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Maintaining quality in the service industry just got easier
September 11, 2015
By: volker hack
PPD
Quality in the service industry is difficult to maintain due to complex processes. It is estimated that 30-50% of the costs in a service organization are related to process inefficiencies as well as the challenges of meeting individual client requests.1 Several techniques have been developed to improve processes in the service industry, such as Business Process Modeling (BPM), Total Quality Management (TQM), Continuous Quality Improvement (CQI) and Lean Six Sigma (LSS).2 Lean Six Sigma principles LSS is a business management strategy originally developed by Japanese manufacturing industrialists to improve product quality and decrease production inefficiencies and costs.2 There are two distinct components to the LSS strategy—Lean and Six Sigma. Lean represents a systematic process management approach by which inefficiencies are eliminated. It begins with assessing work flow via “value stream mapping”2 to identify areas that need improvement. Processes are improved by eliminating non-value added activities that absorb time and resources, such as unnecessary process steps or production downtime due to delays in an upstream process. Six Sigma aims to improve quality by managing “quality at the source” and reduce process variation and defects by using a robust and systematic five-step approach known as DMAIC (see figure 1) to help organizations strive for excellence and a competitive edge. Figure 1: Five-step methodology (DMAIC) of Six Sigma1 LSS combines the best of Lean and Six Sigma models to provide a customer-service driven, systematic and measureable process improvement model that can significantly impact clinical research and drug development by decreasing cycle times and expenses while simultaneously improving deliverables and customer satisfaction.2 LSS concepts initially were applied to health care and pharmaceutical industries in the 1980s.2 The U.S. Food and Drug Administration (FDA) and other regulatory agencies adopted the methodology to shift to a process and quality improvement-centered approach in order to increase safety and quality control defined by current good manufacturing practices (cGMP). In 2009, the National Institutes of Health (NIH) developed a road map for medical research in an effort to improve clinical research processes by funding research institutions through the Clinical and Translational Science Awards (CTSA) program.2 LSS is now used widely in the clinical trial industry by pharma companies, contract research organizations (CRO), laboratory vendors, Phase I units and Institutional Review Boards (IRB).2,3 However, LSS and other process improvement methodologies are highly disciplined processes that require trained process improvement analysts to guide project teams through the rigid methodology. The programs are resource and time intensive, making them difficult to implement and execute. This article addresses the use of LSS principles in the CRO industry by focusing on typical client services, such as customer progress reporting, contract negotiations and team communications, to identify opportunities for enhancement beyond process improvement initiatives. The authors suggest that LSS techniques are relevant for the daily work outside of the rigid process improvement methodology because they allow teams to identify innovative solutions that create value for the customer by challenging the status quo and viewing their work from the customer’s perspective. In addition, this article points out that LSS can benefit the individual through increased ownership and job satisfaction. Five lightweight techniques using LSS principles in your daily work If you doubt LSS principles could support your daily work, you should ask the following questions: Do I ever wait unnecessarily because an upstream activity was not delivered on time? How often do I have to chase down information to complete a task? Do I ever redo work because something failed the first time? Do the processes I use include unnecessary steps, lead to duplicate efforts or frustrate because of their unpredictability? Is information I need ever lost? Does communication ever fail? Am I confronted with an unhappy client due to a low-quality deliverable or significant variation in quality over time? If you answered yes to any of these questions, then you need to ask why, how can it be changed, what can be improved and how do you initiate these changes, as depicted in figure 2? Figure 2: Flow diagram of executing change2 The following are typical issues a project manager in clinical research might face. By using a process improvement mentality with LSS principles, resolutions could be identified quickly. Issue #1: Services that are not adding value to the customer (e.g., study progress report covering multiple non-relevant key performance indicators) Tip: When working on a project progress report, you should consider which components are relevant for the customer. Ask for regular client feedback and include a checklist regarding the usefulness of key performance indicators with each progress report. Eliminate everything that is no longer required and try to automate the remaining data input in order to reduce the time for creating the progress report and to simultaneously improve quality for the client. Issue #2: Significant variation in project process (e.g., development of a contract modification took much longer than expected) Tip: When trying to solve a problem you want to identify underlying causes, which will help you prevent fires rather than just extinguishing them. The most common root-cause analysis (RCA) methodology is “Asking the Five Whys.” Follow these steps to identify the root cause: Bring relevant parties together, avoid “blaming the bad apple” and concentrate on the process breakdown. Discuss the potential root cause of the issue by repeatedly asking “why,” develop a solution, share lessons learned with stakeholders and establish some effectiveness checks of implemented actions. This will lead to improved learnings from previous errors, prevent recurrence and reduce variability of results.4 Here is an example:
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