Location Intelligence
Location, location, location. An oft used phrase that originated in 1926 was used to attribute the success or failure of a real-estate investment. This phrase continued into the retail world and became the mantra for the strategy of place for businesses wanting to select the right location and achieve success. A HBS article mentioned that “… the strategic value of a new location depends on three things, …, the strength of available resources, …; the company’s ability to seek and retrieve knowledge in this setting; and its capability to do something better than competitors.”
Fast forward to today, organizations leverage all kinds of data to make site selection decisions. I was fortunate to see a major bank in Thailand reduce the number of physical branches and yet continue to increase the amount of deposits and customers using spatial analytics. Location intelligence was used to term this process of amalgamating business intelligence data with spatial or mapping data to derive insights and drive decisions. While we hear of this bank’s success, I personally worked with several retail organizations trying to replicate their location intelligence process in US and Europe in Asia only to find the limited availability of authoritative data, particularly demographic data and its’ derivatives, being the biggest roadblock.
Data as the new oil
Clive Humby, a UK Mathematician and architect of Tesco’s Clubcard mentioned in 2006: “Data is the new oil. It’s valuable, but if unrefined, it cannot really be used. It has to be changed into gas, plastic, chemicals etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.” Ginny Rometty, IBM CEO went further to expound in a 2013 speech “I want you to think about data as the next natural resource.”
So, it was great for me to see that 5 years since that experience to see governments in Asia taking the first steps to making data available (see Open Government Data in 6 ASEAN countries). Data is the new natural resource and a lot of data is locked up within statistics departments and data archives. Governments continue to collect massive amounts of data and in fact is the best source of demographic data. By distilling income tax data, we can get information about purchasing power of communities. Imagine the kind of insights we can glean from processed data from employment records, company types, etc.
Spatial and Temporal Dimension of Data
Whilst Governments make the effort putting data out for organizations to use, it would be interesting for Governments to add spatial and temporal dimension to these datasets. This would help organizations better understand the communities around their businesses. Retail organizations, banks and service providers can better serve the surrounding areas if they get a sense of the community they are in.
In my LinkedIn post, Digital Transformation in Retail, I recast the term urban center to a smaller and yet dense area of activity and introduced the concept of Urban Center Vibrancy as a way to view the resonance of the urban center within its’ communities. A great example of an urban center is a shopping mall and we can see how well a mall is performing by looking at a leading indicator in the form of crowds – hence vibrancy. We are beginning to see the decline of the bricks and mortar aspect of retail, which is under tremendous threat from the online cousins.
If the Government data on the communities are available as a service with spatial and temporal dimensions, a retail mall operator and their tenants can take advantage of these “crude oil”, mine, refine and derive insights to allow these physical retail entities to adapt and evolve and continue to be relevant and resonate with the communities they serve. Of course, the physical retail entities also need to value add with an array of hybrid online-physical-mobile application services which increases a visitor’s experience.
Real Time Data & Strategy of Space
Fast forward to the not-too-distant future. Urban Centers themselves can leverage a lot of real-time data being collected today from commuter and traffic systems. The data collected by the transportation departments of governments can be of tremendous value for Urban Centers to amalgamate with their own human traffic data to bring their operating efficiency to a higher level as well as optimize their retail space to provide superior customer experience.
Some of the exciting data being collected are the mass-rapid commuter traffic across Singapore’s train and bus systems, Uber’s and Grab’s commuter data as well as human queues at taxi points in Changi Airport. Imagine these data being made available and organizations learning to capitalize on these datasets will ultimately develop competitive strategies to fully utilize their physical spaces.
