THE ANALYTICAL LABORATORY AS FACTORY - ACS Publications

THE ANALYTICAL LABORATORY AS FACTORY: This is the first in a series of A/c INTERFACE articles that will address the issues of analytical laboratory management with particular emphasis on integrating information technology. We will look at changing corporate management styles and certain technological forecasting issues and examine changes in benchmarking, work flow, operational research, total quality management, information distribution, and implementation strategies. The future is a foreign country—things are done differently there. Some fear of change is normal, but rejection of needed change is lethal. Previous A/c INTERFACE articles

have often focused on the technology itself. This series will examine the changes and benefits that technology can bring to the laboratory. The intent is to expose managers to new trends and tools so that they may better develop or defend scenarios suitable to their environment. Articles will be written by individuals with considerable industrial experience in a respective area and will provide background information, pertinent vocabulary, and literature references for further reading. This article will demonstrate why these topics were selected, explain the bonds connecting them, and address the first topic area: "The Analytical Laboratory as Factory." Raymond E. Dessy Series Coordinator

Raymond E. Dessy Chemistry Department 0212 Virginia Polytechnic Institute and State University Blacksburg, VA 24061

Samples go into an analytical laboratory—results and reports come out. Parts go into a factory—subassemblies and complete products come out. The analogy is obvious. The wave of change affecting businesses and plants should also be influencing the analytical laboratory. Yet most analytical chemists are content to roam the library and look only at publications on chemical science, which have "RS" call numbers. They seldom visit the sections with call numbers "HD," "HE," and "T." These categories deal with business and management science, which can contribute equally to success. Increased sample load, the need for great precision and accuracy at low concentrations, regulatory and fiscal imperatives, work force reductions, and increased automation place tremendous pressures on laboratories. In addition, laboratories must become more proficient in scheduling and using both personnel and instrumentation, in converting data into information and knowledge, and in relaying results in a timely, simple manner to customers. New instrumentation and automation are not enough to meet these challenges. The laboratory manager needs to understand and introduce the tools of project management, information

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transfer, and work reengineering that already have been applied successfully in other disciplines. The effectiveness of automation depends on organizational preparedness and acceptance of the type of work and management environment that is required by integrated information technology (IT). This article addresses some of the operational, logistic, and strategic issues that are essential for an analytical laboratory to meet current and future demands. It focuses on the various ways to improve the efficiency and effectiveness of laboratory management. The new LIMS

Currently available laboratory information management systems (LIMS) are merely laboratory data management systems. What they do not supply, but should, are data on sample preparation and analysis time as well as data on instrument and personnel use. These systems should also have the ability to present the status of a project in various ways and to analyze report distribution and use. This information can be used to model laboratories after factories; then performance can be evaluated and future operations can be improved. Such statements immediately engender animosity among most scientists because they feel that laboratories cannot be treated as production environments because of the nature of the work. This is not true. PERT/CPM and beyond. The tools for analyzing complex laboratory operations are available (1-4). Most scientists are familiar with the 0003-2700/93/0365-802A/$04.00/0 © 1993 American Chemical Society

A Metaphor for Our Times performance evaluation and review technique (PERT) developed by t h e Navy; Lockheed; and Booz, Allen & Hamilton to optimize time-to-completion for the Polaris missile project. The critical path method (CPM) was originally developed by DuPont and Remington Rand Univac to optimize cost v e r s u s t i m e for m a i n t e n a n c e and construction. Tasks analyzed by PERT traditionally have been variable, with a large uncertainty in the performance t i m e of a n y activity. CPM has been used in deterministic cases in which small variations are involved. Modern software has gradually merged t h e s e tools. It is now possible to t r e a t modern analytical laboratory problems by t r a d i n g off time, cost, and resources. Suitable mainframe packages exist, and n u merous microcomputer packages are available (la, 1c). The concepts of project m a n a g e ment are simple. The most familiar form of r e p r e s e n t i n g a c o m p l e x project is the Gantt chart, which is a histogram that illustrates the length of time and, perhaps, the money and energy involved (Figure la). Limited information is available about the synchronicity among the various operations. To show the complete interconnectivity of the operations, each task is broken down into subactivities, represented by arrows. Figure l b shows nodes, representing significant event m a r k e r s , t h a t are connected by arrows indicating the sequences and pathways involved in reaching the goal. The most revealing project representation is a timescaled network (Figure lc). This pre-

