Nonprofit Organizational Assessment

order for a company to posture and focus their efforts effectively across the breadth of
their customer base. They must analyze and understand the products in demand or
have the potential for high demand, predict customers' buying habits in order to promote
relevant products at multiple touch points, and proactively identify and mitigate issues
that have the potential to lose customers or reduce their ability to gain new ones.
Analytical customer relationship management can be applied throughout the customers'
lifecycle (acquisition, relationship growth, retention, and win-back). Several of the
application areas described below (direct marketing, cross-sell, customer retention) are
part of customer relationship management.
Child Protection
Over the last 5 years, some child welfare agencies have started using predictive
analytics to flag high risk cases. The approach has been called "innovative" by the
Commission to Eliminate Child Abuse and Neglect Fatalities (CECANF), and
in Hillsborough County, Florida, where the lead child welfare agency uses a predictive
modeling tool, there have been no abuse-related child deaths in the target population as
of this writing.
Clinical Decision Support Systems
Experts use predictive analysis in health care primarily to determine which patients are
at risk of developing certain conditions, like diabetes, asthma, heart disease, and other
lifetime illnesses. Additionally, sophisticated clinical decision support
systems incorporate predictive analytics to support medical decision making at the point
of care. A working definition has been proposed by Jerome A. Osheroff and
colleagues: Clinical decision support (CDS) provides clinicians, staff, patients, or other
individuals with knowledge and person-specific information, intelligently filtered or
presented at appropriate times, to enhance health and health care. It encompasses a
variety of tools and interventions such as computerized alerts and reminders, clinical
guidelines, order sets, patient data reports and dashboards, documentation templates,
diagnostic support, and clinical workflow tools.
A 2016 study of neurodegenerative disorders provides a powerful example of a CDS
platform to diagnose, track, predict and monitor the progression of Parkinson's
disease. Using large and multi-source imaging, genetics, clinical and demographic data,
these investigators developed a decision support system that can predict the state of
the disease with high accuracy, consistency and precision. They employed classical
model-based and machine learning model-free methods to discriminate between
different patient and control groups.
Similar approaches may be used for predictive diagnosis and disease progression
forecasting in many neurodegenerative disorders
like Alzheimer’s, Huntington’s, amyotrophic lateral sclerosis, and for other clinical and
biomedical applications where Big Data is available.
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