Make Better Logistics Site Decisions

Over the last six years, Logistics Today and Expansion Management magazines have worked together to develop and evolve the Logistics Quotient as a usable tool for site selection. The driving force behind the tool was the trend toward more frequent network re-view and optimization, which came about with the evolution of supply chain management and increased globalization.

In the end, every logistics site selection decision is regional. A company doesn't locate a distribution center (DC) in Seattle to serve the southeastern United States, nor do many companies operate a single massive distribution center to serve the whole North American market.

There are two sides to a logistics operation: inbound and outbound. Increasingly, inbound means import, and that suggests being close to an ocean port or having good connections to a port. With China presently dominating most companies' sourcing the U.S. West Coast plays a major role in most logistics networks. If that facility is primarily a deconsolidation center or cross-dock, many companies opt to outsource those functions, often blending them with the transport portion of the supply chain operation. But from there, the goods will enter a domestic distribution network that will vary in size and type of facility based on the service requirements of the market or specific customer needs.

One issue under discussion in distribution circles is the use of smaller regional distribution operations established to maintain consistent service levels in key markets or with major customers. The mega DC hasn't disappeared, but its reach may soon be extended by smaller DCs closer to the customer.

Smaller satellite DCs close to an end market can reduce the real estate and manpower requirements in markets where both may be scarce or expensive. But DCs, which typically sit on less expensive real estate near metropolitan areas, have been doing double duty as hosts for other business functions such as customer service call centers as companies find ways to reduce their requirements for high-priced urban office space. While the actual distribution needs for the facility may be less, the space requirements can be increased by the need to provide office space. Some of the data and telecommunications requirements this adds actually coincide with developments in logistics, so the needs are complementary.

The Logistics Quotient has also changed. Some of those changes involve subtle shifts in data sources or elements supporting the conclusions in the 10 major categories for which each metropolitan area is ranked. Some more noticeable changes may be visible when comparing past rankings to the current list. For instance, in the past six years, the U.S. Census Bureau has redefined some standard metropolitan statistical areas (SMSAs), dividing some former SMSAs along new lines or combining some metro areas to create new SMSAs (there are now 362 vs. the 328 when the Logistics Quotient started).

One major change in how we present the data lies in the elimination of the overall numerical ranking in the national and regional lists. Past regional versions displayed a national ranking for each SMSA included in that region and then later versions added a ranking within the region. This was somewhat confusing because it inferred a greater difference between some of the cities than actually existed. This edition groups cities among their peers. For instance, there may be 20 cities in the top rank (5 stars). The qualitative difference between the number one city and number 20 is relatively inconsequential overall. The difference between cities in the 5-star category and those in the next group (4-stars) does have an order of magnitude, but specific needs and opportunities may out-weigh those differences. For example, a heavy user of air freight will naturally put greater emphasis on good air service and access to airport facilities than a bulk shipper who depends on rail.

To overcome some of the bias the numerical rankings may carry, the cities are listed alphabetically within the broad rankings from 5 stars (top) to 1 star (lowest). Numerical values are still used in the 10 principal categories, and those numbers refer to a position on a national scale of 362 SMSAs where number one is the highest rank and number 362 the lowest. Thus, the New York/Newark SMSA is ranked number one in air cargo in the nation based on measures such as capacity, frequency and volume. Some rankings are based on a broader or statewide regional rank and so some cities will have the same rank for a category like rail.

One reason for using numerical rankings within the core categories and not adopting the star rating in each is the role the individual distribution center may play in a particular supply chain. A northeastern distribution center may provide regional service, but it may also be the principal hub for imports. This could add emphasis to air and ocean connections that would not be factors for regional distribution. By the same token, an import hub that also performs regional distribution depends more on highway infrastructure and local road density, safety and congestion than an international gateway might.

As with any guide this large and all encompassing, the Logistics Quotient is intended to support decision making. Its emphasis is on logistics-related factors. It can aid decisions to locate manufacturing or distribution facilities when combined with input from other functional areas and incentives offered by the state or municipality.

