Site Selection A look at the most logistics-friendly locations in North America |
Despite a company’s bestlaid logistics plans, site selection is a constantly changing variable. Companies frequently reach a crossroads in their logistics network optimization, often driven by some strategic change — a new product, a lease coming due, automation not working, or changes in product mix. That’s when logistics executives typically need to reevaluate and analyze their network and requirements.
The “where” in a logistics network affects the product mix as much as it is affected by product mix, says Vincent Gulisano, senior vice president of global sales, marketing and solutions engineering for APL Logistics (www.apllogistics.com). Product mix dictates transportation needs, but it isn’t a clear-cut linear relationship. Changes in product mix also affect storage and handling characteristics and automation needs, which can render an efficient facility sub-optimal.
Sometimes a location becomes wrong over time because of changing transportation rates, changing demographics, or other changes in a company’s business. For businesses driven by inbound and out-bound truckload shipments, the optimization process will favor points nearer manufacturing based on the economies of transportation, says Lamar Duncan, senior director of services engineering with APL Logistics. The optimization decision is cost- driven, and truckload moves are more economical. Goods are handled once, they go onto a truck and they are delivered.
However, when you start changing modes, the optimal location may change. Where the scenario is truckload in and less-than-truckload out, the more expensive outbound transportation will dictate the distribution center be located closer to demand points to minimize transportation costs. Transportation is the larger part of the location equation, accounting for as much as $3 or $4 for every $1 spent on warehousing.
Though transportation is the item most logistics executives are trying to reduce through optimization, the expectation is often that both warehousing and transportation costs can be reduced in the network optimization process. The process might involve two or three iterations, or it could run as high as 15 or 20, says Duncan. Optimizing a logistics network is complicated, after all, and may require running numerous factors through the decision cycle a number of times to come up with the right answer.
“I’ve seen people fall in love with technology and automation in their facilities,” says Gulisano, “and it becomes a noose around their necks.” Another risk is buying or leasing a facility built for someone else’s automation requirements and trying to retrofit it to your product. Gulisano remembers a consumer packaged goods company trying to fit its product down chutes designed to handle T-shirts. It was workable until the company hit seasonal volumes, then the inappropriateness of those automated chutes became
painfully obvious.
On the automation theme, Gulisano recommends planning for changes in product, order sizes and load design. Improvements in storage methods have to be weighed against the added labor. For instance, increasing stacking heights may require 10% more labor hours and 10% more spending for equipment to access product at the higher stacking levels, which reduces the overall benefit.
Getting the facility right is important, even if it is the lesser of the two major costs. Gulisano says it’s more complicated and harder to change the facility than it is to change transportation. If volumes
increase, you can throw more trucks at the dock, provided you have the dock space. But, you don’t always have the quare footage or people to throw at new volumes.
It’s always good to spend a little more on the facility for design features like dock cutouts or door knock outs that allow more flexibility, but Gulisano questions whether the project can gain approval with the added expense.
The facility is the heart of the supply chain, says Gulisano. “It’s pumping the blood out into the arteries. The transportation network is waiting to receive the blood, and if the facility is not designed right and you have trucks backed up and waiting, you won’t be able to optimize and get that network moving.”
“You find more catastrophic supply chain problems with the facility not working than with transportation not working,” Gulisano adds. “It’s easier to change carriers or transportation modes than it is to uproot a facility, products, people, and all that goes with it.”
Some organizations review their networks periodically to ensure they remain at their optimal level, but for those organizations that review on an as-needed basis, they often aren’t prepared to complete the process. The one thing they lack most often is a firm set of transit times.
Transit time is a strategic decision based on customer service levels and cost to deliver those service levels. The decision can be centered on a set of customers, by product, or by region. If a company with national distribution patterns wants to provide two-day service to the majority of its customers, it typically takes five distribution centers to get it done, Duncan says. If, however, the service level can be five days, then two or three distribution centers might be sufficient.
Logistics executives should enter the network optimization process armed with shipping data on all current facilities and all of the economics associated with that network. More facilities will typically mean lower transportation costs because you are getting closer to the customer. But, there’s a practical limit to the number of facilities that will reduce transportation costs and still generate at payback.
There’s no rush to ownership despite historically low interest rates. Most manufacturing and distribution firms want to focus on their core competencies and minimize the risks associated with owning warehouses or distribution centers. Even thirdparty logistics providers (3PLs) don’t want to own property, says Duncan. Logistics executives who want to outsource distribution center operations need to recognize that 3PLs will expect them to share some of the risk associated with brick and-mortar operations.
A 3PL will typically commit to a market for a longer period than its client may be willing to lease a facility. That gives the 3PL an advantage in negotiating lease terms with a property owner, but it doesn’t let the client off the hook.
