An MES Reality Check

Aug. 5, 2005
Simple survey methodology may be used to determine real-dollar ROI for MES platforms.
Ross Benson

A Manufacturing Execution System (MES) is a software-driven, client-server or web-based network designed to link plant floor data to broader enterprise resource planning (ERP) platforms, so that information to any department within a facility can be transferred in real time, accelerating troubleshooting and reporting. A growing number of pharmaceutical manufacturers today are using the technology as a final tie-in, to key manufacturing and decision-making functions, as well as product release, into one common network.The arguments for moving to an MES platform are compelling. In reports provided by the MES Association (MESA), a consortium of hardware and software vendors, companies claim that 50% to 80% of their paper batch records contain errors, putting added pressure upon quality assurance personnel, production planners and supervisors. In some cases, it can take reviewers several weeks before records are processed and the errors caught. This presents more problems as the trail of batch tracking grows cold and many errors may not be explained due to the elapsed time since processing.If implemented properly, an MES system can enable near-paperless batch processing, allow for integrated electronic signatures, and help with developing and maintaining bills of materials and equipment, and dispensing raw or in-process materials. By integrating plant floor IT and ERP, MES allows operators to key in current batch data at any point within a manufacturing process so that the data are available, in real time, to all areas of production, planning and supervision. An MES eliminates various manual data entries, manual calculations, manual checks and the “opportunity” to miss a step. For example, operators no longer have to check their calculations; the system will do the calculations for them via formulas entered into the master recipe by an author. This eliminates errors, which in turn helps reduce cycle time. Manufacturing operators no longer need to read a scale weight and write down the weight. The system automatically retrieves the weight from the scale and places it in the electronic batch record. This also eliminates errors and will then automatically compare this weight to the weight obtained in the dispensing operation while informing the operator if there is a discrepancy.This process streamlines the product release by reducing the number of after-the-fact checks that are needed. Each manufacturing area performs these after-the-fact checks in accordance with its own policies. Some facilities have associates check calculations and other entries after each manufacturing operation. Other areas have associates check at the end of the entire manufacturing process. An MES network offers savings opportunities in both of these areas.At its core, MES tracks work-in-process through detailed product routing and tracking, labor reporting, resource and rework management, production measurement and data collection. Since data are transferred in real time, batch evaluations and updates can occur almost immediately and be sent to relevant departments — for example, quality control, document management and plant-floor dispatching. Finding the real-dollar impactHowever, an MES platform is not a small budget item. Implementation costs range from an average of $1 million to $6 million, and annual support and licensing fees can run into the tens of thousands. Given the costs involved, most pharmaceutical manufacturers are content to stick with more limited Manufacturing and Resources Planning (MRP) systems. Corporate management typically requires substantive data to convince them that investing in an MES system will add to the corporate bottom line.An economic analysis of the Return on Investment (ROI) and the costs and benefits of installing an MES system is imperative, both for pharmaceutical manufacturers who are evaluating the software, and for those who have already implemented it, to gauge its impact on their ongoing operations. And this research must determine the real-dollar impact that the platform has on the key performance indicators (KPIs) at any pharmaceutical manufacturing facility:
  • cycle time
  • cost of goods manufactured
  • direct and indirect labor hours required for batch processing
  • deviations per batch.
This article will propose a survey methodology that might be used to gauge the ROI, actual or potential, of an MES platform in a pharmaceutical manufacturing operation, in real-dollar terms, using these KPIs. Functionality and financeData are available on the benefits of MES systems. Software providers, both independently and through MESA, sell their products based on the probability of what an MES network might do for a given manufacturing company [1]. Much of what is available focuses on functionality, not finances, to justify the use of an MES. The push to “zero errors” is cited as a major driver for implementing MES for pharmaceutical manufacturing operations. Vendors typically promise that MES will reduce manufacturing costs, improve compliance with Good Manufacturing Practices (GMPs), and reduce process deviations and inventory levels (Box).To gain objective data, any pharmaceutical manufacturing team that is evaluating the use of MES should examine initial implementation costs, the feasibility of using an MES network within its environment, and the technical support staffing and network maintenance costs involved. These factors are beyond the scope of this article, which, instead, will suggest a way to survey staff.Setting up a surveyIn order to determine the KPIs, all production planners and quality reviewers at the site should be surveyed twice during each of two three-month intervals, to cover two full quarters of production and six months worth of fiscal data. Primary production planners would be asked to monitor KPIs on a weekly basis, using a production database with information from the MRP system to look at trending and monitor KPIs. The KPIs, in turn, would direct the analysis toward data that would differentiate between the two methods of batch processing, indicating either financial gain or financial loss. The data could then be used to compare KPIs for paperless vs. paper-based operation, and to trend and monitor them. Identical surveys would be sent to production planners and quality reviewers, although the QA staff would not use the special cross-referenced, production-linked database. A short, 10-question survey would be developed using a Likert scale method of recording. The data used to complete the survey would be derived from monthly or quarterly reports retrieved by both production planners and quality assurance reviewers containing KPI information. Each question would focus on an individual KPI that affects production costs, cycle time or batch processing problems.Production analysts’ input would provide an overview of the financial impact of EBR vs. paper processing based on KPI measurement. The survey would allow for percentages of change to be applied to each KPI associated with a particular type of batch processing, whether for solid oral dosage forms, liquids or other delivery systems.The survey would then be generalized and applied to all production staff at the facility to gain insight into product and process variations. This test and retest method would be used over two consecutive quarters to obtain a high reliability coefficient. This figure would then be averaged to eliminate any effects of trending on the analysis.Finally, the data retrieved from the surveys would be calculated and averaged prior to comparison with a baseline obtained through historical information on the same KPIs and product batch information before the implementation of electronic batch records (EBRs). Similar analysis of KPI data for companies that have not yet implemented MES would show areas ripe for improvement, and indicate where the technology might provide benefit. Statistical analysisThe KPIs would be the key factors in the statistical analysis. Once data from the surveys were totaled and separated into the two primary categories of electronic batch records or paper batch records, the results from each key performance indicator could be summed as follows: KPI(1) Survey 1 + KPI (1) Survey 2 + KPI (1) Survey 3 … = KPI(1) TotalThe KPI totals could then be compared between the two subgroups to determine a dominance of one subgroup KPI over another. In individual KPI instances, this may result as a cost saving or an increase in expense. In some instances, both paper and non-paper data are collected. Data collection specialists (QA) may or may not have data available in parallel for similar products where one has been converted to MES and the other has not. However, a phased approach to implementation allows this information to be collected. The implementation should begin with the process or product whose ROI has the highest impact, and progress in a phased approach from there. The final step is to review historical data gathered prior to the implementation of electronic batch records for the exact products examined in the survey. This would eliminate any product-specific characteristics that might cause variations in the manufacturing costs. More likely than not, this research will vindicate the decision to implement an MES. But it can also be a useful tool for fine-tuning the implementation, or, for companies still on the fence, can either challenge or support investing in the software.References1. MESA International. (1997). MES Reference Materials from MESA International [Online]. Available: the AuthorRoss Benson is head of engineering and maintenance at Martec Pharmaceuticals, Inc. (Kansas City, Mo.). He has more than 18 years of manufacturing experience in various industries, including automated food processing, aerospace, healthcare and pharmaceuticals. He has held positions in assembly, engineering, management, technical development and quality assurance. Ross holds a Master of Science in Industrial Management from Central Missouri State University. Contact him at [email protected]
About the Author

Ross Benson | Head of Maintenance and Engineering