Organize a Project

This assignment is intended to help you use leadership skills to gather project members from cross-functional departments and skill sets and lead them in the fulfillment and implementation of a mock project.

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Discoverthe various responsibilities of a project manager by organizing a project. See Chapter 19, sections 19.9 and Cases.

Apply project management tools and a PM outline type of your choice to structure and plan the project by defining, planning, and controlling. The project will be a continuation of how to improve the process you chose in Weeks 1 and 2.

Create a presentation (supported by Excel and Word as needed), with detailed speaker notes, that includes the following:

Project description

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Project Management Charts (Critical Path, Gant Chart, etc.)

Improved Process Flowchart from Week 1

Meeting cadence/rhythm and timing

Metrics to measure the project’s success

  • Financial and budgetary considerations
  • Description of the project reporting structure
  • Cite references to support your assignment.
  • Process Improvement Flowchart
    University of Phoenix
    OPS/574
    As-Is Process Flowchart Evaluation
    As-Is Process Flowchart
    Below is the as-is process flowchart for the online order fulfillment process at Walmart: Below is
    the as-is process flowchart for the online order fulfillment process at Walmart:
    Customers place
    an order online
    Order is received
    by Walmart
    Order is recorded
    in the system
    Fulfilment centre processes the order
    Items are picked from inventory
    Items are packed for shipping
    Order is shipped to the
    customer
    Order is sent to the
    nearest fulfilment
    centre
    Evaluation of As-Is Process
    The As-Is process was made subject to process improvement techniques, including Value Stream
    Mapping (VSM) and Root Cause Analysis (RCA), to evaluate its effectiveness. Here are the key
    findings:
    Bottlenecks: The bottleneck in the order processing time due to the prolonged periods spent at
    the fulfillment centers is an obvious but unavoidable problem.
    Redundancies: Some packing operations contain repetition, including
    redundancies, hence causing inefficiencies.
    Errors: An error in order picking is usually observed, and wrong items shipped to the customer
    arise.
    Process Improvement Flowchart
    Improved Process Flowchart
    According to this evaluation, automation can enhance procedures, and the implemented steps can
    be minimized.
    Below is the process improved flowchart:
    Order is received
    by Walmart
    Customers place
    an order online
    Order is recorded
    in the system
    Order is sent to the
    nearest fulfilment
    centre
    Fulfilment centre processes the order
    Items are picked from
    inventory
    Items are packed for shipping
    using automated system
    Order is shipped to the
    customer
    Customer Receives
    the order
    Automated
    feedback system
    collects customer
    feedback for
    continuous
    improvement
    Executive Summary
    The process under examination is Walmart’s online order completion process. It consists of
    several stages of processing the employee’s orders, picking, and packing the products, which
    causes overflows, keeping the elemental cycles, and mistakes. These types of inefficiencies have,
    therefore, a negative influence on the overall satisfaction level of customers as well as the longterm performance of the company, which consequently calls for an in-depth analysis and reform
    of the process (Lukinskiy, et al., 2023)
    Applying the Valued Stream Mapping (VSM) and Root Cause Analysis (RCA), fundamental
    problem points were detected in the current process. The biggest challenges we face are shipping
    and fulfilling the order because it takes very long administrative actions. It is also the reason why
    the process of packing could be more active, and we have frequent mistakes in picking. These
    inefficiencies lead to an increase in the order processing times, less order accuracy, and
    dissatisfied customers via the process of customer satisfaction.
    To tackle these issues, a process aimed at automation was introduced as a solution. Many
    systems had automation that handled diverse tasks, for example, order allocation, picking, and
    packing. By utilizing advancing technologies like robotics in picking and packing processes, the
    overall steps are easily managed, decreasing the reliance on human labor and error-prone human
    workmanship (Orman et al., 2022).
    The new process flow chart illustrates a faster system with a higher degree of efficiency, where
    automation is a core element in speeding up the process and improving the accuracy level. The
    indicators employed to assess the process cover order processing time, order accuracy
    percentage, and customer satisfaction rate. These metrics will only present a comprehensive
    picture of the process and the critical elements for further enhancement.
