There is much truth in the axiom that a “picture is worth a thousand words”. The power of Visual Data and its effectiveness in guiding actions and forming an understanding about complex issues is amply clear to anyone who has reviewed an article full of text and data vs. infographics representing that same information. In the past, the computational tools available to generate such graphical data were either cost-prohibitive, too time-intensive or too technically complex or simply clunky to use. For small, medium-sized companies (SME’s), especially, data visualization tools were beyond their resources.
The good news is that there is a host of relatively simple and inexpensive tools and apps that are available today that can be put to use very effectively and very quickly. This article is not intended as an overview of available options but rather a demonstration of how simply and quickly data visualization can be accomplished today using one tool that I came across recently. A 2012 startup, CartoDB is an application that allows users to take existing location data and create visual maps that can greatly increase the effectiveness of processes and decisions. CartoDB has a free option, making it a risk-free exercise if someone wanted to experiment with the platform.
In this article, I intend to demonstrate two simple applications of how CartoDB can be used by a business trying to streamline their existing processes. One application is for the Sales function and the other for the Purchasing function of an organization. For Small, Medium-Sized Enterprises (SME’s) this simple tool can prove to be a time and money saver.
Sales application: Visualizing density of customer locations
Recently I came across an interactive visual map, by Robert Manduca, that could benefit the sales function of a company. The interactive map gives a clear indication of the density of jobs in a given area making it simple for a company to focus their sales or marketing activities in those areas showing a high density of jobs in the specific area of interest for them.
Similarly, companies can take their customer and potential customer databases, and upload the geographical information to CartoDB and within less than half an hour, have a visual map of that data. An example of this is shown in a map I created of small and medium-sized manufacturing companies in the SIC codes ranging between 32 and 38, in Indiana and Illinois.
CartoDB also allows for additional data fields, such as sales volume, size-of-company or other relevant data to be represented on the maps using a simple layering technique. The options include cluster, choropleths, heat, torque, etc.
One can zoom in and explore the companies and details relevant to it by hovering over the data point as shown in the image below.
A salesperson looking to maximize their sales visit productivity can take a quick look at the map and plan out their day or week and make a list of companies to call on in certain geographic zip codes, within the least amount of time. At present, they may be using Google maps or some other tedious tool to try to get an idea of the spatial distribution of their accounts or potentials. Using CartoDB maps such as the one shown above can save a lot of time in planning out a sales visit schedule for the week. The more time saved in planning the calls means more time selling.
Purchasing application: Visualizing the geographical location of suppliers
This example shows how a hypothetical company located in Elkhart, Indiana, can use their supplier location data and the historic spend volume from each and use it to plan for cost reductions, for example, in freight costs. The map (based on fictitious data) shows supplier locations as well as the spend amount with each of them (represented by the size of the bubble).
A buyer looking at this map can try to arrange for freight consolidation from a certain area by timing the delivery schedules to ensure that the optimum number of shipments can be picked up from suppliers within a certain geographic area on the same day.
Additionally, graphical data like this may identify suppliers who are located quite a distance away from their facility, hence additional freight costs. A freight consolidation exercise as explained above may help reduce these costs. Now, If that supplier happened to be the only one in that particular geographic area, then the buyer would be well served to explore the areas with a high density of supplier (from the map) to find an alternate supplier.
Conclusion
Data visualization is a powerful tool and is not just limited to Excel graphs and charts. CartoDB and similar applications provide some powerful technology to assist people from all functions to benefit from the use of visual data. A couple of very simple examples was presented to make that point.
Happy Visualization!!
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