Never has the need to validate Life Sciences data been more crucial
by Rob Burborough, Partner at 3PM
What do these statements all have in common?
The Great Wall of China can be seen from Space.
Humans have five senses.
We only use 10% of our brain capacity.*
The answer is that they are all false but widely believed to be true. Why? Because enough people have presented them as facts over
time and people never really researched the original presentation source.
We are at a critical point in the Life Sciences evolution where there is a lot of the same data flying around – the highest demand for
lab space, no space available, too much space in the pipeline.
Is there really a lack of R&D space or is it more the wrong kind of space in the wrong areas? Or is there, however, a lack of
understanding and experience propagating this statement as fact because it’s too complex to imagine space being freed up from
other sectors to plug the gap?
When it comes to conversion and retrofitting, Life Sciences is really no different from other sectors: it seems difficult but, coupled
with genuine insight into the sector at a macro level, the right building and adaptable /flexible fit-out is possible. On the flip side,
some are oversimplifying the conversion of offices to labs – a large proportion simply wouldn’t work for the sometimes unique and
intricate requirements of different science occupiers future undefined needs.
Thus – on the occupier requirement need – the smart thing to do is question where the data comes from, validate it and question how
it is captured in a timely manner and deployed successfully as an investment decision making tool.
For example on the demand side an agent may be looking for lab space of between 50,000 sq ft to 100,000 sq ft for a tenuous client over
18 months to 3 years but the client isn’t fully bought in to moving and the initial demand requirement may of course change, disappear,
shrink or grow as technology adapts. If those compiling the total demand figures have, say three or four of these included in their figures,
the demand total – presented as research – could be as much as 50% inaccurate. But, as it’s research, the market takes it and uses it again
and again thereby validating the need as fact. When in fact the need is a culmination of many moving parts held by many different organisations.
It’s not a unified approach.
While on the supply side, we may have a scheme with a variety of tenure sizes, complete with ancillary services and common areas. Generally,
these are marketed as spaces available to suite the science need from 1,000 to 50,000 sq ft but some might not include the total of shared or
flexible space and some will which leads to confusion over the common baseline. To an agent or researcher crunching figures over total supply,
that’s quite a discrepancy to factor in when assessment total independent validatable demand.
These examples work the other way around too of course: I’m not implying that demand isn’t there and supply is but pointing out that it’s
important to check the data when financing, developing and determining the strategy is important along with more tangible business case
and projects decisions involved.
We must also challenge what is being included and how it is being measured in these requirements: gross vs net, core vs common areas,
plant v floor plate, what is the chargeable structure for tenants on this basis?
The truth is, there are few genuinely experienced professionals in life sciences who see all the data from all sources with many experts entering
the market post-Covid. Usual real estate knowledge doesn’t automatically translate, and it takes a tried and tested practitioner in both science
and property to know what to ask and how to plan for any number of workspace idiosyncrasies different SciTech or bio pharma firms want
incorporated in their bespoke space.
And that’s without the curve ball of balancing conflicting needs of, for example, a biological occupier who needs constant and regulated
environment for part of the space, against operational sustainability that will ultimately deliver net zero.
That’s not to say that it’s too complicated to convert existing property into lab space for example. But suffice to say that it’s more complicated
than designing standard commercial space and expecting a one size fits all for a variety of lab fit out needs.
Those who recognise this will be the ones who question the data. It’s crucial that they do to facilitate the evolution of the sector to accommodate
the right space being delivered and avoid market dislocation.
