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DB FPX 8720 Assessment 5 Harvard Business Review Summit- Virtual Presentation

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DB FPX 8720 Assessment 5 Harvard Business Review Summit- Virtual Presentation Student Name Capella University DB-FPX8720 Strategic Digital Transformation Professor Name Submission Date [blur_section id=”postDownload” button=”Free Download” form_id=”e9df100″] Student Name Capella University DB-FPX8720 Strategic Digital Transformation Professor Name Submission Date Slide 1 Title Slide Good morning, everyone. I am Eliel, and thank you for joining me today. I am excited to share. Good morning, everyone. I am going to begin the podcast by identifying myself as I’m talking to you today: I’m _________. I am thrilled to present some of my work on my new project, “Strategic Digital Transformation Fundamentals: Transform jobs and enhance with AI and big data,” where I use AI to analyze big data and make transformations in jobs. This project is looking to change the way that digital transformation is done. Slide 2 Introduction Technologies such as machine learning and natural language processing can help automate complicated tasks, analyse huge amounts of data, and make informed decisions in a short time. By analyzing large amounts of data and identifying patterns, businesses can leverage AI to see far into the future and make more informed decisions and predictions, which leads to improved business planning and operations. By using AI and big data together, businesses can gain a whole new level of productivity, as the AI takes care of repetitive tasks and streamlines workflows. By optimising the use of resources, boosting accuracy and speeding up processes (such as in marketing, HR, and customer service), AI saves time and money, allowing for more efficient processes that yield better business results and a competitive advantage in the marketplace. Slide 3 Strategic Digital Transformation Fundamentals To drive digital change within an organisation, there are a number of key principles that need to be adhered to: vision, leadership, culture, and technology adoption. The vision provides clarity of purpose and direction for the digital transformation process, influencing decision-making and bringing stakeholders together with a common vision. There needs to be clear and effective leadership where the leader is able to inspire, communicate, and empower staff to accept and facilitate the change. Leaders who support digital programmes and create an environment that is flexible, innovative, and supportive will help to ensure innovation and digital development flourish. To ensure a sustainable digital change, creating a positive culture is key. This includes providing an environment that encourages creativity, learning, and collaboration, and that allows for experimentation and the learning process without fear of failure. There needs to be continuous learning and a focus on rewarding learning practices that can lead towards digital innovation. Last but not least, it is crucial to strategically implement technology. It involves a focus on initiatives that provide value, prototypes, and pilots to test out new ideas and a systematic approach to the integration of technology to improve processes and outcomes. Slide 4 Best Practices for Developing a Digital Transformation Strategy There are a number of best practices that can be followed to develop a successful digital transformation strategy. First of all, it’s important to evaluate what this organization currently has in place and how developed the technology is, to determine where it can improve and to make sure that the organization is prepared for the change. The first step is to do an in-depth analysis of existing processes, systems, and market conditions. Defining goals is the next step that is crucial. Objectives need to be specific, measurable, achievable, relevant, and timely (SMART) to give direction and enable progress to be monitored. Slide 5 Another key element is to involve stakeholders, making sure that everyone who will be impacted by the transformation is engaged and supportive of the transformation. Good engagement with stakeholders involves determining who these stakeholders are, what they need, and what they are concerned about, and engaging them in the decisions. Finally, the strategy can be applied in an iterative manner so as to be able to provide continuous feedback and improvements. This way, risks can be mitigated, and transformation will be on track with business objectives and market needs. Slide 6 Leveraging AI for Big Data Analysis AI can greatly improve big data analysis by automating the data analysis process, detecting patterns, and providing actionable insights, all of which are achieved at a much faster speed. AI can analyze large amounts of data and uncover patterns, outlier data points, and other relationships that are difficult to find using traditional analysis techniques. This feature allows companies to make informed decisions more quickly, more efficiently, and with greater accuracy. AI has been in use for years to enhance operations in the supply chain, from predicting demand fluctuations to managing inventory levels, which has led to lower costs and higher customer satisfaction in companies such as IBM. AI-driven analytics have been used in the financial industry to identify fraudulent transactions, which has led to a decrease in fraud and savings of billions of dollars per year. In healthcare, for instance, AI systems have been leveraged to examine patient data and forecast outbreaks of diseases, enabling prompt measures to be taken and the more effective use of resources. The examples illustrate the applications of AI in improving data analysis and how this can translate to better business results with more informed and proactive decision-making. Slide 7 Foundations of Organizational Learning Continuous learning, sharing of knowledge, and adaptive processes are important foundational elements of organizational learning. To ensure that employees keep up to date with technological advances and changes in the marketplace, continuously upgrading their skills and knowledge is continuous learning. Knowledge Sharing means the systematic process of sharing critical knowledge and experiences across the workforce, such that valuable knowledge is accessible to all the workforce ( Digital transformation is about enabling learning in organizations by putting in place tools and platforms to facilitate good continuous learning, knowledge sharing, and adaptation. Artificial Intelligence, machine learning, and cloud-based technology allow for individualized and scalable training courses, which promote ongoing training throughout the company. These digital tools also facilitate the sharing of knowledge, […]

