Excerpt from next paper: Linking GEM Lease Analytics? to a Standard Demand and Supply Curve

About the Author

Don Gilbert is a Retired Specialist Retail Valuer (“SRV”), an economist with commercial law qualifications and experience retail lease consultant. Since 1993 he has published and presented the outcomes of his actual fieldwork, thereby building up a significant Body of Knowledge linking retail leasing to rental rent. All his works including Software he has written is thoroughly copyrighted.

In the process he invented a six step, Step-by-Step methodology. It uses Sophisticated Software (as a Service), which quickly and accurately evaluates a Reasonable Rent for ONE Retail Premises incorporating several recognized Valuation Methods. Such a flow-on effect would be enormous to lift Valuation Standards.

Whilst it is extremely accurate (Garbage in Garbage Out); he refuses to call it an AVM (‘Automated Valuation Model’); but it uses the most comparable metrics; which in effect ‘slice and dice’ and “Test” the veracity of all the metrics, which then openly and transparently link and compares evidence, the Profits Method, industry benchmarks, a newly invented Weighted Average method and Averages to the highly specific business and the site. Colour coded graphing makes reading and understanding the complex analytics, involving millions of probabilities eg. colour coding, sorting, arranging, re-arranging, etc. far easier.

In effect Mr Gilbert who is constantly frustrated by Specialist Retail Valuer inconsistencies, lack of audit and accountability, the basic elementary methodology used, which enables one to slip through the cracks, he believes that it could be done far far better.

His original thinking dates back to his first paper in 1993, then the subsequent definition of current market rent (Gilbert, D. 1995) now an International Standard (2000), the principles thereof are embedded into the Software. All his papers presented in Asia, Europe and Australia carry hints of his software invention.

GEM Lease Analytics? as it is called, was coded in 2010 in basic form, and continuously improved upon in bursts of enthusiasm and quietly launched in February 2021. It is on a GeneXus Platform and Amazon servers. It can be “transplanted” anywhere in the World by changing language, measurement and currency.

Security is on unique Lotus Software platform. It is a full Software as a Service.

During the process, Mr Gilbert has unearthed important information in regard to surveying / valuation / appraisal, which was first documented in 1523. Very few economists academics have touched on these things; and Mr Gilbert’s Intellectual Property fills some important gaps, which he will tease out in his book: ‘Property economics: an update from 1523’.

He provides independent, impartial advice to landlords, prospective investors and tenants. If required get independent impartial legal and financial advice. Whilst he has retired he still takes on consultancy work and is in the process of marketing their Software as a Service product. It is For Sale and he believes an ideal long-term owner will be Google Maps or equivalent matching the Software to their Three-Dimensional Equivalent.

Copyright ? Donald Evan Gilbert and Gilbert Family Trust (1993 – 2023)

TITLE

‘Excerpt from next paper: Linking GEM Lease Analytics? to a Standard Demand and Supply Curve'. Full title of paper: 'GEM Lease Analytics?: a Sophisticated Decision-Making Tool; to Evaluate a Reasonable Rent for ONE Retail Lease'

?An Invention is:?“……… a unique or novel device, method, composition or process. The invention process is a process within an overall engineering and product development process. It may be an improvement upon a machine or product or a new process for creating an object or a result. An invention that achieves a completely unique function or result may be a radical breakthrough. Such works are novel and not obvious to others skilled in the same field. An inventor may be taking a big step in success or failure”.?https://en.wikipedia.org/wiki/Invention

TARGET AUDIENCE

Retail Tenants, Landlords, Investors, Valuers & Property Professionals (and their Associations), Banking and Finance Industry, Regulators, Academia and other Professionals. Mediators.

