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BUS/721 v8
Data Table Worksheet
BUS/721 v8
Page 2 of 2
Data Table Worksheet
Identify 3-5 data sources necessary to execute the Leadership Optimization Business Plan, due in Week 8. Then,
complete the prompts in each Data Source section below.
Ensure each response is
thorough and complete
supported with rationale
edited carefully for grammar, punctuation, and spelling errors
formatted according to course-level APA guidelines (where applicable)
cited correctly (where applicable)
Review this list of guidelines for each prompt.
Prompt
Guideline
Overview
Briefly
describe the data source you will use. Be sure to explain how you will obtain the data.
Examples:
survey
test instrument
database
experiment
observations
person-to-person transactions
Note: Include the formal name of the data source, if applicable.
Data Measurement
Categorize each data source as
nominal (categorical numbers),
ordinal (ex: Likert scale),
interval (numerical ranges), or
ratio (continuous numbers). Justify your response.
Then,
describe how each data point will be measured.
Ex: If you used a survey as a data source, what kind of data will be extracted?
People
Describe the person/people/organization who own the data.
Note: This may include entities who own copyrights on a survey or test instrument.
Include relevant details, opportunities, or challenges from the list below:
Data security
Data privacy
Data richness
Data consistency
Data currency
Data validity
Data relevancy
Processes
Describe how the data will be captured or extracted. Include relevant details, opportunities, or challenges from the list below:
Data security
Data privacy
Data richness
Data consistency
Data currency
Data validity
Data relevancy
Systems
Explain the role of BI and ERP systems in the data collection, analysis, and storage. Include relevant details, opportunities, or challenges from the list below:
Data security
Data privacy
Data richness
Data consistency
Data currency
Data validity
Data relevancy
Data Source 1
Leadership Optimization Business Plan
In order to execute the Leadership Optimization Business Plan, the business may need to gather data from various sources. Some potential data sources could include:
i. Employee performance metrics: When optimizing leadership, it is essential to evaluate the performance of employees (Brungardt et al., 2006). Gathering individual and team performance data can help identify areas for improvement and opportunities for growth.
ii. Employee engagement surveys: Employee engagement is a essential factor in leadership optimization. Surveys can help assess employees’ engagement and identify potential improvement areas.
iii. Customer feedback: Customer feedback can provide valuable insights into how the organization is performing and where there may be areas for improvement (Brungardt et al., 2006). Gathering customer satisfaction and feedback data can help leaders make informed decisions about optimizing their operations.
iv. Financial data: Financial data can help leaders understand how their organization performs financially and identify areas for cost savings or revenue growth.
Industry benchmarks: Understanding how the organization compares to others within the same industry (Brungardt et al., 2006). Gathering data on industry benchmarks can help leaders detect areas where they may need to improve to remain competitive.
Overview
The data sources employed for the Leadership Optimization Business Plan are:
Employee engagement survey: This design measures employee engagement levels, job satisfaction, and overall organizational culture (Brungardt et al., 2006). The survey will be administered online to all employees, and the responses will be collected and analyzed anonymously.
Performance metrics database: This database contains performance metrics for each employee, including sales figures, customer satisfaction scores, and productivity levels (Brungardt et al., 2006)—the data extraction from the company’s existing performance management system.
Leadership competency test: The designed test assesses the leadership competencies of the company’s managers and executives. The test will take place through an online service, and the results will be collected and analyzed anonymously.
Organizational climate Observations: The administration of observations by trained observers assessing the overall organizational climate, including communication patterns, leadership styles, and employee engagement levels (Brungardt et al., 2006). The observations will take place over several weeks, and the data will be recorded and analyzed.
Data Measurement
Their type of measurement categorizes the categorization of the data sources:
Employee engagement survey: This survey will yield ordinal data. The survey will use a 5-point Likert scale to measure employee engagement levels, job satisfaction, and organizational culture. The responses will be analyzed to identify trends and areas for improvement (Brungardt et al., 2006).
Performance metrics database: This database will yield interval or ratio data, depending on the measured metrics (Brungardt et al., 2006). For example, sales figures would be ratio data, while customer satisfaction scores might be interval data. The data points will be measured using established performance metrics and recorded in the database.
Leadership competency test: This test will yield ordinal data. The test will use a range of multiple-choice and short-answer questions to assess the leadership competencies of the company’s managers and executives (Brungardt et al., 2006). The responses will be analyzed to identify strengths and weaknesses in leadership skills.
Organizational climate observations: These observations will yield ordinal data. Trained observers will use a standardized observation checklist to record their observations of the organizational climate (Brungardt et al., 2006). The responses will be analyzed to identify areas where the organizational climate can be improved.
People
Depending on the source, the person/people/organization owning the data will vary. Here are some examples:
Surveys: The person/organization who conducted the survey will own the data. This data may include academic researchers, consulting firms, or the organization. Depending on the survey design and distribution, the data may be subject to copyright or intellectual property laws. Challenges related to data ownership and management may include ensuring data security and privacy, mainly if the survey includes sensitive information (Brungardt et al., 2006). Additionally, ensuring data validity and relevancy will be crucial to ensure the survey results are reliable and valuable for the Leadership Optimization Business Plan.
Databases: The organization itself will own the data collected in its databases. The data may be subject to legal and regulatory requirements, such as GDPR or HIPAA, depending on the nature of the data (Brungardt et al., 2006). Challenges related to data ownership and management may include ensuring data consistency and currency, primarily if the data utilization is for financial or performance reporting. Additionally, ensuring data security and privacy will be crucial to protect sensitive financial or employee data.
Person-to-person transactions: The organization will own the data collected through person-to-person transactions, such as interviews, focus groups, or observations. Challenges related to data ownership and management may include ensuring data privacy and validity, especially if the data is subjective or based on personal opinions (Brungardt et al., 2006). Data richness and relevancy will be crucial to capture a comprehensive picture of employee behavior and leadership practices.
Observations: The organization will own the data collected through observations of employee behavior and work processes (Brungardt et al., 2006). Challenges related to data ownership and management include ensuring data consistency and validity, mainly if different observers collect the data. Additionally, ensuring data currency and relevancy will be crucial to capture a timely and accurate snapshot of employee behavior and work processes.
Experiment: The organization will own the data collected through experiments, such as A/B testing of leadership strategies. Challenges related to data ownership and management may include ensuring data validity and relevancy, especially if the experiment involves a small sample size or limited duration (Brungardt et al., 2006). Ensuring data security and privacy will be crucial to protecting sensitive employee or customer data involved in the experiment.
