Big data refers to computer analysis of data sets too large for the human mind to process. Trends and patterns, which computer algorithms spot, can offer businesses powerful insight allowing them to be more efficient, to better understand their customers or spot trends they may otherwise have missed. By making better decisions, companies can reduce costs, risks and improve their efficiency.
A variety of industries have been tapping into big data for years. Insurers are able to study data to model the likelihood of claims arising from different scenarios, such as extreme weather. City traders crunch numbers in real time to buy and sell investments through largely automated systems.
The world of real estate is clearly less fast-moving than equities. Yet the sector actually has a big data machine that was in use decades before music streaming or online insurance businesses became popular.
IPD, the benchmarking and analytics firm formerly known as Investment Property Databank, crunches property rent, value and management cost data, allowing investors to compare their performance against a benchmark.
While it is routinely used by major investors and fund managers, it does not cover the entire market. Properties in the mid and low end – not the kind typically held by the major funds – are excluded, meaning there is little oversight of many riskier areas of the market.
Unlike equities or commodities, property is a far more complex asset. The occupier can make a huge impact on returns, so understanding their business performance versus their sector can also be crucial.
With rules over energy efficiency tightening over the next two years, better understanding a building’s energy performance when occupied will also be key for investors and lenders. For those exposed to hundreds of properties, being able to slice and dice data is a much better way to properly understand the diversity of risk across their portfolio.
The benefits of big data
By lagging behind in adopting big data, property companies could be in danger of exposing themselves to potential risks. In a recent survey of 300 real estate managers, Canadian real estate advisory firm Altus Group, found that $11 trillion of real estate assets are being managed by manually inputted spread-sheets.
The errors and risks possibly arising from this state of affairs are numerous, ranging from simple clerical mistakes to rampant, criminal abuse by employees. But property firms and investors can harness big data to give profounder insights into the risks their business may face.
Investors in real estate, such as fund managers and private equity houses, will have large portfolios that they may not be tracking at a granular level.
Big data allows asset managers to see if their portfolio has the right mix of exposure to different risks and indeed, different assets.
Real estate is a complex asset that can play a variety of roles in a portfolio, such as adding a defensive element or offering index-linked income to counterweight more volatile elements of a multi-asset portfolio. Crucially, rigorous analysis can help ensure investors are hitting a particular asset class at the optimal opportunity.
The data can also help firms engage with and understand their regulatory risk. With the minimum energy efficiency standards (MEES) soon set to be introduced in Europe, property managers will need to understand exactly how large their risk of being hit by fines is for not meeting the standards. By using big data they can easily track what percentage of their portfolio needs to be brought up to the new standards, and which properties have to be prioritised.
Big data also enables smart buildings. By using a variety of sensors, smart buildings can merge a variety of normally independent operating systems – from heating to lighting – to maximise efficiency and performance.
Data captured across this broad spectrum can also give insights across the building’s entire lifecycle, from conception and construction, through tenancy and to demolition.
Insights about whether space is being under utilised can be gleaned from this, including tracking the parts of an office being occupied via the use of sensors. This can identify idle space that could be better made use of.
By using big data to shine a light on trends like this, a firm can rationalise its costs. Fundamentally, this could be as simple as making sure the building’s main lights are switched off once everyone has left.
Macro vs Micro
Big data can be used at both the macro and micro level. Particularly for micro applications, the real benefit is that it can be used in real time, and so can inform business decisions today, not tomorrow.
Appraisers would find value in adopting big data in this way. The insights gleaned from it can find what price points the market is at – whether properties are selling above average or below average. Given that there are so many data sources for appraisers, using it to condense them not only saves time, it allows more accurate thought to be given to the state of the market.
Managing Data Risk
Properly harnessing big data also involves having strict rules in place around its use. Training staff in proper data handling procedures is vital, as is ensuring that any IT system has adequate safeguards in place to prevent either internal or external theft.
While not using big data is a risk, being hacked and losing that information is also a danger that is worth protecting against. But with the correct infrastructure in place, it can give companies a holistic understanding of their business, help reduce risk and ensure they’re maximising their efficiencies.
Guest blogger Paul Turnbull is Head of Client Services, for Willis’ Real Estate Practice, where he is responsible for a number of major property sector clients. He joined Willis in 2005 and has more than 28 years of experience within the industry.