Supply
The RSPM for the UK uses our own database of 1.2 million records of multiple and independent retailers, leisure operations, restaurants etc. A record includes details of unit location, address, fascia and product category. Many also include other details such as unit size. We have developed this as our own database called StorePoint (which contains details of the main multiple retailers) and Advanced Business Locations (which contains details of all multiples and independents).
Demand
We have created grids of hexagonal geographic areas to which details of the resident population are attached. These include demographic and spend profiles, as well as the drivetime to each unit or retail centre and to other hexagons. At its finest level, where each hexagon is only 500 metres across, there are 1.4 million - 150 times more detailed than postal sectors, where only 9,300 cover the UK.
Two Types of Catchment
The RSPM enables catchments to be modelled using:
- consumer research. This gives us an historic catchment, valid only for the time the consumer interviews were conducted. We generate these as soon as research is available and store the catchments as images. Hence we call these Pre-calculated Catchments - Precalcs for short
- attractiveness values exclusive to ORC. These allow us to replicate consumer shopping patterns and release us from dependence on historic research. This allows us to forecast future performance. Catchment area data is refreshed for each project and catchments are run anew. Hence we call these Real-Time Catchments
Pre-calculated Catchments are based on actual consumer research and so they provide us with the benchmark against which we can calibrate and validate the RSPM in order to produce accurate Real-Time Catchments.
For our Real-Time Catchments, the attractiveness value attributed to a retail centre or unit determines its gravitational pull relative to nearby competition. This is a function of the size and variety of brands of retail units in each location.
Modelling Changes to Local Markets
The RSPM allows us to take account of changes planned to local retail markets, looking forward 5 years (usually). We:
- increase local area spend values to take account of increases in housing, population and consumer expenditure
- add any new scheme or retail unit openings
- delete any closures
- amend it to take account of scheme or unit extensions
- amend the road network to take account of planned changes (new roads, dualling etc)
The flexibility to model changes to all of the influences upon local markets makes the RSPM ideal for running "what if?" scenarios.
Impact
Modelling these changes allows us to forecast their impact upon all retail centres/units in the region for any given year before or after the review date of the study. Examples of the impact of changes to housing and roads are shown in the section called "Why Drivetimes Don’t Define Catchments". An Impact Report is produced reporting on the relevant type of retailing (foodstores, retail warehouses, town centres etc) the following example is of town centres:
Calibration and Validation
The process of calibrating the RSPM for retail units has taken four years. This is the process whereby we can ensure that the RSPM produces sales or spend forecasts of an acceptable level of accuracy. It is a process of comparing RSPM results with actual operating unit or retail centre catchment areas, generated using consumer research. It forecasts sales using empirical data regarding units, their locations, fascia and product category.
The RSPM has been most rigorously tested in the foodstore sector in the UK.
For foodstore sales forecasts, validation has come from two primary sources:
- using comprehensive research into consumer spending patterns by store fascia to predict individual store sales and calibrating the RSPM to replicate such results
- comparing RSPM sales predictions with actual sales of which we become aware
The RSPM foodstore sales predictions have been greatly improved, as a consequence of a better understanding of the impact of imperfect car parking, site access and site visibility upon sales. The RSPM now produces consistently good sales predictions.
In those instances where ORC has been able to validate its foodstore sales predictions, in 80% of instances the forecasts are accurate to within +/- 7%.
Improvements to the RSPM as it is applied to individual stores leads to a similar improvement in the model as it is applied to town centres, shopping centres, retail parks etc.
In related markets we have also been able to demonstrate the accuracy of RSPM results against reality, particularly for non-food retail warehouses, town centres and factory outlet centres. The following examples are of:
- Meadowhall’s catchment mapped using:
- 3000+ consumer responses
- the RSPM
- Teesside Retail Park’s catchment mapped using:
- 400 consumer responses
- the RSPM
These examples record spend by hexagonal geographic area as hot spots (red) through to cold spots (blue). At this resolution, the hexagonal geographic boundaries cannot be seen easily.
The RSPM forecasts full-year sales performance - i.e. the visit and spend patterns of all visitors to a retail centre, retail or leisure unit. The example catchments for Meadowhall and Teesside Retail Park generated using consumer research results are, of course, based on a very limited sample of the total annual visitors. We would expect RSPM catchments to show more intensity, especially around the limits of catchments, because the RSPM is forecasting full year sales from all visitors to these schemes, not just the sample limited to a few weeks consumer research.
Meadowhall Catchment All respondents vs RSPM Results
Hexes by Spend Value
Teesside Retail Park
The Affordable Rent Model
Now an integral part of the RSPM, the Affordable Rent Model is unique to ORC. It is designed to forecast in detail individual retailers’ Profit and Loss Account performance. It draws upon our own Retail Performance Database - a record of sales & profit performance for individual stores and companies developed ever since 1990.
It is highly successful and the most comprehensive assessment of retailer sales and expenses available. It forecasts:
- sales and profits
- levels of rent affordable
- whether proposed Zone A’s are achievable (for schemes)
- potential total rent roll
- prospects for rental growth over (say) 5 years
Each P & L assumes that a retailer will want to make at least last year’s company average gross margin as profit in any new unit otherwise new units would dilute company performance. What is left over is available for rent and super profit and is the Affordable Rent.
The following example is of a proposed Next unit in a scheme in the north of England, from the mid 1990’s.
Typical Output
For typical outputs, refer to the individual sections on: