Building a Smart Laboratory 2012 Business requirements


respective analytical methods, regardless if working on paper, hybrid systems or fully electronic systems. To support the human work, we should


also provide automation in the form of integrated laboratory instrumentation with data handling systems and laboratory information management systems (LIMS) as necessary to perform the work. In any laboratory, this integration needs to include effective audit trails to help maintain data integrity and monitor changes to data. Supervisors and quality personnel must monitor these audit trails to assess the quality of data being produced – if necessary a key performance indicator (KPI) or measurable metric could be produced.


Knowledge management


When it comes to purchasing and implementing laboratory systems soſtware, return on investment is inevitably one of the key drivers. Te up-front requirements to justify the expenditure are usually aligned to process improvement and productivity. However, there are oſten secondary and unquantifiable requirements about improving knowledge management in the organisation by sharing and making lab information accessible across departments, sites and geographies. ‘Knowledge management’ is the term


being applied to the processes that address this gap. Te term carries with it some semblance of a business fad since it comes with its own language and mystique, but the reality of business dependence on knowledge means that there is a growing requirement to do something to manage the organisation’s intellectual capital. Knowledge management is a business


initiative that has become increasingly familiar in recent years amongst organisations striving to compete effectively in the information age. In some respects knowledge management is a logical progression from TQM (total quality management) and


BPR (business process reengineering). TQM defines the concept of continuous incremental improvement (doing things well) through a data-driven, statistical quality control approach. BPR represents a paradigm shiſt (doing things better) by introducing high level, re-designed, integrated processes that exploit information technology. Knowledge management extends these


processes by addressing the contribution that the organisation’s collective knowledge can make (doing better things) by taking into account the skills, expertise and personal knowledge of the workforce. It is perceived by many as a mechanism for manufacturing and service operations to bring about business transformation through alignment with the benefits and demands of the ‘information age’. What is knowledge management?


Very simply, it is a term used to describe the processes which bring people and information together to address the acquisition, processing, storage, use and re- use of knowledge to develop understanding and to create value. Te ultimate objective is to improve the performance of the business


“Te ultimate objective is to improve the performance of the business and maximise the value of its intellectual capital”


and maximise the value of its intellectual capital. In some respects, knowledge management is part of a continuum that starts with data management and progresses through information management. However, the transition between data and information is governed by rules and context. Te transition between information and


knowledge is governed by context, but also by the application of a number of human qualities such as insight, understanding, intuition, skill and experience. It is this human element that sets knowledge management aside from TQM and BPR;


knowledge management is about people, not about information technology. Definitions, theories and strategies about


knowledge management abound to the point of confusion. It comes with, inevitably, its own taxonomy and semantics to add to the confusion. However, the basis for knowledge management can be represented by three fundamental components: 1. Enabling technologies (typically information technology – but it could be pencil and paper!);


2. People (the organisation, its behaviours and culture);


3. Processes which bring people and information together (the knowledge processes). Te principles of knowledge management


(KM) all make good sense, it’s just that an ‘industry’ seems to have grown around the topic that sees it as a potential revenue stream. Te following conclusions add some perspective: • KM solutions do not come in a shrink wrap box;


• You cannot implement KM, it is an outcome;


• KM is about people – technology can facilitate good KM, but that’s all. Basically, information technology is a big part of the problem, but a small part of the solution.


Longer-term benefits accrue from sharing and making information accessible, ensuring that systems are easy to use, and evolving a culture based on collaboration. In terms of the smart laboratory, three simple rules are: 1. Align knowledge management initiatives with business strategy – KM has, eventually, to deliver some bottom-line results otherwise it will have no credibility;


2. Integrate knowledge management processes into the corporate culture – if it’s not ‘the way we do things around here’, in terms of behaviour and culture, it will not get any sustainable buy-in;


3. Deliver the right information to the right people at the right time – if the ‘technology enablers’ are not doing the right things, the strategy will collapse.


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