Month: December 2018

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International Trade Data, Organizing Data and Client Support

On December 19, I agreed to talk at the New Orleans Data Group. The previous speakers presented work that was largely for internal audiences, so I wanted to focus on something more applied. With my interest in trade, this seemed a good fit.

Globalization refers to interconnected economies, and in a connected world, this largely is tied to investment (such as Foreign Direct Investment), Services, and Goods. (Here is a good place to start if one wants information on U.S. global activity) So, the rest of the talk focused on trade in goods.

There are many reasons why post World War II trade growth blossomed, but the economy benefited from transportation and telecommunication innovations and regulatory changes. (A good discussion of some of this was referred to in Wired magazine’s article “The 20-Ton Packet”)

But trade represents the sum of many things. For example, here are two different industries, such as toys (left) and cut flowers (left). So, there are seasonal patterns to importing merchandise, as there is just as strong seasonal exports of grains and other products. As such, trade represents the sum of decisions between many companies, (a significant amount of trade is intracompany flows).

But we don’t see “TRADE”, we see transportation. Have you ever wondered what was in the truck? The picture on the right was trucks stopped in Louisiana because of a flood in 2016, but most trucks in the Southeast are moving cargo that is intrastate or internal to the Southeast. Trade, as a share of total trade, is actually only 17% of the total traffic activity. However, in Louisiana, as a very strong maritime trade, maritime trade represents a significant industry when compared to other states. (ITTS Working Paper 1 – “International Maritime Trade Benefits the Nation’s Economy“)

There are different pieces of information tied to an international shipment, such as the cargo’s origin and destination, its port of entry, and destination, duties, etc. What is not represented in the chart below is information about the shipper and receiver, the value of the cargo, who is paying for what activity (and is bearing the transportation risks) and other details. The data regarding international trade could thus represent a transaction (generated in respond to an event) or metadata, such as regarding the cargo itself, that is independent of its location and movement. (When conducting trade research, one has to remember U.S. Government disclosure rules do influence how much information can be released.)

Cargo is more likely to move via truck or air for time-sensitive shipments; on the other hand, water tends to handle large, less time-sensitive shipments with lower per unit costs. People make this trade-off. The more expensive the product, the more likely it is that air or trucking will be the
mode selected. Depending on the shipment size, people are more likely to use water, rail or pipeline for similar cargoes. As a result, people’s mode selection is based upon the value, timing, and size of the cargo.

So, there are many things related to trade. The researcher would need to know the details about season patterns, mode, etc., when organizing the data and/or query.

What was delivered…

As part of an ongoing research work, I put several databases into Tableau for the Institute for Trade and Transportation Studies member states. The effort was to develop workbooks with international trade data and other sources of information that may be of use to local planners and economists.
The video about how to engage the dashboards is here.

Working Paper 21 – “Executive Briefing Book”  (June 2018)

The following table represents the metadata regarding the data released for the states. (There are other sources of trade data not included in this study.)

The above graphic shows some metadata about the data sets I integrated into Tableau for the ITTS member states.

In reviewing the project, I talked about the need for the client to understands how to access the data and the data elements are included, so they can duplicate/review the work. I also discussed how to organize the data into Tableau, including challenges I faced regarding one to many joins and matching geography.

If you are interested in more discussions on trade data, I did a presentation at the University of Southern Mississippi regarding trade brochures developed for the ITTS member states (there are some other trade reports posted at http://www.ittsresearch.org/state-reports.html).

The real takeaway from all this…trade data is complicated, especially if one forgets the metadata, for surely the devil is in the details.

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How Does Intelligence Fill Santa’s Sack?

Based on my earlier blog post, that intelligence is the information that one uses as the basis of wisdom, I would add yet another examination of Santa and Kringle Inc’s use of big data and system processes. 

So, I start with the obvious, the goal of Kringle Inc., namely, to determine what gift goes to what child in what location on a certain day.   So, when Santa talks about his busy day, he is managing a lot of information so that he can manage many items, ranging from sourcing, production, trade and duties, and personnel matters, from reindeer training to elf productivity.  In all cases, the clock is ticking (I wonder if Santa screams like Tom Hanks in Cast away). 

We know that Santa has list concerning a child’s conditional status concerning a child’s ranking! The child, based on the behavior (crying, asleep, good, and bad), is collected from various sources, such as parents, teachers, mail, (Ray Steven’s song suggests it may borderline on obsessive).  Given the times, I wonder if Santa purchases search and social media information, or aggregated email services. So, if the child passes  “the Good Test”, the next item is what should a child should receive.  Here Santa evaluates the child’s gift(s) based on preferences, previous year’s gifts, age, etc.   In many ways, Kringle Inc. maintains several relational databases of each child’s demographic (location, age, etc. and preferences) that is joined to another database on gifts. 

