Showing posts with label julianne pepitone. Show all posts
Showing posts with label julianne pepitone. Show all posts

Wednesday, March 19, 2014

The Weighted Morris Number (Morris Number 06)


THE MORRIS NUMBER, WITH WEIGHTS

When I calculated the range of ordinary Morris Numbers (OMNs) for the five tech companies discussed in Julianne Pepitone's CNN Money article, I thought about adding weights. Weights help to discriminate (npi) between companies with the same OMN but a different ordering of females and males. Weights are a way to take account of the gender pattern above the fifth highest ranking woman.

A SIMPLE EXAMPLE

Two companies have an ordinary Morris Number (OMN) of 5: there are 5 men above the 5th highest ranking women. In one company the top 10 positions alternate between M and F. In the other company the top five positions are held by men, the next five by women.

To distinguish between such situations, we can use weights. Counting down from the top, the more men above each successive woman, the higher (worse) the metric will be.


The Weighted Morris Number (WMN) is calculated by using different weighting factors for the number of men whose position at the company is higher than one or more of the top five woman. The weights go down as you go down the hierarchy. The number of men higher than the top woman is multiplied by the biggest factor. Let us set it at 15. If the CEO is a woman, the contribution to the Morris Number for Female #1 is 0. If the top woman is 6th in the company, the contribution is 75 (5 x 15).

The set of multipliers might be:
     15 for the number of men above Female #1
     10 for the number of men between Female #1 and Female #2
       6 for the number of men between Female #2 and Female #3
       3 for the number of men between Female #3 and Female #4
       1 for the number of men between Female #4 and Female #5
The size of the steps between weights are 5-4-3-2.

ALTERNATING MEN AND WOMEN AT THE TOP

If men and women alternate in the top 10 positions, the ordinary Morris Number is either 4, if a woman is at the top, or 5, if a man is at the top. The difference between the OMNs for those two situations is 1. The difference between the two WMNs is more dramatic. With a man in the number 1 position, the weighted Morris Number is
     1 x 15
     1 x 10
     1 x   6
     1 x   3
     1 x   1
for a total of 35. If a woman is in the top position, the weighted Morris Number is 20.
The bonus for a female CEO might make the weighted Morris Number a less desirable metric: it could encourage companies to rely on the Indira Phenomenon rather than ending discrimination.


Company 1: There are 50 men before you reach any women. The next 5 positions are held by women. The OMN is 50.

Company 2: The CEO is a woman. Then there are 5 men between her and F2, 35 men between F2 and the next two women, F3 and F4, then 10 more men between F4 and F5. The OMN is 50.

In Company 1, the top 5 females are below the executive tier. (I say that because it is rare for an organization to have more than 50 people with substantial executive clout.) Company 2 has a female CEO and another female also within the top 10. So far so good, but the Indira Phenomenon may dominate after F2.

Now consider the WMNs for these two companies: Company 1:
     750 = 50 men above F1 x 15
         0 = No men between F1 and F5
     ------------------------------------------------
     750 = WMN

Company 2:
          0 = 15 x  0 men above F1
       50 = 10 x  5 men between F1 and F2
     210 =  6 x 35 men between F2 and F3
         0 =  3 x  0 men between F3 and F4
        10 = 1 x 10 men between F4 and F5
     ------------------------------------------------
     270 = WMN

Company 2's WMN is about a third of Company 1's. Imagine if that fact were publicized at job fairs and university career offices and in a tweet that went viral. Company 2 would attract more and better women job seekers and more and better women customers. It would be able to achieve a level of excellence that company 1 could only envy until its top management finally realized that quality women should replace mediocre men.

March 19, 2014; rev 1 20140331,0403

Morris Number Ranges for Some Tech Companies (Morris Number 05)