    Metrics and Measures
    Order Processing Time: This measures the length of the delivery process, from customers’ order
    placement to the end of fulfillment.
    Order Accuracy Rate: Learn the ratio of orders handled and quoted without spelling mistakes
    or other errors.
    Customer Satisfaction: The level of customer fulfillment is checked using delivery surveys,
    which help us gather such data.
    Order Processing Time: Implementing such technology will directly affect the time between
    handling the order process (allocation, picking, and packing) and having the order shipped to the
    customer. Delivery time speed and the capacity for the system to handle a number of orders
    within the same time duration further enhance performance.
    Order Accuracy Rate: Automation helps eliminate risks of human error that may result in hightech accuracy rates. This results in fewer discrepancies, whereby wrong items are not shipped to
    customers. Ultimately, this improves customer satisfaction and saves on the costs of returns and
    corrections.
    Customer Satisfaction: Shorter processing times and more precise results are also significant
    components of this highest level of customer experience. Satisfied customers have a much higher
    probability of returning and suggesting the service to others; businesses prosper.
    The process improvement project involves several key steps:
    Implementing Automated Systems: The key to the outcome is replacing manual order picking
    and packing procedures with automatic systems. This integration should be effected so that the
    newly designed system merges with the existing ordering system.
    Training Staff: Employees will require training to work and maintain the new automatic system
    installations. This training comprises various tasks such as exploring the technologies, resolving
    issues, and ensuring the operations’ functionality.
    Continuous Monitoring: The critical factor is ensuring the performance metrics are monitored
    continuously to detect new problems or issues. Customer feedback should be taken seriously and
    utilized to improve our product continually.
    Hence, Walmart is able to improve the order fulfillment process by being more precise and
    efficient and putting the client first. The planned benefits, such as improved processing time,
    accuracy, and customer satisfaction, will go a long way in the company’s operations and will also
    give the company a competitive advantage.
    References
    Lukinskiy, V., Lukinskiy, V., Ivanov, D., Sokolov, B., & Bazhina, D. (2023). A probabilistic
    approach to information management of order fulfilment reliability with the help of perfect-order
    analytics. International Journal of Information Management, 68, 102567.
    Orman, K., Romano, G., Tee, A., Thornburgh, J., & Turner, M. (2022). Walmart: Predictive
    planning, ordering, and monitoring.
    Theory of Statistical Process Control and Process Improvement
    Theory of Statistical Process Control and Process Improvement
    Statistical process control (SPC) is one type of quality control that utilizes statistical tools
    to monitor a process. SPC assists in keeping the process at optimal performance by generating
    more goods according to specifications with less material quantity classified as spoils or
    reversion. SPC involves measuring any method with a measurable output that is a ‘conforming
    product,’ which is a product that meets specifications.
    Lean Concept and Waste Elimination
    Lean manufacturing, as opposed to lean production, can be described as an efficient
    means of eliminating wastage in the manufacturing system without compromising on the
    system’s efficiency. Lean also defines overburden as another type of waste, and the condition
    where the workload is not evenly distributed is another type of waste. Lean manufacturing aims
    to reduce the amount of waste and promote efficiency and effectiveness or improvement through
    continuous improvement methodologies. Lean on the concept of many tools and techniques,
    among them Value Stream Mapping (VSM), which maps and analyses the flow of material and
    information.
    Use of Six Sigma for Defect Mitigation
    Six Sigma is defined as a methodology used to provide solutions for improving
    organizational processes. Six Sigma was pioneered by Motorola engineer Bill Smith in 1986
    while developing the technology for enhancing semiconductor yields (Tran et al., 2022). Six
    Sigma methods aim to address the quality of the output of a process by eradicating the sources of
    deviations and reducing the extent of fluctuations in manufacturing; this is done with statistical
    analysis and by training and assigning specially created roles within the organization (Black
    Belts or Green Belts) to experts in these techniques. By definition, every Six Sigma project in an
    organization has phases and instructions to be followed sequentially. In contrast, the project’s
    goal or objective is expressed in monetary values, such as cost reduction or profit improvement.
