Climbing the Stairway to Wisdom

There’s a broker who’s sure that all sites turn to gold
And she’s selling the stairway to heaven.
When she gets there she knows, if the sites are all sold
There’s a vacancy coming to save her.
And she’s selling the stairway to heaven. 

– Led Zeppelin (adapted)

One of the popular metaphors for decision-making in the information age is the “Knowledge Hierarchy.”  It is based on the idea that we start with raw data and gradually process it through stages until it becomes wisdom suitable for making good choices.

Some people apply this to professional development over the career of a chain store real estate executive.  When you’re young, you simply see data, but as you get more experience and insight, you are able to use your wisdom to evaluate sites.

The fact is, each site must be evaluated through a process that starts with raw data that is enhanced with verification, context, and benchmarks until it is ready for the application of human wisdom. 

The human brain uses pattern recognition and analogies to analyze complex decisions.  This is why “analog stores” are popular in site selection.  If we can find existing stores that are similar to a proposed location, we can adjust the details and apply our knowledge of its sales performance to the new site. Continue reading

What Gets Measured Gets Done

Everyone knows the value proposition for chain store real estate research:

“If you avoid closing one or two stores it pays for itself.”

So why are people so hesitant to invest in analysts, predictive analytics, and information systems to support better real estate planning and site selection?

I’ve been asking this question for nearly 20 years, and I think I’m finally beginning to see the answer.

It’s about measurement.

Here’s how the argument goes:

Summary (simplified):  If we invest in better research, we can use a predictive model to estimate sales performance for proposed sites.  If we know the population and income of the trade area, the distance to our competitors, and the quality of the site, we can use the weighting factors in the model to calculate the sales potential.  We’ve heard that it’s possible to have a model where the estimate will be +/-  20% reliable at least 80% of the time.  In the past we have only been +/- 20% correct 65% of the time.

Therefore, the avoidance of bad stores alone will more than cover the investment in people and tools to build and use the predictive model. Continue reading

2012 Predictions for the Chain Store Real Estate Industry

I guess it’s a good time to do a “2012 Predictions” post.

I’ve been talking to a lot of people about best practices in real estate planning and site selection during the past year.  Many of my observations and insights have appeared in this blog since May 2011.  Looking ahead to the next year, there is evidence that some of the “forward looking” comments from last year will begin to appear in the practices of leading companies in 2012.

Retail store sales during the 2011 holiday season were flat compared to last year (there are so many stats I don’t even want to quote one).  The bigger news was the increase in online sales, and the biggest news of all was the increase in purchases from mobile devices such as smartphones and tablets.  This puts “teeth” in the trend toward “omnichannel retailing” that signals a new paradigm in consumer behavior and requires a new approach to retail real estate planning.

Here are two general predictions about the chain store real estate business for 2012:

#1 Betting on Clicks or Bricks

Given the continuing weakness in the economy, capital investment in store development will be more carefully scrutinized by senior management than ever before.  Given the growing success of the online and mobile channels, there will be more conversations between The CEO, CFO, CMO (Chief Marketing Officer), and CDO (Chief Development Officer or VP Real Estate in most companies).

New questions will be on everyone’s minds and lips.  Instead of “how many stores should we add this year net of closings,” people will be asking “how much can we grow sales without adding stores?”  Another way to ask the same question might be “what’s the ROI on store development compared to promotion and discounting through other channels?”

These questions will lead to some innovative planning and business models that will look very different from the traditional approaches that have not changed much in the past few decades.

#2 Performance Improvement

Investments in technology to improve real estate planning and site selection have grown dramatically in the past five to ten years.  Most of the larger chains and many smaller ones have a Real Estate Research Director or Senior Analyst who is responsible for delivering strategic plans and sales performance estimates to the decision-makers.  They have armed themselves with mapping and demographic programs, databases, and analytical tools based on everything from excel to sophisticated statistical models.  Almost everyone agrees that research can improve performance and that the investment in analysts and their tools is worthwhile.

The question remains:  how much of the potential value from research activities is being realized?  Is there room for improvement?

My prediction for 2012 is that investments in analysts and technology will continue, especially for companies that have been slower to get on the analytics bandwagon.  However, the new focus will be improving the “people” side of research.  This starts with benchmarking business processes against best practices in the industry and extends to consistent training programs to align the deliverables from research with the decision requirements of everyone in the real estate process including senior management, dealmakers in the field, and people in other departments such as marketing and merchandising. 

There’s been a lot of talk about “enterprise GIS” and “localized assortment planning” in the past few years.  The reason this is on my list of predictions is that all of the prerequisites to actually implement such performance improvements are now in place.

a)       The technology is good and has become affordable, especially with “cloud computing” which allows companies to build a platform gradually with variable costs instead of committing to a huge IT infrastructure investment to get started.

b)       The need to integrate real estate planning with other channels at the highest level is crystal clear based on the growth in online and mobile sales and the social media phenomenon

c)        The large capital investment required for bricks and mortar stores has become harder to justify in a weak economy that shows no signs of bouncing back quickly as in past cycles.

By this time next year there will be some great case studies of companies that are actually doing these things and reaping the financial benefits (although it might take another year to quantify this in a convincing manner).

In the interest of accountability, I have marked my calendar to follow up on these predictions one year from now.  I hope I can find some good cases to talk about then or we may not have a very happy new year in 2013 and beyond!

Do We Have Industry Standard Practices in Retail Real Estate?

Why does any industry have standard practices?  Every business is different, even within an industry, so what’s the point of trying to standardize?

Industry standard practices are a lot like the rules in a game.  They provide a systematic, consistent, and proven framework within which the players develop their strategies and exercise their skills.  Having rules doesn’t make you a winner, but they make it possible to become a winner by promoting the following competitive strengths: Continue reading

Analytics vs Modeling: “Democratizing” Decision Support

Mistakes are expensive.  Everyone wants a model to help them avoid mistakes and repeat successes.

We want a good business model that provides a framework for success.  If the business model works and we stick with it, we will make money.

In the chain store business, we want to make good site selection decisions.  Avoid bad real estate; pay the right price for good real estate.  We want a sales forecasting model that will help us estimate the top line number to plug into our pro forma operating model for a store (which is based on our business model, of course). Continue reading

The Voice Of The Customer: Can You Hear It Through The Screaming?

Listening to the “voice of the customer” has been the hallmark of successful retailers, restaurants, and service businesses for years.  Technology has greatly increased our ability to capture and analyze customer data.  With the explosive growth of Facebook, Twitter, and other networks, social media are becoming the loudest, clearest, most current voice of the customer yet!

The challenge today is finding the “signal” in the data so that we can reduce the voice of the customer to actions such as real estate planning, site selection, marketing campaigns, and assortment planning.  With data warehouses full of customer transactions, household files with demographics, and feeds from social media, it’s harder to understand what the customer is saying than to guess the Dow Jones average by walking onto the trading floor of the New York Stock exchange! Continue reading