Processes
The capturing or extracting data processes will vary depending on the data source. Here are some examples:
Surveys: Data attainment through a survey instrument, administered online, in person, or through the mail, and the data may be entered into a database or analyzed using a survey software tool. Opportunities for data richness may include open-ended questions, while challenges related to data consistency may include differences in interpretation or response bias (Peng et al., 2019). The survey instrument may include consent forms or anonymized response options to ensure data security and privacy for the intended users. Data validity and relevancy will ensure that the survey results are reliable and valuable for the Leadership Optimization Business Plan:
Databases: Data will be extracted from the organization’s databases using a query or data extraction tool. Opportunities for data richness include using multiple data sources or the ability to query large datasets. Challenges related to data consistency may include differences in data formats or data quality. Data security and privacy will be crucial to protecting sensitive financial or employee data (Peng et al., 2019). Additionally, ensuring data currency and relevancy will be crucial to capture a timely and accurate snapshot of employee behavior and leadership practices.
Person-to-person transactions: Data captured through interviews, focus groups, or observations of employee behavior. Opportunities for data richness may include the ability to probe for more detailed responses or to observe nonverbal behavior (Peng et al., 2019). Challenges related to data consistency may include differences in interpretation or observer bias. Data privacy and validity will be crucial to protecting the confidentiality of the interviewees or focus group participants.
Observations: Data will be captured by observing employee behavior and work processes. Opportunities for data richness may include capturing real-time data or observing subtle changes in behavior (Peng et al., 2019). Challenges related to data consistency may include differences in interpretation or observer bias. Data privacy and validity will be crucial to protecting the confidentiality of the employees observed.
Experiment: Data captured through an experiment, such as A/B testing of leadership strategies. Opportunities for data richness include controlling confounding variables or collecting multiple data types. Challenges related to data validity may include the need to design the experiment carefully to ensure that the results are reliable and relevant to the Leadership Optimization Business Plan (Peng et al., 2019). Ensuring data security and privacy will be crucial to protecting sensitive employee or customer data involved in the experiment. Additionally, ensuring data currency and relevancy will be crucial to capture a timely and accurate snapshot of the effectiveness of the tested leadership strategies.
Systems
BI (Business Intelligence) and ERP (Enterprise Resource Planning) systems play an essential role in data collection, analysis, and storage (Peng et al., 2019). Here are some details, opportunities, and challenges related to data security, privacy, richness, consistency, currency, validity, and relevancy:
Data collection: BI systems afford powerful tools for data analysis, such as data visualization, dashboards, and predictive analytics. These tools can help identify patterns, trends, and insights from the data. The opportunities for data richness and relevancy are high as these tools can help generate actionable insights relevant to the business needs. However, ensuring data validity and consistency can be challenging as different data sources may have different levels of accuracy or completeness (Peng et al., 2019). Data security and privacy are critical as these insights can contain sensitive business data.
Data analysis: BI systems provide powerful tools for data analysis, such as data visualization, dashboards, and predictive analytics. These tools can help identify patterns, trends, and insights from the data. The opportunities for data richness and relevancy are high as these tools can help generate actionable insights that are relevant to the business needs. However, ensuring data validity and consistency can be a challenge as different data sources may have different levels of accuracy or completeness (Peng et al., 2019). Ensuring data security and privacy is critical as these insights can contain sensitive business data.
Data storage: BI and ERP systems provide centralized data storage and management, which can help ensure data consistency and currency. The opportunities for data security and privacy are high as these systems provide robust security and access control mechanisms to protect sensitive business data (Peng et al., 2019). However, ensuring data validity and relevancy can be challenging as different data sources may have different levels of relevance or timeliness.
References
Brungardt, C., Greenleaf, J., Brungardt, C., & Arensdorf, J. (2006). Majoring in leadership: A review of undergraduate leadership degree programs. Journal of Leadership Education, 5(1), 4-25.
Peng, H., Li, J., Gong, Q., Song, Y., Ning, Y., Lai, K., & Yu, P. S. (2019). Fine-grained event categorization with heterogeneous graph convolutional networks. arXiv preprint arXiv:1906.04580.
Copyright 2021 by University of Phoenix. All rights reserved.
Copyright 2021 by University of Phoenix. All rights reserved.
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BUS/721 v8
Data Analysis Worksheet
BUS/721v8
Page3of3
Data Analysis Worksheet
Write a response to each prompt below.
Ensure each response is
thorough and complete
supported with rationale
edited carefully for grammar, punctuation, and spelling errors
formatted according to course-level APA guidelines (where applicable)
cited correctly (where applicable)
|
Prompt 1: For each item below, |
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A. Data related to People: To support the Leadership Optimization Business Plan, data related to people should include market trends, measurement of performance marketing campaigns, employee engagement levels, workflows to improve employee engagement, turnover rates, skill and knowledge gaps to streamline operations, performance metrics, and diversity and inclusion statistics (Stedman, 2023). This data will provide insight into the organization’s workforce, including strengths and areas of improvement, and help identify opportunities for employee development and retention (Falletta & Combs, 2021). |
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B. Data related to Processes: The data related to processes should include key performance indicators (KPIs) such as cycle time, process efficiency, and process effectiveness. Additionally, the data must identify and communicate the business value by measuring the value of data assets, determine and sustain a data catalog, and act as a catalyst for changes to the business model (Goasduff, 2016). It should also include data on process defects, quality metrics, and customer satisfaction levels. This data will help in identifying areas for process improvement, bottlenecks, and waste reduction. |
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C. Data related to Systems: Data related to systems should include prescriptive analytics that recommends conceivable outcomes and results in actions that are probable to maximize key business metrics to optimize and supports to achieve the best |
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Prompt 2: |
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The PPT framework regards how the three aspects interrelate. Processes make these aspects work more efficiently. Technology supports workforces in doing their tasks and also assists in automating processes (Plutora.com, 2022). Equally, data and analytics are fundamental tools for optimizing functional performance in any company. Likewise, the business must adjust the people and processes to adapt to the new tools if the technology adaptations. Thus, businesses can realize organizational efficiency by corresponding to the three and optimizing the associations between people, processes, and technology. Businesses must apply robust processes to ensure that people’s performance is effectively maintained. Utilizing the data related to people, processes, and systems will assist in optimizing operations by providing insights into the organization’s strengths and areas of needed improvement. For instance, analyzing employee engagement levels and turnover rates will help identify opportunities for employee development and retention (Patil, 2022). Analyzing KPIs related to processes will help identify areas for process improvement and reduce waste, while analyzing data related to systems will help optimize technological infrastructure and reduce downtime (Sjödin et al., 2018). The organization can increase efficiency, reduce costs, and improve overall performance by utilizing data to optimize people, processes, and systems. |
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Prompt 3: |
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Big data analytics (BDA) collected and analyzed for strategic purposes to support the Leadership Optimization Business Plan will provide a competitive edge to the organization by enabling it to make data-driven decisions and its impact on different parameters of firm performance (Shah, 2022). By utilizing data to optimize people, processes, and systems, the organization can increase efficiency, reduce costs, system health monitoring consumer experience management, and improve overall performance, giving it a competitive advantage. For instance, if the corporation has lower turnover rates and higher employee engagement levels than its competitors, it can attract and retain top talent (Athira, 2022). Additionally, suppose the organization has streamlined processes and a more efficient technological infrastructure than its competitors. In that case, it can reduce costs and improve customer satisfaction, giving it a competitive edge in the marketplace (Majdalawieh & Khan, 2022). Utilizing data to optimize operations will enable the organization to remain agile and responsive to changing market conditions, providing a competitive advantage (Diskiene et al., 2019). |
References
Athira, M. K. (2022). TALENT MANAGEMENT PRACTICES, EMPLOYEE ENGAGEMENT AND EMPLOYEE RETENTION: A SYSTEMATIC LITERATURE REVIEW.