sentation is essential if the primary consideration is to avoid overloading labor or facilities. Often an alternative view is used, in which activities are represented at nodal points; this is called precedence d i a g r a m m i n g (la). Software can prepare and play "what-if" scenarios to assist the laboratory manager in decision making. Project m a n a g e m e n t methods are used to find where slack exists in a system. Slack is the amount of time by which the actual completion of an activity can exceed the earliest expected completion time without delaying the overall goal. A laboratory manager might also be interested in deadtime or resource allocation. For example, studies in one laboratory reveal t h a t in chemical extraction, thin-layer chromatography, clinical diagnosis, g a s - l i q u i d chromatogra-

AND, exclusive OR, and inclusive OR, as well as b e t t e r ways of h a n dling stochastic, deterministic, and p r o b a b i l i s t i c c o n d i t i o n s (2). Cons t r a i n t s such as t h e sequencing of activities, nonconcurrency of certain tasks, and inability to split (or interr u p t ) t a s k s m a y be i n c l u d e d . R e source utilization (Figure Id) may be a d d r e s s e d by a p p r o a c h e s d e r i v e d from the original SPAR program (la, 3). Tools are available that use icons a n d s p r e a d s h e e t t e c h n i q u e s . Even discrete event dynamic systems, such as totally automated, evolving plant and laboratory operations, have been addressed (4). Discrete s i m u l a t i o n and anim a t i o n . A hospital clinical laboratory is faced with scheduling the act i v i t i e s of a n o p e r a t o r w h o is responsible for several instruments.

A/C INTERFACE phy, and colorimetric analyses, direct labor or attention is not required 6 0 - 7 5 % of the total time (5). An analyst's efficiency is increased if other tasks are scheduled for this time. Industrial engineers have produced successive generations of helpful p r o g r a m m i n g t e c h n i q u e s a n d languages for project m a n a g e m e n t . Graphic, modeling, and simulation programs (such as GERT, Q-GERT, SLAM, TESS, and GPSS) led to the introduction of logic elements into the project network diagram to handle c o m p l e x i n t e r r e l a t i o n s h i p s . These include functions, such as

One i n s t r u m e n t is a highly a u t o mated sample preparation unit t h a t requires loading samples into an input tray, filling an output tray with empty aliquoting vials, and unloading diluted sample vials. The instrument sounds an alarm when it is eit h e r empty or filled and t h e n stops operating u n t i l it is serviced. How long can the unit be left at a standstill, while the operator tends to another task, without adversely affecting the efficiency of the operator or the unit? This case was modeled by discrete simulation computer tools using ani-

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Figure 1. Various ways of viewing the same project. (a) Typical Gantt chart shows a collection of tasks comprising a project. The horizontal bars represent relative completion times. The thickness of the bar represents cost estimates. (b) Project network diagram with activities represented on the branch lines interconnecting the nodes that represent significant event markers. The interdependency of the tasks is more evident than in the Gantt chart. Ε can start as soon as Β is finished. The last part of Ε cannot begin until E1, A3, C, and D2 are finished. Numbers under the arrows represent relative completion times. The "dummy" line represents a synchronizing constraint, (c) A time-scaled network showing dotted lines that represent slack paths requiring less time to perform than allowed (float time). Activities B1, C, and D3 have no slack components and represent the critical path (CP). (d) Resource allocation diagram. (Adapted with permission from Reference 1 a.)

