At roughly this point in journals of my timeline on the Coast Guard’s Data Readiness Task Force (DRTF), from June 13th, through June 16th, 2022, I elected to discuss my experience at the Military Operations Research Society (MORS) 90th Symposium. Overall, I had mixed feelings about the MORS Symposium (to date it is the only in-person MORS Symposium I have attended). I started my work as a data scientist in the Coast Guard in February of 2020. So, the MORS 88th and MORS 89th Symposiums were each virtual (due to the COVID-19 pandemic), and the MORS 90th Symposium was my first in-person experience. I am left with a trio of distinct impressions.

1. I wish I were a data scientist in the Department of Defense.
2. The Department of Homeland Security analytic (“quant”) senior leaders do not understand the frustrations of junior data scientists.
3. The best thing I can do is keep up the grind and further my experience as a data scientist.

Department of Defense Analysis

In part, the first bulleted impression I wrote is impacted by the second impression. Nevertheless, from multiple presentations I attended, it was apparent the opportunities for data scientists in the Department of Defense (DoD) are much more abundant (and much more extensive) than the opportunities offered to Department of Homeland Security (DHS) data scientists.

Thus far in my blog, I have largely highlighted the Coast Guard’s struggles to implement a modern data solution that gathers disparate data sources in a central location and makes it available for analysis. Following that narrative across the previous ten posts, would it surprise you to hear the Army has already achieved this in different use cases across their service?

Specifically speaking, I attended a presentation titled, “In-Stride Analysis of Tactical Network Data Driving Project Convergence”. In this project, the Army consolidates communications data on the terabyte scale to complete campaign analysis and inform decision making on a daily basis. Further, the Army is accomplishing this at a SECRET level of classification. Now, setting up the stand-alone classified network is likely how the Army gained flexibility with regards to implementation. Nevertheless, the logical argument stands, if this can be done at a classified level, how is it that it cannot be done at an unclassified level?

Howbeit, the main reason I began to wish I was a DoD data scientist was because of the messaging from their senior leadership in comparison to the messaging from DHS’s senior leadership.

As a data scientist in the Coast Guard (and one who was willing to respond to the solicitation for the Data Readiness Task Force), and gleaning information from Jim Simmons (mathematician and founder of Renaissance Technologies hedge funds) I identified some key metrics I believe the Coast Guard should be working towards in its data journey to becoming a data driven organization. Roughly ordered, these metrics are:

1. Everyone in the organization has access to the data relevant to their team/work.
2. There is a transparent entity (or entities) who is (or are) responsible for data quality.
3. Opinions are voiced only when accompanied by supporting data.
4. Numbers are communicated even (and especially) when they communicate negative messages.

Within the Coast Guard, we are still working to overcome the first and second bullets (so we can begin to address the third and fourth bullets). Unfortunately, it seems that a significant amount of effort for the Data Readiness Task Force (DRTF) is simply getting senior leadership within the Coast Guard to support efforts like:

1. Ensuring everyone in the organization has access to data relevant to their position, and
2. Designating data owners to be responsible for data quality across the different data sources throughout the organization.

The senior leadership represented at the MORS 90th Symposium from the DoD effectively communicated an understanding of these metrics and the sentiment of frustration amongst junior data scientists with regards to them. This alone, stands in stark contrast to my experience within the Coast Guard, in addition to the impression I get from the DHS quant leadership who were present at the MORS 90th Symposium.

Department of Homeland Security Analysis

At the MORS 90th Symposium, the senior leadership representing DHS were all associated with the DHS Science and Technology Directorate (DHS S&T). An unfortunate and glaring example of how I began to form the impression DHS’s senior leaders do not understand the frustrations of junior data scientists is with respect to the DHS junior/senior analyst panel.

At the MORS 90th Symposium the junior/senior analyst panels were intended to offer a dialogue between junior and senior analysts regarding the shared areas of interest in our profession. Unfortunately, for the DHS senior analysts, their plans for this panel were seriously misguided.

It was apparent the senior analysts prepared for a panel targeting entry-level, junior analysts. However, these senior analysts failed to realize within DHS, there are very few employees who would qualify as entry-level analysts. Anyone entering an analyst position in DHS typically has work experience if not additional post graduate level education. So immediately, the “eat your vegetables” advice being shared was condescending.

Realistically, most of the junior analysts in the room were middle management. And the interaction quickly devolved into middle management “poking the bear” that was senior analysts. However, the senior analysts continued with their planned narrative, and the result was unproductive.

I will always remember the point at which a junior analyst asked how we will approach a truly analytically informed operations center? The junior analyst elaborated on integrating data from multiple sensors and sources and informing operational decisions with machine learning and other analytic techniques in real time. And the most senior analyst from DHS S&T just replied that we need data standardization.

From my perspective, data standardization seems like a convenient deferral of blame and responsibility. Throughout my blog I lament what makes failure in progression towards these data technologies so frustrating is the technology for the vision already exists. There is nothing outside the realm of the possible with respect to the question posed. Yet, it often feels like we are no closer to this modern data structure today than we were yesterday. “Data standardization” is the excuse for not making progress.

As a data scientist, I am understanding of messy data. Most of the work for every analysis I contribute to is cleaning data. But this alone betrays two things with respect to the senior analyst’s statements:

1. data standardization is not a strong excuse for not achieving in data and
2. the senior analyst does not believe this.

Perhaps I have a stronger risk tolerance than senior leaders? Perhaps my approach of not accepting perfections in data standardization is too bullish for working with data as it currently exists within DHS? But I do believe the point I am making is legitimate. Which is, if every data scientist were waiting for perfect data before starting analysis, then analysis would never get done.

Be the Best Analyst You Can Be

At the MORS 90th Symposium I spoke for three different presentations and was involved as a moderator for a fourth. For each of these presentations, I was approached by someone else and encouraged to present the work I contributed to. In each of these cases, I was humbly unaware people may be interested in the work I did or was doing. I simply had my head down and my nose to the grindstone.

On 06/15/2022 I co-presented, “Aids to Navigation Team Saugerties Location Alternatives Simulation Analysis” and presented, “SURVEYOR: A DISA BDP as an All-Domain Analytics Platform”. On 06/16/2022 I co-presented, “Simulation and Value Modeling Air Station Closures”.

Yet, as I stressed over and completed my presentations, it struck me in the end I did not feel I accomplished much of anything by presenting. I talked through sound math and practice. And the presentations were well received. And then they were over.

When I first graduated from the Coast Guard Academy, I decided I would consistently work hard, and the things like evaluations, assignments, promotions and accolades would all take care of themselves. As I reflected upon the MORS 90th Symposium, this stood out to me more than ever. It is easier for me to work hard and let everything else take care of itself.

These views are mine and should not be construed as the views of the U.S. Coast Guard.