With so many variables to consider selecting a distribution location, choosing the right criteria for the search can be art and science. Yes, site selection involves math and science. But the decision is more than numbers. You must interpret information that is not numeric. You must go and observe the sites. Too many factors can make Logistics Network Optimization projects a vague decision. Leaving the decision to the machine is management malpractice.
Some logistics consultants and their network optimization systems can lead you to a city that “swims” with the promise of high tax abatement incentives, low land costs and even lower transportation costs. However, you could find yourself diving into an empty labor pool. Worse, the pool could be full of low skilled and low quality prospects, high competition and low supply, or trade union pressure, eating whatever savings exists.
Demographics and labor competition are key factors that many companies either fail to address or get wrong. Understanding where the labor pools are, what is in the pools and why they exist is key to success. Forecasting labor supply and demand is important. More important is developing creative ways to find out where the best labor pools are, and how to get them to come to you. The issue comes down to key this criteria question: What really matters in the long-term operation of the operation, low cost or steady labor quality?
Most companies fixate on cost reductions—looking at the cost of land, construction, rent, and labor, to make the site selection decision. Costs are important factors to consider since costs are measureable in any analysis. However, beyond costs—many site selection teams overlook quality factors in the process, like the availability of qualified labor.
Transportation is by far the largest cost component in the selection models when looking at the macro solution. When the analysis becomes “micro” in scope transportation cost matters much less. I advise not to put too much faith in the accuracy of transportation models in small areas. The model could suggest “Willie Nelson’s Farm” if it struggles with limited street accuracy.
Moving a facility a few miles to a location closer to highway access can have a positive impact on transport cost. One example is a facility built about six miles from the interstate highway, along a road not approved for STAA trucks. Once the DC operation started, the highway patrol began ticketing large over the road trucks for violating the road limitation. A parcel closer to the highway was another $2,000 per acre. That could have been a bargain—the fines exceeded $20,000 in the first year.
Most companies do consider labor costs in the selection process—they rely on consultant and real estate broker provided macro-economic and macro-demographic data to make a decision. This approach is fine for city to city comparison, but sometimes fails to consider changing trends, competition in the micro labor market, and public transportation patterns. There is a lack of consistent public access data to use in a remote process. Local Economic Development offices often collect and publish micro-market data, but the data can be suspect or out of date. Data provided by the major Industrial Real Estate brokers is not micro enough, as is Department of Commerce data.
So how do you measure micro-market labor costs? Well, that effort is more an art than a science. While all great artists are creative, there is a method that each develop to help them be creative. However, in all cases a concerted effort and investment of “shoe leather and tires” in the prospective micro-markets is usually the best protection from making a major mistake. The successful practitioners in the game go into the field. They look at how the site relates to the local community. They become part detective and investigate the options.