mated visual icon images of all com p o n e n t s (Figure 2a). It w a s found t h a t t h e o p e r a t o r could leave t h e sample preparation unit idle for as long as 15 min. Any less and the op erator was being used inefficiently; any more and the sampler was being used inefficiently. The 15 min was

long enough to allow the operator to service a n o t h e r i n s t r u m e n t . T h i s type of time and motion study is sel dom performed in analytical labora tories, except by guess. Yet, easily used PC tools based on t h e classic general purpose simulation system (GPSS) package were used in t h i s example (6, 7). Multidimensional structures, technological forecasting, and s c h e d u l i n g . The modern laboratory is often complex. It is possible to en vision many networks that lie on in teracting planes. In some cases the planes are parallel and are connected only at one or two points by junction lines. Some planes intersect, creating many j u n c t u r e points. These s i t u a tions are often encountered in tech nological forecasting. They have been h a n d l e d by w h a t is called a s e m i M a r k o v i a n a p p r o a c h (8). T h i s method is based on the assumption t h a t s e q u e n t i a l technological p r o cesses involve an uncertain sequence of d e v e l o p m e n t a n d a n u n c e r t a i n l e n g t h of t i m e b e t w e e n successive steps. Software is also available to h a n dle the scheduling of analytical ser vice laboratories where new samples are constantly being added to the in put s t r e a m . Unilever (The N e t h e r lands) has achieved a 30% through p u t i n c r e a s e by u s i n g s c h e d u l i n g software. Long-, intermediate-, and short-term rescheduling is necessary to optimize t h r o u g h p u t of samples. Such p r o g r a m s m a y also t a k e into c o n s i d e r a t i o n s u d d e n losses of r e sources. One software program, CLARA, h a s been designed to work with either h u m a n or robot operators and is robot h a r d w a r e - i n d e p e n d e n t (Figure 2b, 2c) (9). Linked integrated manage m e n t system. For most applications of project management the concepts are simple, t h e tools are available, and the terminology is easy to learn. Professionals are available to adapt the LIMS to the laboratory. So, why are they not being used? The expla nation lies in the traditional belief t h a t t h e previously mentioned a p proaches cannot satisfactorily be ap plied to p u r e r e s e a r c h o p e r a t i o n s . However, e n v i r o n m e n t a l a n a l y s i s , q u a l i t y control, d r u g m e t a b o l i s m , and pharmacokinetics laboratories are not Monte Carlo situations. These methods are therefore applica ble and essential. A good LIMS would provide m a n a g e r s w i t h a view of t h e i r existing systems as well as the facts and tools to improve t h e m (10). Such a LIMS would incorporate information about


time, energy, synchronicity, and r e sources. It would allow direct access to the proper project planning, oper ations research, and simulation/ a n i m a t i o n software. Expert system and automatic knowledge extraction tools would be readily available. This would lead to a true information age for the analytical laboratory, or what Alvin Toffler h a s called t h e " t h i r d wave." Combining operational, logis tic, a n d s t r a t e g i c tools, t h i s e n t i r e p a c k a g e m i g h t be b e t t e r called a "linked integrated management sys t e m " — a t r u e LIMS for our t i m e s (Figure 3). We will explore this con c e p t in m o r e d e t a i l i n a n a r t i c l e planned for the future. Chaos Currently t h e r e is interest in plan ning systems in which small isolated changes produce large impacts or in which total system behavior cannot be determined by combining models of subsystems (2). This area is called spatial dynamics. It recognizes t h a t technological, political, and societal p r e s s u r e s induce n o n l i n e a r evolu t i o n a r y p a t t e r n s , bifurcation, a n d chaotic behavior (8). I n f o r m a t i o n c h a o s . Chaos can come from many sources. Each form can be suppressed in unique ways. A previous article in A/C INTERFACE (11) focused on computers t h a t cre ated data faster t h a n they could be used or stored properly for future re trieval, and an analogy to chaos the ory w a s d r a w n . Look a r o u n d your l a b o r a t o r y . You may a l r e a d y h a v e access to a LIMS, a n electronic li brary, and online corporate reports. E x a m i n e w h a t is a v a i l a b l e e x t e r nally. Sources for information could include the traditional Chemical Ab stracts Service or Dialog services, Ci t a t i o n Index, and the N a t i o n a l Li b r a r y of Medicine d a t a b a s e s . Less t r a d i t i o n a l sources include WorldWide Web (WWW), Wide Area Infor mation Service (WAIS), and the Go pher functions. In m a n y cases the computer may unleash a "sorcerer's apprentice" t h a t drowns us in a deluge of watery facts. The heterogeneity of the mate rial, its transient value, poor presen t a t i o n , a n d irreconcilable f o r m a t s lead to information t h a t cannot be used. This problem m u s t be solved before those who desire to convert i n s t i t u t i o n s into a n "electronic vil lage" succeed. Windows Online, an electronic bul letin board, is a n excellent example of what a good user interface can do. It is essential that systems in the in dustrial laboratory reflect what cus-

