What specifically would we get back?
- The Comparable Set report for one location and four comparable spaces of your choice.
- The Comp Set report shows revenue per square feet, revenue per desks, occupancy and ancillary revenues.
- We break down the key metrics by segments (private offices, dedicated desks, hot desks and meeting rooms).
As soon as we have your data and the ones of the Comparable Spaces. We can produce your dashboard before having the data of the Comps and then add them as data enter.
What would we be asked to share?
We start working on your report as soon as we have the data.
Who else will be participating?
Major operators have joined. Get in touch to know whether are Comparable Space to yours. Otherwise, we will reach out on your behalf.
How do you ensure my data are anonymous?
- The Comp Set shown are the average of at least four Comp - never the individual data.
- Your input sheet has a hashed code so that the real name and address of the location never shows up on our system
- There is a number of rules on the aggregation of the Comp Set e.g. the 4 spaces need to correspond to 4 different companies and one can only do two changes at the same time to avoid the ability to reverse-engineer an individual Comp data as described in our rules here: https://coworkintel.com/policy.html
What are you doing to ensure data quality/integrity?
- First of all, we have worked with the early adopters to make sure that the metrics tracked correspond to business needs and mitigate manipulation risk. For instance our definition of seat capacity corresponds to the maximum legal capacity to avoid gaming by adding or removing desks.
- Second, we conduct regular checks of the data with our brokerage partners and others if it seems suspicious and on a purely random basis.
- If the data is inaccurate by mistake, we revise the report promptly.
- If we find that data has been systematically and intentionally misreported, the respondent is banned for life.
- Last, some operators are using our dashboard for internal purposes eg to benchmark one of their own locations against another - reporting wrong data renders the report useless to them.