    Using SPC methods- Process evaluation
    In evaluating a process using SPC, several steps are involved:
    Identify Critical Quality Characteristics (CQCs): These are the main factors that should be
    controlled and tracked closely to ensure that the overall process stays under control.
    Data Collection: Gather information about the above-stated CQCs; this can be done through
    sample techniques. In this regard, the view held here is that the generalization from sample to
    population is achievable in one of the following ways:
    Create Control Charts: Control charts are essential tools of SPC. They plot specific variable
    data over time to look for evidence that the process is out of control. The X-bar, R, and S charts
    are the most commonly used control charts in organizations.
    Analyze Control Charts: Check the control chart to note any sign of a process or pattern that
    might indicate it is out of control. Such can imply looking for trends, shifts, or any other point
    that may lie beyond the control limits.
    Implement Process Improvements: The conclusion from the above analysis includes making
    necessary adjustments to ensure that the process is brought back into control and that the
    capability is improved.
    Control Chart and Process Metrics: Control charts and other process metrics are used as
    process control tools to monitor and regulate process performance.
    The Use of SPC Methods to Evaluate Control Charts
    Calculation of Metrics: Real numbers like mean, range, and standard deviation, as well as
    process indices like Cp and Cpk, should be computed.
    Developing Control Charts: Control charts should be constructed for the above process metrics
    on motor parameters. For example, an X-bar chart can be used to observe the changes in the
    process mean over time, while an R chart can be used to observe the range or variability.
    Evaluating the Control Chart: Control chart analysis involves looking at plotted points about
    the control limits to determine whether they allow process control. Patterns within the control
    limits and points outside the control limits can be explicit indicators of particular cause
    variations.
    Process Capability Analysis: A process’s center line measures the data’s average in process
    capability analysis. At the same time, the range determines the spread of the process data to the
    specification limits. These measurements also assist in establishing how well the process will
    perform given specifications.
    Process Improvement Flowchart
    Therefore, a process improvement flowchart should be developed and worked on to
    facilitate a schematic view and analyze the process stages. Thus, this is useful for determining
    where changes can be made within a process, whether that change can be made by an automated
    system, whether a step can be removed, and whether the number of errors in a process can be
    reduced.
    Lean and SP (Statistical Process) Control Techniques – SN2 Executive Summary
    Summary of Process Evaluation: Lean was applied to analyze which process steps added value
    for the consumers and defined inefficiencies as wastes. Essential zones to focus on include
    incorporating waste within the packing process cycle and mistakes of order picking.
    Evaluation of Control Chart and Process Metrics: Other tools used included control charts,
    which were established for significant measures such as the order processing time, the rate of
    order accuracy, and the level of customer satisfaction. By scrutinizing these beans, it was easy to
    identify points in the process that needed to be controlled.
    Use of Six Sigma and Lean Tools: A study was conducted to determine the degree of Six
    Sigma and Lean in the process, and it was identified that the process leverages benefited greatly
    from these tools. These tools supported the reduction of variability and the number of defects,
    better process control, and increased capability and effectiveness.
    SPC Project and Recommendations: The various technical solutions in the SPC project
    included the mechanical replacement of manual order picking and packing. Other measures
    included training staff on new systems implemented for the organization and monitoring the
    process to enhance the process for the future (Yuan et al., 2020). The benefits derived from the
    improvements were improved response time, reduced probability of order errors, and improved
    customer satisfaction.
    References
    Yuan, C. C., Chung, W. H., Cai, C., & Sung, S. T. (2020). Application of statistical process
    control on port state control. Journal of Marine Science and Engineering, 8(10), 746.
    Tran, P. H., Ahmadi Nadi, A., Nguyen, T. H., Tran, K. D., & Tran, K. P. (2022). Application of
    machine learning in statistical process control charts: A survey and perspective.
    In Control charts and machine learning for anomaly detection in manufacturing (pp. 7–
    42). Springer, Cham.

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