tomers want, not what implementers desire. Bringing order out of the chaos of unpalatable implementa tions is an essential step. Structural chaos. Laboratories have traditionally relied on collect ing data in a horizontal domain and feeding a muddle of middle manage ment. Middle managers condense the data into information that is passed on to those in higher manage ment. Operational, logistic, and stra tegic systems are separated by a ver tical corporate structure and by barriers that distort communications within the organization (Figure 4a). Computers have made it possible to convert this "inverted-T" decision structure into an "A-frame" that as sumes a more horizontal architec ture (Figure 4b). The goal is to bring those who collect data and informa tion and those who run operations and logistics closer to those who use the knowledge and make strategic decisions. This compression elimi nates management levels that add "noise" to the system or subvert the flow of information for their own in terests. This is another step in bring ing order out of chaos. S o c i e t a l c h a o s . The rapidly changing nature of technology and politics poses a problem to institu tions not prepared for change. Fear of change is endemic, but it is possi ble to learn how to cope and take ad vantage of the swirl of events. The recent pressures on pharmaceutical firms by governmental bodies, citi-

Figure 2. Modeling, simulation, and scheduling approaches. (a) A single frame from a simulated animation series of a clinical laboratory. Real time is shown in each frame (courtesy of Wolverine Software, Vancouver General Hospital, and Andronic Devices, Ltd.). (b) Robotic setup menu screen for analysis of a sample requiring sequential addition of five different reagents with a time delay between each addition (courtesy of Scitek). (c) Individual and collective sample activities suggested by a scheduling algorithm. Each sample bar represents sequential dispensing of five reagents into the mixture (each reagent is represented by a different color). Time offsets for each addition are determined by the chemistries of the systems. Starting times for samples are staggered by a scheduling algorithm to optimize the resources of the robotic system. The solution shown would probably not be obvious to the human scheduler (courtesy of Scitek).

Figure 3. Linked integrated management systems. The χ dimension displays levels of available facts; the y dimension, levels of corporate planning; the ζ direction, levels of corporate functioning. Highlighted are the location of classic LIMS, electronic notebooks, and a powerful decision support system at the intersection of knowledge, reports, and strategy (upper left). In most installations, only the lower right-hand corner and production operations research tools (in the center) have been implemented (10).


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zens, and political action committees have been acute. Some industries are rapidly responding by increasing efforts to create common access structures to databases, using expert syst e m s to c a p t u r e knowledge t h a t is disappearing as a result of early r e tirement and downsizing, and introducing techniques to accommodate a work force declining in technological

ability. Scientific electronic n o t e books, automatic knowledge acquisition tools, and a new focus on project planning methods are being funded. This positive response is akin to the flourishing of mammals as the dinosaurs died out. Of the almost 50 prescriptions t h a t Tom Peters recommends in Thriving on Chaos (19), his book for the busi-

ness community, at least half apply directly to analytical laboratories. A few t h a t are immediately evident include u s i n g m u l t i f u n c t i o n a l , selfmanaging teams for all R&D activit i e s , s u p p o r t i n g f a s t f a i l u r e s to encourage innovation (i.e., p e r m i t ting short-term, high-risk ventures), designing some h u m a n slack in the system to allow prototyping and exploration, reducing vertical layers of management, increasing the span of control of supervisors, encouraging supervisors and managers to be facilitators and boundary smashers, sharing virtually all information, and decentralizing strategic planning.

