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A commodity item or strategic business system?

The multitude of commercially-available laboratory information systems (LIMS), and the fact that so many laboratories now have them installed, indicates that a LIMS package has become a piece of commodity software – an item that a laboratory must have to be in business, but which may not provide real business and competitive advantage, akin to the word processing or spreadsheet software used in the lab. However, whether or not this is the case clearly depends on how the role of LIMS is looked at within the context of both the laboratory and the organisation as a whole, and therefore of necessity the role of the laboratory itself within the organisation. In addition to this, LIMS' overall role within laboratory informatics, which encompasses much more than just information management, must be considered.

This article will look at the role of LIMS within the laboratory and the organisation to see if it is really a commodity item or if LIMS should be a truly value-adding system used to support the strategic decision-making process within the laboratory and the business as a whole. It will also show how the history of LIMS has meant that some laboratories have not been well served by existing commercial systems, and how these issues are being addressed in the commercial market.

Is LIMS a commodity product?

Unfortunately the answer to this question is both yes and no – and, to discover why, we need to look at some of the history of LIMS, its adoption and its use. There is a case for saying that LIMS have traditionally, and most successfully, been deployed within routine testing laboratories, such as manufacturing QA/QC and water testing laboratories. These laboratories can be described as sample-centric. Samples are scheduled regularly and results are generally seen to be of importance only if they are outside of specification or if they are part of a sequence of results showing a defined trend. Within a properly-controlled business or operation, therefore, the majority of test results are likely to be seen as having little intrinsic worth.

However, if we look at the laboratory in more detail and, in particular, the products of the laboratory, it can be seen that in the vast majority of cases three distinct products can be identified. These are data, information and knowledge. Data is used to create information which, in turn, can be used to help create knowledge. This cycle is illustrated in Fig 1.

Fig 1. The data, information and knowledge flow.

This cycle can be seen as a filtering process that takes a mass of data, transforms it into a reduced, but more meaningful, information set which, in turn, can be used to create or generate knowledge. In addition, as the data is 'transformed' to knowledge, its value increases and there is a change in how it is used and by whom, as illustrated in Fig 2.

Fig 2. The data, information, and knowledge flow indicating increasing value, decreasing volume, different users and differing usage.

Traditionally, in the sample-centric laboratory as outlined above, the majority of attention has been focused on the data and information part of the equation, with little attention paid to knowledge generation or management. This raises two issues:
1. Are organisations that have adopted this model missing an opportunity to gain real benefit from their LIMS?
2. If LIMS have traditionally been tailored to this type of environment, what can laboratories with a different focus be offered, i.e. R&D and analytical services laboratories?

A challenge to the traditional role of LIMS

LIMS have been successfully deployed in thousands of QA/QC-type laboratories throughout the world as sample management systems. However, the need for these basic sample handling systems may be called into question by the use of on-line and at-line analysers, the adoption and acceptance of practices such as Process Analytical Technology (PAT) and the integration of these with corporate systems such as MRP/ERP. Such systems are not LIMS, but their adoption opens the possibility that LIMS that have been implemented to meet just the data and information needs of a specific department within an organisation could be seen as redundant.

A well implemented LIMS can, however, be used much more effectively to provide real business benefit to the organisation by pushing into the knowledge generation part of the model shown above. However, this can only be done effectively if the type of knowledge required can be identified. This in turn requires an understanding of business needs and strategy of the organisation and consequently a close relationship between the laboratory, its customers and the business in general. Examples of this extension of LIMS capabilities can already be seen in some organisations where LIMS is a vital part of daily, weekly and monthly capacity planning that aids efficient and effective utilisation of the laboratory's resources – including people, equipment and space. The knowledge that this information can deliver can also be used to plan for future growth and change, which itself is a vital part of laboratory management. The knowledge generated, therefore, is used to make business decisions which, in turn, may change the data and information created. Similarly, more LIMS functionality deals with access to and from external systems rather than the more traditionally focused 'lab management information approach'. This then changes the data/information/knowledge cycle illustrated above to something more meaningful, as illustrated in Fig 3. The point to emphasise is that in the commercial area the creation of knowledge is only useful if that knowledge is used to make informed business decisions.

Fig 3. The data, information, knowledge and decision cycle

Another application for this enhanced knowledge management role of LIMS can be seen in the definition and management of service level agreements with customers. Accurate information about past performance can obviously be used to measure performance against agreed service levels (business targets) but, perhaps more importantly, it can be used to ensure that reasonable and attainable service levels are defined and that customer expectations are clearly set and managed.

