Category Archives: Learning

Research Connections: Is It Safe To Come Out Now?

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ImageThe “brain trust” of the chain store research industry gathered again for the annual ICSC Research Conference in Chicago Sept. 30-Oct. 2.  Among the 235 attendees, there were many new brains and some notable absences (you know who you are).  I have to say that this was a well-run event with excellent sessions and the usual stimulating dialog (hats off to the organizers and the attendees who shelled out big airfares and hotel rates).  My only real complaint was the quick removal of coffee at the breaks.

I was able to personally connect with about a third of the attendees and it’s clear from those conversations that the shakeout of the past few years has created winners and losers.  Most of the large players are on the sidelines for expansion, but busy dealing with closings, relocations, and remodels.  Retailers and restaurants with strong concepts and balance sheets continue to feed on the soft real estate markets, though many report firming prices for better locations.

Lo and behold, some companies are having trouble finding analysts to support their growing levels of activity!  One theory is that the layoffs and malaise of the last few years has dried up the labor supply, especially for people with 3-5 years of experience (think about which 3-5 years those would be:  2007-2009).

There seems to be an increased appetite for predictive analytics and technology to support the market planning and site selection process.  There were more vendors exhibiting this year and the traffic around their booths was steady throughout the conference.  Maybe the tools will reduce the need for entry level analysts and mitigate the labor supply problem.  However, this will only work if field real estate reps are diligent in collecting and loading validated location data (competition and site characteristics) so that maps, reports, and models will portray an accurate picture of the deals they are evaluating.  It remains to be seen whether the “dealmakers” will actively and reliably play this role.

I also heard stories from people in larger companies about the consolidation of real estate research activities under the finance groups.  As much as we appreciate the importance of the viewpoint provided by finance people (highlighted in the session on integrating finance with research), there is a lot more to market planning and site selection than numbers.  This will become even more evident as the “omnichannel” customer experience evolves and collaboration between marketing, assortment planning, and store development muddies the water further for analysts.  Some of the recent staff reductions have left companies without much “institutional memory” of the existing stores and what makes them tick, which could impair the vision of executive teams as they prioritize their investments in remodels and new development.  Navigating with the rearview mirror is only going to get harder as new distribution paradigms emerge, and finance will be the last to know what’s going on.

One more observation:  I think that those who have attended this conference for many years need to work harder at welcoming the newer attendees and building relationships with them.  I remember the first few conferences I attended in the 1990’s and how difficult it was to meet new people because everyone seemed to be catching up with their old pals and hanging out.  A few kind souls went to the trouble to seek me out and introduce me to their friends so that over time I have gotten to know many people.  It’s very easy to focus on the people you know and ignore the new folks, so this requires a conscious effort on the part of all the veterans to make it work.

Feel free to post your comments about the conference on this blog and share your insights.

The Value Proposition for Chain Store Predictive Analytics

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How many times have you seen a “Value Proposition” slide with statements like these?

  1. “We are experts in “best practices” in chain store real estate analytics and we can help you join the 21st century.”
  2. “Our scientists have developed proprietary algorithms and methods that produce the most accurate predictive models possible.”
  3. “Our technology platform will deliver user-friendly maps, reports, and sales forecasts to everyone in the enterprise who wants them; with a 90 day deployment.”

Why wouldn’t these value propositions of “better” and “faster” be compelling for everyone?

In theory, they would.  But every chain store company has a point of view about its real estate program, and if vendors don’t understand it, they will never sell them anything…that works!

Let’s flip this around and look at it from the viewpoint of the chain store real estate executives.  They will invest in predictive analytics when they see the value of a proposition, not the proposition of a value. 

Most companies have a “committee meeting” where real estate deals are considered and approved.  There is usually a representative from each of the departments that has a stake in the quality of a new store, which is all of them:  finance, merchandising, marketing, operations, and of course, real estate.  Do they lose sleep over “best practices?”  Are they fascinated with mathematical models?  Do they enjoy rolling out new software applications? NO, NO, NO!  They didn’t become senior executives by contemplating their navels and fantasizing about perfection.  They know how to get stuff done. Why do they even want to talk to a vendor who offers chain store predictive analytics?  

There are several possible reasons.  First, the end game is getting and satisfying customers.  The real estate strategy and program must clearly “map” to this goal.  That means that a store, restaurant, or service center should:

  • Be Convenient
  • Have what the customer wants
  • Make it fun and easy to fulfill their needs

Convenience is based on the location of the store, which includes what it’s near, its visibility, and its accessibility.  This is the focus of the real estate decision, and the profitability of a store is heavily dependent on location quality.  Anything that helps the chain acquire better locations is worth consideration, whether it’s data, software, training or predictive analytics.  Chances are that some combination of these things can contribute to better locations. The challenge is assessing the needs of the organization and designing a plan that blazes a clear path from the current situation to a desired state that increases the number of happy customers and drives profit.

At any given point in time, the executives in a company will have the ability to visualize a better state that is achievable from where they are.  The plan must be manageable over a one to two year period, because business must continue while changes are implemented.

The trick is to foster a dialogue that leads to a needs assessment, a game plan, and a set of expectations that represent a compelling return on investment.

What are the ingredients in such a plan?  It varies dramatically from company to company.  Here are some factors that influence the best approach to good real estate decisions:

  1. Breadth of customer profile.  If 80% of your sales come from girls between the ages of 14 and 18, you need to make sure that the trade area of a store has enough teenage girls.  If your customer could be anyone, successful stores might have many profiles, and the analytics required to figure this out are more tedious and complex.
  2. Size of the store.  If you are opening 50,000 square foot stores, you will be investing more capital, opening fewer units, and evaluating fewer opportunities, so you will be able to justify more field research.  This means that you don’t need to rely as much on screening tools and complex multi-user systems that are designed for fast decisions.  If you are opening 1,200 square foot stores, it’s about screening out the dog locations to allow enough time for the ones that deserve serious consideration.
  3. Format of the store.  Predictive models for enclosed malls are very different from models for open-air centers or street retail.  Malls are mostly about the quality and tenant mix of the mall, but open-air centers require a careful analysis of the trade area demographics and competitive landscape.
  4. Decision styles of senior executives.  Some companies place greater emphasis on quantitative analysis than others, and you can’t easily change this.  There are many winning combinations of people and tools, art and science, book smart and street smart.

