Modern data analysis, made possible through innovations in technology and software development from companies like BairesDev, is helping public service professionals in many fields to improve the world. With data insights, these professionals can evaluate the tough issues they face and figure out how best to solve them.
Here are just a few of the ways professionals across a range of industries are using data analytics to enhance decision-making and achieve positive results.
Healthcare providers, researchers, and administrators are tapping into the huge volume of health-related data that exists to help patients in a variety of ways:
– Disease prevention
Doctors are using results from data analysis to better recognize patterns, identify risks, and recommend disease prevention strategies. In the hospital setting, providers can predict and prevent infections before symptoms even appear. Data from wearable smart devices provide the basis for personalized plans to prevent chronic conditions.
– Remote services
Medical facilities use smartphone technology to transmit data directly into Electronic Health Records to track changes and identify warning signs early on. A recent HealthTech article noted, “An effort to use patients’ wireless blood pressure cuffs to transmit readings to their Apple Watches is the first of its kind in the U.S. to help patients manage a chronic condition.”
Doctors use this approach with patients suffering from life-threatening conditions to alert medical staff immediately when significant declines occur. Patients use remote in-home monitoring after surgery to prevent complications and help with pain management.
To reduce the rate of diagnostic errors, computers use machine learning to interpret medical images, like MRIs, x-rays, and mammograms and accurately detect problems. Additionally, scientists use data from large numbers of people to identify meaningful patterns between early symptoms and the emergence of diseases, informing future diagnostic practices.
Government officials use data analysis to assess current conditions, promote good policymaking, and determine efficient resource allocation. Huang Zhongwen, director of Digital Planning Lab at the Urban Redevelopment Authority in Singapore, reported, “Geospatial and data analytics allow our planners to gain deeper insights into current and future scenarios and to plan in a more precise manner to cater to the needs of the population.”
This approach helps governments create optimal delivery of public programs and services, then accurately measure success, including in the areas of:
– Transportation and traffic monitoring
– Poverty relief efforts
– Education services
– Pollution prevention and waste management
– Recreation offerings
Staff at nonprofit organizations typically use data analysis for fundraising, volunteer management, and communications. In fundraising, donor analytics help improve the effectiveness of campaigns by not only analyzing past giving history but also using machine learning to predict future giving through algorithms.
Volunteer managers analyze data to better understand the skills and needs of volunteers, schedule volunteer time more effectively, and track volunteer work efficiency and satisfaction.
Communications professionals within organizations identify donation and volunteer patterns to more thoroughly understand and respond to supporters. They also personalize communication (emails, letters, social media, etc.) to build stronger long-term relationships.
One of the hottest issues in the energy industry is the transition to more renewable resources. In the past, energy professionals found it difficult to determine just how much non-renewable energy would be needed to fill in the gaps resulting from the variable nature of wind and solar power.
As demonstrated in the following examples, the industry can now use artificial intelligence (AI) to analyze data and accurately predict well ahead of time how much electricity renewable sources will generate in particular locations.
IBM collaborated with the U.S. Department of Energy to harness its AI engine, Watson, to promote cleaner power. The resulting solar and wind forecasting technology, Watt-Sun, now predicts solar and wind conditions 15-30 days ahead, and is 50% more accurate than the next best solar forecasting model.
Deep-Mind, a British AI company owned by Google, applied machine learning algorithms to Google’s wind power capacity in the Midwest. Analyzing weather forecasts and historical turbine data, the program predicted wind power output 36 hours ahead. Over one year, this effort boosted the economic value of wind energy by around 20% compared to a baseline scenario.
Xcel has significantly lowered its wind power forecasting errors by using machine learning algorithms. This action has saved its customers $60 million since 2009 and reduced CO2 emissions from non-renewable sources by over a quarter-million tons per year.
5. Urban Planning
Urban planners use data analytics to gain insights into current and future trends so they can plan accordingly. This approach helps them evaluate choices by accurately predicting future levels of need for infrastructure, parking, utilities, water supply, housing, and amenities. Increasingly, planners utilize data from Internet of Things devices to create smart cities with optimal resource management.
Planners study usage patterns of social services (e.g., elder care, healthcare, childcare, schools) to identify areas they need to improve and gaps they need to fill. Data analysis can help them answer questions like: How often is a facility used? Why do people choose one facility over another? Where are facilities located in relation to the people they serve?
Public service professionals throughout a range of industries, such as healthcare, energy, and urban planning are making innovative use of data analytics. This approach enables them to successfully take on big challenges and help more people live better lives.