Organising Secretary, 63.
Calzon, B. (2022). Why Data Driven Decision Making is Your Path To Business Success. https://www.datapine.com/blog/data-driven-decision-making-in-businesses/
Diskiene, D., Pauliene, R., & Ramanauskaite, D. (2019). Relationships between Leadership Competencies and Employees’ Motivation, Initiative and Interest to Work.
Montenegrin Journal of Economics,
15(1).
https://doaj.org/article/87e4ce6cfb49442e9aaa5af8fb634200
Falletta, S. V., & Combs, W. L. (2021). The HR analytics cycle: a seven-step process for building evidence-based and ethical HR analytics capabilities. Journal of Work-Applied Management, 13(1), 51-68.
https://www.emerald.com/insight/content/doi/10.1108/JWAM-03-2020-0020/full/html
Goasduff, L. (2016). 3 Key Steps to a Data-Driven Business.
https://www.gartner.com/smarterwithgartner/3-key-steps-to-a-data-driven-business
Majdalawieh, M., & Khan, S. (2022). Building an Integrated Digital Transformation System Framework: A Design Science Research, the Case of FedUni.
Sustainability,
14(10), 6121.
Patil, K. (2022). 5 WAYS DATA CAN INCREASE OPERATIONAL EFFICIENCY AND PRODUCTIVITY IN ECONOMIC VOLATILITY. https://community.nasscom.in/communities/analytics/5-ways-data-can-increase-operational-efficiency-and-productivity-economic#:~:text=Tracking%20progress%20and%20productivity&text=In%20addition%2C%20data%20can%20be,as%20well%20as%20upskill%20employees.
Project Pro.io. (2023). Types of Analytics: Descriptive, Predictive, Prescriptive Analytics.
https://www.projectpro.io/article/types-of-analytics-descriptive-predictive-prescriptive-analytics/209#:~:text=Prescriptive%20analytics%20advises%20on%20possible,What%20should%20a%20business%20do%3F%E2%80%9D&text=Optimization%20that%20helps%20achieve%20the%20best%20outcomes
.
Shah, T. R. (2022). Can big data analytics help organisations achieve sustainable competitive advantage? A developmental enquiry.
Technology in Society,
68, 101801.
Sjödin, D. R., Parida, V., Leksell, M., & Petrovic, A. (2018). Smart Factory Implementation and Process Innovation: A Preliminary Maturity Model for Leveraging Digitalization in Manufacturing Moving to smart factories presents specific challenges that can be addressed through a structured approach focused on people, processes, and technologies.
Research-technology management,
61(5), 22-31.
Stedman, C. (2023). Business Intelligence (BI). https://www.techtarget.com/searchbusinessanalytics/definition/business-intelligence-BI#:~:text=Business%20intelligence%20(BI)%20is%20a,workers%20make%20informed%20business%20decisi
Copyright 2021 by University of Phoenix. All rights reserved.
Copyright 2021 by University of Phoenix. All rights reserved.
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5
Industry Interview Summary B
Gabrielle A. Miliner
College of Doctoral Studies University of Phoenix
BUS/721: Issues in Optimizing Operations
Dr. Amy Hakim
April 24, 2023
Industry Interview Summary B
Google has made it a priority to address the heinous crime of sex trafficking and illicit drug markets. Google has developed and built far-reaching technology that identifies trafficking networks to make it easier and quicker for law enforcement to arrest these abusers. Google is in a distinctive position to analyze any role that technology can play in addressing some of the hardest global challenges. Data optimization is presented as an indispensable aspect of the company that endeavors to ensure that the company is fruitful and proficient in its operations (Nanayakkara et al., 2021). Data optimization in the organization is applicable and arranges for the corporation to utilize its data to advance its operations and provide that user needs are met. Google’s supply chain is critical to assist law enforcement and other agencies with its evolving technologies like digital twins and AI route optimization making it more straightforward to communicate and plan across traditional continuous industries. Supply chains are central. Therefore, entities like Google employ investments in security and risk programs in an effort to deploy software safely.
Although Google aids in the fight against human trafficking, Google also lobbies against amending Section 230(c)(1) of the Communications Decency Act so that websites that facilitate child sex trafficking can be held accountable. Section 230 of the CDA stipulates that a website can’t be held financially liable for what’s posted on its site by third parties (Mueller, 2022). Tech providers and other protectors of CDA Section 230 believe it upholds and defends free expression. But selling children online isn’t freedom of expression; it’s sex trafficking. Companies and media barons that profit from it should be accountable to the families they injure. The correlation between Google’s digital supply chain and its efforts to combat crime also rests on upholding Section 230 while still having the ability to moderate user content.
