Data Democratization and the Right Bright People

Kim D. Desrosiers

Kim D. Desrosiers is a Managing Director within the Environmental Solutions practice of FTI Consulting, an independent global business advisory firm, dedicated to finding solutions to clients’ complex problems.

Her research, developed from geospatial analyses and big data, has been published by numerous institutions, including The Brookings Institute,, and the Northeast Clean Energy Council. She currently serves multiple groups as a neutral fact-finder and cost allocation consultant in the resolution of high-stakes environmental claims at Superfund Megasites.



Reaching the BHAG with Spatial Data Democratization and the Right Bright People

In my environmental practice, we know a lot about sewers. We like it, but I will admit, it isn’t a glamorous job. When I started in the environmental field, I studied the research of garboligists, scientists who looked at how garbage was transported and densified in landfills. (Yes, it is surprising, but that is a real thing.) As environmental enforcement has moved from landfills to sediment sites, we have moved as well, studying the history of sewers, how they were designed and built, and have developed our own methodologies to reverse engineer from current-day infrastructure the historical pathways that served to direct or bifurcate flow. And now you may ask why that is a thing? It is a thing so that parties involved in environmental claims involving historical discharges can determine if they or their predecessor’s liquid waste ended up in the river, or not. We call it historical sewerology, and the work is so specialized, even Google can’t seem to find anyone else who does it.


Start with One

As with all engineering problems, in professional services, we start with a scale model of a possible solution to a problem. Once we have worked successfully to the problem’s solution using the model, we scale-up. The model reflects the most efficient method of solving the problem, and contains within it the wisdom of the previous failures. In our historical sewerology work, the same principle applies – start with one engineer (that’s me), figure out first how to solve the problem, then create a system that allows that problem to be solved many times by others (emphasis on plural). It is the “others” learning how to run the model that is good for our clients, and for our firm. Why? Because in professional services, the economics of “teaching mentees to fish” is widely recognized as a growth-oriented business model. With higher leverage on engagements, so comes lower blended rates to clients and higher gross margins. The first step is actually finding the suitable fisherpeople, and in my real-life example, historical sewerologists, but we’ll leave that to later. Let’s first find that ideal fishing rod.


Geospatial is Born

In 1968, only two years prior to the establishment of the US Environmental Protection Agency, one of the most effective “fishing rods” in the environmental field was invented: Geographic Information Systems, or “GIS.” GIS orients information in such a way that it can be interpreted in relationship to the surface of the Earth, and it changed the way we worked with environmental data. Before its advent, geologic formations, topography, sampling results, and the like were examined via paper media, with more sophisticated professionals using transparencies laid over top one another. Remember your teacher’s transparencies in class? Just like that.

This method was reasonably effective from the environmental specialist’s point of view. The expert created the transparency layers appropriate for the analysis of the problem based upon their assessment of what was important, and could rearrange, add, or remove layers as necessary. From today’s point of view, this manual process of creating the layers has its obvious limitations. Dr. Roger Tomlinson, the father of GIS, also had that view, and as a result, developed a digital system so that he could conduct spatial analysis of convergent geographic data. This specialized form of data is now commonly referred to as geospatial data.


Geospatial as Your Go-To Rod

Environmental professionals now routinely collect and query geospatial data. As we have worked with geospatial data sets, and particularly the true cost of collecting, maintaining, and updating those sets so that our queries are relevant, so too have we developed best practices to create and maintain only that which is needed to solve a well-defined problem. This form of analytics has been so successful, it is now routine to look for identifiable spatial relationships inherent in collectable data. The combination of software availability and familiarly with geospatial relevancy has brought about a tectonic shift in how GIS is used by decision-makers, with expansion into areas as diverse as cybersecurity, customer relationship management, healthcare, economic competitiveness, mortgage risk, supply chain management, and geodemography, to name a few.

In my practice at FTI, we are a part of this geospatial sea-change. We have learned how to harness spatial technologies to increase dimensionality and gain efficiencies by solving two interrelated but distinctly different project challenges – the first of these related to project scale, and the second, schedule. The project scale was large – over 300 individual problems needed solving, with only one sewerologist who also happened to be our only GIS software analyst. In essence, the engineer had to function as both the subject matter expert, and the software expert. Given both scale and schedule, overcoming this skill silo was to become our Big Hairy Audacious Goal (BHAG).

It is common for projects to end before they start when the project manager realizes that their GIS analyst is too busy. In fact, the inability to liberate geospatial information from the technologist that knows the software has been one significant dampener on the geospatial movement in business, and a fundamental barrier to the wider application of GIS. While the geospatial “rod” is a powerful tool, like most specialized software weaponry, wielding it takes significant investment in training. But what if it didn’t?


Adding “Spatial” to Data Democratization

“Data democratization”, according to Forbes’ Bernard Marr, “means that everybody has access to data and there are no gatekeepers that create a bottleneck at the gateway to the data.” It requires access, and a simple way for people to understand the data. For five decades, IT departments have been the data managers for business. With data democratization, businesses liberate big data out of the IT silo, putting information, and the ability to query that data to answer questions, directly in the hands of the decision-makers. Those decision-makers are ideally positioned to then apply actionable intelligence and pivot quickly.

Similarly, to meet our BHAG, we had to find a way of liberating our geospatial data from our GIS software silo. To do that, we first had to create an intuitive, multi-user system that presented sewer engineering schemas both spatially and temporally so that reverse engineering routines could be streamlined. Because we work with the historical record, much of our “data” only exists as a scanned document. The historical record at play in all of our sewerology projects covers schemata drafted by engineers during the last hundred years, some even dating back to the late 1800s. One typical GIS approach would be to “rasterize” these documents, a process that results in a series of pixels, dots or lines within a georeferenced image file. In our historical sewerology project example, rasterizing did not present a viable option, not exclusively for issues of schedule or budget, but rather, for issues specific to the need to allow the engineer to read the document in its entirety. Historical engineering documents are special beasts; they require context, and the analyst an awareness of the engineering art employed at the time each document was authored. Instead of making raster images, we developed a spatially-related approach to launching the document such that the engineer could localize their system analysis with the full set of engineering plans layered onto other geospatial data sets. And it worked.



Once our intuitive, multi-user system was launched internally to our team of engineers and historical sewerologists, it worked so well, and was so easy to use, we knew we needed to share it externally with our clients. Our clients can now perform the same routines as our internal teams using our Allocation Process Geographic Information System or APGIS. Our AEGIS system was developed to serve geospatial data in an even more simplified and elegant form.

Our system of spatial data liberation ultimately was successful because of the transformation method we developed to put the data in the hands of our subject matter experts, our historical sewerologists. Getting to our BHAG was not easy, but it was simple. Liberate the skill silos of the past, and empower the right, bright people of the future. It isn’t just a thing; it is the thing.




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