2017 will be a significant year for ‘big data’, with more organisations gathering, processing, storing and deriving value from all forms and sources of data. The number and size of systems that support significant volumes of both structured and unstructured data will rise inexorably too.
To many, this momentum is powered by the belief that the effective management of big data is the driving force behind sound and responsible best practice. However, it is not always the IT stalwarts that are the greatest protagonists of big data’s impact. For example, Aberdeen Group recently reported that, “organisations with big data are 70 per cent more likely than others to have business intelligence projects that are driven primarily by business users, not by IT.”
By studying the benefits of big data technology, we can understand why this business-led prerogative is in the ascendancy. Some of main pay-offs are that big data can:
- Accelerate business analytics and reduce the time to decision insights and competitive analysis;
- Share computer resources to optimise collaboration and utilisation and therein reduce costs;
- Deliver a better balance between cost and performance and therein drive efficiency;
- Reduce systems complexity and simplify management.
These are all good business motivations. As Geoffrey Moore, author of ‘Crossing the Chasm’ and ‘Inside the Tornado’ said recently, “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”
The clear implication here is that C-level management needs big data to drive strategic direction effectively. However, it is the sheer scale of the data sources that concern them most, or rather how best to use the data that they have gathered or could gather.
It’s a valid concern as the use of the technology continues to expand to hitherto unimaginable levels. And you can forget the principals of data warehouses or mountains and interrogating the data with pre-defined questions. Now, it’s all about ‘data lakes’ and finding the answer even before you knew what the question was. And this volume of data will continue to expand; where there were once terabytes, there are now zetabytes.
Certainly, in the mainstream business world, I can see more and more examples of the benefits that big data delivers when managed successfully. For example, Experian can identify those most likely to need financial support in the future. This has led to a more supportive and caring attitude to credit.
While such data analysis can be used effectively across all market sectors, social housing is one of the areas where I feel passionately that the potential of the ‘art of big data’ has not been fully realised. Yet it is perhaps one of those areas where big data offers the greatest potential. It’s certainly fascinating to see the data from different sources combine and to contemplate what this might tell us.
For any single property, there’s data about the property itself, data about the type of tenancy, the background of the tenant and historic data from across the different housing providers’ departments including housing, income, repairs, care and estate management. There’s probably a whole load of tangential data too, such as nearby traffic management, ASBO issues or even policing statistics. To this external data, one could add data about regional demographics, cultural characteristics, education and health. In the future, IoT data from inside the property will also count – all provided by sensors that detect effective heating levels or water usage and which can even optimise boiler replacement times.
In fact, it’s quite mind-blowing that you can find correlations in the data that you didn’t know were there. Recently, I came across some research proving a close correlation between cancelled gas certificate inspections and late rent payments. This kind of information gives housing providers the ability to potentially tackle issues before they become problematic.
Indeed, by using big data management, one can already deliver all the relevant data in a refined and accessible format (ref. both the tenant and a property) to the smartphone or tablet of a visiting operative. For example, within 1st Touch, field workers and mobile operatives now have comprehensive 360-degree access to all relevant data available online, in a refined format, through their devices. This allows them to handle all outstanding issues in a single visit. Thus, a housing officer can take a rent payment and book a repair or gas inspection. They can also discuss care issues or the need for a discretionary housing payment. By the same token, a gas engineer servicing a boiler could also report an ASBO issue or report on estate conditions. By being able to solve multiple cross-function issues in a single visit, it frequently means that the right outcomes are delivered far faster to an even happier customer. It also means that the costly requirement for a second or third, fourth or fifth visit is eliminated.
This is a wholesale change in the customer interface and the satisfaction ratings will leap as a result. However, there is also a real chance here to dramatically slash costs; by solving all the issues in just one multi-function visit, a housing provider can do more with less. This potentially means that they can reduce the recruitment bill for the same function. And if there are fewer staff involved, then there’s every chance that other fixed costs such as office rental costs could also be reduced.
This ‘do more for less’ opportunity explains why the driver in social housing is more a business issue than an IT one. It also explains why housing providers’ senior management are keen to get into the data to see exactly what’s in there, as opposed to looking for pre-defined answers.
As a consequence, one can see that it is the holy grail of ‘predictive big data analytics’ that will continue to drive future development. We have already found that many of the more customer-focused and efficient housing providers are keen to work with us to exploit our 2020 vision of the market. In doing so, they aim to identify the trends within the data they have collected and to understand ways in which they can translate these into positive actions. While they are aware that both the data and the task ahead are big, they are motivated by the fact that the opportunities for their customers are even bigger.
Greg Johns is CEO of 1st Touch.