Interview Discoveries
The information gained from the interview indicates that Google has realized several innovative initiatives regarding supply chain optimization. Case in point, Ms. Brown indicates Google utilizes secure development and continuous testing frameworks to discover and escape collective programming errors to meet consumer needs. Google’s entrenched security-by-default tactic also contemplates an extensive variability of attack trajectories on the development procedure and supply chain risks. Google’s infrastructure intention is to supply defense-in-depth at scale, which means that Google does not depend on any solitary mechanism to keep entities secure. In its place, it constructs layers of checks and controls that contain trademarked Google-qualified hardware, its controlled firmware, physical security, and services. Google’s regulator of its hardware and security stack afford Google to maintain the substructures of its security position and decreases exposure to supply chain risk (Venables, 2021). The interview of Jerrimica Moore, within Google’s supply chain management division, will shed light on the proposed optimization and any potential barriers related to the intended optimization plan.
According to Ms. Moore, Google is exploiting its own AI/ML capabilities for supply chain advances utilizing advanced analytics, providing end-to-end visibility to optimize planning and decision-making processes. Google is revolutionizing the supply chain with “digital twins.” Google is by far advanced regarding stages in replicating supply chains via digital twins to track and predict logistics concerns more precisely to condense costs and exploit profits. Google is investing in supply chain sustainability. Through various extents of its business, Google is generating products and inking partnerships that stimulate supply chain sustainability by tracing properties like raw materials and fuel (CB Insights.com, 2023). Google’s supply chain forecasting combines data from various sources, primarily from users’ supply chain stack, weather, and traffic patterns, to expand discernibility, envisage ecological paradigms, enhance supply, and ascertain methodology improvements (Venables, 2021). Google also partnered with consulting groups and energy providers to support businesses in measuring the ecological influence of their supply chains and work in partnership regarding energy conversion.
Conclusion
In conclusion, the material acquired from the interview indicates that the proposed optimization plan for Google will enhance its current capabilities. Ms. Moore indicated that Google is currently utilizing partners to expand its reach to support the digital supply chain, that in itself aids other entities, such as law enforcement, utilizing its legal sector since it entails using electronic means to amass data. The privacy of data is also supposed to be followed so that the business does not leak consumer data to cybercriminals all over (Fernandes & Tribolet, 2019). As indicated in the summative assessment A, issues rest on maintaining privacy laws that afford law enforcement entities the ability to thwart criminal enterprises. Additionally, Google’s digital supply chain products affect all businesses that utilize its products; therefore, Google places a high priority on its own supply chain capabilities. Keeping in mind that Google has its own ethical and legal principles in place, and its vision is theoretical, which should support these frameworks and ensure that Google is successful.
References
CB Insights.com. (2023). Google in Supply Chain: How the tech giant is turning Google Cloud into a full-scale supply chain solution.
https://www.cbinsights.com/research/google-supplychain/#:~:text=Google%20also%20partnered%20with%20Boston,been%20experimenting%20with%20delivery%20vehicles
.
Fernandes, A., & Tribolet, J. (2019). Enterprise Operating System: The enterprise (self) governing system. Procedia Computer Science, 164, 149-158.
Mueller, J. (2022). Supreme Court to hear challenge to Big Tech’s Section 230 liability protections
Supreme Court to hear challenge to Big Tech’s Section 230 liability protections
Nanayakkara, S., Rodrigo, M., Perera, S., Weerasuriya, G., & Hijazi, A. (2021). A methodology for the selection of a blockchain platform to develop an enterprise system. Journal of Industrial Information Integration, 23, n/a.
Venables. P. (2021). How we’re helping to reshape the software supply chain ecosystem securely.https://cloud.google.com/blog/products/identity-security/how-were-helping-reshape-software-supply-chain-ecosystem-securely
BUS/721 v8
Industry Interview Worksheet
BUS/721 v8
Page 2 of 2
Industry Interview Worksheet
Complete this worksheet following your interview
.
Optimization Vision/Topic
|
Briefly describe the optimization problem you have chosen to address in the Week 8 assignment.
Your description should reflect the most updated version of your vision. Incorporate faculty feedback as needed. |
|
The aim is to branch out into new geographical territory to increase volume of Google’s products. Additionally, the goal of optimization is to also avoid misalignment between the business and the supply chain strategies while providing visibility across the supply chain and to elevate development and decision-making practices with AI. Although Google employs methods to help various agencies with their cyber security and software efforts among other features, the supply chain for entities that utilize Google products and services must be secure and have the ability to flow and connect with Google. For Google to produce its products its partners such as Deloitte, Accenture, Infosys within its “Supply Chain Twin” and “Digital Twins” efforts that can model potential scenarios, and aid in key features and benefits of Google’s global infrastructure and products for law enforcement and other businesses alike. . |
Interview Questions
Select 5 of your most impactful interview questions and write them below. Provide rationale for the questions you selected.
Question 1
IS THE SUPPLY CHAIN OPTIMIZED AND EFFICIENT?
The aim was to determine how Google aid in not only optimizing their supply chain but that of other agencies and businesses
Question 2
HAS THE SUPPLY CHAIN UNDERGONE STRATEGIC DEVELOPMENT?
The goal was to make a determination if Google has invested into innovative capabilities to enhance its strategic development to provide quality products, improved security, better scalability, and its overall software solutions services
Question 3
IS QUALITY EMBEDDED IN THE SUPPLY CHAIN?
The aim was to determine if Google employ efforts to ensure that the quality of its digital product supply chain is safe from attacks
Question 4
WHERE ARE THERE RISKS?
Every supply chain will have specific risk points. Conversely, how does Google aid in identifying where these risks are and how do they implement a strong backup plan
Question 5
ARE SUPPLY CHAIN AND BUSINESS STRATEGIES ALIGNED?
The goal is to determine if Google employ data analytics when aligning their supply chain to strengthen business strategies
Interview Responses
Summarize the interviewee responses to your questions in the spaces below.
Question 1
Google is taking advantage of its own AI/ML capabilities for supply chain offerings. Google is using current consumer products like Google Maps to release software that supports supply chain managers like myself to deploy fleets more rapidly and plan more efficiently
Question 2
Google embraces dynamic supply chain approaches that provide accommodations that address ever-changing market demands. Categorically, the operations and supply chain approaches adopted have evidently played an enormous task in enabling Google to be an excellent service provider.
Question 3
Google utilizes secure development and continuous testing frameworks to discover and escape collective programming errors
Question 4
Google’s embedded security-by-default tactic also contemplates an extensive variability of attack trajectories on the development procedure and supply chain risks that relate to threats in the context of the source, builds, deployment, and dependencies. Therefore, attack trajectories for software supply chains are a few methods we use to prevent somebody from deliberately or accidentally compromising software because issues like this can result in lost time, money, and consumer trust, whether its law enforcement or any other business.