Chaos as a p o s i t i v e d r i v i n g force. Analytical laboratories should use chaos advantageously and allow it to drive change. Yet we see comp u t e r s emulating established m a n ual systems or robots mimicking the h u m a n worker. Blind or politically e x p e d i e n t a d h e r e n c e to t r a d i t i o n , stagnating government regulations, or m i s u s e of technology cannot be tolerated. For companies to survive, they m u s t evolve, not revolve. Current pressures in the pharmaceutical i n d u s t r y are forcing desirable changes t h a t make the organization more efficient and capable of m a n u facturing products in a shorter time f r a m e . P r e s s u r e s to m e e t t h e d e mands of European Community competition have led petrochemical and i n s t r u m e n t a t i o n f i r m s to a d o p t ISO 9000 standards (12, 13). People and companies benefit from change. As chaos increases it is i m p o r t a n t t h a t effective communication p a t h ways exist in the h u m a n or corporate brain to affect new responses. The trilogy by Alvin Toffler, Future Shock (14), Third Wave (15), and particularly Powershifl (16), is essential reading for the chemical manager. Of equal interest is the trilogy by Tom Peters, In Search of Excellence (17), A Passion for Excellence (18), and particularly Thriving on Chaos (19). Another book of interest by Peters is Liberation Management (20). Less known, but most enlightening, are Management in the Third Wave (21) and Information Anxiety (22). Communication—then and now

Figure 4. Types of organizational structures. (a) Classic vertical "inverted T-square" structure with long communication pathways, (b) Evolving "A-frame" horizontal structure with more efficient communication.


S t u d i e s done before t h e c o m p u t e r age indicate t h a t there are different modes of accessing "messages" leading to t e c h n i c a l i d e a s r e l e v a n t to problem solving in t h e l a b o r a t o r y (23). Technologists tend to rely about equally on customer and vendor contact and on analysis and experimentation time (~30% each). Scientists place a heavy emphasis on the liter-

a t u r e (—50%) and previous experience (—20%). The ratio of literature use to total communication time reveals that technological problems involve relatively more communication w i t h colleagues t h a n do scientific projects. This difference in contact with others is not merely q u a n t i t a tive; it also involves interaction with diverse types of people and distinctive ways of communicating. These studies also reveal t h a t in most organizations t h e r e are inform a t i o n g a t e k e e p e r s who a r e u s e d heavily as internal contacts and consultants. The cost in time and energy to the gatekeeper is obvious. In addition, it is e s t i m a t e d t h a t each PC used in i n d u s t r y requires - $ 2 0 0 0 $4000 per y e a r of h i d d e n i n t e r n a l consulting support. The cost engendered by inefficient a p p r o a c h e s to asking any technical questions internally is equally hidden. F e a r of a p p e a r i n g i g n o r a n t a n d losing one's reputation within an organization leads to a reluctance to communicate openly or to use external consultants. Other strategies involved in asking questions are selfdenigration to a p p e a r h u m b l e a n d reading manuals or contacting neutral acquaintances to obtain information. Even the physical layout of t h e l a b o r a t o r y a n d office space is critical in face-to-face encounters. When territorial or building bounda r i e s need to be crossed, or s t e p s need to be climbed, communication efficiency drops. The electronic laboratory age offers a plethora of new communication p a t h w a y s , such as voice-mail, e-mail, fax, and video and audio conferencing, which require changes in work h a b i t s a n d c o m m u n i c a t i o n styles. The electronic library necessitates even more drastic changes. Few o r g a n i z a t i o n s r e c o g n i z e t h e need to analyze how scientists should and will use the new communication links. Some interesting questions to ask yourself are: Does your laboratory r o u t i n e l y save or d i s c a r d old e-mail messages? Is the distribution list c a p a b i l i t y of e - m a i l u s e d too much or too little? Do users tend to treat e-mail as a low-resolution media, with informal chatter and misspellings commonplace? Have users learned to use voice-mail properly? Do engineers and scientists use teleconferencing as efficiently as a group meeting? How has library use been changed by computers and networking? Is internal fax transmission of library articles in use? Are m u l t i media CD-ROM materials available over the network? Does the labora-

