At 1st Touch, we have always been committed to integrating the latest technology trends for the benefits of our customers. These include technologies such as the internet of things, digital by default, frictionless computing and big data. We look at them in their own right and we also study how others use them. This allows us to explore how we might integrate the smarter aspects of these technologies into our own systems.
Of these, big data is particular exciting in terms of the potential it offers both housing providers and their tenants. The clever part though, is understanding how to translate this technology into driving positive change in the social housing sector. The good news is that there are some leading figures who seem to understand the tremendous opportunities available and who can articulate both the science and processes involved.
Presenting with me at the recent Housing Technology 2017 conference was Brian Moran, the deputy chief executive of Adactus Housing Group. His expertise regarding Big Data is both widely acclaimed and deeply respected.
In his presentation, ‘Adventures in Data Science’, he summed up the benefits of big data as he sees them, providing a useful insight into how data science drives some very key deliverables – it’s an insight that bears serious scrutiny.
In Brian’s view, big data is ‘statistics on steroids’. The rapid growth of this technology is partly explained by the massive recent increase in computing processing power and also the augmentation of data by clever use of algorithms. These algorithms can approximate solutions on problems which many used to think were impossible to solve. In practice, the science of big data is a team sport combining business ‘domain’ knowledge with good maths and stats skills, alongside programming expertise, plus an excellent understanding of machine learning.
In terms of what big data science can do, there are two main categories – descriptive techniques and predictive techniques. On the descriptive side, these can be summarised as pattern discovery and clustering. On the predictive side you have forecasting and classification. Somewhere between these two categories are simulation techniques which allow you to look at possible future scenarios.
There are many business and consumer applications now benefitting from these techniques. Indeed, as Brian points out, big data is now pervasive in everyday life. You can see examples of it if you use a satnav, make a Google search, use Netflix or submit a credit card application. However, both my and Brian’s point of interest is to discover how this technology can deliver interesting applications in social housing.
Well, the three main areas that big data applications can help with are:
- Better services: by improving client satisfaction and automating processes;
- Better control of risk: by managing costs and improving levels of productivity;
- Better business planning: by scenario analysis, making cashable savings, reducing costs and increasing revenues.
For better services, one can look to frictionless self-service applications as one example. So, through our own self-service tenant portal and apps tenants can request repairs, report problems such as ASB or estate issues or check their tenancy agreement. They can do this from the comfort of their own home, using their own device 24/7. Customers can now book appointments using our iAppoint module; these appointments are then automatically confirmed back to them by text with details of the operative visiting and the registration of their vehicle.
The big data helps make these services friction-free by helping to reduce the number of touch points between contact and action. In many ways, this reflects the ethos of global players such as Amazon, which has used big data analytics and behavioural research to introduce one-click ordering and the like.
In a similar way, Adactus itself has created a model to streamline its online service delivery. Using machine-learning techniques, their system analyses a customer’s query for keywords such as ’wet’, ‘pipe’, ‘leak’, ‘taps’ before making a prediction that a plumber is needed.
Adactus also uses clustering through ‘HDBSCAN’. Here, machine learning looks at data to identify clusters of customers with similar needs and requirements. This, along with pattern analysis enables better targeting and segmentation of services and offerings.
Big data also allows Adactus to control risk better. They achieve this through both pattern recognition and anomaly detection. By reducing risk, its management team can focus more on improving services and managing the business better.
Overall, by combining all these benefits, big data allows organisations such as Adactus to plan better for the future. This has real benefits. It boosts value for money, efficiency and customer services while also driving down costs.
At 1st Touch, we have also looked at how the data can be used for different groups. So through our 360° system, we can combine all of the relevant data relating to a tenant, tenancy, property and estate onto a single integrated screen. While visiting a customer, the system allows a housing manager to use their device to book a repair or for a gas operative to report an ASB or estate issue.
By making operatives multi-functional and frictionless, it reduces the need for separate visits by each organisational silo. This greatly saves time and cost and is received extremely well by tenants. It can also reduce the recruitment of staff to fill the posts and with fewer staff, there is the opportunity to reduce the amount of office space required too.
Looking to the future, big data will continue to drive service and customer care and, combined with technologies such as artificial intelligence, will delivery even greater efficiencies. True, it requires an initial investment to unlock the potential but when it comes to delivering improvements, it’s a small price to pay for bigger services, bigger customer ratings and bigger cost savings.
Greg Johns is CEO of 1st Touch.