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Evidence based analysis – the benchmark for property forecasting

According to Tim Brown, director of JLL’s Strategic Consulting practice in New South Wales, property as an asset class is often the ‘poor cousin’ when it comes to the quality of research that is used in its forecasting.  By comparison to the equity and debt markets, he notes, property doesn’t share the homogeneity and real-time mark-to-market features which make quantitative analysis easy.  As a result, significant real estate decisions are often taken without the detailed analysis which could minimise their risks and enhance their chances of success. Whether through lack of awareness or simply hubris, he regularly witnesses the effects of decisions based on simple extrapolation of short run trends and anecdotal evidence.

The failure to take sufficient account of cyclical real estate supply/demand imbalances or to recognise the structural changes flowing from demographic or technological changes can have far reaching consequences. Whether through office projects which are obsolete before they are completed or residential developments which come on stream just as the market slumps, the costs of such misjudgement can be far reaching.

As the largest commercial property research house in Australia, JLL benefits from a dedicated team of researchers who update key metrics relating to all major investment-grade asset classes on a quarterly basis and can draw upon data sets stretching back to 1970. Harnessing this comprehensive data and analysing the drivers beneath it enables the firm to provide its clients with the insights they need to make more informed real estate decisions with fewer unpleasant surprises.

Whilst recognising that no forecast is likely to be completely accurate, Brown offers below some suggested steps which he says can help ensure you are not just in the right ball park but as close as possible to the goal:

1. Consider the economic context

Any property based forecast should be set in the context of prevailing economic conditions as well as those anticipated in the longer term. This requires considering both global and national risks and opportunities.  Critical to the interpretation of any economic forecast however, is its implications on specific property asset classes and distinguishing between short-run economic conditions and structural. By example, Brown cites changes in industrial structure, growth in e-commerce, revolutions in 3PL and supply chain management and advances in infrastructure that are all impacting the long term demand for industrial land, such that past conditions can no longer be relied upon to predict the future.

2. Account for the historic context and drivers

 The Suburban Trend – Historic Sydney Metro Office Market

Short term data series and anecdotal evidence can be misleading and dangerous – Brown stresses the need to consider the drivers and longer term trends holistically as well as individually.  His recent work in forecasting the growth of suburban office markets for the NSW Department of Planning and Environment identified key trends impacting the distribution of office space in the metropolitan area and the decreasing dominance of the Sydney CBD.  Examining the bigger picture tells much more about the forces behind this changing distribution than could be obtained from a simple examination of individual markets in isolation.

​3. Account for the current market conditions
The current strength of the residential market has led some to an unrealistic view of this asset class.  The Sydney residential market has shown unprecedented growth in development site values, with average sites doubling in price over a 3 year period.  A fuller understanding of the complex interplay of demographic processes, financial factors, economic growth and regional changes helps put this growth into perspective and provides insight into how the market is likely to perform into the future. 

Residential Development Site Sales (Average rate per unit 2012 to 2014)

4. Consider carefully the forecasting approach and use all available ‘check’ approaches
Forecasting requires flexibility of approach based on a consideration of a range of factors including the availability and reliability of the data.  Brown advocates choosing a primary approach and utilising a reasonable level of ‘blind’ check approaches, with any differences then reconciled.  With large datasets now available, multiple regression techniques which allow the identification of relationships between the many factors which influence an outcome can readily be applied within the property environment.  From analysis of the various attributes which determine rental levels in different buildings to forecasting how a new rail line may add value to surrounding properties, the JLL team uses statistical analysis based on detailed property data to provide greater insight and understanding.

5. Have a clear and transparent rationale  
Brown believes forecasts should be open for the reader to see the rationale and assumptions underpinning the forecasts.  All too often he feels, property analysis is presented as a ‘black box’ which places too much reliance on ‘based on our experience’ style of commentary as a substitute for critical reasoning.

6. Take a view on future trends

Off-shoring and activity based working have and will continue to impact office markets. Online retailing will continue to impact demand for retail space. Driverless cars, pre-fabricated construction, fintech businesses and 3D printing are all set to disrupt the way we currently interact with commercial real estate. Although the outcomes are unclear and unpredictable, Brown argues that analysts should make an informed view in their forecasts and account for it.

7. Undertake sensitivity analysis

Identify the likeliness of impact of variations in your assumptions.  This provides the reader with a real sense to the risks.  Probability analysis using techniques like Monte Carlo analysis can be used to explore how changes in key variables can affect the outcome.  Rather than simple sensitivity testing which considers the effect of single or pairs of variables in isolation, probability analysis enables the simultaneous impact of multiple variables to be explored and the results assessed in terms of the likelihood of particular outcomes.  It can tell you, for example, that there is an 80% likelihood of the IRR or ROI exceeding your target.  Knowing there is a 20% probability of the project not breaking even and which factors have the greatest impact, can be more useful to informed decision making than a sensitivity table which simply shows a 15% increase in construction cost will result in red ink.  The key is being able to estimate the range within which each variable is likely to fall, which requires judgement based on consideration of both past trends and future expectations. 

Example of Risk Analysis using Monte Carlo Simulation 

8. Identify limitations 

Finally, Brown stresses the need to recognise the limitations and challenges of attempting to forecast the future, acknowledge it and identify the key limitations and sensitivities of the forecast. He points out that crystal balls, by their nature are cloudy, but sound research backed by rigorous evidence based analysis can make them less opaque. Indeed the aim may not be to predict a single outcome, but to aid judgement by putting forward a reasoned and soundly based argument, well documented and backed up by facts and clearly stated assumptions. Discussing the range of possibilities based on verifiable data he says can be far more useful to than seeking unfounded precision.  

JLL’s Experience in Property Based Forecasting
JLL’s Strategic Consulting team applies its analytical skills and real market knowledge to help clients gain the insights they need to make the most informed real estate decisions.  It draws on the knowledge amassed from the firm’s day to day market activities across Australia and around the globe and the depth of analysis arising from its commitment to professional property market research stretching back over 40 years. 

JLL has developed a market leading position in real estate forecasting in Australia;, the Consulting team applies these insights to real world issues and challenges facing government and private sector owners, investors and occupiers.

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