Linking GEM Lease Analytics? to a Standard Demand and Supply curve

The simple rules in regard to Micro Economic theory go is as follows:

1.????Price of homogeneous product eg. butter, carrots, beef, gold, coal, etc. is shown on vertical axis or Y-axis;

2.????Quantity is shown on X-axis;

3.????When price is at its highest, demand is at its lowest; as price falls demand increases. This relationship is presented on the Demand Curve and the relationship is shown on Y-Axis and X-Axis;

4.????When price is low, there is limited or no interest to supply a good or service. As price increases, more producers manufacturers builders developers will enter the market and supply a good or service;

5.????The equilibrium point is at where Price P meets Quantity Q on Y-Axis and X-Axis respectively;

6.????Moving to Figure 2 below, Step Five of the GEM Lease Analytics? retail lease rental modelling, all data points depict a Demand curve on two Data Series: all the data points are either on a rent per square metre basis (could be per square foot) presented by a red line graph, or exactly the same range of data adjusted to the same floor area and shown as an annualized gross rent standardized to the size of the shop on the coloured bar graphs whose lease is being evaluated.

Following on whilst each data point is for a homogeneous product say: retail premises for book shops or pharmacies or supermarkets or hardware stores, the price or “value” of each data point eg. landlord evidence, tenant evidence, a suitable vacant shop, each one, is matched to a real “Supplier” of retail space which makes up the Demand curve.

The higher priced or valued rents congregate towards the LHS (and typically there are fewer of them) and as one moves towards the RHS and as the price aka the rent falls, one tends to find more and more landlord tenant vacant shop evidence.

Interspersed with this actual “tested” evidence which one can refer back to from Steps One, Three and Four, in Steps Five and Six are the pivotal checks and balances eg. equivalent Industry Benchmarks[1], the product of P & L Eval (the Profits Method) and our proprietary Weighted Average method.

These arguably are the checks and balances; the “Demand” points that throw up red lines and how and where some of the other evidence might be congregating.

As all these data points including the leased shop’s current (if relevant) and asking rent are on the same data series, one might then start to decide where the data points of “reasonableness” lie?

What is one searching for? What is one trying to predict? Surely one is trying to reach an informed conclusion of where / what: “Willing informed Landlords and Tenants” would reach an informed decision on, in regard to a Market Rent or equivalent (IVS 40.1); the point where “Supply” equals or ought to equal “Demand” for this highly specifc mostly generic retail floor space which is sunk cost to a landlord, relative to specific Business Capital. In legal terminology; the rent under these lease terms, for this type of business where there is a meeting of the “minds” of a willing landlord and tenant free from duress, misrepresentation, etc. willing informed parties.

Another thing that one is trying to understand, where could that point be? Where could the intersecting point of supply and demand be? One is matching a Body of Evidence, in the main it is non-homogeneous (imperfect) evidence, different sites, different locations, different sizes, different efficiency levels, different frontage depth ratios, different competition profiles, etc. etc. the list is endless, to the rent being paid, seeking to justify one’s case. Perhaps linking it to an industry benchmark might satisfy an argument? Does the P & L Eval and or GEM Lease Eval prohibit even contemplating going ahead with a lease because it can and does go into negative territory if one cannot amortise one’s business establishment expenses and or sales and margins are too low? Get financial and legal advice.

What the GEM Lease Analytics? Six-Step step-by-step methodology does really well, is link and match real thoroughly tested data metrics to the lease whose rent is being evaluated.

The Author has drawn in imaginary Supply Curves S1 and S2 and a most probable region where one might contemplate entering into a lease in Figure 2.

Step Six also has two data series; one common to both being a rent per square metre / square foot, the other being the equivalent Occupancy Cost (rent: sales ratio) linked back to the leased shop at its forecast future maintainable sales. By rotating between Steps Five and Six linking and comparing occupancy costs to annual and the rent per square metre should assist one to conclude a reasonable outcome.

Lastly, once a Demand Curve is defined, and it has defined (sliced and diced) that highly specific market, a party to a rental dispute, can introduce a metric (an annual equivalent gross rent, an occupancy cost to sales ratio or a rent per square metre) and superimpose it on one or the other graphs and compare it to the existing data for its relevance. ?

[1] GEM Lease Analytics? has some 600 benchmarks programmed into it, from landlord tenant industry sources, here and overseas with significant overlap representing the same or similar metrics and even range of metrics