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CIO Applications Weekly Brief

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Editor's Pick (1 - 4 of 8)
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Lies, Damn Lies, and Data Visualization

Lies, Damn Lies, and Data Visualization
Douglas Duncan, CIO, Columbia Insurance Group

Predictive Analytics in Healthcare: It's Not Happening

Predictive Analytics in Healthcare: It's Not Happening
Kirk Kirksey, VP & CIO, UT Southwestern Medical Center

Predictive Analytics Key Component of Customer Experience Management

Predictive Analytics Key Component of Customer Experience Management
Richard Barton, CIO, American Management Association

Predictive Analytics in Higher Education

Predictive Analytics in Higher Education
Linda Hartford, CIO, Northeast Wisconsin Technical College

Trusted Data in a Post-Pandemic Era

Trusted Data in a Post-Pandemic Era
Peter Serenita, Chief Data Officer, Scotiabank

Revitalizing Data Collection with Next- Gen Technology

Revitalizing Data Collection with Next- Gen Technology
Marci Augustine, Director, Business Intelligence & Analytics, Xo Group Inc.

The Numbers Game: Making Hospital Data User-Friendly

The Numbers Game: Making Hospital Data User-Friendly
William Feaster, M.D., VP, Chief Health Information Officer, Choc Children’s

Predictive Analytics in the Insurance Industry

Predictive Analytics in the Insurance Industry
Hongyuan Wang, PhD & MAS, Director of Predictive Analytics, Data and Analytics, Employers

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Know how to Tackle these Major Predictive Analytics Challenges

By Joe Phillip, CIO Applications | Tuesday, March 09, 2021

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Since risk management can often be a small department, approval for large acquisitions, such as data or predictive analytics software, can be challenging to obtain. Risk managers should define a data analytics budget by calculating a system's ROI to resolve this.

Fremont, CA: Predictive analytics, like most software or techniques, can create difficulties or issues for businesses, which are often not noticed until the technology fails to produce the expected results. Often these issues may occur from bad planning or unreasonable expectations, but there are some simple ways to ensure that these problems do not happen. These obstacles, however, are easily solved or prevented.

Here are four ways to solve predictive analytics challenges:

Skill Shortage

top predictive analytics consulting companies

It is critical that individuals in the team understand the capabilities of technology and how to leverage them. They will expand their positions by helping to improve the strengths of your team. During the recruiting process, you should also ensure that analytical skills are available and provide an easy-to-use analysis framework. It also means that irrespective of their abilities, anyone can use the framework.

See Also: Top Risk Management Solution Companies

Budget Restrictions

Since risk management can often be a small department, approval for large acquisitions, such as data or predictive analytics software, can be difficult to obtain. Risk managers should define a data analytics budget by calculating a system's ROI (Return on Investment) to resolve this and make a clear business case for the advantages that can be gained. The storage costs of holding vast volumes of data should also be taken into account, and how best to solve this.

Lack of Organizational Support

Without organizational aid and support, data analytics cannot be useful. This is across all parts of the company-from risk managers to data submitters. Organizations should prioritize all facets of the organization's risk control and education on the system's benefits.

Lack of Strategy

Understanding your priorities and goals will help you determine which software is most appropriate for your business. It will complement the priorities and, while trying to ensure that resources are placed in ways to achieve the plan, help keep this purpose in mind. Analysis, as well as putting together the right data sources, should be carried out. Before introducing the latest technology, you can also do some informal experiments (pilot studies) to understand the technology and how it can be used in real-world business situations.

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