Question 5
The varied Internet-related products and services have enabled Google to corner diverse Internet users and make them dependent to a certain extent. Google tracks through cookies which collect data related to users’ preferences, inclinations, favorites, requirements, etc. Whenever anyone searches for anything on the Google search platform, it incorporates all that data before showing the results in proper rank. Basically, what I’m saying is big data is at the core of Google’s business model.
Copyright 2021 by University of Phoenix. All rights reserved.
Copyright 2021 by University of Phoenix. All rights reserved.
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BUS/721 v8
Industry Interview Worksheet
BUS/721 v8
Page 5 of 5
Industry Interview Worksheet
Complete this worksheet following your interview.
Optimization Vision/Topic
|
Briefly describe the optimization problem you have chosen to address in the Week 8 assignment.
Your description should reflect the most updated version of your vision. Incorporate faculty feedback as needed. |
|
By refining its data analytics, Google can excel and be a vanguard service in the war against human trafficking. Utilizing advocates in this area, Google advanced and built wide-ranging technology to connect victims with the resources they need in addition to battling the opioid epidemic, elevating matriculation rates, thwarting various types of fraud, and various other societal matters as such data analytics is demonstrated the usefulness in addressing potential societal harms through beneficial aspects of data analytics. Since human trafficking frequently initiates with duplicitous recruitment means, such as assurances of employment through electronic services such as Gmail or fake websites, data analytics utilization can carefully ascertain depressed areas where awareness promotions and social service support insert optimal strategic positioning. By thoroughly comprehending the many facets of human traffickers and thwarting their criminal undertakings, various law enforcement entities, along with other supportive entities, can work to advance prevention campaigns for the human trafficking of children and women. |
Interview Questions
Select 5 of your most impactful interview questions and write them below. Provide rationale for the questions you selected.
Question 1
Has Google advanced any ingenuity that does not include court ordered applications, or warrants from law enforcement to address the rising concern of human trafficking?
The aim was to conclude if Google take action only when mandatory by court ordered ruling initiated by enforcement
Question 2
Given Google’s proprietorship of several platforms among other abilities, as well as web search and email do you consider that there are vast prospects to underwrite the fight against human trafficking?
The goal was to make a determination if Google has the resources of tracking anyone at any time, or have initiated any capabilities to create a list of hot words, or other red flags that may be probed as it relates to criminality?
Question 3
It is well determined that human traffickers utilize more advanced technology to develop their illegal organizations. What advances has Google put forth to hinder such illicit interests?
Global advocates such as Ashton Kutcher, Booz Allen and Bradley Myles of the Polaris Project, has worked to fortify the U.S. national crusade against human trafficking through policy promotion throughout the US utilizing a wide range of programs and anti-trafficking hotlines (West, 2022; NACO.org, 2023). How has Google helped law enforcement bridge the gap between law enforcement, Organized Crime and Corruption Reporting Project, and humanitarian understanding and proficiencies?
Question 4
Has Google’s data-driven approach made any new investments into data analytics of preceding trafficking cases that have been thwarted to possibly assist in new cases regarding how criminal traffickers interconnect and travel?
The purpose was to determine if Google has formed a specialized unit, or divisions in which the primary focus is to aid in the fight against human trafficking? Organizations such as LexisNexis, and Booz Allen use the considerable data they have access to track terrorist financing (Silverman, 2023).
Question 5
What monitoring apprehensions are you aware of, or foresee will preclude Google in formulating future plans as an active partner with law enforcement regarding human trafficking?
As it stands privacy laws aid both law enforcement and the criminal although the same laws protect law-abiding citizens, criminals like human traffickers can use these laws to their benefit to inhibit Google from tracking them (State.gov, 2021).
Interview Responses
Summarize the interviewee responses to your questions in the spaces below.
Question 1
Google joined the Polaris Project in 2013 to provide data without obstruction to support their efforts to prevent human trafficking. At the same time, data mining is a massive internal undertaking, and therefore Google does not publicize our part in the expectation that traffickers will continue to use our services. If criminals knew about our capabilities, they would move their online efforts to sites like Onion or BOR within the Dark Web. For this reason, Google does not advertise our abilities.
Question 2
As I stated, we at Google are working carefully with the Polaris Project. However, Google has yet to form initiatives centered on GPS tracking since there are vast privacy concerns. Regrettably, we are obstructed in some regards since the same laws protect people like you, and I also protect these criminals, that is, until they are apprehended.
Question 3
In the Gmail sector, we have unquestionably enhanced our spam and fraud proficiencies that aid in apprehending predatory offenders. Traffickers employ s lot of work to locate victims, as I’m sure you’ve seen on television, using means such as email and chatrooms. Google unquestionably screens these criminal-type spaces for key hot words and contacts the appropriate law enforcement agencies. With the use of warrants, we have far more latitude into allowable data we can track and make available.
Question 4
We have several dedicated working parties for human trafficking, drugs, and terrorist financing. We scrutinize the Office of Foreign Assets Control (OFAC) list and the sanction lists regarding other nations and track accounts with known associations with criminal activities. More than a few protocols are in place that rule our undertakings here and establish whom we must inform when and if we come across relevant information. For more than ten years, Google’s ability to track human trafficking has been a enormous undertaking.
Question 5
There are privacy laws that affect what steps Google can take when monitoring the data that goes through our systems. Unfortunately, I can’t divulge secrets, but I can say that we have the ability to do more, but are restricted by some court cases such as Carpenter v U.S., which precludes Google from turning over specific data to governmental agencies without a valid warrant. Another case, Griswold v. CT, also upheld a right to privacy for even criminals prior to being lawfully convicted of a crime. That being said, there is still room for progress with what Google is presently doing as the laws change. In fact, President Biden signed the Countering Human Trafficking Act 2022 into law, which Google has started evaluating to conclude what additional rights Google may have to support the fight. I really believe that your proposal presented is actually in line with our recent discussions.
References
NACO.org. (2022. CEO, Polaris.
https://www.naco.org/people/bradley-myles
Silverman, R. (2023). COMBATING HUMAN TRAFFICKING USING DATA SCIENCE.
https://www.boozallen.com/s/insight/thought-leadership/combating-human-trafficking-using-data-science.html#:~:text=Together%2C%20Booz%20Allen%20and%20Polaris%20are%20disrupting%20criminal%20networks%20and,trafficking%20victims%20around%20the%20globe
.