How to use the Logistics Quotient

The Northeast Regional Logistics Quotient matrix provides an overall ranking of each city within the Northeast region, assigning a rank of 5 stars to the top tier, 4 stars to the next group and so on down to a 1-star rank. The Logistics Quotient also features 10 logistics-related categories with national numerical rankings on a scale from a top score of 1 down to 362 (the number of Standard Metropolitan Statistical Areas ranked). Those categories are:

Transportation and distribution industry—based on business and employment base providing transportation, distribution, warehousing and related services.
Work force—geared to existing and available logistics-related workers in the area.
Road infrastructure—measures factors like available lane miles per capita, interstate highway access, miles of paved roads etc.
Road density, congestion and safety—ranks the city on traffic volumes and delays as well as accident statistics and other factors affecting the smooth flow of traffic.
Road condition—draws on state performance and includes condition of highways and bridges among other measures.
Interstate highway—includes access to interstate highways, spending on highway construction and maintenance.
Taxes and fees—provides a measure of logistics-related costs, including highway and fuel taxes and related business activity taxes.
Railroad
—offers a state-based rank of access to Class 1 and other rail services and miles of track.
Waterborne commerce—includes ocean port capacity as well as inland waterways.
Air cargo—ranks the city on its access to cargo services, including wide-body passenger service by combination carriers, international and expedited services.


