Challenge Analytical CRM Is The Process Through

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Challenge: "Analytical CRM" “Analytical CRM is the process through which organizations transform customer-related data into actionable insight for either strategic or tactical purposes." -Q1) Depict an analytical application (app) for controlling COVID-19, by designing (and explaining) an analytical detailed localized mobile scenario (or scenarios), in a diagram interface schema (i.e., screens), from analytical extrapolated feature functionality generically learned by you from a customer relationship management (CRM) Analytical Software (not sales or service) Vendor chosen by you*.

Hints: , , [email protected], and CRM.com might be Vendor sources for you You cannot choose a CRM Analytical Vendor if already chosen (and posted) by another student. * You cannot choose any CRM Sales Force Automation (SFA) Vendor if already reviewed by other students in Student Critique 2.

Format: 3 Pages (Double-Spaced) References: 5 References dated 2020 Challenge: "Privacy Issues " (Buttle & Maklan, Chapter 12, pps. ) -Q2) Explain implications on privacy from COVID-19 current state-of-the-art management tools, as interpreted by government officials in privacy regulations (or non-privacy regulations) in countries with democratic governments (e.g., European Union vs. United States) vs. non-democratic governments (e.g., People's Republic of China). Hint...

Paper For Above instruction

Introduction

The emergence of COVID-19 has necessitated innovative approaches to pandemic control, leveraging data analytics through Customer Relationship Management (CRM) systems. While originally designed to manage customer data and interactions, analytical CRM applications can be repurposed to monitor, analyze, and respond to pandemic-related data. This paper presents a detailed conceptualization of an analytical CRM-based mobile application aimed at controlling COVID-19 at a local level, along with an exploration of privacy implications influenced by differing governmental privacy frameworks.

Design of an Analytical CRM Application for COVID-19 Control

The proposed application, termed "COVID-19 Local Tracker," integrates advanced analytical features derived from traditional CRM software functionality. The core objective is to assist public health authorities and local communities in tracking infection spread, managing contact tracing, and deploying targeted interventions.

Application Features and Interface Schema

The app's design comprises several interconnected screens, each enabling specific analytical functionalities:

1. Dashboard Screen: Provides real-time visualization of COVID-19 hotspots via heat maps, infection rates, and resource allocations. The visualization is powered by GIS data integrated with anonymized user location data, reflecting analytical extrapolation from CRM customer data models.
2. Contact Tracing Screen: Allows users to receive alerts if they have been in proximity to confirmed cases based on aggregated location data. Analytical algorithms assess the risk levels by integrating mobility data with infection timelines, akin to CRM segmentation techniques.
3. Risk Assessment & Alerts Screen: Presents personalized risk levels based on demographics, health status, and recent activities. Uses predictive analytics similar to customer lifetime value modeling in CRM to estimate the likelihood of exposure or severe outcomes.
4. Data Entry & Feedback Screen: Enables users to provide health updates and report symptoms, which are analyzed to detect emerging clusters or "hot" areas requiring intervention.
5. Resource Allocation Screen: Visualizes local healthcare resource availability—such as hospital beds, ventilators—and predicts future needs using trend analysis, similar to CRM forecasting modules.

The schema facilitates data-driven decision making, utilizing location intelligence, predictive analytics, and real-time data visualization, adapted from CRM analytical functionalities.

Extrapolated Analytical Functionalities

From CRM analytical software, this app extrapolates features like customer segmentation, predictive modeling, and behavior analytics—here applied to populations for health risk profiling, disease spread forecasting, and resource planning. For example, demographic segmentation aids targeted messaging, while predictive models anticipate outbreak trajectories, enabling proactive measures.

Privacy Issues and Privacy Regulations

The deployment of COVID-19 tracking systems raises significant privacy concerns, especially regarding data collection, sharing, and user consent. Governments worldwide differ markedly in their approach, heavily influenced by political frameworks and cultural norms.

In democratic nations like the European Union, privacy regulations such as GDPR impose strict constraints on data collection and processing. These frameworks mandate transparency, consent, data minimization, and user rights, significantly limiting government access to personal data and emphasizing individual privacy (De Vynck, 2020). The EU emphasizes privacy preservation, which complicates large-scale contact tracing but fosters public trust.

Conversely, in the United States, privacy regulations are less comprehensive at the federal level, resulting in a patchwork of state laws. The emphasis tends to be on public health benefits over individual privacy, with some states permitting voluntary tracing apps and less restrictive data sharing (Webb, 2020). While this facilitates rapid deployment, it raises concerns about data misuse and lack of transparency.

In non-democratic regimes such as China, authorities leverage extensive surveillance infrastructure to implement mass contact tracing with little regard for individual privacy. These systems utilize facial recognition, mobile data, and social media monitoring to enforce quarantine measures and monitor citizens in real-time (Charlemagne, 2020). While potentially more effective in curbing outbreaks, they pose profound privacy and human rights challenges.

The divergence in approaches reflects underlying political values—public health prioritization with minimal privacy safeguards in authoritarian regimes, versus privacy rights protections in democratic societies. These differences have long-term implications for civil liberties and international trust in health data practices.

Conclusion

The integration of CRM analytical functionalities into COVID-19 control applications exemplifies the versatility of data-driven systems in public health. While technologically promising, such applications intensify privacy debates, heavily influenced by governmental regulatory environments. Democratic nations emphasize privacy protections, often limiting data utility but safeguarding individual rights, whereas authoritarian states leverage surveillance for holistic control, often at the expense of privacy. Balancing these interests remains a key challenge for policymakers and technologists alike.

References

• De Vynck, G. (2020). The Trouble with Tracing Applications (Apps). Bloomberg Business Week, May 25, pp. 16-18.
• Webb, A. (2020). A Question of Privacy vs. the Pandemic. Bloomberg Business Week, May 25, p. 64.
• Charlemagne, D. (2020). COVID-19 Is Bad News for Europe's Privacy Panjandrums. The Economist, April 25, p. 44.
• European Data Protection Board. (2020). Guidelines on Data Protection and Contact Tracing. EDPB Publications.
• Shen, J., et al. (2020). Privacy-Preserving Contact Tracing Frameworks in Pandemic Responses. Journal of Public Health Policy, 41(4), 461-474.
• Golin, G., & Boughzala, I. (2021). Implementing Data Analytics in Public Health: Challenges and Opportunities. International Journal of Information Management, 56, 102263.
• Li, F., et al. (2020). Mobile Data in Epidemic Control: Privacy and Utility. Nature Communications, 11, 2547.
• Chen, Y., & Zhao, D. (2020). Big Data and Privacy in COVID-19 Contact Tracing. IEEE Transactions on Big Data, 8(4), 982–987.
• Johnson, C. Y., & Mittal, S. (2020). Surveillance and Public Health in the Age of COVID-19. Surveillance & Society, 18(3), 369-377.
• European Data Protection Supervisor. (2020). Recommendations on Contact Tracing Technologies. EDPS Publications.