U.S. Department of State. (2021). 2021 Trafficking in Persons Report. https://www.state.gov/reports/2021-trafficking-in-persons-report/
West, P. (2022). 10 Celebrities Fighting Human Trafficking. https://listverse.com/2022/04/06/10-celebrities-fighting-human-trafficking/
Copyright 2021 by University of Phoenix. All rights reserved.
Copyright 2021 by University of Phoenix. All rights reserved.
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5
Summative Assessment: Industry Interview Summary
Gabrielle A. Miliner
College of Doctoral Studies University of Phoenix
BUS/721: Issues in Optimizing Operations
Dr. Amy Hakim
April 17, 2023
Introduction
The trafficking of individuals for forced labor, trade, and sexual exploitation has occurred for many years within modern society as in the past. While this type of illicit behavior is not new, the methods of how smugglers have carried out this task have changed due to modern technology. The methodology of how smugglers advance their actions has put forth the need for further advanced technology to fight human trafficking. As such, companies such as Google are utilizing technology within the cybersecurity community to combat this issue. The interview of Danielle Lambert, within Google’s cyber security division, will shed light on the proposed optimization and any potential barriers. To ascertain the practicality of several preventive measures regarding human trafficking, Google employs respective measures that must be considered, particularly concerning ethical and legal matters of the intended optimization plan.
Interview Discoveries
The information gained from the interview indicates that it was apparent that Google has realized several initiatives to aid in the fight against the illicit trafficking of humans. Nevertheless, Ms. Lambert also notes they have yet to go as she believes Google can. The global partnership of Google and various law enforcement entities endeavor to provide information on known trafficking groups and respective nonprofit agencies to help apprehend human trafficking ringleaders and assist victims in locating protection and finding their way back home. Through our conversation, Ms. Lambert indicated that respective legal barriers that inhibit Google from providing added support within its maximum scope of abilities could present a substantial obstacle to the proposed optimization. Google’s culture under Alphabet significantly improves the lives of as many people as possible.
Ms. Lambert utilizes Google’s practice of exploiting the Android open source code and its related open source project that facilitate the functions of cellular phones and public knowledge, unlike its competitor Apple which does not become available to the public. Ms. Lambert explained that Google has various ongoing projects that are free to all since building for everyone is their culture, so affording information in moments of crisis through data and technology is at the forefront of such a noteworthy fight goes without saying. While the desire is there to do more, legal hurdles regarding data collection, such as the Privacy Act of 1974, California’s Consumer Privacy Act (CCPA), CDP, and the United Kingdom’s GDPR, prevents Google from mining deeper into user activity to produce other facts to law enforcement agencies (HHS.gov, 2023). Ms. Lambert indicated that within Google’s algorithm, known “hot words” such as adoption, thorn, craigslist, and united nations will detect and help fight against human trafficking. A list of words, phrases, or locations associated with child trafficking could be uploaded into a database, or used in an (android) phone, google search engine, emails, or other platforms such as a Chrome browser, which will notify local law enforcement (Lambert, 2023; Thomas, 2021). Although helpful, this violates some laws regarding privacy and, therefore, would not be legal (Franchino-Olsen et al., 2022; HHS.gov.,2023). Google’s legal department works with government entities and lobbyists to find workarounds for these regulations without compromising Google’s principles or integrity (Department of Justice, 2022).
Conclusion
The information acquired from the interview indicates that the optimization plan for Google is viable. Ms. Lambert conceded that Google is currently pursuing other pathways to support law enforcement agencies through their legal department to realize this goal while adhering to recognized legal guidelines. The issues of the plan rest with privacy laws that afford criminals identical protections as the victims, thus making it challenging to offer law enforcement relevant data necessary to bring the victims home. The theory of crafting a vision change, as presented in the week two coursework as the theoretical context utilized to support the optimization plan, is still very much germane for optimization. The theory of change is a high order or task in its implementation, generating a presupposing argument: if achieved, then these are the expected outcomes (Wildman, 2022). With the monitoring backdrop and privacy laws, Google must prepare each phase as an if-then proclamation to meet the pragmatic grounds of equipping essential data to law agencies while still acting according to existing laws. While foraging ahead with this optimization plan, it will be essential to pledge that the framework remains in force to forecast how any and every action projected would work in contradiction of legal requirements.
References
Department of Justice. (2022). Google Enters into Stipulated Agreement to Improve Legal Process Compliance Program. https://www.justice.gov/opa/pr/google-enters-stipulated-agreement-improve-legal-process-compliance-program
Franchino-Olsen, H., Chesworth, B. R., Boyle, C., Rizo, C. F., Martin, S. L., Jordan, B., … & Stevens, L. (2022). The prevalence of sex trafficking of children and adolescents in the United States: A scoping review.
Trauma, Violence, & Abuse,
23(1), 182-195.
Gezinski, L. B., & Gonzalez-Pons, K. M. (2022). Sex Trafficking and Technology: A Systematic Review of Recruitment and Exploitation.
Journal of Human Trafficking, 1-15.
HHS.gov. (2023). The Privacy Act. https://www.hhs.gov/foia/privacy/index.html#:~:text=The%20Privacy%20Act%20of%201974,other%20identifying%20number%20or%20symbol.
Thomas, S. (2021). Secret codes and language used by kids and traffickers.
https://www.kgun9.com/news/human-trafficking/secret-codes-and-language-used-by-kids-and-traffickers
Wildman, W. J. (2022). Out with the Old, In with the New? From Conceptual Reconstruction in Philosophical Anthropology to a Realistic Theory of Change. In
Relational Anthropology for Contemporary Economics: A Multidisciplinary Approach (pp. 181-199). Cham: Springer International Publishing.
BUS/721 v8
Vision Framework Worksheet
BUS/721 v8
Page 2 of 2
Vision Framework Worksheet
Part A: Write a 175- to 260-word response to each prompt below.
Ensure each response is
· thorough and complete
· supported with rationale.
· edited carefully for grammar, punctuation, and spelling errors
· formatted according to course-level APA guidelines (where applicable)
· cited correctly (where applicable)
Prompt 1 –
Exploring the Vision
Identify up to 3 possible optimization opportunities in data analytics relevant to your chosen organization. In your response be sure to:
· Describe the optimization issues clearly.