It is only by moving away from LIMS as a sample management system to a true business system in ways such as described above that LIMS in this type of environment will move away from being a commodity item. However, it is incumbent on LIMS users themselves to identify how this can be done within their environment and to ensure that any system they implement can meet their identified business needs. To gain real business benefits, users must look beyond sample management and sample workflow to understand the role of the laboratory function within the organisation and the data information and knowledge needs that the business and organisation have.

LIMS within the R&D environment

Historically, LIMS have been less successful within R&D-type environments; or at least the internal rate of return has been less encouraging. As described above, LIMS have typically been implemented successfully in sample-centric environments. R&D laboratories tend, however, to be more project and result (data delivery) orientated with researchers being interested in all the results obtained from the work within the research project being undertaken. In other words, the totality of data and information generated is used to create knowledge for the research project being undertaken. Therefore, from a laboratory informatics perspective, it is important to be able to collect, store and – most importantly – retrieve all the data and information generated. However, the nature of research also means that much of the information generated may be unstructured and therefore not suited to storage within a typical LIMS database structure. For example, this type of information may include an individual's knowledge-based interpretation of data in the form of written reports, informal email discussion threads between colleagues and original raw data from instruments – as well as the results gained from desktop or enterprise processing environments, which may include comparison (i.e. library) systems for previous work. All of this information may be important for making informed decisions on a project, and it is in support of the decision-making process that knowledge generation and management provides real benefits.

Given the different needs of the R&D environment, it is not surprising that traditional LIMS may not have been successful within this environment. The last few years have, however, seen an increasing interest in products designed to meet the needs of the R&D and analytical services laboratory. Electronic Laboratory Notebooks (ELN) are perhaps the most familiar example of this type of system, but are dogged by a lack of proper understanding of exactly what they represent, which is a data collation, processing and reporting environment, not a wireless portable or tablet PC carried about the laboratory.

The need to be able to collect, store and retrieve data and information has also led to the development of Enterprise Content Management (ECM) systems specifically for the scientific market. These systems are designed to manage all the data and information of all types that is generated within the laboratory environment and, most importantly, make it easily available throughout the organisation. These systems have moved away from sample management systems, and indeed some models show LIMS as just one part of the laboratory informatics infrastructure that contributes data and information to the ECM. Perhaps it is the case that ECM may bypass ELNs before ELNs have really become established. But perhaps it is more likely that ELNs will become a crucial subset of ECM.

The adoption of ECM-type systems moves the laboratory informatics world more towards the ideal informatics situation as envisaged by many commercial organisations; i.e., the controlled management of all data and information within the organisation and the adoption of Business Intelligence (BI) tools to retrieve relevant and valuable information in support of strategic decision-making. While many organisations talk about this, actual examples of where this has been a strategic success may be harder to find. However, this should not prevent the laboratory from adopting this approach as a way of helping maximise its value to the organisation as a whole. Indeed, the specialist and self-contained nature of the laboratory and its associated informatics systems, make it a more controllable and manageable business model to work on.

Of course there is another area of LIMS that exists; these are specialised systems that address a specific laboratory function. Examples of these include systems for ADMETox, Pharmacokinetics and Biobanking. These systems are specifically tailored to these functions, but it must be remembered that the information contained within them is likely to be of value throughout the organisation and should be made available. The market is, by definition, not large, but a great deal of support is required to make any of these systems return high value to owners. Specialist applications of this type perhaps offer further evidence for the adoption of an integrated business approach to information management systems throughout the laboratory. It should be noted that the more specialised a LIMS, the more work (or expense) will be required to fill the 'white space' between applications within an organisation.


Any organisation that looks at a LIMS as a commodity item that just manages samples through the laboratory is missing the point. However, forward-thinking laboratories are looking at ways to gain additional benefits from the often large investment made in LIMS and therefore turning LIMS into a true business system. This may mean using the information that should exist within LIMS to help ensure the laboratory meets the strategic needs of the business and customers. Alternatively, an approach that is not that different, but which may be more relevant to R&D-type environments, is to ensure that information generated by the laboratory is efficiently managed in such a way that it is readily available and retrievable by the people who need that information to create knowledge and make decisions. This is the 'soft return' of informatics. While it may be difficult to measure, it can provide the biggest returns.

Any reputable LIMS designed for the QA/QC market should be able to meet the first set of needs described above, provided that the organisation itself knows what it is trying to achieve. However, the market for the more R&D-based approach is still relatively immature, and users looking to implement this type of solution need to approach the selection of any such system with caution. Some organisations will claim to supply this type of solution, but care will need to be made during the selection process. As is so often the case in the world of informatics, having the technology and having the ability to deliver a working solution may not be the same thing.

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