Corporate real estate
Manual cleaning surveys are time and resource hungry.
Without an automated process it can take a contractor a couple of weeks and it is an expensive task for a Business Development Manager to price a job,” explains Keith.
It is an even slower process to capture all the cleanable assets within the space too, so in general these are not accurately accounted for. As a result it is not uncommon for contract pricing to get set at the higher end and then tolerated year-on-year.
“Without accurate detail it’s very difficult to determine how savings can be made,” Keith says. “While our client was very happy with their cleaning service, they were still curious about how it would compare to the benchmark.”
REVOLUTIONISING CONTRACT PRICING THROUGH AI & ML
As the corporate world begins to return to the office after a year characterised by remote working, procurement teams have a significant opportunity to find cost savings in their cleaning and soft services bills.
Here, founder and CEO of ScanQuo Keith Ryan describes how a major London-based accounting and investment house took advantage of ScanQuo’s approach to contract cleaning benchmarking, resulting in a combined overspend of 20%.
The organisation’s Head of Procurement was a contact ofKeith, Ryan, ScanQuo’s Co-CEO
ours and when we outlined what our algorithms could do he
was keen to learn more,
- Manual cleaning surveys are time and resource hungry
- Difficult to capture all the cleanable assets
- With no detail, it’s hard determine how savings can be made
- Identified a 20% Overspend
- £150K saving identified.
Indirect Cost: £750,000
- 30% overspend on consumables
ScanQuo’s approach enables Procurement teams to identify cost savings accurately and efficiently without compromising quality.
“Our client brought us in to carry out a full like-for-like price benchmarking exercise across cleaning, consumables, pest control, washrooms, and mat rental,” Keith explains.
“Typically, procurement teams are aiming for a 3–5% cost saving year-on-year.
In this case they were very curious how the granularity of detailed, building-specific DNA in ScanQuo could drive their commercial decision-making process”
“We are the first technology of our kind to factor globally recognised productivity ratings and like-for-like wage costs into an automatically generated benchmark.” To save on scanning all 13 of their clients’ sites across the UK and Ireland, ScanQuo then applied this benchmark to each space as a representative average with tolerances of 10-15% accuracy.