Channel shift has been a hot topic in housing for a few years now and certainly for us IT suppliers, it has been a buzz phrase that we’ve all been riding on the back of for a while.
Channel shift is essentially all about trying to get tenants online and reduce the number of times they contact call centres by phone. We’ve all worked very hard to get them on and using our portals and applications and encouraging them to do so by offering a plethora of web-based services.
In a world where housing providers are having to achieve more with less funding and fewer resources while continuing to provide better services to tenants and increase the number of affordable homes being built, we need to look at achieving what I call true channel shift. We really need to not only get the majority of tenants away from using call centres but also move away from back-office staff having to make countless decisions based on the information coming through from the various communication channels and systems in use.
What I’m talking about is the next generation of efficiency savings for housing providers and pretty much shutting down those expensive call centres. All of the technology to achieve ‘the empty call centre’ is already available and could be adopted today. It may be too early for a truly comprehensive service without the need for human involvement but the next few years will provide us with the advances in conversational interfaces and artificial intelligence (AI) to really make this work. It’s safe to say that a lot of people will also have to get their heads around this concept over the coming years, just as they did with cloud (who remembers everyone objecting to the cloud just a few years ago?).
Let’s trail this concept of an empty call centre and work through a quick case study of a tenant with a problem with their central heating.
Instead of waiting for the tenant to log a problem online via your tenant portal, we can deploy smart devices into their home to be much more proactive at alerting us when an issue is either happening or likely to happen.
We can also deploy IoT-based sensors to check on the temperature, humidity, carbon dioxide and monoxide levels, even movement if we wish (I am well aware that we’re stepping into some potentially dodgy areas here regarding monitoring people’s movements and certainly explicit consent will be key).
If we now take this technology and use AI to start making sense of the information that these smart sensors and devices are sending to us then we can begin to not only remove the need for humans to be involved in the decision-making process but we can also be much more proactive with our service.
So, back to the example of a tenant with heating problems. Let’s presume that we have deployed a smart boiler to this property and it is triggering an alert that it has an error code. This data alone doesn’t really enable a computer to make a decision about what to do. However, if we add to that the fact that we’ve environmental monitoring in place, we can see that even though the boiler is failing, the temperature in the property is still within comfortable limits. The system can now begin to prioritise this potential repair job without a human involved.
If we then add to that information feeds from the web about the external temperature over the next few days, data from our CRM or housing management systems to gain some knowledge on the customer (perhaps their age) and then finally we add in historic data collected about this and other similar properties about how quickly they are likely to get cold in the forecasted conditions then we can enable our IT systems to make a priority judgement and decide to get someone out as soon as possible.
We can go a step further and, still keeping people out of the loop, the system can then use information from our back-office systems regarding the availability of repair operatives and their current workloads, location, availability of parts and so on.
We can even proactively make an appointment and book this in direct with the tenant via a text or email. In fact, if we’re really harnessing the power of conversational interfaces and natural language processing, why don’t we get the computer system to give the customer a call or use their existing home device if they have one (perhaps Amazon Echo) and let them know in a conversational way that firstly there is a problem and secondly details of when someone will arrive to fix the problem.
As we’re using a true conversational interface here, the tenant can then discuss options with the system. Perhaps they aren’t going to be around when the appointment has been made and therefore they would prefer a later appointment. The system can then handle the rescheduling of the work and communicate to the operative where necessary. Now we’ve got truly dynamic and automatic scheduling!
This solution also can enable a complete shift away from operatives’ traditional mobile apps. We can instead let them communicate conversationally with all the relevant back-office systems to ask where their next job is, what parts they may need and where to pick them up from on the way.
With a solution like this, we can completely remove the need for customer apps and portals, do away with mobile field-worker applications and truly achieve channel shift and move to a world where we don’t need many or any call-centre workers taking routine calls, planning work or communicating with customers and operatives.
The technology to deliver the above scenario is available now; with it, housing providers can aim to achieve the next wave of significant efficiency gains, cost savings and customer-service improvements.
Peter Luck is technical director of ROCC.