Most 3PLs will try to arrange their leases so they’re contiguous
with the contract terms. If the client isn’t willing to commit for the full term of the lease, 3PLs often try to make the customer the assignee of the lease so that if there is an early termination of the contract, the customer takes over responsibility for the remainder of the lease term. In other cases, customers may take on the lease and reduce the margin the 3PL builds into its responsibility as lease holder.
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Logistics Today’s Logistics Quotient of American Cities — Southwest |
Regional Rank | Metropolitan Area | Logistics Industry Rank | Road Industry Rank | Work Force/ Labor Rank | Road Infra- structure Rank | Density/ Congestion/ Safety Condition Rank | Inter- state High- ways Rank | Taxes & Fees Rank | Rail- Road Rank | Water- borne Com- merce Rank | Air Cargo Rank | 2001 National Rank | 2002 National Rank |
1 | San Diego, CA | 76 | 71 | 77 | 114 | 314 | 24 | 173 | 13 | 47 | 26 | 9 | 7 |
2 | Los Angeles-Long Beach, CA | 40 | 74 | 205 | 117 | 314 | 13 | 173 | 13 | 3 | 1 | 12 | 8 |
3 | Houston, TX | 2 | 14 | 202 | 315 | 141 | 55 | 186 | 38 | 1 | 13 | 15 | 11 |
4 | Dallas, TX | 5 | 16 | 211 | 307 | 141 | 4 | 186 | 38 | 197 | 2 | 31 | 31 |
5 | San Antonio, TX | 21 | 10 | 167 | 286 | 141 | 24 | 186 | 38 | 197 | 41 | 32 | 26 |
6 | Corpus Christi, TX | 111 | 46 | 154 | 224 | 141 | 160 | 186 | 38 | 5 | 100 | 40 | 34 |
7 | Fort Worth-Arlington, TX | 9 | 6 | 208 | 305 | 141 | 4 | 186 | 38 | 197 | 85 | 42 | 29 |
8 | Beaumont-Port Arthur, TX | 101 | 39 | 94 | 300 | 141 | 160 | 186 | 38 | 6 | 183 | 57 | 48 |
9 | Austin-San Marcos, TX | 43 | 7 | 178 | 301 | 141 | 160 | 186 | 38 | 197 | 20 | 58 | 54 |
10 | Denver, CO | 184 | 61 | 226 | 108 | 64 | 16 | 269 | 141 | 197 | 6 | 59 | 74 |
11 | Riverside-San Bernardino, CA | 59 | 97 | 128 | 133 | 314 | 55 | 173 | 13 | 197 | 107 | 60 | 35 |
12 | El Paso, TX | 12 | 15 | 311 | 236 | 141 | 125 | 186 | 38 | 197 | 29 | 61 | 52 |
13 | Las Vegas, NV-AZ | 105 | 41 | 268 | 165 | 38 | 125 | 128 | 213 | 197 | 25 | 64 | 116 |
14 | Amarillo, TX | 79 | 86 | 158 | 261 | 141 | 85 | 186 | 38 | 197 | 97 | 70 | 70 |
15 | Tulsa, Okla. | 199 | 29 | 237 | 140 | 301 | 114 | 26 | 166 | 59 | 63 | 73 | 76 |
16 | Brownsville-Harlingen-San Benito, TX | 31 | 11 | 316 | 190 | 141 | 298 | 186 | 38 | 50 | 76 | 75 | 53 |
17 | Salt Lake City-Ogden, UT | 144 | 26 | 223 | 116 | 83 | 24 | 288 | 205 | 197 | 32 | 76 | 61 |
18 | Laredo, TX | 14 | 4 | 306 | 121 | 141 | 160 | 186 | 38 | 197 | 188 | 79 | 56 |
19 | Lubbock, TX | 104 | 44 | 143 | 258 | 141 | 160 | 186 | 38 | 197 | 88 | 81 | 77 |
20 | Odessa-Midland, TX | 107 | 88 | 146 | 249 | 141 | 160 | 186 | 38 | 197 | 85 | 95 | 71 |
21 | Greeley, CO | 217 | 181 | 45 | 11 | 64 | 85 | 269 | 141 | 197 | 193 | 99 | 121 |
22 | Oklahoma City, Okla. | 201 | 9 | 233 | 186 | 301 | 16 | 26 | 166 | 197 | 75 | 101 | 89 |