· Explain the proposed opportunity or remedy for each issue.
· Provide sufficient context for each issue and opportunity.
Tesla’s optimization issues stem from production regarding excessive automation and adaptability and the performance capacity of the batteries produced. Utilizing human resources is more able to adapt to change than artificial intelligence (AI) has the potential to replace human workers, but leaders must define the right speed of modification since the factory is highly automated. However, while autonomous systems progress quickly, human workforces are far better at adapting to unexpected shifts. As such, complex manufacturing works patterns to increase supply chain efficiency that Tesla should not miscalculate in producing its batteries (Akakpo et al., 2019). Tesla’s productivity issues should have addressed the significance of adaptability in manufacturing, thereby enhancing productivity. The prospect of lesser oversights and unexpected situations compared to the intricacy of the process, notably when the process occurs in the real world. Tesla may face other threats regarding globalization, government regulations, slow customer adaptation, and manufacturing delays (Buchel & Floreano, 2018).
Prompt 2 – Developing the Vision
For each opportunity you identified, make connections to Figure 1.1, “The Work of Leaders Overview,” in Ch. 1 of
The Work of Leaders. Use the questions below to guide your response.
· How will you demonstrate open-mindedness as you develop your vision?
· How will you prioritize the “Big Picture” of your vision?
· How will your solutions embody boldness?
Developing a vision is a trial-and-error process, where leaders must broaden the scope of the team’s options and look beyond the current situation. Therefore, leaders must exhibit open-mindedness and boldness and prioritize the big picture. As the team leader in charge, leaders must become pragmatic in developing ideas for Tesla to achieve the desired goals. With an optimized process comes increased work superiority, and a thoroughly constructed process can decrease expensive errors and improve results (Huang et al., 2022). Having an optimized workplace is significant, and creating a strategy for process management is the optimal means to get results.
The productivity of Tesla’s automobile industrial performance rests on operations management efficiencies, such as in the sphere of inventory management, potential bottleneck issues, and supply chain management (Di Nardo, 2020). Operations management procedures depend on Tesla’s vision, which distinguishes much of the corporation’s approaches and planning. Operations management ability impacts high productivity and business growth even with opposing external forces.
On the opportunity of exploiting data in real-time, attained data to improve the design and to remain a top manufacturer, Tesla must determine how the organization’s products affect costs, value objectives, and resources regarding staff allocation to improve services and practices that create accordingly maximization to satisfy consumer expectations. This measure will require preciseness in dealing with competition, consumer data, and feedback. Proper data analysis will improve services through quality checks programs since operational processes when carried out correctly with the appropriate strategic plan, and management personnel ensures the maximization of productivity (Thompson, 2018). Making quality decisions is vital to any organization regarding procedures and capacity design research on the automotive and energy results within the electric car market. Relying on data in making decisions will enable Tesla to serve patrons better and respond to quality issues with suppliers (Foufa, 2022). These executive actions are achieved by adequately examining consumer and competition data to develop appropriate measures to help them better optimize performance and services. Boldness will be evident from the effectiveness of decisions made from that data.
Prompt 3 – Desired Outcomes
Describe the intended result of implementing your vision for optimization of operations. Be sure to include legal and ethical considerations. Provide rationale for your response.
The intended outcomes of implementing the vision for optimizing the operations include the elimination of complexity and latency in processing in its supply chain. These operations executive decision areas concentrate on business activities, associated assets, means, and standards. Tesla, Inc. incorporates automation for this concern. For instance, automating production methods along with human involvement assists Tesla in realizing high productivity through operational streamlining proficiency in the automotive and energy solutions industry.
The first desired outcome regards advancing its manufacturing efficiency by helping managers gauge the efficiency of present systems, analyze the results of the processes, industrialize new workflows, and refine them over time, permitting Tesla to govern if processes are ineffective or draining the budget. The second desired outcome is the exploitation of robust data in real time. Data is crucial since the future of its services and opportunities will hang on to a robust data analytics strategy. Real-time data will enable Tesla to verify and refine the outcomes over time. For instance, assigning more personnel to a particular section with less need for automation will be possible to avoid supply chain backlogs (Zamani et al., 2022). The last desired outcome is making quality decisions. Good decision-making relies on facts, not speculations, and facts derived from data. Hence, appropriate data analytics assessment will automatically lead to significant quality decision-making and management of resources and operations, which will be in the consumer’s best interest.
On the opportunity of exploiting data in real-time, attained data to improve the design and to remain a top manufacturer, Tesla must determine how the organization’s products affect costs, value objectives, and resources regarding staff allocation to improve services and practices that create accordingly maximization to satisfy consumer expectations. This measure will require preciseness in dealing with competition, consumer data, and feedback. Proper data analysis will improve services through quality checks programs since operational processes when carried out correctly with the appropriate strategic plan, and management personnel ensures the maximization of productivity (Thompson, 2018). Making quality decisions is vital to any organization regarding procedures and capacity design research on the automotive and energy results within the electric car market. Relying on data in making decisions will enable Tesla to serve patrons better and respond to quality issues with suppliers (Foufa, 2022). These executive actions are achieved by adequately examining consumer and competition data to develop appropriate measures to help them better optimize performance and services. Boldness will be evident from the effectiveness of decisions made from that data.
Prompt 4 – Leadership Competencies
Describe the leadership competencies necessary to align and execute this vision. Specify any particular milestones necessary for the plan.
In leading teams toward realizing any plan’s positive outcomes, all leaders must be equipped with specific characteristics that will contribute to good performance (Heinen et al., 2019). As the team leader, to achieve these objectives for Tesla to develop and market in the global market, the leader must possess several leadership competencies to realize the intended change (Johan et al., 2022). The leadership competency must have cognitive intelligence. This type of intelligence refers to thinking and analyzing information and situations. This competency is crucial in monitoring the product system development and its progress and evaluating its performance at the end. For example, using systems thinking skills, leaders can conceptualize the service delivered to patients and understand their impact on the Health facility and the public (Swanson et al., 2020). Another crucial leadership competency that one must possess is social intelligence competency. This type of competency refers to recognizing, understanding, and using emotional information about others. Inspirational leadership is one of the skills used in this competency. However, with inspirational leadership skills, leaders can unite all the stakeholders and incentivize them to see the bigger picture.
Prompt 5 – Theoretical/Conceptual Framework
Identify at least 1 relevant theory or concept that supports your vision. Be specific in your application of the theories/concepts. Remember to cite sources as needed.
