Outside our window in downtown San Francisco, there are dozens of street vendors clumped together at the corner. We admire their entrepreneurial spirit to fill a market niche, but we take exception to their strategy. While clumping together to sell Giant's T-shirts for the World Series isn't necessarily a bad strategy, it is not the best.
It turns out that the same market forces at work for picking a dominant strategy for street vendor location are the same ones at work for banks looking to open a branch, loan production office, kiosk or ATM. More importantly these days, the same model is used to shed or modify branches to ensure the least impact on customers and the most positive impact on earnings. It turns out that geographic decisions matter a great deal in banking, and as such, we recommend a quantitative framework to help make these complicated decisions.
When looking at locations, most bankers work on gut instinct and take into account generic geographic and demographic information, as well as lease/buy data to make a decision. Consultants are hired and money is spent, but the problem is that while these factors are important, they don't account for a substantial amount of the correlation to location earnings. In reviewing location decisions for many banks, management teams often fail to get granular enough in their analysis and so often ignore items like traffic flow, profitability profile (different than demographic information), future development, taxes and existing competition.
The process of geographic selection often breaks down from the very start, as whenever a bank decides to open or close a location, a specific set of objectives is not clearly stated. The goal of "increasing profitability" is good, but it is not as specific as "increase market share by 2%," "generate 12% greater non-interest bearing deposits," or "double fee income." Each objective can have a different impact on a bank's location, as customer traffic isn't all the same. One classic mistake is a bank that wants to attract more business customers that opens a downtown location in a major metro area. Unfortunately, usually this location turns out to be better suited to attract out-of-area retail deposits than business deposits, as higher rents usually inhibit small businesses from taking space. Locations in suburban areas, industrial parks or metro outskirt locations may be better suited if the bank is seeking a small business customer with $2mm to $5mm in annual revenue. In a similar vein, price sensitivity matters so locating next to competitors helps with traffic, but also attracts more price sensitive customers (as they tend to have other choices with little switching cost).
Once objectives are determined, they need to be prioritized in a manner that allows you to determine relative weight. Is creating a location to retain your current customers the most important or is generating loans the top priority. The best way to do this is to give all decision-makers 100 votes and have them spread those votes around the available objectives. By doing this, a weighted set of objectives can be obtained (and it is fun as well).
We will pick this back up tomorrow when we talk about collecting required data to make better decisions and how to build a framework for opening or closing a branch location. In addition, we will examine how best to employ a competitor-based strategy. Until then, we will be picking up some extra "Panda" and "Fear the Beard" T-shirts for customers that stop by on their way to the game.