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DB FPX 8720 Assessment 4 Creating an Example of Student Work

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DB FPX 8720 Assessment 4 Creating an Example of Student Work The Role of Technology in Modern Supply Chain Management: Enhancing Efficiency and Resilience Student Name School of Business and Technology, Capella University DB-FPX8420: Teach Business in Higher Ed Professor Name Submission Date [blur_section id=”postDownload” button=”Free Download” form_id=”e9df100″] Introduction The world has become global, and supply chain management in today’s world is undergoing a transformation owing to technological advances. AI, Blockchain, and the IoT in small letters (IoT) are changing the game. These technologies are the ones that are changing the way companies optimize their operations with tools that increase operational efficiency, streamline processes, and minimise risk throughout the supply chain. AI can help better predict customer needs, helping businesses adjust accordingly, optimise stock levels, etc. The blockchain provides traceability and security, guaranteeing transparency for the traceability of products from their origin to their destination. Meanwhile, IoT devices enable the real-time monitoring and tracking of products, leading to better visibility and decisions in supply chains. This essay will explore how new technologies are impacting supply chain management and how they can help companies sustain their operations and keep up with disruptions. It will also put forward a strategic plan that will be a practical blueprint for organizations to take advantage of these technological trends. The essence of this agile, co-creative, and continuous innovation process is a tool to stay competitive and resilient. Technological Advancements and Their Impact on Supply Chain Management As AI and machine learning become more prevalent in supply chain operations, businesses are now seeing more accurate and agile decision-making. The integration of AI and machine learning into supply chain processes has bolstered decision-making, and it allows companies to make more accurate and agile decisions than ever before. With their proactive nature, AI-driven forecasting tools analyze data from diverse sources, such as market trends, historical sales, and real-time customer behaviors. This analysis can help businesses plan for changes in demand and make decisions accordingly, such as avoiding stockouts, minimizing overstocking, and streamlining resource usage. These predictions are supplemented with machine learning algorithms that learn the patterns and trends in the data as it arrives, providing even more precise predictions. AI can be used to optimize delivery routes by analysing traffic, fuel prices, and delivery constraints to bring down delivery time and transportation costs and improve operational efficiency (Magd & Ruzive, 2021). Similarly, blockchain technology has transformed transparency and traceability in supply chains by offering a ledger to trace products throughout the supply chain. The decentralized nature of this system allows the tracing and authentication of products, which minimizes the risk of product fraud, counterfeit products, and compliance violations from suppliers to end consumers. By maintaining a transparent and tamper-evident process of transactions, blockchain helps to establish trust among stakeholders and improve accountability. Moreover, it enables firms to know and correct issues like product recalls or safety concerns. It allows for greater transparency and assures adherence to increasingly stringent regulations across the globe and enhances trust and integrity of the supply chain (Fernando, 2024). Framework Recommendation for Adapting to Technological Trends To harness technology, a key element of Agile Supply Chain Management is required. The flexible, adaptable, and responsive nature of this approach allows businesses to navigate unexpected market changes, such as fluctuating consumer demand or supply issues, or even crises. Real-time data analytics and linking up with suppliers will allow businesses to make decisions quicker and change their approaches to continue operations (Christopher & Towill, 2001). The Agile Supply Chain Framework also enables the smooth integration of technologies such as AI, blockchain, and IoT, which can help organizations work more accurately and transparently, and with a greater degree of traceability. These innovations can be adopted and implemented, giving companies the advantage in the market and making them more efficient in their supply chain. Agility in supply chain management has the ability to shorten lead times, reduce waste, and support companies to better satisfy customer needs in terms of speed and accuracy (Christopher & Towill, 2001). By establishing a shared framework for the supply chain, the Agile Supply Chain Framework also encourages collaboration with suppliers and other stakeholders, ensuring efficient communication and aligned objectives, which enhance the overall performance of the supply chain. The use of real-time data means that all partners are informed of the latest developments, enabling them to make decisions and take action in a coordinated manner and ahead of the curve when it comes to challenges. This approach can make supply chains more resilient to change and uncertainty – the only thing that is certain in these times of constant change is change itself (Christopher & Towill, 2001). Real-World Application A well-known example of the Agile Supply Chain Framework, which has been put into practice, is the use of AI systems for stock monitoring and inventory management in real time for the retail giant Walmart. By leveraging machine learning and predictive analytics, Walmart can more closely match demand and minimize the risk of running out of stock and overstocking its warehouses. This real-time information helps Walmart optimise its inventory replenishment processes, ensuring that products are available to meet customer demand while minimising the risk of excess stock, reducing holding costs, and preventing waste. The flexibility in managing the inventory brings about agility in the operations, which helps in improving customer satisfaction and enhancing the efficiency of operations (Magd & Ruzive, 2021). Beyond AI, the food sector has seen the transformative potential of blockchain technology with its applications in supply chain transparency and traceability. Apart from AI, blockchain technology has been revolutionising the traceability and transparency of food supply chains too. IBM Food Trust blockchain platform can be used to trace food from farm to fork, offering full supply chain visibility. Using blockchain, IBM has enhanced food safety by providing transparency into food origins for retailers and consumers, thereby guaranteeing food safety and ethical sourcing. A high degree of transparency can help foster consumer confidence and help respond quickly to potential food safety problems like […]

