Zeitgeists, wind gusts and the analytics of environmental turbulence

Big Data Evangelist, IBM

The environment within which our lives transpire is always one part nature and one part nurture. In other words, it’s a tangled, chaotic fabric of interacting geophysical and social forces. As we confront natural forces—such as the weather—we often find their risks exacerbated by the patterns of living that our species have established on this planet.

For example, we build our cities on or near oceans, rivers and lakes, and we build dams, levees, dikes, seawalls and other structures to hold it all back. So when a major weather event with the force of, say, Hurricane Katrina breaches those barriers and inundates our cities, we need to recognize that we’ve unwittingly placed our civilization in harm’s way. The same principle applies, even more ominously, to worldwide risks from global warming, which is—as many scientists now agree—the product of human-caused greenhouse effects in the atmosphere.

Weathering the politicization of environmental issues

As we consider the role of nurture—in other words, social sentiment, beliefs and practices—in perpetuating environmental risk factors, clearly the impacts may swing either way: toward mitigating the risks or worsening them. When environmental issues such as global warming become politicized to the point that constructive remedies are difficult to push through, we can’t help but notice that social sentiment—also known as zeitgeist—is itself a type of weather. And just like the rain and wind, this type of weather is not entirely under anyone’s control.

Still, we can mitigate those sentiment-driven risks in our business plans and daily lives. And we can do it in much the same way that we purchase flood insurance and weatherproof our houses, for example, to keep the natural risks at bay.

From a risk-mitigation standpoint, the analytics of environmental turbulence are well established, though the underlying data science challenges of modeling multivariate turbulence remain daunting. At their heart, the requisite data scientific approaches involve predictive modeling of environmental data, incorporate steady streams of real-time data updates and extrapolate past trends into likely future scenarios. Increasingly, the weather data feeding these analyses come from Internet of Things sensor data in the cloud, and the sentiment data from an equally awesome fire hose: social media such as Twitter.

Influencing mission-critical applications with weather and social data

Various industries are leveraging the analytics of intertwined weather and social data in mission-critical applications.


Insurers can integrate weather and social sentiment data to address underwriting challenges in the insurance industry. For example, statistical models can help quantify the likely effects of severe weather on claims. These analytics can also predict weather impacts on call center volumes, real-time and expected claim activities, required staffing and supply chain strategies to provide onsite customer service and proactive customer alerting. Also, tapping into weather and social data enables insurers to monitor social media discussions about perceived lapses in the company’s customer service on weather-related claims. sector

Social sentiment data can illuminate popular awareness of weather-related risk factors, and indicate the extent to which government-orchestrated emergency planning, disaster preparedness and response campaigns in the public sector are likely to mitigate the most salient threats to public safety. Considering how the public is responding or likely to respond to various weather scenarios has a strong bearing on the optimal deployment of fire, police, hospital and other key services.

Likewise, integration of social and weather data analytics can drive which sorts of public safety messages and hyperlocal event-management alerts should be broadcast to which audiences prior to and during adverse conditions. The analyses can also be used to predict weather-related demand on public resources, services and infrastructure—for example, water, roadways and sanitation.


Retailers can combine weather and social data analytics to forecast the impact of seasons, storms and other atmospheric conditions on consumer demand. Likewise, these analytics can prove invaluable in gauging the downstream weather impact on suppliers, shippers and other components of the retail value chain, which can sour sentiment by impacting service to those customers who brave the elements to visit brick-and-mortar outlets. Weather data analytics can even affect business by triggering subtle shifts in customer sentiment, as when prolonged heat waves increase general levels of listlessness and fatigue.

Commissioning direction for a new cloud services group

Recognizing the global importance of on-demand analytics for extracting actionable intelligence from weather, social and other environmental signals, IBM recently established the Insight Cloud Services (ICS) group, acquired the digital assets of The Weather Company and further underlined its partnership with Twitter. And in acknowledging that environmental turbulence—often the result of tangled weather and social forces—affects every industry in various ways, IBM has chartered the new group with several initiatives: 

  • Providing customers with easy-to-use, prebuilt cloud services that don’t require deep domain knowledge on weather, social and other environmental phenomena
  • Helping clients integrate external data with their own data to render the environmental factors that are important to them to use without complexity
  • Offering specialized analytical models to enable explorations of environmental context, detect more weather and social signals, make high-quality predictions and take enhanced actions for risk mitigation and other purposes
  • Enabling users to easily embed weather, social and other environmental data and insights into mobile apps, enterprise applications and business processes
  • Accelerating discovery of unprecedented weather, social and other environmental insights in unstructured, streaming data of all sorts
  • Delivering repeatable IBM Bluemix industry solutions that leverage environmental data sets, including but not limited to sourced weather data by IBM and The Weather Company and Twitter-sourced social media chatter 

For those interested in learning more about ICS and how it can help address the risks of a turbulent physical or social environment, explore the ways to address these challenges through on-demand access to weather, social and other data-driven insights.