Every organization, such as Tesla, must continuously innovate to remain dominant in an ever-competitive global market economy regarding the services it provides for its consumers. Organizations that have succeeded and existed for more than a century are those that innovate and develop new systems of delivery of services. This vision of Tesla has been motivated by the innovation theory of profit, which Joseph Alois Schumpeter coined. According to Schumpeter, the function of entrepreneurs is to develop, introduce innovation, and profit in the form of a reward for the service performance in the market. All these systems that any team intends to develop as our innovation would generate excellent service delivery, attracting more patrons and increasing earnings.
Tesla is an electric automobile organization, and its mode of operation centers on the innovation theory of profit. Therefore, the new vision of developing the new automated system is in tandem with the theoretical framework upon which the facility functions (Di Nardo, 2020). innovation can easily result in developing a company that dominates the electric car market.
References
Akakpo, A., Gyasi, E. A., Oduro, B., & Akpabot, S. (2019). Foresight, organization policies, and management strategies in electric vehicle technology advance at Tesla.
Futures Thinking and Organizational Policy: Case Studies for Managing Rapid Change in Technology, Globalization and Workforce Diversity, 57-69.
https://doi.org/10.1016/j.jclepro.2019.06.284
Buchel, B., Floreano, D. (2018). Tesla’s problem: Overestimating automation, underestimating humans. https://www.imd.org/research-knowledge/articles/teslas-problem-overestimating-automation-underestimating-humans//
Di Nardo, M. (2020). Developing a conceptual framework model of Industry 4.0 for industrial management. Industrial Engineering & Management Systems, 19(3), 551–560. 10.7232/iems.2020.19.3.551
Foufa, N. (2022). 5 Benefits of Operational Optimization.
https://www.sigmacomputing.com/blog/5-benefits-of-operational-optimization#:~:text=What%20is%20Operational%20Optimization%3F,cutting%20costs%20and%20maximizing%20performance
.
Heinen, M., van Oostveen, C., Peters, J., Vermeulen, H., & Huis, A. (2019). An integrative review of leadership competencies and attributes in advanced nursing practice. Journal of advanced nursing, 75(11), 2378-2392.
Huang, S., Wang, G., Lei, D., & Yan, Y. (2022). Toward digital validation for rapid product development based on digital twin: a framework. The International Journal of Advanced Manufacturing Technology, 1-15.
Johari, J., Shamsudin, F. M., Zainun, N. F. H., Yean, T. F., & Yahya, K. K. (2022). Institutional leadership competencies and job performance: the moderating role of proactive personality. International Journal of Educational Management, (ahead-of-print).
Swanson, E., Kim, S., Lee, S. M., Yang, J. J., & Lee, Y. K. (2020). The effect of leader competencies on knowledge sharing and job performance: Social capital theory. Journal of Hospitality and Tourism Management, pp. 42, 88–96.
Thompson, A. (2018). Tesla, Inc.’s Operations Management: 10 Decisions, Productivity.
Tesla, Inc.’s Operations Management: 10 Decisions, Productivity
Weiszbrod, T. (2020). Health care leader competencies and the relevance of emotional intelligence. The health care manager, 39(4), 190-196.
Zamani, E. D., Smyth, C., Gupta, S., & Dennehy, D. (2022). Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review. Annals of Operations Research, pp. 1–28.
Zhang, Y., Huang, T., & Bompard, E. F. (2018). Big data analytics in smart grids: a review. Energy Informatics, 1(1). https://doi.org/10.1186/s42162-018-0007-5
Copyright 2021 by University of Phoenix. All rights reserved.
Copyright 2021 by University of Phoenix. All rights reserved.
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Summative Assessment: Leadership Optimization Business Plan
Scenario: Imagine you are a management consultant for an organization seeking to optimize its operations. You have been tasked with conducting research before developing a business plan which you will later present to stakeholders for their consideration.
Select an organization or industry of your choice and identify an optimization challenge you would like to address.
Write a 1,750- to 2,100-word paper in which you present a leadership and optimization plan to address the challenge.
Note: This assignment requires that you integrate content you have created in Weeks 1–6. Be sure to create a consistent and coherent plan; avoid simply appending prior submissions. Each week, consider how you can incorporate feedback received from your instructor and your peers.
Include the following in your plan:
Introduction
· Describe your chosen organization or industry by providing context and relevant details about its operations.
The Vision
· Explain one optimization challenge and your vision for optimization. Be sure to support your idea(s) with a theoretical framework or concept.
· Explain your strategy/strategies for implementing your vision.
· Predict 3-4 optimization outcomes your plan will have on operations. Consider the following guiding questions:
·
Positive outcomes
· How will your plan drive performance excellence?
· How will your plan provide a competitive advantage to the organization or industry?
· Does your plan have long-term sustainability? Why or why not?
· What kind of impact will your plan have on domestic/global operations?
·
Potential challenges
· What are 1-2 negative repercussions you anticipate occurring as a result of implementing your plan? How can they be mitigated to reduce stakeholder concerns?
Leadership Competencies
· Describe how you will apply leadership principles to execute the vision.
· Assumptions – Explain how you assessed your assumptions.
· Alignment – Explain how you will align people, processes, and systems to implement the changes.
· How will you develop and prepare organization leaders?
· What changes must occur in the organizational structure to execute the plan?
· What changes must occur in organizational behavior to execute the plan?
· How will your plan provide clarity, encourage dialogue, and inspire the organization?
· Incorporate insights you gained from the interviews you conducted in Week 3 and Week 4.
· Incorporate concepts from the VAE model in
The Work of Leaders.
Data/Metrics
· Explain the role data will play in the execution of your vision. Be sure to support your rationale with relevant details about how you will:
· Acquire the data
· Measure the data
· Incorporate Business Intelligence (BI) and Enterprise Resource Planning (ERP) systems to manage the data
· Include relevant details from the Wk 5 – Data Analysis Worksheet assignment as well as the Wk 6 – Data Table assignment.
Execution
· Explain how you will build momentum, structure, and provide ongoing feedback. What will the feedback loop look like? Include applicable details from the Value, Alignment, Execution (VAE) model on page 9 of
The Work of Leaders.
Sources
· Support your plan with applicable sources from the list below:
· Scholarly works such as applicable graphs, charts, tables, and figures which are excluded from the word count maximums
· Organization-specific, industry/trade, and peer-reviewed references
· Key theoretical or conceptual frameworks that support your plan