Submitted by Greg Johns CEO on 11th May 2017
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 IoT, 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 associations 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 Housing Technology recently 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 sums 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 his 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, Big Data science is a team sport combining: business 'domain' knowledge with good maths skills and good stats skills alongside programming expertise with 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 every day life. You can see examples of it if you use a SatNav, make a google search, use Netflix or submit a credit card/loan application. Both Brian’s and my point of interest though, is to discover how this technology can deliver interesting applications in social housing.
Well, the three main areas that Big Data applications can help delivering are:
For better services one can look to Frictionless self-service applications as one example. So, though our own Self-Service Tenant Portal and Apps customers can request repairs, report issues such ASBO 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. This in may ways reflects the ethos of mainstream 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 key word such as ’wet’, ‘pipe’, ‘leak’, ‘taps’ before making a prediction that a plumber is required.
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’ allows for 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, management are better able to focus 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 whilst 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 are able to combine all the relevant data relating to a tenant, tenancy, property and estate onto a single integrated screen. Whilst visiting a customer, the system allows a housing manager to use their device book a repair and a gas operative to report and ASBO 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 tenant. It can also reduce the recruitment of staff to fill the posts and with less 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 like AI will delivery even greater efficiencies. True it requires an initial investment to unlock the potential but when it comes to delivering improvements, it is a small price to pay for bigger services, bigger customer ratings and bigger cost savings….
1st Touch helped us to design and build a first rate system that will not only transform what we do but add a whole new positive dimension to the customer experience we deliver.
Director of ICT
The 1st Touch solution ticked all the boxes in respect of our pre-defined criteria. In particular, we liked their approach to implementation and flexibility in delivering
Systems Development Manager