The enterprise-level data delivery challenge
In the current global economic environment, where margins are scrutinised for every possible opportunity for efficiencies and cost savings, companies everywhere are facing the necessity of a reduction in their capital expenses as well as their operating costs. Companies that rely on laboratory data are looking for ways to make the most of the mountain of data they generate, and turn it into useful revenue-generating information. To increase the opportunities for laboratory-generated data to be able to deliver these results, companies are seeking ways to obtain tighter integration of their processes so that information may be shared and utilised across an organisation in ways that have the most direct impact on decision-making that affects the bottom line. Solutions providers are likewise delivering new methodologies that can provide the integration necessary to move laboratory-generated data into the core of the management decision-making process.
Barriers to making effective business decisions
One of the key challenges facing companies today is the inability to turn the vast amount of laboratory data into useful information that enables management at all levels of the organisation to make timely and effective decisions. With multiple applications across the enterprise, generating reams of data that sit in separate silos, aggregating and mining this data is a very real and complex problem. Many companies, from pharmaceuticals to process industries, from food producers to the petrochemical industry, still use manual processes for collecting, analysing and reporting this data. Often the reports that distill this mountain of data into relevant information are extremely tedious to create, taking scientists away from the work of science and thereby losing time and money performing administrative report generation instead of furthering the scientific work of the lab. And, because data formats and applications are inconsistent and not well integrated, there has been no coherent way for scientists to aggregate all of their work in one place. All of these are barriers to making effective business decisions.
Laboratories across a variety of industries are now implementing next-generation data management tools to help manage the increasing amount of data generated by their organisations and move one step closer to a paperless operation. These tools enable scientists and researchers to replace manual processes for collecting, analysing and reporting on data, which is made up of both structured and unstructured content. It is estimated that approximately 20 per cent of laboratory data is structured, which means it is captured, stored and retrievable with software systems like laboratory information management systems (LIMS) and chromatography data systems (CDS). The remaining 80 per cent of laboratory generated data is unstructured, primarily manually processed, and not easily managed. But new technologies and innovations in data management systems can help connect this disparate data generated in a variety of systems, thereby giving management a more holistic view of operational data and experimental research.
For businesses today, a coherent strategy that can integrate data from the wide range of different sources of potential data across the organisation is critical to containing costs and maximising revenue. Enterprise-level LIMS now allow for the integration of data from laboratory instrumentation and enterprise systems so that management can have the right information at exactly the right time to make the most effective decisions for their business.
To address this need for managing laboratory data, and to provide a means to further reduce the ever-growing pressure on the expense side of the balance sheet, companies like ours are harnessing our wide range of capabilities to help bridge the gap between laboratory-generated data and the enterprise-level information that is required for mission critical management decisions. We are engaging with our customers to facilitate management-level discussions about the necessity of integrating all of the sources of potential data, including laboratory instrumentation, informatics software like LIMS, CDS and ELNs, enterprise systems like MES, PIMS and ERP, enterprise communications tools like SharePoint, BizTalk or document management systems like NextDocs and Documentum, thereby elevating the role of the laboratory in the day-to-day mission critical decisions required of management throughout the enterprise.
Integrating the enterprise will facilitate better planning, data quality, collaboration, and end-to-end report generation, all with the goal of providing management dashboard views of key business metrics that are essential to running their operations effectively. This means that management will have the critical data they need before, not after, any point of crisis.