By Peter Buckingham, Managing Director, Spectrum Analysis Australia

I am not an economic soothsayer, but if you haven’t noticed, the economic climate has taken a downturn in the last 12 months! Inevitably this has taken the drive away from wanting to open sites, to more of a mode of retaining the good ones, and minimising the potential damage where possible.

My previous life in the oil industry places me in a position of one who has seen this before, over many years. In 1970’s, there were estimated to be over 20,000 retail service stations in Australia, which by 1995 had reduced to around 9,000 and in 2008 is believed to be around 6,000. The reasons for this have been a combination of economic efficiency, and the best commercial use of the land.

Over the years, my view was that we closed some sites for the wrong reasons, and once done, it is economically irreversible. The reasons could be Franchisees unable to achieve a satisfactory return, or just opportunism that a certain number of sites had to be closed, and an opportunity arose – industry rationalization.

Current market conditions

You would be very correct to say many of the Franchisors that were in a growth mode are now expressing a holding position, or actually reducing store numbers. The high growth strategies are being replaced with more selective store openings, and in many cases, store closures will outstrip openings.

The biggest issue a Franchisor has to face is whether the store they are leaving is being done because of lack of potential or profitability, or simply a poor operator has been unable to make it work. Once the door is closed, the signs are down, and you are out of the lease, there is no coming back!

Many of the older ones amongst us remember these downturns, and how the markets can reverse, and all moves up again. I have no intention of predicting when it will happen, just that it eventually will.

Costs of closure

Every store has a different cost to close. If you are at the end of a lease period, then you can walk away, and meet the conditions in your lease to achieve that. This may relate to removing signage, cleaning up and possibly restoring to some pre established position.

If you are not at the end of your lease, then the landlord is entitled to expect you to meet your lease obligations, or negotiate a satisfactory result for both parties. This can be a very large figure if you have some period of the lease to go. If this figure is too large, you may have to look at other alternatives.

Weathering the storm

It could be that the site is not the issue, and the problem is more an operational issue. If you feel this is the case, then parting with the existing operator may be the first step, and either finding a new operator, or running the store as a company operation is a better bet.

If your concept is sound – as you have hopefully proven before you decided to franchise your concept, then you should have no qualm in running for a period as a company operation. If you do not see it as viable as a company operation long term, then firstly you should NOT be asking some other potential franchisee to take it over, and you should be asking yourself “how you got there in the first place”!

If you have some confidence that the economy will pick up over the medium term, then running at a loss for some time could be a far better alternative than closing and paying out the Lessor.

 An example may be a franchise where you hold the head lease, and are paying $10,000 per month (and have 2 years to run). Cost to close may be another $50,000.

Alternative 1.

Subsidise the Franchisee’s rent by $4,000 per month to ensure they remain viable, (and still able to pay your royalties). This keeps the site open for its contribution to your overheads, and hopeful long term profitability

Alternative 2.

Close the Franchise and be looking at a $240,000 payment over 2 years, plus the cost to close of $50,000.

Alternative 3.

Run as a company operation, and lose $3,000 per month for the next 12 months, with the expectation that it will move into profitability as the market improves.

Basically, I would think options 1 or 3 would look the best.

How do you decide on a store’s potential?

Using statistical analysis is essential to decide whether or not to open a new location, and the same applies for closing stores as well.

Simple approach

Many of us have a wealth of information, and in most cases do not use it. If I had a chain of stores in shopping centres, I have access to information for each store such as:

Things I can ascertain myself:

·         Average sales

·         Rent paid

·         Size of actual retail store

·         Rating of location within the Centre

·         Mystery shopper score or some operations scoring system

Things I can find out:

·         Size of Shopping Centre (GLAR)*

·         Annual Turnover of Centre (MAT)*

·         Pedestrian count

·         Social economic surrounding – ABS data such as SEIFA*

*GLAR – Gross Leasable Area Retail

*MAT    – Moving Annual Turnover

*SEIFA - Socio-Economic Indexes for Areas

From information such as this I can benchmark my stores to see what is occurring in the network. If a store is similar to the rest of my network in rental, comparative to other shopping centres of the same size, size of store etc, yet had very poor sales and operation scores, then I really should be looking at the operator, not the site location.

