Gradient Systematics

Data Analysis & Visualization

We turn your data into clear, reliable information for planning, operations, and decision-making.

Reports That Give You an Answer

Most organizations have plenty of transportation data. The challenge is turning it into information that can be understood, compared, and used to make a decision.

We turn raw records into defined measures, analyze them against the appropriate benchmarks and context, and present the results clearly. Whether the output is a technical report, a set of maps and charts, or a recurring performance report, the goal is the same: a clear answer supported by the underlying data.

25+ Years of Experience in Transportation Engineering
100+ Successful Projects Nationwide

From Data to a Decision

Good analysis starts with reliable records and ends with information that can support a decision. The important work happens between the two.

1

Records

Counts, transactions, incidents, maintenance records, model outputs, weather, and other source data provide the foundation for the analysis.

2

Measures

We define the measures that matter for the project and apply them consistently so results can be compared across locations, time periods, or scenarios.

3

Indicators

A measure becomes useful when there is something meaningful to compare it with: a previous year, a target, a peer location, a design standard, or an expected result.

4

Decisions

The results can inform planning, operations, investment, project evaluation, prioritization, and other decisions.

Numbers Built to Be Examined

The difference between an answer that takes days and one that takes months is whether the numbers were built to be questioned in the first place. Ours are.

Defined Once, Applied Everywhere

Every measure has a written basis behind it, so the same question asked twice returns the same answer. Definitions live in the system, not in someone’s spreadsheet.

Reconciled, Not Absorbed

What we produce is tied back to the totals you already report. Where the numbers differ, we show the difference and explain it rather than quietly closing the gap.

Traceable End to End

Any published number can be followed back to the raw record it came from. When a reviewer, auditor, or board member asks where a figure came from, the answer takes minutes.

Standing, Not Rebuilt

The system stays current on its own. New measures are added as definitions rather than as projects, so a new question does not start a new build.

Forecasts You Can Measure

Forecasting is only useful when you know how well the model performs. We test forecasts against data the model has not seen and measure error across different forecast horizons.

Rather than presenting a single number as if it were certain, we provide a forecast range and show how uncertainty changes over time. We also track actual results against the forecast so changes can be identified and investigated as they occur, not months later when the reporting period has closed.

How You See It Is the Last Decision, Not the First

The same measures can arrive in whichever form is actually useful to each audience.

A recurring pack

For a board, a client, or an agency, on a fixed cadence and a fixed set of definitions.

A working spreadsheet

Because a great deal of real analysis still happens in one, and it should be a good one.

A feed into your tools

So the numbers live where the decisions are actually made, not in a separate place people have to visit.

A live dashboard

When it earns its place, shaped around the questions you ask most, not around what is easy to chart.

We work in whatever your team already uses, including Power BI, Tableau, Python, and Excel. The analysis does not change based on where it lands.

Our Services

Specialist capabilities that sit on the same foundation.

Dynamic Dashboards

Live views built on the measure layer, so what you see on screen carries the same definitions as everything else we produce.

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Traffic Modeling Visualizations

Road network visualization using TransCAD, CUBE Voyager, and VISUM integrated with GIS tools, including 3D views that make a complex analysis legible to a non-technical audience.

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Machine Learning and AI

Learned models used where they genuinely outperform, always alongside a structural model rather than in place of one, so a result can still be explained.

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Ready to Put Your Data to Work?

Tell us what you are trying to decide, and we'll suggest the measures that would answer it.

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