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DB FPX 8720 Assessment 3 Business Project Idea- Developing a Business Study

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DB FPX 8720 Assessment 3 Business Project Idea- Developing a Business Study Student Name Capella University DB FPX 8720 Professor Name Submission Date 1.1 Introduction The use of artificial intelligence (AI) in the analysis of large volumes of data is transforming the way that industries are operating and changing the employment dynamic in today’s digital world, while also improving productivity. The ability to analyze huge datasets at a rapid pace and with high accuracy, offering businesses more insight for better decision-making and creatively exploring solutions, is another key benefit of AI integration. For example, AI’s ability to analyze large volumes of data can enable companies to make predictions, streamline supply chains, and tailor their services to individual users, all of which can give them an edge. As revealed in Jada and Mayayise’s study, the level of productivity that can be gained from implementing AI in data analytics is up to 40%, which is truly a transformative opportunity. As effective big data analysis becomes more crucial, AI technologies are essential for businesses to maximize their benefits, thereby changing job descriptions and boosting productivity. 1.2 Problem of Practice The general challenge is that organisations with a big data analysis theme are struggling to fully realise the value of big data because of the complexity and quantity of the data, and are not making optimal decisions and therefore missing opportunities. It is a problem that can manifest itself in many industries and sectors, impacting businesses, the health care sector, educational institutions, and more. Adversity faced is manifested as inefficiencies, increased expenses, and failure to take advantage of opportunities for innovation and development (Kulkov et al., 2023). While artificial intelligence (AI) can definitely benefit big data analysis, it’s difficult for many organizations to effectively make use of AI technology. The issue is that while U.S. businesses have access to all this big data, they don’t know how to use the right skills and strategies to adopt AI into their processes, leading to the inefficient use of data and loss of productivity. It is felt especially in the sectors where making decisions is highly reliant on data, e.g., finance and health. 1.3 Gap in Practice Today, numerous organisations find themselves battling the challenges of massive amounts of data and are unable to make the best use of the skills and intelligence that AI technologies offer. This leads to sub-optimal use of the data, higher costs and lost opportunities to innovate and grow – in many cases, these businesses lack appropriate methods and strategies with regard to efficient data usage. In today’s scenario, where organizations are facing challenges with the inability to fully leverage the capabilities of big data without AI integration, the problem lies in the lack of proper AI integration. Businesses or healthcare service providers find it difficult to effectively make data-informed decisions and thus experience poor performance metrics and less competitiveness. The desired state is a future where these entities have fully embraced AI in their data analytics workflows, seamlessly analyzing data to generate actionable insights, improve decision-making, and fuel organizational growth and success. The gap in practice is between the actual struggles with the integration of AI and the potential for optimized use of data. 1.4 Purpose of the Project and Project Questions Purpose The team needs to include a purpose and a set of questions. The team should have a purpose and project questions. Qualitative inquiry project aims: Explore case study approach and skills that will help business leaders in the United States to effectively incorporate artificial intelligence (AI) into their big data analytics processes. Through the identification and understanding of these strategies and skills, the project will help close this gap in practice by ensuring that data is used more effectively and improving productivity in industries that are heavily reliant on data, such as Finance and Healthcare. This study will employ a case study approach to gain more in-depth knowledge from business leaders who have been successful in implementing AI in their data analysis. Project Questions What are business leaders’ specific skills that they feel they need to be successful with the integration of AI in their big data processing? What strategies have business leaders been able to employ that have proven effective in tackling the challenges of incorporating AI into big data analysis? 1.5 Preliminary Terms and Definitions Artificial Intelligence (AI): AI, or artificial intelligence, is intelligence exhibited by machines, which, like humans, are capable of learning and making informed decisions. In big data analytics, AI helps automate processes, augment data analysis, and create insights that can assist in better decision-making and operational efficiency. Big Data Analytics: Big Data Analytics is the ability to analyse these large and varied datasets or “big data” to discover information, including hidden patterns, correlations, market trends, and customer preferences. This information can prove useful to companies to aid them in making business decisions that are informed, and boost productivity and efficiency. Data-Driven Insights: Data-driven insights are worthwhile insights that can be gained from studying data, and they assist in making well-informed business decisions. Insights from patterns and trends within the data sets can help a lot in the decision-making process. These insights can be improved by AI’s capacity to take data into account and analyse it more effectively, as it’s able to process huge amounts of data more efficiently (Oncioiu et al., 2019). 1.6 Project Justification The intended project is to combine artificial intelligence with big data analysis to improve leadership development in organisations. This project has identified a need highlighted in practitioner and scholarly literature that explores the need to harness AI tools to manage and analyze vast amounts of data in today’s business landscape. The amount of information organizations are collecting has never been greater, and it’s no longer possible to rely on conventional data analysis techniques to cope. AI can greatly enhance decision-making and leadership development initiatives by analyzing and comprehending vast amounts of information. The emphasis on business leaders is important because they are key decision makers when it comes […]