2006 Rating METROPOLITAN AREA T& D Industry Metro Rank Work Force Cost Metro Rank Road Infrastructure Metro Rank Road Density, Congestion and Safety Metro Rank Road Condition State Rank Interstate Highways Metro Rank Taxes & Fees State Rank Railroad Metro Rank Waterborne Commerce Metro Air Cargo Metro Rank
5 out of 5 Albany-Schenectady-Troy, N.Y. 89 149 6 162 347 15 352 34 45 69
5 out of 5 Baltimore-Towson, Md. 21 70 157 199 288 3 152 34 24 36
5 out of 5 Boston-Cambridge-Quincy, Mass.-N.H. 10 56 82 213 296 23 109 34 31 17
5 out of 5 Buffalo-Cheektowaga-Tonawanda, N.Y. 44 31 6 106 347 81 352 6 60 57
5 out of 5 Charleston, W.Va. 115 126 223 171 251 36 247 63 6 115
5 out of 5 Harrisburg-Carlisle, Pa. 63 51 104 116 329 23 332 34 109 63
5 out of 5 Hartford-West Hartford-East Hartford, Conn. 49 85 40 154 325 36 223 34 225 31
5 out of 5 New York-Newark-Edison, N.Y.-N.J.-Pa. 1 34 5 234 346 1 159 2 3 1
5 out of 5 Philadelphia.-Camden, Pa.-N.J.-Del. 7 87 83 294 324 15 162 3 8 9
5 out of 5 Pittsburgh, Pa. 26 103 104 121 329 23 332 4 7 34
5 out of 5 Rochester, N.Y. 75 81 6 177 347 52 352 10 92 56
5 out of 5 Syracuse, N.Y. 81 96 6 55 347 36 352 102 85 65
5 out of 5 Washington-Arlington, D.C.-Md.-Va. 16 48 175 305 222 9 124 63 24 23
5 out of 5 Worcester, Mass. 83 114 17 96 329 52 127 63 31 107
4 out of 5 Allentown-Bethlehem-Easton, Pa.-N.J. 67 99 81 140 345 157 264 17 225 99
4 out of 5 Bangor, Me. 158 121 302 108 293 120 268 151 78 119
4 out of 5 Bridgeport-Stamford-Norwalk, Conn. 51 54 40 184 325 157 223 151 225 96
4 out of 5 Burlington-South Burlington, Vt. 181 186 272 54 290 120 162 34 123 143
4 out of 5 Manchester-Nashua, N.H. 122 119 206 158 264 120 98 225 225 63
4 out of 5 New Haven-Milford, Conn. 91 223 40 126 325 52 223 24 225 111
4 out of 5 Portland-South Portland, Me. 109 196 302 146 293 81 268 63 64 99
4 out of 5 Poughkeepsie-Newburgh-Middletown, N.Y. 97 123 6 156 347 81 352 63 225 84
4 out of 5 Providence-New Bedford-Fall River, R.I.-Mass. 47 106 156 147 362 81 207 151 225 77
4 out of 5 Scranton-Wilkes Barre, Pa. 79 76 104 23 329 52 332 24 225 143
4 out of 5 Springfield, Mass. 106 153 17 180 329 36 127 17 225 193
4 out of 5 Trenton-Ewing, N.J. 156 110 1 166 347 81 30 151 225 154
3 out of 5 Binghamton, N.Y. 239 334 6 43 347 81 352 102 225 217
3 out of 5 Erie, Pa. 213 242 104 269 329 81 332 34 79 193
3 out of 5 Hagerstown-Martinsburg, Md.-W.Va. 150 282 205 89 269 81 218 63 225 166
3 out of 5 Huntington-Ashland, W.Va.-Ky.-Ohio 155 165 242 24 250 157 219 151 225 166
3 out of 5 Lancaster, Pa. 104 91 104 252 329 288 332 34 225 166
3 out of 5 Norwich-New London, Conn. 243 291 40 63 325 120 223 102 225 263
3 out of 5 Utica-Rome, N.Y. 211 147 6 22 347 120 352 151 225 193
3 out of 5 Vineland-Millville-Bridgeton, N.J. 164 126 1 97 347 288 30 102 225 263
3 out of 5 Wheeling, W.Va.-Ohio 248 214 202 15 241 120 227 151 16 263
3 out of 5 York-Hanover, Pa. 121 75 104 246 329 157 332 63 225 134
2 out of 5 Altoona, Pa. 248 218 104 58 329 288 332 102 225 193
2 out of 5 Atlantic City, N.J. 197 208 1 154 347 288 30 151 225 233
2 out of 5 Johnstown, Pa. 255 234 104 64 329 288 332 63 225 263
2 out of 5 Ocean City, N.J. 346 342 1 12 347 288 30 151 225 107
2 out of 5 Reading, Pa. 135 169 104 241 329 280 332 151 225 154
2 out of 5 State College, Pa. 293 263 104 53 329 288 332 151 102 193
1 out of 5 Barnstable Town, Mass. 186 268 17 207 329 288 127 310 225 263
1 out of 5 Cumberland, Md.-W.Va. 301 299 175 91 271 157 186 347 225 263
1 out of 5 Dover, Del. 251 285 208 163 29 288 133 225 225 320
1 out of 5 Elmira, N.Y. 335 326 6 38 347 288 352 310 225 263
1 out of 5 Glens Fals, N.Y. 332 271 6 160 347 157 352 151 225 298
1 out of 5 Ithaca, N.Y. 358 339 6 144 347 288 352 310 225 263
1 out of 5 Kingston, N.Y. 262 239 6

173

347 157 352 310 225 320
1 out of 5 Lebanon, Pa. 311 213 104 56 329 288 332 310 225 347
1 out of 5 Lewiston-Auburn, Maine 298 301 302 16 293 280 268 151 225 298
1 out of 5 Morgantown, W.Va. 285 255 223 33 251 157 247 225 225 347
1 out of 5 Parkersburg-Marietta, W.Va-Ohio 223 262 207 307 243 157 246 225 225 263
1 out of 5 Pittsfield, Mass. 332 321 17 41 329 288 127 151 225 298
1 out of 5 Salisbury, Md. 287 309 157 28 288 288 152 310 225 263
1 out of 5 Weirton-Steubenville, W.Va.-Ohio 309 315 202 2 241 288 227 102 225 298
1 out of 5 Williamsport, Pa. 304 254 104 161 329 280 332 225 225 233
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