CALCULATING MORRIS NUMBERS FOR TECH COMPANIES

Employment data is not easy to come by. But almost exactly a year ago, Julianne Pepitone published an article in CNN Money entitled "Black, female, and a Silicon Valley 'trade secret'" and subtitled "Silicon Valley Boys' Club" in which she sought to answer the question "How diverse is Silicon Valley?" Pepitone had managed to obtain employment data from five tech companies willing to permit such information to be public: Cisco, Dell, eBay, Ingram Micro and Intel. I discussed the article, and its excellent interactive tables, here.
Pepitone had sought information from twenty tech companies. Only three, Dell, Ingram Micro and Intel, cooperated; Intel alone has a policy of making such data public. After a FOIA request was filed seeking employment information that government contractors have to give the government, information about two more companies, Cisco and eBay, was obtained. Final tally: 20 companies, 5 with data, 15 not. Ten of those fifteen, including Amazon, Facebook and Twitter, had no government contracts so the FOIA request did not touch them. The other five -- Apple, Google, Hewlett-Packard, IBM and Microsoft -- successfully petitioned to prevent disclosure on the grounds that it would cause "competitve harm," hence the 'trade secret' joke in the title of the article. Would a company with an excellent record of diversity want to make sure nobody saw the numbers? Hmmm. If you know of further developments in the quest for this kind of information, please let me know.
Pepitone's tables present the numbers of employees in six categories. She explains that these are averages over 5 years. [See "Methodology" below the interactive tables and click "Read More."] Those categories are related to a set of ten codes from an EEO-1 form that all companies with more than 100 employees must file with the EEOC. Those ten codes are aggregates from the 300 occupations the US census uses. See http://www.eeoc.gov/employers/eeo1survey/jobclassguide.cfm.
The EEOC, however, is prohibited by statute (subsection e of 42 USC 2000e-8) from divulging EEO-1 information, which is why the CNN Money investigators first asked the companies directly, and then used a FOIA request addressed to the Department of Labor. Unlike the EEOC, the Department of Labor is not subject to a gag rule but the contractors do have the right to petition to keep secret any trade secrets.
Pepitone reorganizes the data to focus more on upper level employees. She breaks out the subcategories of the EEO-1's top code (1.1: executive/senior officers and 1.2: First/Midlevel Officials and Managers), identifying the first as "Officers and Managers" and the second as "Midlevel Officer or Manager." She also collapses the lower five EEO-1 codes into a single "Admin/Other" category.

Total employees for each company are not displayed, so I have calculated them here.
           Company
Category
Cisco
Dell
eBay
Ingram Micro
Intel
Officer/Manager
225
125
55
236
41
Mid-level
6,496
3,374
1,804
574
5,027
Professional
24,100
11,237
3,977
846
28,306
Technical
59
3,370
58
119
10,970
Sales
2,850
5,895
163
714
577
Administrative/Other
902
4,820
2,700
2,123
2,000
Total
34,632
28,821
8,757
4,612
46,921

Apparently the five companies give different interpretations to the EEO codes. For example, Intel, which I calculate has almost 47,000 employees, has only 41 "Officers and Managers," less than 0.1% of the workforce. By contrast, Ingram Micro has 236 "Officers and Managers", almost 6 times as many as Intel, out of a workforce of 4600, one-tenth the size of Intel's. That means Ingram Micro's Officers and Managers are 5% of its workforce. Is Ingram Micro that top-heavy and is Intel that lean? Or what?

The CNN Money interactive tables let you view the total number of people the company designated in each category, as well as how many are men or women, or your choice of any combination of gender -- all, men or women -- and ethnicity -- all, Asian, Black, Hispanic, White, or Other.

Because all five companies have at least five women in the top category, it is possible to calculate a range of Morris Numbers. We cannot determine the precise value without more information about people's actual positions. (See Part 03 of this series for a discussion of different ways to rank employees using objective data.) Sometimes the companies' webpages help, at least for the very top of the top. I analyze some of this information below.

A suspicious mind might suspect that companies use as broad a definition as they can for the top category in order to have as few zeroes in the non-white-male boxes as possible. The range for the Morris Number [LOW, HIGH] for each company does not prove or disprove that theory. The greater the overall number of employees in the top category, however, the higher (worse) the upper limit on the Morris Number range.

MORRIS NUMBER RANGES FOR THE FIVE TECH COMPANIES

If we do not know the precise rankings of the women in a company's top management, we can at least calculate the range. The best (lowest) Morris Number is obtained by assuming the first five woman are clustered at the top, above all the men, the highest (worst) Morris Number by assuming that the fifth and all lesser-ranked women in that category are clustered at the bottom. (The ordinary Morris Number is the same whether the first woman is in that bottom cluster, too, or is the CEO. I propose the weighted Morris Number to take into account the actual positions of the four women you pass on the way to finding the fifth highest ranking woman.

Let's take an example, first with numbers, then without, to understand how this works.
        Total people in the category Officer and Managers is 105.
        Number of women in that category is 5
        Number of men = 105-5 = 100

If we assume the least sexist (genderist?) case, the 5 women are all at the top, the 100 men come below them, and the Morris Number is 0. In the worst case, the 5th woman is ranked below the 100 men and the Morris Number is 100. We can write the range as [0,100].

We can derive a formula, too. If T = total and W = women, then the worst number is T-W. If there are 5 or more women in the category, the best number is 0. If there are less than 5, then the next category has to be included to get the Morris Number.