23 | Orange County, CA | 54 | 100 | 183 | 126 | 314 | 125 | 173 | 13 | 197 | 138 | 104 | 35 |
24 | Wichita Falls, TX | 188 | 68 | 85 | 205 | 141 | 160 | 186 | 38 | 197 | 193 | 114 | 95 |
25 | Abilene, TX | 207 | 69 | 79 | 245 | 141 | 160 | 186 | 38 | 197 | 169 | 124 | 130 |
26 | Phoenix-Mesa, AZ | 129 | 45 | 203 | 222 | 51 | 85 | 269 | 282 | 197 | 12 | 125 | 99 |
27 | Waco, TX | 175 | 42 | 115 | 271 | 141 | 160 | 186 | 38 | 197 | 193 | 138 | 118 |
28 | Flagstaff, AZ-UT | 288 | 158 | 24 | 10 | 67 | 85 | 278 | 243 | 197 | 175 | 143 | 123 |
29 | Killeen-Temple, TX | 148 | 66 | 281 | 159 | 141 | 160 | 186 | 38 | 197 | 193 | 151 | 140 |
30 | McAllen-Edinburg-Mission, TX | 52 | 5 | 278 | 304 | 141 | 298 | 186 | 38 | 197 | 106 | 171 | 153 |
31 | San Angelo, TX | 212 | 138 | 91 | 130 | 141 | 298 | 186 | 38 | 197 | 174 | 171 | 170 |
32 | Sherman-Denison, TX | 154 | 136 | 71 | 210 | 141 | 298 | 186 | 38 | 197 | 193 | 179 | 182 |
33 | Longview-Marshall, TX | 112 | 49 | 261 | 301 | 141 | 160 | 186 | 38 | 197 | 193 | 183 | 182 |
34 | Galveston-Texas City, TX | 164 | 209 | 243 | 281 | 141 | 160 | 186 | 38 | 33 | 193 | 190 | 107 |
35 | Pueblo, CO | 318 | 269 | 35 | 9 | 64 | 160 | 269 | 141 | 197 | 192 | 194 | 225 |
36 | Grand Junction, CO | 310 | 207 | 110 | 21 | 64 | 160 | 269 | 141 | 197 | 193 | 198 | 194 |
37 | Colorado Springs, CO | 276 | 230 | 191 | 45 | 64 | 160 | 269 | 141 | 197 | 100 | 199 | 174 |
38 | Bryan-College Station, TX | 213 | 118 | 81 | 208 | 141 | 298 | 186 | 38 | 197 | 193 | 200 | 160 |
39 | Tyler, TX | 167 | 25 | 256 | 323 | 141 | 160 | 186 | 38 | 197 | 193 | 206 | 191 |
40 | Tucson, AZ | 226 | 95 | 253 | 196 | 51 | 85 | 269 | 282 | 197 | 61 | 216 | 154 |
41 | Brazoria, TX | 124 | 131 | 98 | 312 | 141 | 298 | 186 | 38 | 197 | 193 | 217 | 115 |
42 | Ventura, CA | 136 | 216 | 82 | 109 | 314 | 298 | 173 | 13 | 197 | 193 | 222 | 146 |
43 | Santa Barbara-Santa Maria-Lompoc, CA | 249 | 202 | 39 | 79 | 314 | 298 | 173 | 13 | 197 | 170 | 225 | 142 |
44 | Bakersfield, CA | 146 | 239 | 116 | 50 | 314 | 298 | 173 | 13 | 197 | 193 | 229 | 197 |
45 | Provo-Orem, UT | 245 | 121 | 163 | 100 | 83 | 160 | 288 | 205 | 197 | 193 | 233 | 235 |
46 | Lawton, Okla. | 323 | 109 | 245 | 60 | 301 | 160 | 26 | 166 | 197 | 193 | 237 | 238 |
47 | Boulder-Longmont, CO | 312 | 258 | 176 | 46 | 64 | 160 | 269 | 141 | 197 | 193 | 247 | 286 |
48 | Victoria, TX | 190 | 147 | 287 | 295 | 141 | 298 | 186 | 38 | 42 | 193 | 249 | 246 |
49 | Albuquerque, N.M. | 272 | 55 | 282 | 303 | 250 | 85 | 141 | 256 | 197 | 28 | 268 | 247 |
50 | Fort Collins-Loveland, CO | 296 | 285 | 258 | 40 | 64 | 160 | 269 | 141 | 197 | 193 | 275 | 269 |
51 | Las Cruces, N.M. | 298 | 51 | 184 | 282 | 250 | 85 | 141 | 256 | 197 | 193 | 284 | 277 |
52 | Yuma, AZ | 301 | 262 | 247 | 20 | 51 | 160 | 269 | 282 | 197 | 193 | 293 | 257 |
53 | Enid, Okla. | 314 | 196 | 266 | 143 | 301 | 298 | 26 | 166 | 197 | 193 | 314 | 294 |
54 | Santa Fe, N.M. | 328 | 141 | 204 | 284 | 250 | 160 | 141 | 256 | 197 | 191 | 319 | 307 |