Many of us take for granted our ability to access not just maps and directions, but real time traffic, accident and road construction alerts on our smartphones. And if the jam is too bad, another layer reveals the closest sources of ice cream, complete with photographs and ratings that tell us whether the local favourite is worth driving beyond the off-ramp.
We make a decision - to exit for ice cream or stick it out in traffic - in a matter of seconds without needing to interpret a column of traffic flow numbers - the thick red line tells us everything we need to know.
Search “visualisation” on the Internet and you can fritter away hours on the latest mash-up--data as art, statement, experimentation. But for business, the power of visualisation is to make sense of the disparate, often unstructured data - the “Big Data” you keep hearing about - to inform decisions, indicate actions, and create shared understanding.
How can organisations mine the flotsam constantly generated by sensors, blogs, social media, public agencies, and third-parties, not to mention theirown operations, to influence consumer behaviour or calculate risks or optimize pricing? What can the relationships buried in the data tell an organisation about managing its supply chain or retaining talent?
The possibilities are as wide as the questions an organisation needs to answer.
If lack of data isn’t a problem, a lack of imagination might be. Exploiting data for business intelligence requires some creativity and a willingness to experiment. Luckily, there are a number of organisations already experimenting with innovative visualisations to manage their own operations and understand the world around them.
As hurricane Irene was bearing down on the US in 2011, Walmart combined information about curfews and road closures culled from social media with storm maps from the National Weather Service and GPS data from its own trucks to prepare for the storm’s impact on operations and devise a logistics strategy for response and recovery.
This type of application might also identify instances of food-borne illness, allowing companies and public health officials to work backwards from the spread to the retail location to the distributor and so on. Similarly, a company could monitor sentiment, product complaints, or safety issues to identify trends and take action before a crisis develops.
Global supply chains are now visible, to competitors and consumers, who are increasingly invested in the environmental, ethical, and health attributes of the products they use.
Sourcemap, a directory of crowd-sourced product supply chains, allows users to piece together localized observations and independent research to recreate global commerce paths, providing an up-to-date picture of any product’s components and its path from input through manufacture and distribution. Seeing their part in the bigger picture may cause participants to renegotiate roles, eliminate certain paths, or control critical dependencies.
A good visualisation builds on familiarity and intuitiveness to transform things with which we are all familiar, but not too fond, such as the pages-long list of results from a search engine.
The US National Science Foundation recently funded a project to depict citation patterns in scientific journal databases to help researchers and funders better understand patterns of scientific inquiry, controversy and breakthrough occurring at any given time in a way not possible in traditional search.
Even for people typically comfortable with a large amount of data, such as stock traders, visuals can simplify complex relationships. The StockTouch app transforms the classic ticker into a heat map that displays top US and global companies and provides the additional layers of statistics, performance graphs, and news articles about the stock.
Maps are perhaps the most common and instantly recognizable visualisation. With open-source tools and publicly-available data, users can create neighbourhood-level maps based on a variety of parameters. For instance, the Neighborhood Visualizer generates heat maps that depict material and energy use within a city; similar thinking could be applied to a factory or office complex.
Working off the Ushadi platform, citizens around the world, from Dublin to Lagos, New York to Moldova, use mobile phones to report pressing problems - infrastructure, crime, corruption, pollution - in real-time with geographical context.
The resultant maps empower employees to address specific instances of the target problem and enable government, policy makers, and the public to discuss issues as they exist in reality. Other visualisations draw from the vast US Census data to allow users to compare various attributes at a county level and make correlations from their own observations of other data (for example, income, age, education, household size.)
In the US, geospatial predictive analytics help law enforcement use drug arrests, equipment seizures, and reports of toxic dumping to track and predict drug activity. Similar models are being explored for auto theft and gang activity.
More efficient processing and less expensive technology are making a different type of visualisation possible: reality augmented with layers of relevant data. Applications like Wallit, which lets user’s layer messages over a smartphone’s camera feed, are primarily social.
A similar tool could enable a transit employee to scan a crowd and identify passengers without a valid payment or a technician to view schematics, prior repair notes, and real-time use characteristics as she points her phone ata turbine, leaving behind “virtual graffiti” notes for the next technician.
Layers of real-time information can provide situational context for any response organization: whether that be emergency crews adapting to road closures in a natural disaster or a corporation adapting to consumer sentiment after a public relations gaffe.
Visualisation is no longer the exclusive domain of some special group of data wizards. A number of tools such as D3 and Spotfire put the power of visualisation for business intelligence at your fingertips. Once an organisation has developed a model to describe business performance, real-time data can feed it, helping drive better decisions on an on-going basis.
Data visualisation is not about dashboards. Or charts. Or more spreadsheets and slide presentations. It is about combining data - data the organisation owns and an enormous amount it doesn’t - in new ways. It is the increasing volume, velocity and value of Big Data that makes the ability to visualise data, and to explore its relationships to other data, imperative.
Eric Openshaw is the vice chairman and US Technology, Media & Telecommunications leader at Deloitte. JR Reagan is a principal at Deloitte and leads the HIVE (Highly Immersive Visual Environment).