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DB FPX 8720 Assessment 2

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DB FPX 8720 Assessment 2 Student Name Capella University DB-FPX8720 Strategic Digital Transformation Professor Name Submission Date [blur_section id=”postDownload” button=”Free Download” form_id=”e9df100″] Coming Soon. [/blur_section]

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DB FPX 8720 Assessment 1 Integrating SOBTH Doctoral Networking Resources with the Doctoral Capstone Guidebook

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DB FPX 8720 Assessment 1 Integrating SOBTH Doctoral Networking Resources with the Doctoral Capstone Guidebook Student Name Capella University DB-FPX8720 Strategic Digital Transformation Professor Name Submission Date [blur_section id=”postDownload” button=”Free Download” form_id=”e9df100″] Student Name Capella University DB-FPX8720 Strategic Digital Transformation Professor Name Submission Date Integrating SOBTH Doctoral Networking Resources with the Doctoral Capstone Guidebook The SOBTH Doctoral Networking Resources have been integrated into the Doctoral Capstone Guidebook, which is now more enriched by content and advice from professional networks, faculty, and peers, to enhance the quality and relevance of the capstone project. Chosen Video or Webinar Theoretical and Conceptual Frameworks Webinar Recording I’ve selected a theoretical and conceptual framework webinar. This webinar has been selected to provide a better understanding of the different types of frameworks that can be utilized in research and capstone projects. It speaks about theoretical, conceptual, and applied frameworks (Capella University, 2024). This resource is designed to increase the understanding of what the purpose of a frame is, and how it is used in Research and in Academic and Professional Practice. DHA Learner Huddles: Gaps in Practice Webinar Recording I’ve selected areas where there are no practice videos. It was chosen for this video to complement the current knowledge of the elements of a Capstone project – purpose statements, questions about the project, and gaps in practice (Capella University, n.d.). It offers instruction on the effective way to communicate these in an accurate and succinct way. The video aims to help students come up with better and sound research proposals. Main Points or Key Concepts Theoretical and Conceptual Frameworks Webinar Recording The webinar contains a number of key concepts and main points. Theoretical, conceptual, and applied frameworks have a bit of a difference in their areas of application. Webinar offers information about different uses of several frameworks for various disciplines such as dissertations and capstone work (Capella University, 2024). It offers guidance on choosing and/or adapting rules that meet the needs of a specific project. The webinar includes a question-and-answer section where the moderator will answer questions from the viewers and present extra content. DHA Learner Huddles: Gaps in Practice Webinar Recording The presenters emphasize creating succinct and apt purpose statements and posing questions for Capstone projects in the video. The project question should be related to the problem, purpose, and identified gap in practice (Capella University, n.d.). The video also highlights the importance of choosing a specialism where there is a gap that the practitioner or publications have to fill. The problem statement, purpose statement, project question, and the gap in practice are the four key elements to the coherence of a research project. Elements of Doctoral Capstone Guidebook Theoretical