Housing providers like us are suddenly dealing with a LOT of data. Our recent pilot scheme to use Switchee devices in the hunt for more data on how our customers are using the energy and heat in their homes is a great example; it will see real benefits for our customers but it adds to what is already a very busy data picture.
Data overload
Making sense of all this data presents a huge threat to IoT projects from data overload. Our world is more data-driven than ever but is data literacy prominent in our teams? Is it listed as an essential skill on enough job specifications or is it still siloed in just the IT and data departments of your organisation? How much time is it taking your staff to look at and understand your data when we should be providing actionable insights? It’s concerning that too much data and not enough intelligence around it could mean some critical alerts are missed, such as alerts from equipment that monitors falls in supported living.
Plenty of sector-risk profiles have recently highlighted that data integrity is key and we know regulators are even keener on it being a high priority.
“All too often in the sector we see poor control over data, and a lack of awareness around how the information across the business is managed… [There is a] lack of transparency around what, where, why and how data is used, updated and reported as well as who has responsibility for it.”
Mazars 2022
All this ‘too much too soon’ can lead to an organisation struggling to retrofit a data strategy, if one exists, into the new world. By that, I mean not just treating IoT as just another system but adapting to a new way of collecting data and a new mentality. We should approach it as a way of addressing business pain-points, such as damp and mould or assistive technologies for vulnerable customers, where it helps us focus on end-users and their requirements. By understanding their capacity for information analysis and how they interact with data and insights, we can create a people-centric approach that considers all the decision-making automation we can now apply while recognising that there’s still going to be a human affected at some point.
Triaging your data
In housing, we’re well aware of the risks because we’ve already seen some governance rating downgrades because of poor data quality. The solution comes from defining clear goals and objectives before collecting data, thereby reducing the chance of collecting irrelevant or unnecessary information. Then prioritise it, because not all data is created equal, so we know what is most critical. Use automation to process and analyse data so you can act on those important insights, and work hard on how you present that data to others so it’s in an easy-to-understand format. Use machine learning to identify those patterns that help you make decisions, and train more of your staff to be data-literate and democratise data so it isn’t just in the realm of IT.
Knowledge vs. data
We always come back to our customers because we must have the benefits for them in mind. It’s not just about compliance or efficiency KPIs, it’s also about the decisions we make on the investment of our resources. That’s why you need to deliver knowledge rather than data so it can be combined with other information to build a picture. At Platform Housing, our in-house data quality tool is helping us to produce a score for our board on the data we present to them. Developing something that focuses on the picture we present and what then should be acted on is proving vital to how we make decisions.
“The best-performing associations tend to regularly promote awareness on the importance of data ownership and stewardship responsibilities across the organisation… …Well-developed data governance frameworks promote regular communication between data owners of key datasets across the organisation, allowing for best practice implemented within respective directorates around ensuring good data integrity to be effectively communicated to other data owners.”
Mazars 2022
Another risk we are all concerned about is security. Almost 20 per cent of organisations have detected an IoT-based cyber-attack in recent years, according to Gartner. This can happen due to poor visibility and understanding of the devices your organisation has. Then, do you know where your data is going to be transferred and stored? Is it in the UK or offshore? You’ll need to be aware of liability should your IoT devices let you down or, even worse, a breach, attack or failed data request that brings reputational damage.
Is it right?
There are ethical questions, too. Yes, having a device that monitors heating being turned on or hot water being used would indicate a customer is home and could be contacted for sales purposes, but is it right? Without a good data ethics framework, there’s no definition on what data you’re going to collect and what you’re going to do with it. It’s where we can be clear and transparent with customers and a place where we can keep our promises.
It makes us think about privacy issues because more data involves more teams needing access and therefore who should and shouldn’t have permissions. Remember, IoT data can form part of any subject access request (SAR) or GDPR enquiry that your organisation receives, so who deals with that?
As we make moves to fight off this potential data fatigue, we need to be wary of duplication. Think holistically across your IoT environment and avoid users needing to be responsible for managing multiple solutions. Define your security and understand how the organisation plans to use IoT so that the risks are identified early on, including the involvement of your security teams from the outset. Think about how your new approach should be embedded in your ethics with transparent codes of conduct.
Automated responsiveness
The results we can achieve from all of this ‘thought before data’ can be great, such as real-time data triggering a workflow to book an engineer for a boiler problem or a housing officer contacting a resident who it appears hasn’t been in touch for a while. Let predictive analytics alert you to a problem before it happens and become proactive in maintaining your stock and preventing downtime.
Let IoT help you collect data on your metrics and identify areas for improvement, and so it grows. Next thing you are integrating IoT with other business systems such as ERP or CRM to get a more complete picture of your operations. Then you can start identifying opportunities for real optimisation and gaining insights that might not be apparent from the data alone.
Before you know it, all that data is not slowing you down, and it’s enabling cross-functional collaboration between departments identifying all kinds of new opportunities to offer even better services for those all-important customers.
Jon Cocker is the CIO of Platform Housing Group.
