Social housing is under pressure across the world, particularly in the Americas, Europe and Oceania. The challenges of 2020 sharpened pre-existing pressures to squeeze the sector, with heightened demand coupled with government austerity measures.
Statistics are still being compiled, with preliminary estimates that:
It is clear that demand for social housing will expand as the immediate and long-term impacts of the economic decisions made around COVID-19 are revealed. A clear demand will be that efficiencies are implemented across social housing networks so that services can be expanded.
Social housing networks need to increase focus on information utility and long-term asset network performance optimization to deliver value to the communities they serve, and maximize the lifecycle of accommodation in the networks. Without excellent asset data and the capacity to make fast robust decisions, social housing networks will expose themselves to a huge financial risk that will compromise the capability for their community to continue serving these crucial needs.
High performing social housing networks will rely on their data – which means, they will rely on having the right data, served in a manner that assists the execution of robust and accurate decisions, at a velocity that lowers maintenance and repair operation (MRO) costs and elevates service delivery. They need to access the right information, quickly synthesize intent and opportunity and react – from operational works through to senior strategic investment policy making.
The social housing sector has long been impacted by outmoded data platforms, heavily manual processes and little coordination between systems and networks. This has put many social housing networks in the position of having weak intelligence on which to draw.
The impact of such weak intelligence foundations include:
Incomplete, inaccurate, and low quality portfolio data makes short and long-term asset management difficult – and it makes asset network performance optimization impossible. Complete, accurate and high-quality asset portfolio data is foundationally vital to understanding network condition, formulating performance optimization plans, and managing the execution of those plans.
With well-founded, fiscally advantageous plans, leaders will be able to gain the support of stakeholders – social housing stakeholders are often combinations of government, NGO and NFP delegates, requiring cohesive agreement to plans.
Technology has enabled a quantum leap in asset network performance optimization; many if not all of these lessons are relevant to social housing asset optimization. That is to say, that asset network managers do not need to increase funding, but instead (or at least first) integrate new digital techniques to better and more efficiently manage housing.
There have always been options for superlative social housing optimization – at a cost. Asseti brings a practical capability to optimize without adding to operational administration at all, and at a very low price. Clients typically see positive return on investment (ROI) within a small number of months.
Instead of increased funding, we advocate for spreading current social housing investment into new possibilities, so the housing stock under management better meets the tenant’s needs while being financially sustainable.
As a dedicated asset network optimization platform, Asseti simplifies onboarding and practical use. Social housing management best practices are explained below, with a guide to how each is simplified with Asseti.
This key point is relevant both technically and ethically. Professionals in the social housing space are always mindful of the people or families, and the properties they inhabit. Simultaneously, from a technical perspective, all inspections, maintenance and repairs are conducted at a property level and data must therefore be just as easily reviewed at a property level as at a family level. It must furthermore be possible to aggregate to an estate, complex, suburb, or region level – any classification grouping your social housing network uses must be easily adapted into the asset network performance and optimization platform you use. Non-traditional assets such as carparks, garden areas, common spaces and playgrounds must also have a place in this management solution.
Therefore the solution must:
Accurate records of the appliances and hardware at sites is key to effective asset network management and optimization. Generally assets that can be damaged and replaced are recorded; internals like carpet or ovens, and external such as guttering. Gutters are an excellent example of how insights can differentiate servicing and decrease maintenance and repair costs – social housing in metropolitan Los Angeles may have no nearby trees and require gutter maintenance annually or less, whereas a regional Georgia property with close vegetation may require gutters to be cleared monthly during autumn, while social housing asset managers in Minnesota need to accommodate both the leaf litter of fall and the challenge of heavy snowfall.
Systems should enable management of:
Asseti is designed for asset management, the built environment , and built-environment adjacent elements in the asset network envelope.
Asset network performance optimization centers on issue identification at a property level, with rectification to avoid major issues. The information used in this can be analysed to identify trends that may reveal systematic issues - why are repairs in arrears 3-months in one region compared to the overall average of 1-month? Are additional maintenance contractors required?
Such issues can only be resolved with data and insight.
Issues notifications should be:
Asseti is built around flexible visual interfaces that facilitate the above at an operational and strategic asset network performance optimization level.
Social housing network providers and leaders must internalize their use of data in decision making, and see it as foundational to performance and performance optimization. Shifting to Asseti enables a digital twin of your social housing network to be formed very economically and quickly, and immediately eliminates the location and composition uncertainty endemic to virtually all asset networks.
As visual and other data layers in Asseti a genomic tapestry is built so that asset performance optimizer can understand in detail conditions at the property and gain predictive insights from the platform within the Asseti Paradigm program.
From this a lifecycle analysis, condition forecasting, scenario modelling and qualitative analysis becomes more and more robust over time. The goal of asset management is understanding risk in a way that is almost prescient, which is finally a reality due to massive advances in data science and machine learning. With intelligent platforms like Asseti, social housing network operators and decision makers can evaluate or make decisions around potentials 1, 5 and even 20 years distant. This insight assists social housing operators and governments to plan appropriately for social housing requirements and optimize existing networks to optimally benefit the community.
The first step is to know your network. Plan an inspection regime that touches all properties so that they are accurately geolocated.
Gaining the information to generate the asset register is the starting place – using this information to generate a lifecycle analysis to know what’s coming up over the next 10 to 20 years is the next stage. What really matters, is using these results to produce a list of planned projects prioritised by risk, based on evidence and optimized by considering available funding.
Understanding and optimizing your social housing asset network is the ‘price of entry’ to securing new investment and expansion of properties and service availability.
Asseti’s dashboards enable reporting by site, asset and issue – with reports configured for the level of zoom required by the user. Dashboard reports can encompass the entire network – to evaluate outstanding maintenance and repair costs, repair velocity (report to repair lapse) or the overall risk level. Users can also drill to regional segments or individual sites for more granular insight.
Social housing networks preparing for the coming years need to start their journey – even if it is as simple as knowing all your property locations! From that simple starting point, Asseti has helped other asset network operators build a lite digital twin view, and build insight up with monitoring zones, components and other layered data.
This can be considered challenging – as all new endeavors are challenging – and the key is to start. Asseti has experience guiding the onboarding of asset networks in a way that promotes best practice; we currently have assets across 5 continents managed through our platform.
Set a convenient time with Asseti for a tailored social housing demonstration, or claim your free trial account at the button below to start loading in your data.