Thermo Fisher: ten years at an uncommonly fabulous company

Many laid-off employees trash their former employer. But my decade at Thermo Fisher stands as one of the richest experiences of my life, despite significant challenges along the way. So I want to remind current Thermo Fisher employees and leadership what they can take pride in:

Exceptional Handling of my On-the-Job Gender Change

I joined the company at the Austin site as “Daniel Edmund Williams” and left from the Carlsbad site as “Emily Marie Williams”. No easy feat.

The (public) transition took place one year into my tenure at the Carlsbad site. My colleagues there embraced my chosen identity completely. Sure there were a few initial hiccups in name and pronoun use, but those faded quickly. No one fussed about the bathrooms or showers.

Yes, a few folks were uncomfortable at first. I took them to lunch. I turned the other cheek. They came around.

Thermo Fisher employees and leadership can therefore take pride in their openness.


Thermo Fisher’s HR department knows what they did for me, along with the challenges I faced. These stories are of course not for public consumption.

I thank them for all their tremendous support. I thank them for all the collaborative problem-solving and for delivering substantial grace.

Thermo Fisher employees and leadership can therefore take pride in their Human Resources Department.

Learned to “Manage Up”

Working at a large corporation for a decade usually means reporting to multiple bosses. Most managed exceptionally well, a few struggled. One was downright abusive. Immersed in this environment, I became skilled at collaborative problem-solving and team-centered idea promotion, skills I’m extremely thankful for.

I also learned how to stand up to the abusive boss—proudly setting an example for my less experienced colleagues.

Company employees and leadership can therefore (mostly) take pride in their management.

Learned to Manage (Down)

An intern reported to me one summer, allowing me to develop my talents at management. While no one specifically coached me on management skills during this period, the many good (and a few bad) management examples set around me directed my compass.

Acquired Technical Skills and Sharpened my Business Acumen

Immediately following my layoff last July I founded Whole-Systems Enterprises, Inc. Employing all the data science skills I learned at Thermo Fisher, we are developing and optimizing day-trading algorithms. We are also selling bioinformatics and data science consulting services. My experience at Thermo Fisher made this possible.

Thermo Fisher employees and leadership can therefore take pride in their technical development.

Why Am I Saying All This?

This blog, and the book I’m writing based on it, covers transgender issues. Employment is a major transgender issue, not just during the public act of transition but encompassing the whole life experience of work. I wanted to celebrate an organization that is getting it right.

The whole proves greater than the sum of its parts.

HRC Corporate Equality Index correlates with Fortune’s 50 most admired companies

The Human Right’s Campaign, one of America’s largest civil rights groups, scores companies in its yearly Corporate Equality Index (CEI) according to their treatment of lesbian, gay, bisexual, and transgender employees [1]. The companies automatically evaluated are the Fortune 1000 and American Lawyer’s top 200. Additionally, any sufficiently large private sector organization can request inclusion in the CEI [2].

Similarly, Fortune Magazine publishes an annual list of 50 of the world’s most admired companies [3]. Companies are rated by financial health, stock performance, leadership effectiveness, customer sentiment, scandals, and social responsibility.

I became curious whether CEI scores correlate with membership in Fortune’s most admired list, so I matched the two datasets and analyzed the outcome. The results (below) are striking. Code implementing the calculations, with the source data, is attached.


Plotting the CEI score distributions by whether a company was included in Fortune’s list produced:

From this difference in distributions it is clear that the status of being “most admired” correlates with a high CEI score, though there are a few outliers. In the distribution on the left, we see that over 50% of the companies in Fortune’s list held the top CEI score of 100, whereas only 25% of the companies not contained in Fortune’s held the top score. The median score for the most admired group was 100 while for the companies not included in Fortune’s list it is about 80. Over 80% of the most admired companies scored 90 or above. The variance is much wider for the companies not included on the list. Statistical analysis comparing the two groups, detailed below, confirms the correlation.

While correlation does not imply causality, this analysis suggests two things: First, the type of leadership necessary to achieve a high CEI score is the same type of leadership that leads to inclusion in Fortune’s most admired companies group. Second, any company aspiring to membership in the most admired group might consider developing its CEI score.

There is one possible source of bias, but I don’t expect that it is large: “Social responsibility” is used in Fortune’s rankings, which may include CEI scores (I don’t know). However, Fortune’s emphasis on financial health and stock price probably trumps any contribution that the CEI would generate alone. Furthermore, in the CEI score distribution for the most admired companies, there are outliers containing extremely low scores. This suggests that the CEI played little if any role in the selection of most admired companies.


I manually copied and pasted the company names and scores from the CEI online database [1]. Then I cleaned up the results to create a manageable CSV file. Similarly, I copied and pasted the Fortune 50 most admired company list [3] into another CSV file. After that, I matched the two datasets by hand. Perhaps I could have performed the match algorithmically, but I would have had to worry about different representations of company names between the two datasets, e.g. “3M Co.” vs. “3M”. There was only 50 cases so the manual match did not take long.

Two cases in Fortune’s list had to be excluded, BMW and Singapore Airlines, because they were not included in the CEI, possibly because they are based outside the USA. In the case of two other non-US companies in Fortune’s list, Toyota and Volkswagen, I matched to Toyota Motor Sales USA and Volkswagen Group of America, respectively.

Finally, I plotted the CEI score distributions shown above and performed the statistical analysis reported below using the attached Python code.

Statistical Analysis

The extreme difference in variance between the two groups makes it impossible to compare medians using a non-parametric test, and the distribution of the CEI scores does not lend itself to a clean regression analysis. Therefore I built the following contingency table from the data:

The p-value for this table obtained from Fisher’s exact test is 4.53e-08, indicating that the proportions are significantly different.



Code and Data