Now let's consider Pepitone's data.

MORRIS NUMBER RANGES FOR FIVE TECH COMPANIES


The Officers and Managers row of the interactive tables shows that
Cisco: Women are 44 of the 225. Morris Number Range: 0 to 181
Dell: Women are 27 out of 125. Morris Number Range: 0 to 98
eBay: Women are 10 out of 55. Morris Number Range: 0 to 45
Ingram Micro: Women are 47 of the 236. Morris Number Range: 0 to 189
Intel: Women are 6 out of 41. Morris Number Range: 0 to 35.

Conclusion: Intel looks the best. Ingram Micro looks the worst, with Cisco a close second.



CISCO: The senior management (according to http://newsroom.cisco.com/exec-bios, last viewed 3/14/14), has only 71 people, compared to the 225 that CNN Money reported was on Cisco's EEO-1. The top level is called the Executive Leadership Team. The 15 members, 11 men and 4 women, are listed alphabetically by last name. The women's titles are SVP and Chief Marketing Officer; Chief Technology and Strategy Officer; CIO and SVP; and SVP and Chief Human Resources Officer. We need only look for one more woman to calculate the Morris Number. Of the 56 people in the next level, the Senior Leadership Team, 6 are women, 50 are men. (The fact that there are more women proportionally in the top level (4/15 = 27%) than in the second level (6/56 = 11% )reminds me of the Indira Phenomenon.) If one of the six women in Senior Leadership is above all the males in the category, the (lowest) Morris Number is 11. If all the men are above F#5, the (highest) Morris Number is 61. Range for Morris Number: [11,61].

INGRAM MICRO: The webpage listing Ingram Micro's senior management (corp.ingrammicro.com/About-Us/Executive-Leadership.aspx, last visited 3/17/14) has only 20 people, compared to 236 on the company's EEO-1 filing as shown on the CNN Money table. Of those 20, apparently listed in rank order, there are 2 females and 18 males. F1 is 11th, F2 is 14th. That means F3, F4 and F5 are below the 20 Executive Leaders. If they are directly below, the Morris Number is lowest: 18. If not, they must be somewhere among the remaining 216 (236-20, consisting of 189-18=171 men and 47-2=45 women). If F3, F4 and F5 are at the bottom with the rest of the women and below the 171 men, the worst Morris Number is 189. Range for Morris Number: [18, 189].

INTEL: The webpage identifying senior management (http://www.intel.com/newsroom/assets/bio/CorpOfficers.htm , last viewed 3/14/14) has the same number of employees, 41, as Intel had reported to the EEOC. The Chairman of the Board, a non-employee, brings the page's total to 42. Within each title -- Executive Vice President, Senior VP, Corporate VP -- people are listed alphabetically by last name so no ranking is revealed. The President, listed after the CEO so overall ranked #2, is female. There is also a female EVP (1 of 4), a female SVP (1 of 6) and six female Corporate VPs (6 of 29). F#5 is thus among the Corporate VPs, but we do not know her rank within that group. If she is top-ranked, Intel has the lowest Morris Number: 9. If she is below all the male Corporate VPs, Intel has the highest Morris Number: 32. Range for Morris Number: [9,32].

Conclusion: Intel still looks best, Cisco looks better, Ingram Micro looks about the same.


I also looked on the web for information about the younger tech companies with high profile women, Facebook (Sheryl Sandberg) and Yahoo (Marissa Mayer). The result was: they like to keep secrets. The Indira Phenomenon may be present at both companies.

Facebook lists only 4 executives on its main company information page, Sandberg and 3 men. The Board of Directors has the same ratio: 2 women and 6 men. A 2012 article in the Business Insider has a photo of 18 people from Facebook who had visited Walmart, 13 men and 5 women. Author Owen Thomas points out that the picture includes some "junior [Facebook] staffers who work closely with Walmart" which seems to include at least one of the women, a customer marketing manager involved with the Facebook-Walmart relationship. The other four women are COO Sandberg, her executive assistant, a (the?) director of design, and the VP for Human Resources (so often the only high level job for someone outside the homosocial reproduction group). If these are the four highest ranking women at Facebook, who and how far down is F5? Is Facebook better than Intel or Cisco?

Yahoo's Proxy Statement filed in 2013 has a table showing the ten most highly compensated current or former executives. Two are women, one with the highest compensation on the list, CEO Marissa Mayer, and one with the lowest. Other than the Proxy Statement, I was unable to find anything from Yahoo with any executive leadership biographies or other information from which to calculate a Morris Number range.