These gifts are then placed into a production stream, employing many elves. (Kringle Inc. successfully hires and trains workers in a rural community, and that is worth something!)  The toys are loaded into the sled, and after negotiating all the appropriate tariffs and import fees, Santa is on his way.  So, Kringle Inc. has to maintain inventory, customs filings, to translate the child gift to the location and delivery window.  I wonder how Kringle Inc. manages to satisfy animal health codes, but that is simply a minor problem considering all the other transportation questions (hazmat cargoes) Kringle Inc. must organize in the sled’s stowing plan.

So, we have the Kringle Inc. decision tree.

But not every gift from Santa goes through this process.  Sometimes Santa shows up (yes this is me in 1984) and hands out toys at a neighbor’s day care.  (And only in Louisiana could a Santa Claus wear rubber boots.)

  • bruce lambert playing santa clause in 1984

Merry Christmas to all,  Bruce Lambert


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Talking Freight-Dec 19- Notes Posted online

https://www.fhwa.dot.gov/planning/freight_planning/talking_freight/december_2018/

Several months ago, I approached Chip Millard about the question of freight data and geography, and so we worked together to put together this session.  I hope you can register and join in! 

Registration is now available for the December 19 Talking Freight Seminar.


Date/Time: December 19, 2018  1:00 – 2:30 pm ET

Topic: Using Freight Data in the Proper Geographic Contexts: Challenges and Opportunities

Registration: https://ops.fhwa.dot.gov/freight/fpd/talking_freight/index.htm

Description and Presentations: While freight activity utilizes a mix of different networks, from the global to the local, each movement depends on the same transportation system.  In many cases, a study area’s geography may be small when compared the users on the system (a local connector study) or so broad that geography may not matter (national traffic patterns).  Not all freight transportation data can be used at every geographic level; some data can only be used for macro-level geographic analyses, while other data are only appropriate to use at small-scale or micro-level geographies.  For transportation agencies and companies that are interested in conducting freight transportation analyses for larger geographies, such as for an entire state or along an entire multijurisdictional corridor, or for smaller geographies, such as for a metropolitan area or county, conducting those analyses can be challenging because data may not be useful for the required level of analysis without additional, analytical rigor.  There are also different of uses for freight data, ranging from simply education to project prioritization, which are not necessarily the traditional mode, commodity, and origin/destination freight data approach.

There are various transportation data sources in the public and private sector. Some of these sources are freight transportation-specific, like the Freight Analysis Framework, while others contain more general measures (demographic, economic, etc.) or geographic data (roadway networks, traffic counties, etc.) that can be adopted into a freight study.  Many challenges exist when transforming data to the proper geographic scope, where the planner’s needs are aligned with the required planning needs.

This webinar will discuss how different transportation entities are examining freight transportation using geography as the research goal, and are trying to make freight data “fit into” the study area.   The presenters will focus on the challenges they have faced in conducting freight analyses at both large and small-scale geographies, and provide insights concerning where data gaps exist and/or future research needs regarding program management, operations, performance metrics, or general planning needs.

Using Freight Transportation Data to Understand the Differences between Metropolitan Areas within a State

A series of presenters will provide an overview of a state DOT’s efforts to understand freight flows within their state through research programs to address freight data gaps. 

SPEAKERS:

  • Joel Worrell, Florida Department of Transportation
  • Thomas Hill, Florida Department of Transportation
  • Holly Cohen, Florida Department of Transportation

Utilizing Freight Transportation Data to Help Prioritize Projects along Key Freight Corridors (SmartScale) and Address Truck Parking Needs

This presentation will discuss how Virginia DOT has identified large and small-scale project needs along key freight corridors within the state.

SPEAKER:

  • Erik Johnson, Virginia Department of Transportation

Using Freight Transportation Data to Examine Last Mile Freight Transportation Needs

This presentation will examine how freight traffic volume information can be integrated into regional and local land use planning.

SPEAKERS:

  • Michael Brown, Metro Analytics
  • Chandler Duncan, Metro Analytics

 If you have not yet participated in Talking Freight, I encourage you to do so. These monthly seminars, sponsored by the Federal Highway Administration, are held via web conference, which means that you view the PowerPoint presentations over the Internet while listening to the presenters over your computer or the telephone. There is no cost involved and you do not have to leave your desk to participate. More information about Talking Freight is available at http://www.ops.fhwa.dot.gov/freight/fpd/talking_freight/index.htm  Links to past presentations and recordings are available on http://www.fhwa.dot.gov/freightplanning/talking.htm.