Management should spend more time in horizontal communication than in vertical communion tory electronically access external lib r a r y m a t e r i a l s ? Are e x t e r n a l and internal special interest group bulletin boards utilized? Are you permitted to use Internet-type contacts? In short, does your organization have a l o n g - t e r m p l a n for effective electronic communication, are you using the new technologies, have your work habits altered, and h a s the change been productive? C h a o s r e s o l u t i o n . In many companies computerization and networking have led to a glut of m a t e r i a l t h a t no one knows how to use effectively and to a network communication pathway t h a t is not used or is m i s u s e d . Effective n e t w o r k i n g should dissolve b o u n d a r i e s w i t h i n the organization and increase com-

munication efficiency. This can happen only when users are receptive to using tools and are championed by a chief information officer (CIO) who has technical mastery, empathy for the user, and power—a "white knight." The most effective CIOs report directly to the CEO. Laboratories might well look to Banc One and Kmart as examples (24). If electronic communication begins to change how we ask, what we ask, and who we ask, then a new group of gatekeepers arises. They are the scie n t i s t s , information technologists, expert-system builders, or management information systems personnel who m a y be far removed from t h e work group m a n a g e m e n t . As such decentralization occurs, m a n a g e ment must restructure itself and its reward system.

Inverted pyramid of management It is common to look to J a p a n as an e x a m p l e of effective r e s p o n s e to stress. We now know that the highly touted industry, university, and government consortia controlled by the Ministry for International Trade and I n d u s t r y (MITI) h a v e been highly o v e r r a t e d . M I T F s focus on fifthgeneration computers and the steel i n d u s t r y was misguided. I n d u s t r y , n o t g o v e r n m e n t , focused on consumer electronics, photographic devices, and the automobile. Neglect of the telephone, pharmaceutical, and PC arenas has left J a p a n far behind in many important areas. The United States should now be taking advantage of the chaos created by this situation.


A/C

INTERFACE book Riv Pyramidema! (26) focuses on the need to f l a t t e n t h e t r a d i t i o n a l pyramid of m a n a g e m e n t (Figure 5) a n d to invert its orientation. Management supports the operating unit by providing proper training and resource c e n t e r s a n d by e l i m i n a t i n g cross-functional bottlenecks. Management should spend more time in h o r i z o n t a l communication t h a n in vertical communion. This is possible w i t h t h e c o m p u t e r tools a n d n e t works available. This compression actually increases information exchange within the organization. Pathways become shorter and more immune to noise. B e n c h m a r k i n g . The first step in r e s t r u c t u r i n g involves e x a m i n i n g yourself by benchmarking the labor a t o r y a n d its u s e of technical a n d h u m a n r e s o u r c e s . I n a d d i t i o n to comparing your laboratory with others and auditing the performance of y o u r o p e r a t i o n s , you s h o u l d a s k yourself the following: Is there good internal communication? Do internal divisions coordinate their work? Are there redundant tasks? Are there excessive m a n u a l data validation steps? Are tasks requiring good synchronization really coordinated? Are personnel r e w a r d e d in h u m a n and fiscal ways? Has a common database descriptor approach been considered? Have ISO 9000 standards been developed? Is the infrastructure for automation and networking in place? Is a useful compound document arc h i t e c t u r e s t a n d a r d in use? (Compound document a r c h i t e c t u r e cons i s t s of mixed t e x t , g r a p h i c s , and chemical formulae t h a t are created, stored, and shared electronically.)