True of false? 1. The younger the tech company, the more secretive about diversity data. 2. The younger the tech company, the worse the Morris Number. (Two more PhD ideas there.)
March 19, 2014; rev 1 20140330,0403

The Morris Number - Introduction (Morris Number 01)


I propose a new metric I'm calling the Morris Number.  It is a way to quantify how gender-neutral an organization really is. It makes it possible to compare employers -- businesses, non-profits, universities, governments -- with regard to their equal opportunity characteristics.  I thought of the concept when I wrote about Silicon Valley: Boys Club last year.  Whatever the organization, the Morris Number answers the following question:
How many men do you pass on the way to finding the fifth highest ranking woman?
Other discriminatory behavior can also be evaluated with Morris Numbers.  Instead of men and women, any two demographic categories can be compared, e.g., whites and non-whites (or, for tech companies, TECMYs and non-TECMYs).
In a perfect world, the Morris Number averaged over many organizations would be 4.5. Assumptions behind the phrase "in a perfect world" are discussed in Part 02. That post also includes questions raised by friends when I first mentioned the Morris Number.

In the real world, almost all employers have a Morris Number above 4.5, often far above. Perhaps if we start calculating and publicizing Morris Numbers we can start to see them change.

The Morris Number may remind some readers of the Bechdel Test, which evaluates movies on a scale from 0 (bad) to 3 (good) depending on the presence of female characters and what they do. Both the Morris Number and the Bechdel test are metrics concerning unequal opportunities for women. They differ, however, in that
  • the Morris Number is for all employers, not just movie producers,
  • unlike Bechdel, and instead like golf and cholesterol, a lower Morris Number is better than a high one, and
  • the Morris Number can be much higher than 3, and almost never, alas, is that low.
A Morris Number in the single digits means that the employer's hiring and promotion practices today are what I would have predicted back when I was in law school.  A Morris Number above 10 reminds me that change sometimes takes a long time.

In the Fortune 500, is the average Morris Number below 30? What about in Silicon Valley?  Among major nonprofits? At the top research universities?  Wouldn't you like to know? I would.

HOW TO CALCULATE THE MORRIS NUMBER

You may be wondering how to identify the fifth highest ranking woman in an organization.  For a start, we can use the employer's organizational chart. 

Starting from the top person in the hierarchy, usually the CEO, count all the men you have to pass before you get to the fifth woman.  That is the Morris Number in its ordinary form.

True, there is an obvious problem with org charts.  If several people have the same title, how do you determine who has a higher rank?  You might want to base your answer on how much power each person has. To evaluate that, you might try objective indicia of power such as salary, budget, or direct reports.  Ideas about going beyond the org chart are discussed in Part 03.

EXAMPLES

In Part 04 I calculate ordinary Morris Numbers for some hypothetical entities and discuss a way to deal with the same-title-different-power problem.  Morris Numbers calculated from the tech company data presented in Julianne Pepitone's 2013 CNN Money article can be found in Part 05.

SAME MORRIS NUMBER, DIFFERENT REALITY

Part 06 presents a comparison of the ordinary Morris Number, which we  might call the OMN, with a weighted Morris Number, WMN.  The reason to add weights is to distinguish between two companies with identical OMNs but different distributions of the sexes. For example, a company with a Morris Number (OMN) of 5 might have men and women alternating in the top 10 positions, or it might have men in the top 5 positions and women in the next 5.  The WMN quantifies the difference.

MORE PhD IDEAS

Comparing Morris Numbers among companies, times, or regions, would be interesting. So would looking at how a company's Morris Number changes when it has a female CEO. We might also use Morris Numbers to examine what I call the Indira Phenomenon. (It probably has a name already but I am not aware of it.)

Another metric for gauging equal opportunity would be to identify the compensation deciles with a 50/50 gender ratio or an ethnic ratio similar to the population in the area.

Those and other ideas for PhD dissertations in Economics, Political Science, Statistics, Sociology, Gender Studies or American Studies are in Part 07.
RJM 3/19/2014; rev 1 20140321;0401

       May 08, 2014
Part 08 has a brief excerpt from Patricia Sellers' October 2000 Fortune article about Women CEOs in which she quotes Cisco CEO John Chambers on the future for women in Silicon Valley companies. It is 2014. Rank Chambers' prediction on a scale from 1 to 5 where 1 is totally wrong and 5 is totally right. And weep.

       June 2, 2014
Part 09 discusses Google's diversity numbers and the quote on its Diversity page about how women do not major in CS like they used to. There's an obvious idea there that Google is somehow missing.