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How Do We Keep Our Stock Condition Data Current When Surveys Are Years Old and Repairs Data Never Feeds Back?

Housing association stock condition data goes stale between surveys. We build a feed from repairs, voids and inspections that keeps component records current.

Updated 3 min readBy SpiderHunts Technologies

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Quick answer — TL;DR

Stock condition data goes stale because the survey is done once every few years, while repairs, voids and planned works change homes every day without updating the asset record. We build a feed that picks up component changes from repairs, void inspections and completed planned works, updates your asset management system, and flags homes where the data and reality clearly disagree.

A new kitchen that the asset system does not know about

Your asset management system says a home's kitchen is due for replacement next year, based on a stock condition survey several years ago. In fact the kitchen was replaced during a void last spring. Another home shows a boiler with plenty of life left, but the repairs history shows it has broken down every winter.

The planned investment programme is built on this data, so kitchens get replaced twice, and failing components wait for their turn in a list that was never updated.

Why condition data drifts

Stock condition surveys are expensive, so they are done on a cycle, often a sample of homes each year. Between surveys, work is done to homes all the time through responsive repairs, voids and planned programmes, but those systems do not update the asset record. The data slowly moves away from reality.

  • Component replacements in voids are recorded in the voids system or on paper only.
  • Repairs jobs describe work in free text, not as component changes.
  • Completed planned works are signed off by contractors, but data returns are inconsistent.
  • Nobody compares repair frequency with the component's recorded condition.
  • Surveyors starting a new survey do not have the latest work history to hand.

What stale data costs

Investment plans built on wrong data spend money in the wrong places. Components are replaced before they need to be, while others fail and generate repeated repairs and complaints. Reporting on the condition of homes to your board and regulator becomes harder to stand behind, and surveys spend time recording what the organisation should already know.

The condition data feed we build

  1. Completed repairs are read from your repairs system, and the job description and schedule of rates codes are checked for component replacements such as boilers, windows, doors, kitchens and bathrooms.
  2. Where a replacement is detected, an update is proposed to the asset record with the date and source. Clear cases can update automatically; uncertain ones go to a person.
  3. Void inspections and void works specify components replaced, and the feed records them the same way.
  4. Contractor data returns from planned programmes are checked for completeness against the properties and components in the programme, and gaps are sent back to the contractor.
  5. Homes where repair frequency on a component is high but its recorded condition is good are flagged for a surveyor to look at.
  6. Updates are written to your asset management system, or the asset module of your housing management system, through its API or import.
SourceWhat it tells the asset record
Responsive repairComponent replaced, or recurring failure
Void worksComponents replaced during the void
Planned works returnProgramme completions with dates
Repair frequencyCondition may be worse than recorded
New surveyConfirms or corrects all of the above

Investment decisions and your asset strategy stay with your asset team. The feed keeps the data they rely on closer to reality.

What your asset team gains

Component records reflect the work actually done. Planned programmes stop including homes already improved, and failing components appear sooner. Surveyors start each survey knowing what has changed since the last one. Reports to the board on the condition of homes are based on current data, with a clear source for each change.

Is your stock condition data like this?

  • Your stock condition survey is several years old for many homes.
  • Components replaced in voids or repairs are not updated in the asset system.
  • Planned programmes include homes that were already done.
  • Homes with frequent repairs show good condition in your data.
  • Contractor data returns are incomplete or late.

FAQ

Frequently asked questions

The questions readers ask us after this guide.

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Do we still need stock condition surveys?

Yes. The feed keeps data closer to reality between surveys; it does not replace surveyors seeing homes.

Can it read free-text repair descriptions?

Yes. Descriptions and codes are read together, and uncertain cases go to a person rather than updating automatically.

Does it work with our asset management system?

Where the system has an API or accepts imports, updates go straight in. We check yours first.

What about contractors' data returns?

Returns are checked for completeness against the programme, and gaps are listed so they can be chased.

What affects the cost?

The number of homes, the systems involved, and the quality of existing repair codes and descriptions.

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