Figure 5. Changes in organizational structures. (a) Top and side views of the pyramidal organizational structure, (b) Inverting and flattening the old authoritarian management pyramid and reducing the layers of middle management to give the lab a new supportive structure with improved communication flow.

Table I gives the views of Japanese strategists on the contrasts between t h e two societies (25). Recognizing t h a t each society's approach is a p p r o p r i a t e for c e r t a i n c o n d i t i o n s , w h a t m i x t u r e of q u a l i t i e s w o u l d make your laboratory better able to adapt to the chaos that surrounds it? Experience suggests t h a t attempts to coalesce older management styles with uncoordinated technical center automation have led to a tangle, r e sembling t h e V a t i c a n s c u l p t u r e of Laocoon and his two sons entwined in the coils of serpents. J a n Carlson's

Networking Binding together all of this change is the network infrastructure. The software a n d h a r d w a r e of today's networking technology is a prime example of chaos. Real s t a n d a r d s do not exist. Excessive hype permeates the field. Most systems t h a t have been installed are rapidly approaching a critical point. When an E t h e r n e t uses 20% of its bandwidth, the system response will begin to deteriorate and new technology must be installed. The telephone companies and new network vendors are competing for a large and important part of t h e corporate budget. Observers face vexing worries t h a t short-term m a r k e t i n g a n d political s o l u t i o n s may lead to a dead end (27). Transmission over copper wires is being pushed to higher speeds, b u t wires have a finite bandwidth. Digital telco switches also are a potential


bottleneck. Optical fiber offers speed and bandwidth t h a t promise to make communication costs insignificant, allowing d i s t r i b u t e d c o m p u t i n g to become a reality. Some see wireless digital signal transmission techniques as the new wave. However, are t h e necessary s t a n d a r d s really going to be developed? What will the actual installed costs be? Cost overr u n s during installation of distribu t e d p r o c e s s i n g a r e commonplace (28). Will c o m m u n i c a t i o n or comp u t e r costs be t h e l i m i t i n g factor? C a n we t r a i n people to t h i n k in a distributed fashion even if automation permits it? Conclusion As this series develops it will become obvious t h a t the major problems are not technical in n a t u r e . Difficulties arise from t h e rapid changes bombarding us, our reluctance to change, and power structures t h a t refuse to evolve to meet corporate needs. The question is: Can scientists and mana g e m e n t c o n c u r r e n t l y a d a p t fast enough to meet the challenges? Major contributions to this work were made by Malcolm Crook (Process Analysis and Automation), William Godolphin (Vancouver General Hospital), Steven Hamilton (Scitek, USA), Robert McDowall (McDowall Consulting), Greg Paris (Ciba Geigy), and Scott Stauffer and Harry Kriz (Virginia Tech). Unnamed, but vital and not to be forgotten, are the scores of scientists in industrial laboratories who provided me with opportunities to learn of the unique problems facing analytical chemistry as we worked together to solve their problems. References (1) a. Moder, J. J.; Phillips, C. R. Project Management with CPM, PERT, and Precedence Diagramming, 3rd éd.; Van Nostrand Reinhold: New York, 1983; b. Awani, A. Project Management Techniques; Petrocelli Books: New York, 1983; c. Kliem, R. The Secrets of Successful Project Management; John Wiley and Sons: New York, 1986. (2) Pritsker, A.A.B. Papers, Experiences, Perspectives; Systems Publishing: West Lafayette, IN, 1990. (3) a. Weist, J. D.; Levy, F. K. A Management Guide to PERT/CPM; Prentice-Hall: Englewood Cliffs, NJ, 1969; b. Woodworth, B. M.; Willie, C. T. Decision Sciences 1975, 6, 525. (4) Discrete Event Dynamic Systems; Ho, YuChi, Ed.; IEEE Press: New York, 1992. (5) Richmond, C. Lab. Pract. 1988, 37, 31. (6) Godolphin, W. Presented at the 2nd International Conference on Robotics in Laboratory Medicine, Montreux, Switzerland, Feb. 1993. (7) The work uses GPSS/H and ProofAnimation software from Wolverine, Inc., Annandale, VA. Inexpensive tutorial versions, Getting Started with GPSS/H and Using Proof Animation, are available; cf. Schriber, T. An Introduction to Simulation Using GPSS/H; John Wiley and Sons: New York, 1991. (8) Kamann, D. F.; Nijkamp, P. Technolog-