and Conceptual Frameworks Webinar Recording The matching of the key topics in the webinar to the sections of the guidebook suggests that the topic was identified and how related it was to each of the sections of the guidebook (ORS Office of Research and Scholarship, 2023). The webinar addresses the fundamentals of research, such as what questions should be asked, how to approach the research process, and the researcher themselves. These topics correspond with the parts of the guidebook, according to which questions that are supposed to be answered in a project, the justification of the selected methods, and the author’s role and existing biases are mentioned. DHA Learner Huddles: Gaps in Practice Webinar Recording The ideas presented in the video relate to a few chapters of the Doctoral Capstone Guidebook. The WritingLab (Office of Research and Scholarship) identified the following elements of the sections to be of immediate interest for the writing process: Problem Statement, Purpose Statement, Project Questions, Gap in Practice (ORS Office of Research and Scholarship, 2023). With the assistance of these sections, the students get the chance to identify problems—general and specific—that their project aims to solve, formulate purpose statements that outline the objectives of the project, and formulate clear project questions. Reflection on Connections Between Resource and Doctoral Capstone Guidebook Theoretical and Conceptual Frameworks Webinar Recording The material presented in the webinar and the guidelines discussed in the Doctoral Capstone Guidebook are very similar. This aligns with the guidebook’s suggestions to identify a specific and clearly worded project question that is compatible with the purpose statement and the chosen method. In the guidebook and webinar, the method choice and his/her reasons for choosing it are highlighted. DHA Learner Huddles: Gaps in Practice Webinar Recording The video’s ideas meet the requirements and recommendations in the Doctoral Capstone Guidebook, as illustrated below. They share the same characteristics in that they both involve the problem statement, purpose statement, project questions, and identified gap in practice. These elements are highlighted in the video to indicate that they should be well co-ordinated and consistent – which is also the main theme of the guidebook. [/blur_section] References for DB FPX 8720 Assessment 1 [blur_section id=”postinstructions” button=”Grab Capella References” form_id=”b4ab3ac”] Capella University. (n.d.). Gaps in practice. Capella University. https://strategiced.zoom.us/rec/play/edmvZ88vp6xXS7ClC-fR_OLZMKYqaiewDoYvfNC9IJT6HGRVr2Mv4RvGw1HX53kQDld_fMMQujHL9oyv.DRa5ooesjvPPHIBD?canPlayFromShare=true&from=share_recording_detail&continueMode=true&componentName=rec-play&originRequestUrl=https%3A%2F%2Fstrategiced.zoom.us%2Frec%2Fshare%2Fq7LFE729hfp-q-1rhI9_z1Jb09VJ37CvgKFcT7u_C3DDrdQTC-6rmDAsJnVrIE8._v7RINT_7a2PoVyP Capella University. (2024). Theoretical and conceptual frameworks webinar recording. Capella University. https://strategiced.zoom.us/rec/play/YzCM3lPkvAw3Zcy34MnOLI9Zw1szGExu06Swm3xKsjQsZfA0ySs8kugUVjPWfloK_gPOC9Kdmb-BAfjQ_-k840xTwLC7PUpxn?canPlayFromShare=true&from=share_recording_detail&continueMode=true&componentName=rec-play&originRequestUrl=https%3A%2F%2Fstrategiced.zoom.us%2Frec%2Fshare%2Fl_JI2EL_oTzk1UqIButgsvOfEui0sFyIVCCq132e-qh0MobykdvcMtLlYjB8KPIr.qLDtGtEzbVmHvftX ORS Office of Research and Scholarship. (2023). Doctoral Capstone Guidebook. ORS Office of Research and Scholarship. https://www.capella.edu/online-phd-programs/capstone/ [/blur_section]

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