Discuss One Project Where You Used Problem Solving Approach

Discuss One 1 Project Where You Used A Problem Solving Approach To A

Describe a project where you employed a problem-solving approach to address a situation involving common-cause variation or a process improvement approach to deal with a special cause. If you lack a personal experience, use an internet search to find a case that exemplifies either of these situations. Examples include personal investment strategies since 2008, reducing waiting times at a hospital or emergency room, or overcoming difficulties in connecting to a Wi-Fi provider.

In your response, answer the following questions: Describe the experience in the project, including the solutions used to address the problem. Determine whether the case was a special-cause or common-cause variation. Do you believe the solution or approach was appropriate for the cause? What would you do differently if you could redo the project? Finally, draw conclusions about the problem-solving or process-improvement techniques employed.

Note: You may create or make necessary assumptions to complete this assignment. While you can reference processes from your current or former employment, ensure you remove any identifying information that could reveal the organization(s) involved.

Paper For Above instruction

In analyzing problem-solving approaches within project management, distinguishing between common-cause and special-cause variations is crucial. This classification guides the selection of appropriate strategies to diagnose and resolve issues effectively. Here, I discuss a project where an improvement initiative was undertaken to reduce patient waiting times in an emergency department (ED), which ultimately involved addressing common-cause variation through targeted process improvements.

The project aimed to decrease patient wait times from an average of 60 minutes to under 30 minutes during peak hours. The primary challenge was the persistent delay that affected most patients, suggesting a systemic issue rather than an isolated problem. The initial step involved data collection, including patient flow data, staffing schedules, and process times. Analysis revealed that the bottleneck was primarily due to inefficient triage procedures and uneven staff deployment, indicating the presence of common-cause variation. These variations are inherent to the system and require process-level changes rather than isolated fixes.

To address the issue, the team employed a process improvement methodology rooted in Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control). The 'Analyze' phase revealed that variability was mostly predictable and attributable to the standard process design. Consequently, solutions focused on streamlining triage protocols, reallocating staff based on patient volume forecasts, and implementing point-of-care testing to expedite diagnostics. These interventions aimed to reduce systemic variability, aligning with strategies to manage common-cause variation.

The approach was appropriate because it targeted the systemic sources of delay rather than treating individual cases, embodying principles of process stability and continuous quality improvement. Post-implementation data demonstrated a significant reduction in wait times, confirming the effectiveness of modifications aimed at controlling common-cause variation. The project underscored the importance of understanding the nature of variation before selecting an intervention, advocating for process-centric solutions rather than symptomatic fixes.

If given the opportunity to repeat the project, I would incorporate real-time data monitoring tools earlier in the process to enable proactive adjustments. This real-time feedback could facilitate quicker detection of new sources of variation, maintaining process stability and further improving patient flow. Additionally, broader staff engagement and training in lean methodologies could foster a culture of continuous improvement beyond initial interventions.

From a broader perspective, this project exemplifies how recognizing the type of variation informs the choice of problem-solving techniques. Managing common-cause variation necessitates systemic process improvements, emphasizing process analysis and redesign. Conversely, addressing special-cause variation involves isolating and mitigating anomalous events. The project reaffirmed that a structured approach—grounded in data analysis and process understanding—is vital for sustainable improvements in healthcare operations or any other organizational setting.

References

• Langley, G. J., Moen, R., Nolan, K. M., Nolan, T. W., Norman, C., & Provost, L. P. (2009). The Improvement Guide: A Practical Approach to Enhancing Organizational Performance. Jossey-Bass.
• George, M. L., Rowlands, D., Price, M., & Maxey, J. (2005). The Lean Six Sigma Pocket Toolbook: A Quick Reference Guide to 100 Tools for Improving Quality and Speed. McGraw-Hill.
• Benneyan, J. C., Lloyd, R. C., & Plsek, P. E. (2003). 『Quality improvement studies in healthcare』. Quality & Safety in Healthcare, 12(6), 459-464.
• Spath, L. (2004). Multifaceted Process Improvement Programs—Part 1: Results of a Review of Published Literature and Other Sources. Joint Commission Journal on Quality and Safety, 30(11), 611-620.
• Antony, J., Snee, R., & Hoerl, R. (2017). Management and success of Six Sigma projects in organizations. International Journal of Quality & Reliability Management, 34(2), 167-181.
• Clarke, R. J. (2009). Healthcare quality improvement and project management: Lessons from a front line perspective. BMJ Quality & Safety, 18(4), 251-256.
• Hughes, S., & Athanassiou, N. (2017). Using Lean and Six Sigma in Healthcare: A systematic review. Journal of Health Organization and Management, 31(6), 748-771.
• Koskosas, I. V., & Iliakis, S. (2013). Applying Process Improvement Methodologies in Healthcare: A Systematic Literature Review. Procedia - Social and Behavioral Sciences, 73, 565-571.
• Moen, R., & Norman, C. (2006). Evolution of the Continuous Improvement Movement. The Journal of Healthcare Quality Improvement, 12(3), 23-29.
• Crump, R., Cooper, D., & Bosger, J. (2019). Data-Driven Healthcare: How Analytics and Data Science Are Transforming the Industry. Elsevier.