American Chemical Society Presents ical Forecasting and Social Change 1 9 9 1 , 39, 45. (9) CLARA is available from Scitec SA, Avenue de Provence 20, 1000 Lausanne 20, S w i t z e r l a n d ; S c i t e k C o n s u l t i n g USA, Suite 105, Barksdale Rd., Newark, DE. (10) Robert McDowall, McDowall Consulting, personal communication, 1993. (11) Dessy, R. E. Anal. Chem. 1992, 64, 733 A. (12) Thayer, A. M. Chem. Eng. News 1993, March 1, 12. (13) M a t h r i e , O. B.; H u n t , O. R.; B a r e foot, A. C ; Conaway, J. E. ACS short course "Good Laboratory Practices and ISO 9000 S t a n d a r d s " ; ACS: Washington, DC, 1992. (14) Toffler, A. Future Shock; R a n d o m House: New York, 1970. (15) Toffler, A. Third Wave; Morrow: New York, 1980. (16) Toffler, A. Powershift, Knowledge, Wealth, Violence at the Edge of the 21st Century; Bantam Books: New York, 1990. (17) P e t e r s , T. In Search of Excellence; Harper and Row: New York, 1982. (18) P e t e r s , T. A Passion for Excellence; Random House: New York, 1985. (19) P e t e r s , T. Thriving on Chaos: Handbook for a Management Revolution; Harper Perennial: New York, 1987. (20) P e t e r s , T. Liberation Management; A. A. Knopf: New York, 1992. (21) Raymond, H. A. Management in the Third Wave; Scott Foresman: Glenview, IL, 1986. (22) W u r m a n , R. S. Information Anxiety; Bantam Books: New York, 1990. (23) a. Allen, T. J. Managing the Flow of Technology: Technology Transfer and Dissemination of Technical Information within the R&D Organization; MIT Press: Cambridge, MA, 1979; b. Williams, F.; Gibson, D. V. Technology Transfer: A Communication Perspective; Sage Publications: Newbury Park, CA, 1990. (24) LaPlante, A. Forbes ASAP, 1992, December 7, 32. (25) Kagano, T.; Nonaka, I.; Sakakibara, K.; Okomura, A. Strategic vs. Evolutionary Management; North Holland: New York, 1985. (26) Carlson, J. Riv Pyramiderna! (English translation Moments of Truth); Ballinger Publishing: New York, 1987. (27) a. Gilder, G. Forbes ASAP 1992, December 7, 1 1 1 ; b. Forbes ASAP 1993, March 29 96. (28) L a P l a n t e , A. Forbes ASAP 1 9 9 3 , March 29, 22.

Raymond E. Dessy is emeritus professor at Virginia Polytechnic Institute and State University and the first recipient of the ACS Computers in Chemistry Award in 1986. He inaugurated the A/C INTERFACEfeature in 1982 and edited the series through 1986. In collaboration with many of his 100 pre- and postdoctoral associates, he has taught ACS short courses on laboratory automation to more than 5000 students worldwide since 1970. His current research group focuses on the development ofbiomicrosensors, chemical applications of expert systems and neural networks, and devices for separation of biomacromolecules. He also lectures and consults on technical center computer integration technology.

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