Vendor Column: Improving Laboratory Operations using Laboratory Informatics for Lean Six-Sigma Initiatives

Ezine

Published: Mar 20, 2012
Author: Chris Stumpf
Channels: Laboratory Informatics / Chemometrics & Informatics

thumbnail image: Vendor Column: Improving Laboratory Operations using Laboratory Informatics for Lean Six-Sigma Initiatives

Welcome to the third in a series of features from Chris Stumpf, a marketing manager at Waters Corporation who focuses on Lab Informatics. Every two months, Chris publishes a new informatics-related article which we hope will build into a worthwhile compendium of informatics material. This month, Chris discusses achieving quality goals by applying Laboratory Informatics and Lean Six-Sigma principles.

Many a scientist has experienced the thrill of implementing a software tool that took a week long manual operation down to a 5-minute automated step - this is laboratory informatics at its most dramatic. Although most people think of laboratory informatics as enabling faster throughput, there is also another aspect that is equally important, the improvement in laboratory workflow quality, e.g., providing real-time feedback, minimizing transcription errors, etc. In addition to efficiency and quality of laboratory workflows, most laboratories must also achieve a business objective. In industry, much of the focus is on generating profits through new product development and optimized manufacturing processes whereas in academia it is the pursuit of fundamental research that can ultimately be published. Workflow efficiency of product development and manufacturing becomes especially crucial because of market competitiveness, but quality perceived by the customer is arguably more important - i.e., maintaining brand integrity is critical for the long term success of any organization. This column will discuss achieving quality goals by applying Laboratory Informatics and Lean Six-Sigma principles.

While not initially focused on laboratory operations, large companies such as Motorola, Toyota, General Electric, and Honeywell had initiated continuous improvement programs in the 1980s and 1990s to improve quality (1). In the case of Motorola, they were having serious quality issues that threatened the business (1). To improve or repair product quality at these companies, the quality programs focused on gaining a statistical understanding of product quality and the methodology became known as Six-Sigma (Motorola holds the trademark for the term "Six Sigma") (1). The name of the game for Six-Sigma methodology is reducing product "variability", e.g., at the Six-Sigma statistical level there would be 3.4 defective products per 1-million manufactured products (1,2). Likewise pharmaceutical, fine & specialty chemical, and food & beverage organizations have also implemented continuous improvement programs to improve the quality of their products (3). The reported Sigma level for the pharmaceutical industry's production is approximately 3-to-4 Sigma (4-6) and to put this into perspective, at 4 Sigma there are approximately 6000 defects out of every 1-million products (1). Hence, a good deal of product is discarded after testing so that low quality product does not reach the consumer. Although the pharmaceutical industry is a relatively late adopter of Lean and Six-Sigma methodologies (4), the industry has enthusiastically embraced them and has benefited from leveraging a newer form of the methodology called Lean Six-Sigma(3). In this methodology, wasteful steps or operations are identified and minimized/removed and then statistical tools are applied to the remaining steps to decrease product variability - reducing waste and variability in that order.

For laboratory based operations, informatics offers many opportunities to minimize waste and variability beyond the dramatic speed enhancements highlighted previously. Available laboratory solutions include chromatography data system (CDS), scientific data management system (SDMS), and electronic laboratory notebook (ELN) as well as business systems such laboratory information management system (LIMS). For example, a CDS can automate chromatography testing, data processing, reporting, and approval, all within the same solution. However, many laboratories under utilize their CDS - leveraging only the data collection capabilities while calculations and reporting are performed in spreadsheets outside the software. The manual transfer of data into a spreadsheet for calculations not only wastes the analyst's time with unnecessary steps, but is also potentially error prone. Once the results are summarized, they usually need approval by a manager for intellectual property protection or regulatory compliance but this process can be wasteful (e.g., waiting for signoff approval) and error-prone (e.g., not always having the necessary information for sign off) when paper based. Making better use of basic CDS functionality could dramatically improve both analyst productivity and result quality. A more capable CDS can also provide a single global standard for data management and common workflows; not to mention removing the waste and variability in chromatographic method development and validation. Hence, simple changes to laboratory informatics infrastructure or making more complete use of existing solutions could reduce waste and variability in the chromatography laboratory.

Many industrial organizations (such as GE, Honeywell, etc.) provide green-belt level training to a large cross-section of their employees (1); however, laboratory based organizations such as those found in the pharmaceutical sector are typically more selective--only choosing a relatively small number of scientists and analysts(3). These green belt trained individuals will then spend a percentage of their time working on Lean Six-Sigma projects that are laboratory focused (usually for a set time of 1 or 2 years) (3). A few may even go on to achieve a black-belt certification (highly skilled experts who spend 100% of their time on Lean Six Sigma projects spanning the entire organization) and even the highest ranking, master black-belt (3). Lean Six-Sigma practitioners in laboratory based organizations often feel reluctant to run projects in regulated laboratories due to uncertainty around regulatory compliance hurdles or resistance from QC/QA staff; hence, they tend to move on to other areas where they can identify bottom line savings $150K or $250K (1,3). Ironically, since quality is indeed the mandate of the quality control lab, they stand to derive significant benefit from the quality improvements offered by Lean Six-Sigma. However, the major obstacle in regulated laboratories centers on the impact to validated processes (4). This is a legitimate concern, but even in regulated laboratories, older technologies are replaced and regulatory issues such as warning letters require changes to processes (4). These occasions may represent an opportunity to reevaluate the existing process to determine whether new workflows might be feasible including Laboratory Informatics solutions such as CDS, SDMS, ELN, and LIMS.

To evaluate existing workflows as a means of identifying opportunities for improvement, Lean Six-Sigma first focuses on reducing waste by identifying the seven kinds of waste -- Defects, Overproduction, Transportation, Waiting, Inventory, Motion, and unused Human resources.(2) Next, the focus turns to reducing variability by employing the five components of Six-Sigma called DMAIC (2) (pronounced "duh-may-ick"). The five components are as follows:

Define the problem
Measure key aspects of the current workflow
Analyze the collected workflow data to understand cause-and-effect relationships
Improve the workflows based on the data analysis
Control the implemented future state solution so that quality is embedded within the workflow

These steps should resonate with the typical analytical chemist or scientist given their similarity to the scientific method, which is a constant in any type of research. Of course, there are other tools utilized by Lean-Six Sigma, but they all help systematically break down the problem into component pieces, analyze the workflows, and then develop solutions for improvement. In a nut shell, Lean Six-Sigma is about taking a "systems" approach to laboratory workflow problems; collecting quantifiable data regarding the workflows, and then designing a solution that is efficient, cost-effective, and provides better quality.

In summary, Laboratory Informatics technologies are ideal for addressing Lean Six-Sigma initiatives since software platforms like a CDS for example can standardize result generation workflows, reduce waste and variability, and include common functionality (such as peak integration, reporting, and electronic signatures). Further, many laboratory informatics solutions are now capable of enterprise scalability (most advanced CDS, SDMS, ELN, and LIMS solutions) so that overall system complexity can be minimized, thereby further reducing waste and variability in everyday laboratory workflows. The next column will take a closer look at workflows that can be improved by Lean Six-Sigma and Laboratory Informatics.

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