Extracting real value from big data
How to harness “Big Data” to manage risk is one of the key challenges facing businesses across all sectors today. And for housing associations, fundamental to this challenge is how to access and link up the masses of data they have – often in multiple systems – to produce one version of the truth and use it to reduce cost.
Clarifying the various data sets and linking that data together can help to illuminate what is leading to claims and other costs. Finding out what falls within a maintenance budget, for example, can help identify trends and possible preventative actions.
Of course, housing associations have a potential wealth of data at their disposal, but too often fail to capitalise on it or even to access it. These unique data sets range from information they hold on their properties, to hazard spotting or pre-notification information about damage or wear and tear that could lead to future claims, to accident book entries, to the cost of responsive repairs and small damage, to claims information that may reside primarily with their insurers and much, much more. By extracting and linking these various information chains effectively, this data can build a valuable picture of the association’s risks and its total cost of risk.
Also, if all of this information is then tied to the Unit Recognition Number (or London Property Gazetteer number for properties in London), you can start to identify trends and also track the frequency of events which result in costs, whether they are insured or uninsured.
For example, multiple leaks across a block of housing might be due to a problem with the same type of heating system that has been used across that block. This trend could remain hidden if the data for properties, responsive repairs and damage is not linked. And, of course, if housing associations become aware of potential problems before they become too widespread, then efficiency and productivity can be improved leading to significant cost savings.
An awareness of the linkage between pre-notification of damage or wear and tear and accident book entries andclaims can also serve to improve health and safety and reduce incidents and costs. For example, if a housing association can better track the occasions on which they are notified of faulty paving slabs, they can act quickly to implement repairs and stop future claims. And taking before and after photographs of those paving slabs – and linking that with the pre-notification data – can help housing associations be alert to those spurious slip-and-trip claims that might be made after a repair has been carried out.
Having the full picture of where multiple claims are made for similar types of events can truly help housing associations to get a much better handle on their risks, to manage those risks more, to reduce repair and claims activity, and ultimately to drive down their overall cost of risk.
Armed with the right tools and the right information, housing associations can implement a centralised approach to effective data management, bringing to the fore all pertinent information, thus gaining knowledge to manage risk and truly unlock the power of big data.