The retail marketplace is a complex system that is constantly changing and is full of surprises. Sometimes these surprises are positive; and other times they are not! It never ceases to amaze me how many different combinations of factors lead to success and failure in chain store performance. Complexity drives statistical models crazy (as well as the people who use them). There seem to be as many exceptions as there are rules, and the best way to understand these exceptions is by listening to experts tell their stories about what happened.
AND NOW… I’m pleased to announce the unveiling of a new page in this blog:
“Site Selection Surprises – Stories from the Field”
Please click on the new page above for the rest of the story…
Not too many years ago, chain store real estate was almost entirely a “people” business. The ICSC was the formal organization that provided regular gatherings among landlords, tenants, brokers, and all the other suppliers to the shopping center/chain store industry. “Going to Vegas” has become an annual pilgrimage for dealmakers since 1986 (the first convention was held in New York in 1958). The telephone and the automobile were the primary research tools. The research department was often located at one of the many bars, restaurants, coffee shops, and golf courses across the country. Continue reading →
What’s worse? Too little science or too much science?
Ahh, trick question. The answer is that science is not a quantity that can be measured and compared to a standard. Most people would agree with this, but we often hear people say “we need a little more science in our site selection process.” Continue reading →
All of us in the chain store industry would love to believe that we are making better real estate decisions today than before we had digitial maps, demographic data, and predictive models. There is no question that some companies have reduced capital losses from store closings and increased profitability of their stores with these tools. Continue reading →
Most chain store modeling experts will tell you that a “good” sales forecasting model will estimate sales +/- 20% in 80-90% of the cases.
Most chain store real estate dealmakers believe that they need a model with no more than +/- 15% error 85% of the time.
Most people don’t agree on how this error is measured or what the role of human judgment should be in determining the “official” sales estimate used in calculating the projected return on investment. Continue reading →
It’s been 17 years since I started the company that became geoVue. That’s a lot of 70 hour weeks with not enough vacation.
It’s been 17 weeks since geoVue was sold to a new owner. That’s a lot of time to think about the last 17 years and gain some perspective on the quest for good practices in real estate planning and site selection.
I’ve decided to spend the foreseeable future using what I’ve learned to help guide chain store operators in making better real estate investment decisions. The focus of this work will be “connecting art and science,” which sums up the greatest need that I have seen among retailers, restaurants, and service companies in building a profitable network of stores. There are many good people and many good technologies being used by companies today. However, they often fail to deliver their potential because they are not integrated properly. Continue reading →