A changing tide – Big Data versus Location Analytics
What are the implications for Location Planning when Big Data and advancements in data visualisation have potentially surpassed the ‘wow’ factor of maps and location analytics?
When I first started in Location Planning over 20 years ago as the only GIS professional at DTZ I was seen as the go-to technical person on anything to do with data. Big data back then was anything that exceeded the 256 columns and 65,536 rows limits of Excel! In my second job as part of a bigger team at The Rank Group we were all seen as the geeky data wizards who blinded everyone with our science, intellect and, of course, our map-making prowess. I still laugh today when recalling one of our internal customers forever waxing lyrical about the fact that we had managed to manually digitise the Casino permitted areas, from a series of old maps from the Ordnance Survey’s Old Mapping department, (as this was over 20 years ago are they now known as the really old mapping department?) in order to focus our site finding strategy for Grosvenor Casinos.
This blog subject was inspired by numerous conversations I have had in the last six months to sharpen my thinking on the future of location planning in the wider context of data driven insight. My thoughts are based on general observations and I know there are location planning practitioners and departments that have bucked the trend and stepped out into the big data world beyond the ‘comfort’ of location planning.
Due to my background as a location planner I can’t help feeling a sense of frustration. You must be living in a bubble if you have failed to notice the large amounts of airtime (and budget) that big data and data science now has in business. The location planning industry could have been at the forefront of this technological wave but as an industry it seems like we are now frantically scrabbling to see how location has a ‘place’ in the race to glean something meaningful from the oodles of data businesses have at their fingertips.
Data science or rebel alliance?
The new kids on the block ‘the Data Scientists’ have stolen our geeky crown and covered it with diamonds. They provide valuable data driven insight to support a wider range of business problems, from marketing, operations, compliance, logistics, and dare I say it, location planning. Are they now trying to demonstrate that they know location planning better than we do? Has it got to the stage where machine learning and big data can do far better at site forecasting than location planners with years of practical experience? Does this mean actual site visits are no longer as important?
The success of data science is largely predicated on the following:
- Access to internal data – often the frustration of in-house location planning teams (depending on where the department sits) is getting access to the vast range of datasets internal to the organisation.
- Budget to buy third party data – because data science is supporting the whole business there appears to be deeper pockets to purchase other datasets.
- Knowledge of open data – ‘if the data doesn’t exist we can create it’ – seems to be the mantra of the Data scientists as they mash up data that provides new insight from the wealth of open and derived data.
- Toolkit – A location planner may have a desktop GIS, Excel, MS SQL Server, Alteryx, and SPSS (or SAS if they are lucky). Data Scientists can leverage a range of additional platforms and skills (Qlik, Tableau, Express Studio, Hadoop, FastStats, R, Python – the list goes on) that are usually outside of the domain of a typical Location Planner.
- Brain power – This is not saying that Location analysts are not clever it’s just that we are usually quite silo’d in our approach. Data scientists seem to have a wider repertoire of methodologies and solutions to aid them in their journey of data discovery.
- Time to test – New data science departments, particularly in the early days, have resource and time to explore as they rapidly seek to add value to an organisation. Existing location planning functions are typically under-resourced and often lack the bandwidth to expand into other areas to demonstrate their capability. Opportunities to apply their skills to other parts of the business may be few and far between.
I have observed the above developments in some larger organisations, with their location planning departments finding themselves in a renewed state of flux about future role and function. I say renewed because a number of departments have already suffered as a result of a reduced emphasis on store network expansion. Smaller and medium sized companies may currently lack the budget for Data Science but in most cases it will only be a matter of time before the business need and budget is found.
Location planners have two options:
- We can embrace these fellow geeks, learn from each other and get back on our surf boards to ride hand in hand on the data science ‘wave’. I am sure there is an opportunity for Location Planners to work more closely with Data Scientists and this is certainly something that I have seen at consultancies such as CACI, Javelin and Grant Thornton.
- For the less progressive amongst us we can sit it out and ride the storm. This is in the hope that these things are all cyclical and location planning expertise will once again be in vogue.
If location planners fail to adapt we may get left behind and end up swimming in the shallows.