How LIMS Facilitates Lean ManufacturingProcesses in the Laboratory

by Simon Wood

Despite the well-documented success oflean manufacturing in the past decades,by and large, laboratories have beenslow to adopt lean manufacturing prin-ciples to help improve their perfor-mance and the services they provide totheir customers. Yet this is far fromunavoidable. On the contrary—as data-rich environments very familiar withprinciples of measurement, laboratoriesare actually well positioned to effec-tively implement and take advantage oflean improvement techniques. Giventhe growing business pressures toincrease laboratory efficiency levels, weare likely to witness a shift toward leanprocesses in the laboratory-centricorganization. Whereas in the past a lab-oratory could delay product, batch, orlot release, the manufacturing environ-ment of tomorrow will not tolerate suchinefficiencies. As manufacturers andresearch organizations streamline theiroperations across the board, laborato-ries will also need to be seen as efficientand effective parts of the supply chain.

The tools for leanimplementationThere are two main reasons that labo-ratory data are not already used tooptimize laboratory processes. First,laboratories have not been compelledto improve their performance in thesame way as manufacturers have. Sec-ondly (and partly as a result of the firstreason), LIMS and laboratory infor-matics suppliers have not provided thetools to help laboratories improvetheir performance. However, both ofthese conditions are rapidly changing:Laboratories are increasingly pressuredto improve their performance, and theResource Planning and Scheduling(RPS) module (STARLIMS Corp.,Hollywood, FL) was designed specifi-cally to make this possible. The RPSmodule was developed by STARLIMSin conjunction with Tefen OperationsManagement Consulting.

The role of measurementAt the heart of any lean initiative orany continuous improvement initia-tive is measurement, i.e., measure-ment to help users understand theircurrent position so that improvementscan be identified, and measurement tohelp users understand if the improve-ments have been successful. TheDMAIC methodology used in sixsigma (which can form an importantpart of any lean initiative) is an excel-lent example of this. DMAIC standsfor Define, Measure, Analyze,Improve, and Control:

• Define the problem in the business• Measure current capabilities as

they relate to the problem• Analyze the problem to discover

the root cause• Improve the process• Control the process to maintain

the improvements.

Clearly, measurement is a vital part ofa number of these stages. It is difficultto improve what cannot be measured,

and measurement is necessary to eval-uate success. The measurement mustthen be continued to ensure that theimprovement is maintained.

When considering lean processes andcontinuous improvement in the labora-tory environment, measurement will beas important as in any other area, envi-ronment, or business. Because the labo-ratory environment is one in whichmeasurement and observation are keyprocesses, the concept of measurementwill be very familiar to all laboratorystaff. Laboratories are also exceptionallydata-rich environments, especially if thedata and information generated by thelaboratory are effectively managedthrough the use of systems such as LIMS.

Leveraging data to streamlinelaboratory processesIn addition, closer scrutiny of labora-tory processes will make it less accept-able than ever for the laboratory todeliver suboptimal results in terms ofthroughput and cost. For example, a

Figure 1 The STARLIMS Dashboard is personalized for each role and user. It summarizes themost relevant information in real time, and presents it graphically as a set of Key Performance Indi-cators (KPI).

Reprinted from American Laboratory September 2006

laboratory must know the minimumnumber of samples required to cost-justify running an autoanalyzer or high-throughput instrument—managing itsthroughput and backlog accordingly. Inaddition, laboratories will need to reactmore readily and rapidly to the chang-ing needs of their customers; this meansbeing able to quickly modify laboratoryand instrument setup, and maintainingmultiskilled and cross-trained staffcapable of taking on a variety of roles.Such processes are essential to main-taining and improving efficiency levels.

Laboratories are data-rich environments,but unfortunately these riches have notbeen invested to improve laboratory per-formance. For example, backlog reportscan provide valuable data in managingday-to-day laboratory operations, andturnaround time (TAT) measurementscan be used to monitor performance lev-els. In particular, laboratories with LIMSin place have deep stores of informationthat can help improve laboratory perfor-mance in multiple scenarios.

Resource planning andscheduling in the laboratoryThe RPS module looks at all aspects ofresource availability, resource utilization,and workload to help laboratories man-age their operations. Within a lean oper-ation, the module can help eliminatewaste by identifying where time is spentwithin the laboratory and how that timeis split between value-adding and non-value-adding activities. In the same way,the module identifies bottlenecks withinthe laboratory process, helping to opti-mize the flow of samples and data (seeFigure 1). This naturally facilitates elevat-ing quality levels. In addition, the com-prehensive data and information avail-able can be used to generate theknowledge that helps establish a trulyefficient system within the laboratory.

To optimize work scheduling, the RPSmodule analyzes the work that needs tobe completed in terms of delivery com-mitments, analyst qualifications, work-load and instruments, equipment avail-

ability, and more. In addition, it allowsfor reporting of laboratory performanceincluding backlog reporting, cycle timereporting, productivity, and measure-ment of other key performance indica-tors identified by the laboratory. Withthis information, laboratory managerscan identify reasons for failing to meettheir target and take action to rectifyany outstanding issues. For example,analysis of this type may identify a lackof qualified analysts to carry out a spe-cific task, and then targeted and cost-effective training can be undertaken.

While the scheduling module itself is ofsignificant value to any laboratory, theRPS module also includes a planningmodule. This permits planning and sce-nario analysis, including the ability tocarry out “what if” analyses. Theresource planning module enables thedetermination of resource requirementsfor a given time period, taking intoaccount expected workloads from allpossible sources, staff, and equipmentavailability. It therefore allows labora-tory managers to determine if addi-tional resources will be required to com-plete a given task (see Figure 2). Suchadditional resources may include short-term contract staff, retrained and cross-trained internal staff, new or upgradedequipment, and the arrangement ofoutsourcing services to handle excessdemand. Using “what if” models, man-agers can gauge the effect of additionalresources (additional shifts, new equip-ment, etc.) or growing demands (higherregulatory requirements, response to apublic health emergency, etc.).

The RPS module is designed to inte-grate with any existing LIMS to extractdata that already exist within the labo-ratory environment, giving managersthe data they need to improve the per-formance of the laboratory operation.Far from simply managing laboratorydata, the RPS is a true business manage-ment system that adds real value to thelaboratory and the business as a whole.

Dr. Wood is Director, Professional Services,STARLIMS Corp., 4000 Hollywood Blvd.#515S, Hollywood, FL 33021-6755, U.S.A.;tel.: 954-964-8663; fax: 954-964-8113;e-mail: simonw@starlims.com.

Figure 2 Clearly presented trend data help managers allocate resources effectively.