The birth of BIM (Building Information Modeling) came about through engineers and quantity
surveyors wanting to a smarter way to measure dimensions, bills of quantities, loads, volumes of
materials and costs. Drawings with databases became a reality thanks new software but what is
the connection between the Spatial Web and BIM? Let me remind you that the aim is to connect the
physical and virtual worlds. BIM designs exist in 3D digital space and are called parametric models.
This means they do not have any connection to the 3D geography of our planet. The solution to
integrating digital CAD models into the real world is remarkably simple by using a process called
geo-coding. This methodology links data point in any BIM model of a building, to a known physical
reference point which denotes its physical location.
This simple routine has the effects of linking two worlds – placing buildings into the geographic
location where they will ultimately be constructed. Old timers always said retail was about location,
location, location, and even in our digital world that still holds true. Most of us are very familiar with
geo-space – thanks to the GPS’s in our cars, Google Maps, Apple Maps or Google Earth. Now that we
have physically placed our store into the real world, a host of other data can be added.
Starting with the external environment, retailers can purchase data that captures the topography
around their stores, or the adjacent buildings and the streets. They can connect the geo-demographics of their store catchments to databases that contain store attributes. Retailers can create
digital fences that represent primary, secondary and tertiary zones around their stores – giving them
a new way to define catchment areas, franchise zones or sales territories. They can track customer
movement and even identify online transaction made on mobile phones, tablets or computers and
allocate them to geo-fenced areas or specific stores.
Big Data providers already analyse mobile phone and camera data to manage traffic congestion
on our highways and track people on our streets. Retailers can purchase data for vehicle, public
transport and pedestrian traffic to help them predict store patronage and sales in different conditions
or within dayparts. Digital giants such Google have mapped a significant proportion of geo-data that
defines our planet, our cities and the external environment in them - right down to street level.
Now let’s focus on the internal environments which retailers trade in. This is a world that is still
largely inaccessible to Big Data because GIS systems are not ideal for mapping interiors. 4G or 5G
technologies systems are not foolproof when it comes to mapping the interiors of buildings like
shops, malls and public spaces. That means that there is a huge amount of cubic space around us
that remains to be digitised. Once those spaces are digitised in terms of 3D coordinates, effectively
creating digital Smart Twins, we can start the process of datafication.
I like to distinguish between digitisation which sets up the spatial framework of our markets, our
buildings and our stores, and datafication which is the process by which we can add rich data to
those frameworks, including store attributes, components, contents and the occupants associated
with the spaces. For example, data such location, dimensions, layout, fixtures, equipment, services
and space allocation by department, or by level, can be captured to create a total digital record of
the store and its interior environment.
Fortunately it is possible to datify stores using same software that is used to design and construct
them. Once you have created an accurate digital record you have taken the first step to having
a Smart Store. A total digital record of stores would be invaluable to all divisions within any retail
For example, finance teams will be able to maintain up to date digital registers of all their instore
assets. Teams responsible for repairs and maintenance of stores will also benefit by installing IOT tags
to show the location of services such as power, water and air conditioning in the event of failures or
maintenance. Security systems and vital equipment like refrigerators and freezers will be monitored
by IOT sensors. Operations teams can monitor and track the movement of customers, staff and
merchandise in their stores. Marketing and VM teams can more effectively apply and measure their
customer communications within their stores.
I believe the true value of the data embedded in Smart Stores will be improved management of stores
- especially in the form of metrics for logistics, operations, merchandising, financial, marketing,
customer service and staffing. I have no doubt that we will be hearing a lot more about Smart Stores
in the future. We will also continue to see the demise of Dumb Stores! The process of datafication
of stores started some time ago, and as it continues we will start to see ways for Old Retailers to
transform into New Retail.
These technologies may be new to some retailers, but in industries like airlines the use of digital
sensors and analysis of the Big Data generated by the tracking devices have dramatically improved
safety and efficiency – and made preventive maintenance of aircraft far more effective. Makers of
jet turbine engines, including GE and Rolls Royce, have found their businesses transforming from
manufacturing to managed services – all based on datafication.
The potential benefits of Smart Stores are significant for retailers. Rent is a huge cost for stores
– and it all comes to down to accurate measurement of GLA ( Gross Leasable Area). Most of the
survey work our teams undertake in stores is now done by 3D laser scanning – a far more accurate
technique. That means the drawings produced of stores, and therefore their dimensions and GLA, are
more reliable. We discovered early in our digitisation journey that the leasable areas of some stores
were incorrect and that landlords were charging more rent than was necessary. How much could
you save if your retail leasable area was overstated by just 1%? You could be missing out on valuable
Digitisation of stores into Smart Twins can help retailers optimise their energy and lighting costs.
Specialist consultants can use the data to create better lighting plans, improved lighting levels
and lower energy consumption. Spatial analysis of digitised stores offers benefits to merchandise
planners. Our experience with buying teams and merchandise planners has shown that they often do
not have access to accurate space allocation data of stores at a detailed level. That data would allow
them to better manage their ROS (return on space) and can be exported from BIM design software
into store planning platforms like Spaceman.