To close a store on this basis may be shooting the messenger, not addressing the real issue, and keeping the store open.

Sales Prediction Modelling

The core tool for any analysis is convincing or comforting yourself that you have some understanding as to what the sales of the business should be. If you believe in this figure, then you have a reasonable base to make a logical decision, not an emotionally driven decision.

Companies such as Spectrum work to give you some level of confidence in the Sales Projections you make internally, to convince yourself whether a location should be retained or closed.

We believe that for established large networks (50+ stores), you can build a sales prediction model based on the sales being achieved by the network. This is done by a Market Analysis where:

• All existing stores are visited and surveyed. The survey can incorporate issues such as size of building, number of counters and tills, seating (if a food business), access, store visibility, signage visibility, parking spaces and convenience, nearest neighbours and other business generators, and many other items. A survey like this also produces digital photographs of all aspects of the site, and gives a benchmark for comparison of stores and standards for the Marketing Department.

• Around 400 demographic variables are extracted for each store in the network either at different radii, by sales territories and/or by catchment areas.

• Competition and generators are then measured to determine which categories of business have positive or negative effects on sales. Possible distance effects, wherein the competitive or generative effect is only active within certain radii, are also examined.

• ‘Exposure’ is approximated based on traffic counts, signage and visibility, and a measure of pedestrian volume and flow.

•  Sales information for all applicable outlets complete the dataset, plus any internal operations measures where available.

Statisticians then go to work to look for the best variables that explain the sales that are being achieved. We normally obtain a Sales Prediction model that typically incorporates variables from each of the above categories (survey data, demographics, competition/generators, exposure, and internal data). Though no guarantee can be given of individual results, we normally obtain models that can be said to be 70 - 80% accurate. The more consistent a brand is, the more accurate we expect the results to be.

The graph displays all stores in a network, each point showing where that store sits in comparing the actual vs predicted sales.

The sales prediction model aims at predicting the sales on mature or established sites, normally that has been open at least 1 year.

Once a Sales Prediction model is built and agreed upon, all sites being considered for closure should be run through the model to give a sales prediction. This may be done by the consultant, or internally if the company has all the necessary resources. Our experience is most companies tend to leave that with the Consultants as:

• They do not have the internal statistical expertise to run the models
• They do not have all the data necessary. Often the model includes some variables from Census 2006 and ABS business counts 2007.

The Sales Prediction Modelling then becomes an integral part of the process that a Franchisor undertakes before agreeing to close a site. It should not be seen as the only part of the decision, as exceptions do occur, however it should be seen as a good “flag” as to what we should expect.

Though this is never 100% accurate, it should allow the Franchisor to have a set of ranges that guide further decisions in the Process. For example, a sales prediction in a range below the Network Average would provide a strong justification towards closure.  On the other hand, if a store’s prediction is in the top 25% of Network Average, then it probably should be retained in the network, even if it means going to company operation.

Summary

The cost of store closures can be very high. Make sure you are doing it for the right reason, because a short term solution of keeping it open may save lot of money, and be far cheaper than either closing the store now, or having to find a new store in the area in 2 years time.

On the other hand, if it looks and quacks like a duck – then it probably is a duck!

Peter Buckingham is the Managing Director of Spectrum Analysis Australia Pty Ltd, a Melbourne based geodemographic consultancy, and a Fellow of the FCA. Spectrum specializes in assisting clients with decisions relating to store and site location using various scientific and statistical techniques. Peter’s background was in the oil industry, with a strong focus in property issues, both nationally and internationally. To contact Peter email or call on (03) 98826488.