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Home / Free Subscriber Access / Mining your data resources, AI & automation

Mining your data resources, AI & automation

In the world of housing management solutions, the focus has always been on capturing data as a user progresses through a process. Historically, most systems were based on the concept of where a software developer thought it made sense to place the data fields, rather than how a logical path through a defined process could be created for the user.

Because of this rather unstructured approach, dissatisfaction in systems was a common theme with the staff who actually had to use the systems, and a legacy of poor-quality data was an inevitable result – something that has often only recently been brought into focus as organisations begin their shift to digitisation and then realise that data quality is a central part of that strategy.

Start with your customers…

Due to the obvious cost and resource advantages, the shift in thinking within the housing sector towards the cloud and browser-based systems has been vastly accelerated during the past few years when home working has become the default, accompanied by IT suppliers in our sector making this journey with varying degrees of urgency. But cloud and indeed software itself are the means to an end, not the end itself. I believe that what will really make the difference in terms of which future solutions will add the greatest value is the adoption of customer value as the starting point, seen in the context of the overall tenant journey.

The key components that will help in adding this value are intelligent automation, clear management information and a focus on processes as the starting point in our thinking.

Introducing automation in the tenant journey

Starting with the concept of intelligent automation, my experience is that the housing sector, like any other service sector, has traditionally done a great deal of repetitive, manual work. Almost every area of the tenant journey will prove this; for example housing providers’ repairs processes have always been notoriously paper-heavy, with works orders, variations requests, completion slips and invoices all requiring manual interventions. Or the arrears management process – with staff trawling through 100s of arrears’ cases every week, sending swathes of expensive printed letters, yet not really understanding the effectiveness of this activity.

The necessity is to analyse where in each process we can add value by automation. Given that a housing management system doesn’t exist in isolation, we see that a lot of the customer-facing work can now be picked up by self-service tools such as portals and apps.

These portals and apps have been augmented by virtual assistants which can deal with both message-based interactions but also voice activation, changing the game as far as customer interactions go. Capable also of integration with other channels such as social media, the virtual assistant becomes a powerful tool in the management of service provision. However, add to this the ability to learn and it increases efficiency even more.

For example, as questions are asked more frequently, the best answer can be ‘learned’ by the software using AI, and so customer enquiries that would once have tied up a customer service representative for five minutes can now be resolved without human intervention at the first stage.

AI for better tenant outcomes

There are myriad other scenarios where the deployment of intelligent automation can add huge value to an organisation. I’ve mentioned the arrears process; simply sending out letter after letter to a tenant because they happen to have an outstanding rent balance is the clerical equivalent of banging your head against the desk – repeating the same activity and expecting a different result.

What if the system could ‘learn’ as it goes along? If an arrears letter, email or text message is sent, and a payment or contact is made by the tenant within a defined timeframe, then we have a more positive result than if no response comes back from the tenant. If the software can begin to learn what the most effective intervention is for a particular tenant, when to send it, and what channel to use, then not only is effort reduced but there is a chance of a better outcome for the tenant as well.

Predictive maintenance to save time and money

Looking at the maintenance side of a housing provider’s business, predicting asset failures is one of the holy grails of controlling costs while again minimising inconvenience to tenants. By flagging up the requirement for probable interventions based on known variables (an example of the massive value lying hidden and mostly unused in housing providers’ existing databases), a system can enable more efficient planned spending on fixing the assets that are more likely to go wrong, rather than relying on tenants to report the repair when it breaks. Using predictive technologies in this area of the business is the modern equivalent of the adage ‘a stitch in time saves nine’.

Data is king

The next area where housing systems have traditionally been weak is the provision of management information. Swathes of printed reports that were the staple of every housing manager 25 years ago, have developed into graphical reports, yet what they tell us is what has already happened. While that may be interesting or even useful, there’s not much we can do about it.

The current vogue is for dashboards to provide more real-time information on performance, tailored to a specific role. Such visualisations can help us to notice trends or problems so that more can be done to correct the situation quickly.

The real value will be realised when AI is added to the mix; after all, almost all housing providers are sitting on vast, barely-tapped data resources, with potentially 20+ years of data in their housing and asset management systems. By applying modern analytical tools to this data, patterns can be revealed that can help organisations in planning and changing the way they do things. If you can begin to understand which factors will make a person’s tenancy succeed or fail within the first three months of moving in, then you can focus your support on those areas and intervene much earlier when needed.

Improving the tenant journey

One of the key areas we are working on is to look at how systems can make the tenant journey as smooth as possible, by enabling housing providers to deliver an efficient service, to spot the bumps in the road ahead and to free up staff from manual tasks so they can be re-deployed in roles that add value to the tenants. I believe these can be achieved by introducing tools that let us all work in more efficient ways across all areas of customer service and end-user experience.

Chris Crane is a solutions manager at Aareon.

See More On:

  • Vendor: Aareon
  • Topic: Housing Management
  • Publication Date: 084 – November 2021
  • Type: Contributed Articles

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