that the finding of no
significant different in these categories should be taken as a tentative
indication rather than a definitive finding.
Technically there is no minimum sample size when using
this statistic. The primary effect of low sample size is the
loss of statistical power. Power is the probability of saying
that there is no effect when one is actually present (i.e., a Type II error).
The low sample size among senior Engineering Executive (n=9)
and 1st Level Executives (n=6) suggests that the finding of no
significant different in these categories should be taken as a tentative
indication rather than a definitive finding.
<5> Salton, Gary
(February 2008). "I Opt" Strategic Styles and
Patterns.
https://www.youtube.com/watch?v=KVOyznCCWB8. This video provides an orientational overview of how styles are used to represent information processing postures. A complete explanation of the theory and application of the technology is available in a ~17 hour online/telephone counseling certification program conducted on demand by Shannon Nelson (shannon@iopt.com).
https://www.youtube.com/watch?v=KVOyznCCWB8. This video provides an orientational overview of how styles are used to represent information processing postures. A complete explanation of the theory and application of the technology is available in a ~17 hour online/telephone counseling certification program conducted on demand by Shannon Nelson (shannon@iopt.com).
<6> A
battery of I Opt “snowflakes” that are predictive of observable qualities and
which cover subjects like general behavior, learning, communication, emotional
impact, corporate culture and general culture are available free of charge at http://www.iopt.com/support-materials.html
<7> The
“p=” value in italics below the significance text is the decimal probability
that the difference discovered between males and females is just a random
variation in scores. The academic standard for marginal significance is p=.05
or a 5% chance that the difference is due to chance variation rather than a
causal difference. In the case of “I
Opt” styles the differences in the LP and RI styles would qualify as
“highly significant.”
<8> Salton, Gary (November, 2006). Gender at the Executive Level.
A 9 minute video is available on YouTube at https://www.youtube.com/watch?v=C1L5_kuwHEI.
A textual summary of the research can be found on the Google Research blog at https://www.blogger.com/blogger.g?blogID=10944318#editor/target=post;postID=116370873786509038;onPublishedMenu=posts;onClosedMenu=posts;postNum=31;src=postname
A 9 minute video is available on YouTube at https://www.youtube.com/watch?v=C1L5_kuwHEI.
A textual summary of the research can be found on the Google Research blog at https://www.blogger.com/blogger.g?blogID=10944318#editor/target=post;postID=116370873786509038;onPublishedMenu=posts;onClosedMenu=posts;postNum=31;src=postname
<9> It is
worth noting that the sample proportions in this study cannot be used to infer
causes of differentials in female versus male participation rates between
various engineering levels. The data is roughly random within categories but
not between them. There is no assurance that the categories are comparable in
terms of migration from one level to another.
However, legitimate inferences can be made between males and females
within a category.
<10> The
marginal significance of the Perfector pattern discrepancy in mid-level
management is due to a combination of style differences. Women have less commitment than do men in
both the analytical HA and idea-generating RI styles (short-term decision strategies).
Neither of these reaches statistical
significance at the style level.
However, patterns multiplicatively combine styles. This combinatorial
process is what elevates the “Perfector” pattern to significance at mid-level. Practically, this illustrates the importance
of small differences. Women will be
considered for promotion based on style. But they may tend to lose out to men
who are likely to be seen as being better equipped to handle the variety of
decisions required by the higher level job (i.e., a
better aligned pattern strategy).
<11> Bureau of Labor Statistics, 2014; “HOUSEHOLD
DATA ANNUAL AVERAGES; 11. Employed persons by detailed occupation, sex, race,
and Hispanic or Latino ethnicity. Accessed: June 29, 1015: www.bls.gov/cps/cpsaat11.pdf
<12> Everyone has access to all information processing styles.
People can elect to use one or another to facilitate particular transactions. Booklets describing how this can be done are
available in the “So You’re a …” series which can be seen at http://www.iopt.com/so-you-are-a.html. However, people make thousands of unique
decisions every day and it is impossible to guide each one through rational
selection. There is no choice but to rely on a generalized strategy as the
guide for the conduct of life. Since all aspects of life are involved adjusting
the global strategy is a major undertaking that takes much time and effort to
effect.
Reliability
studies have determined that changes in strategy are infrequent and when they
do occur they tend to follow a predictable pattern that may not be aligned with
a rationally selected target (e.g., preparation for
engineering leadership). These studies can be seen on YouTube at:
“I Opt”
Style Reliability Stress Test: https://www.youtube.com/watch?v=Vs6eoIsqVkc
“I Opt” Pattern Reliability Stress Test: https://www.youtube.com/watch?v=0SLg28BhNHU
Textual versions of these studies can be
found on the “I Opt” Research Blog at:
“I Opt”
Style Reliability Stress Test:
http://garysalton.blogspot.com/2011/03/i-opt-style-reliability-stress-test.html
“I Opt”
Pattern Reliability Stress Test:
http://garysalton.blogspot.com/2011/03/i-opt-pattern-reliability-stress-test.html
<13> This interaction can take many forms. Periodic luncheons with a rotating sample of
younger professional engineers might be one course. MBWA (Management
by Walking Around) might be another. The basic idea is for the
VP to become aware of and involved with the personal circumstances of the individuals
at the professional level. The technical
elements of development are already tended to through on the job training and
various Engineering Leadership Development Programs. The VP’s role is to make
the cultural tweaks that cause women to want to stay long enough to use those
technical abilities.
