Shortlisting 'Suitable Locations' using Map-based Business Analytics
Updated: Jun 13
My recent posts were focused on using satellite imagery to extract and map information regarding environmental variables such as pollution levels, land surface temperature and subsidence.
Radar-based remote sensing is abundantly useful when it comes to generating insights about the pressing environmental challenges we face on earth - be it on land, water or in the air. Also, it is a deeply technical field - to be able to extract accurate and meaningful information from earth observation imagery requires considerable intellectual expertise. I have only replicated the methodology, which scientists have developed after years of research, to my Area of Interest.
However, satellite-generated data is not individually sufficient to solve many of the challenges or fulfill the objectives of commercial organizations. For example, it can't help an organization to visualize its operations, spot bottlenecks, gain competitive advantage, reduce costs or earn more profits. Fortunately, Mapping is not restricted to analyzing remotely sensed data alone; it can analyze any spatial data i.e. any data which has a location / positional component to it, with equal ease.
A very basic example of this is a Physical Address - any physical address can be plotted on a map. More importantly, if any other information is linked to the address - eg. Supplier Data, Competitor Data, Customer Data etc., it can be plotted on a map too as an attribute of the physical address. With modern mapping technology, a map is not just restricted to being a visual depiction, it is also a repository of information, which can be stored, analyzed and visualized in dynamic ways.
Let us consider a hypothetical situation - You are a mobile phone manufacturer who wants to shortlist a few locations in India suitable to launch a phone specifically targeted for female customers. You have some parameters for the business analytics in mind - a) the female population count in that location has to be considerable, b) the population density in that location has to be above average, c) the purchasing power of the public in general needs to be above a certain threshold and d) the expenditure on Electronics & IT products for that location needs to be above the national mean expenditure.
As you would notice in the image above, with the latest mapping technology, these parameters can be factored in and potential launch locations can be identified in a visually engaging manner. The map-based Solver has honed in on 9 pockets in India which fulfill all our stated requirements. Moreover, the results are easily query-able i.e. you can tweak the constraints to be more conservative or aggressive as per your liking and the map-output will dynamically update in an instant.
Now imagine that alongside these macro-variables, which can be sourced from publicly available datasets, you were to add in your own company's supply chain information. For example, you can add in your existing distribution network, competitor locations, supplier information and customer information. The output of the map-based Solver would become even more relevant for you.
In another hypothetical example, I have mapped the existing branches of a Canadian Bank in Toronto (located towards the northwest of the map below). The bank is considering to expand its branch network and open branches at the right locations across the border in the U.S. The bank has some parameters in mind - a) population density, b) average household size, c) percentage of residents having a savings account and d) median disposable income. Also, I have mapped its competitor information - denoted in red circles.
Please note - bank branch locations and head count information is publicly available in the U.S.A.
As you would observe, this output (shortlisted pockets colored in blue located towards the south in the map) is more relevant as the internal branch network and external competition information is also mapped in addition to the the external four macro-constraints. Alongside the map-based output, several charts are also generated (not shown here) to further enhance your ability to interpret the data effectively so that you can arrive at a better decision. Isn't this useful?
Article Update: 01st March 2022
Below is a video prepared by Mapmyops Intern - Tanisha Jain - which demonstrates how mapping platforms are useful for Site suitability analysis i.e. shortlisting a new site by factoring in operational parameters and constraints. Tanisha has used GIS (Geographic Information System) to site the location of a new hospital.
Basis my experience, when compared to spreadsheet-based Network Design modelling, Map-based Location Intelligence is not only more convenient to operate but also the output is more easier to understand, interpret and modify. You may read my elaborate article which covers both these topics in-depth, here.
Needless to say, the more quality data you can use as part of the site suitability model (internal and/or external), the better your chances are to have a 'more relevant' Location selection output by using mapping technology at your organization for decision-making purposes.
Intelloc Mapping Services | Mapmyops is engaged in providing mapping solutions to organizations which facilitate operations improvement, planning & monitoring workflows. These include but are not limited to Supply Chain Design Consulting, Drone Solutions, Location Analytics & GIS Applications, Site Characterization, Remote Sensing, Security & Intelligence Infrastructure, & Polluted Water Treatment. Projects can be conducted pan-India and overseas.
Several demonstrations for these workflows are documented on our website. For your business requirements, reach out to us via email - firstname.lastname@example.org or book a paid consultation (video meet) from the hyperlink placed at the footer of the website's landing page.