Each chain store company has limited time and money to invest in store location decisions.  Predictive analytics that make a difference will be discovered through a dialogue among experts who know the business and the tools and are committed to working together to find the unique value proposition that maximizes ROI.

Predictive analytics can help increase average unit volumes significantly over time.  Here are some of the ways predictive analytics empower decision-makers to see more clearly:

  • Provide access to more facts to support judgments
  • Reveal patterns in the facts that create insights
  • Simulate decisions before actually executing them
  • Establish a common “language” of factors important to decision-making
  • Benchmarking with a checklist of factors to consider before making decisions
  • Visualization of facts and patterns as a catalyst for interactive exploration and discussion among decision-makers (e.g. “paperless” real estate committee meetings)
  • Maintaining an objective record of decision logic for learning and improvement

These are propositions of value, and when applied to a specific company, they may become part of a value proposition!

The Whole World’s Watching

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We’ve been hearing about global expansion by  chain store retailers and restaurants for years.  Most people probably think that in many parts of the world this is an “imperialistic” initiative by US and European companies.

My blog statistics indicate that there’s global interest in chain store development from local people. Continue reading →

What Gets Measured Gets Done

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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 →

Here We Go Again

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The economy is showing signs of perking up.

Although retail store closings are expected to continue at a strong pace in 2012 (see http://www.forbes.com/sites/erikamorphy/2011/12/31/2012-another-bad-year-for-store-closings/), many retailers and restaurants are staffing up for growth and looking for deals.

Is this the pregame warm-up for the next cycle of boom and bust?  Or maybe, just maybe, there’s a smarter, more disciplined group of decision-makers running the chain store companies today.

As I mentioned in an earlier post, the chain store industry doesn’t have well-defined best practices in real estate planning and site selection.  In order to begin a dialog on this subject I have created a “rubric” that describes various practices at different levels of effectiveness that can be used as a self-assessment tool for people in the chain store industry (click here for the Best Practices Rubric).

There are only nine items on the rubric, so you should be able to complete it in 5-10 minutes unless it causes you to think hard about what you’re doing, which would be a good thing!  Simply circle the description of the practice that best describes your business and when you’re done, add up the points as indicated at the top of each column.

The total points will range from 9 to 36, assuming you complete the rubric.  Based on my experience and exposure to chain store companies over the past 18 years, I would interpret the scores as follows:

0-15 points:  If you are still in business, it’s because you have smart, street-wise people              and probably aren’t doing very many deals each year.

16-20 points:  You are about average for the industry, which is OK if you don’t mind being average.  However, you won’t be able to stay average without improving, given the the struggling economy, growth of “omni-channel retailing” and the new breed of tech-savvy competitors.

21-27 points:  You know that you’re doing a good job because you have made a conscious decision to create good decision-making processes supported by good people and good tools.  You are already thinking about how to stay ahead of the game and work smart, not just hard.

28-36 points:  The business practices of your company are truly “best practices” and you represent the elite of the industry.  You might be reluctant to share what you do because you know that you have a serious competitive advantage.  However, you will probably talk about it anyway because of the positive energy that market leaders generate with employees, investors, customers, and partners.  We thank you for your leadership!

I look forward to your public and private comments on the rubric and the general subject of best practices in real estate planning and site selection.

2012 Predictions for the Chain Store Real Estate Industry

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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?

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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 →

Freedom through Structure: Optimizing Chain Store Real Estate Processes

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You hear the complaints all the time.

“The field people only react to the deals that the brokers present to them.  They don’t take the market planners seriously when we target certain trade areas.”

“The analysts (aka “geeks” or “deal killers”) think they know everything because they have mapping and statistics programs.  They have no idea how the real world works.”

“I can’t open enough stores because the paperwork takes forever.  It’s easier to get a PhD than get a deal through our approval process.”

Is this just the way it has to be?  Dealmakers vs. analysts? People who drive sales and people who prevent sales?  Entrepreneurs vs. bureaucrats? Continue reading →

The Mysterious Origin of New Stores

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In 2002 I was on a panel at the Retail Systems Show in Chicago which was a technology showcase for the retail industry.  The panel was focused on analytics and my topic was the use of predictive analytics in real estate planning and site selection.  I had already been at the show for a couple of days and after speaking with many CIOs, CTOs, and merchandising executives it became apparent that there was little interaction between the real estate department and the other areas of the business.

I started my presentation by telling the audience that I had come to the conclusion that “everyone outside of the real estate department thinks that stores just magically appear.” Continue reading →

What Women Want

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I don’t watch many movies, but I just saw “What Women Want” with Mel Gibson and Helen Hunt.  It may sound strange, but it made me think of the changes in the chain store real estate business in the last couple of decades and consider the changes that are still ahead.

Twenty years ago, most of the dealmakers in the chain store industry were men.  Business was conducted on golf courses, in restaurants and bars, at sporting events, and other venues of the “good ol’ boy network.”  Cambridge Dictionaries Online defines a good ol’ boy  as “a man from the southern US who enjoys having fun with his friends, and disapproves of ideas or ways of behaving that are different from his own (see  also http://en.wikipedia.org/wiki/Good_ol’_boy_network). Continue reading →