Using Strategic Data Management to Boost Efficiency

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Equipment and Processing Report

Equipment and Processing Report, Equipment and Processing Report-05-19-2010, Volume 0, Issue 0

Life-sciences companies spend proportionally more resources on information technology and get less in return on their investment than companies in other industries. The poor return on investment partly results from regulatory costs that are unique to the pharmaceutical industry, but also stems from a failure to manage data strategically.

Life-science companies spend proportionally more resources on information technology (IT) and get less in return on their investment than companies in other industries (1). When companies’ investment funds are limited, this trend is exacerbated because small projects and investments often lead to disjointed IT landscapes.

The poor return on investment partly results from regulatory costs that are unique to the pharmaceutical industry, but also stems from a failure to manage data strategically. Sharing data throughout an enterprise and beyond (e.g., with vendors, research and manufacturing partners, and other contract parties) can make every phase of the drug life cycle quicker and more accurate. Data sharing also can help cut costs and improve business decisions. Yet many companies unnecessarily restrict data to isolated pockets of the organization, thus preventing the close integration that could bring economies of scale in terms of services purchased, partners engaged, and applications used. In fact, an examination of data management in a given company’s laboratory and manufacturing departments reveals numerous opportunities for more efficient data management and for the application of lessons learned by other industries.

Integrating laboratory technology and data
Most pharmaceutical companies have more laboratory information management systems (LIMS) and laboratory notebooks than they can track. Individual researchers or groups often choose their own tools, thus leading to an expensive proliferation of systems. The excess of software solutions reduces large companies’ support capabilities and bargaining power with vendors, rather than helping them achieve economies of scale.

The bigger problem, however, is that the data in these disparate systems become far more difficult to integrate and make useful for various purposes, thus diluting the systems’ value. As a result, data rarely flow from upstream to downstream laboratories. Enhanced data accessibility among laboratories could prevent a great deal of rework and inefficiency and improve collaboration. Although most modern LIMS solutions can be integrated with other systems, they are primarily used in isolation to manage small data sets.

Firms in other industries have sorted and integrated their analogous software systems. For example, many engineering and electronics companies have centralized their configurators and collaborative design and testing tools. Many chemical companies have integrated their internal LIMS capabilities. By following their lead, pharmaceutical manufacturers could reduce costs and improve efficiency.

Tapping the potential of an ERP
To manage data strategically, a pharmaceutical company doesn’t necessarily need to buy additional technology. Rather, it can take advantage of and integrate fully its current applications. For example, many life-science companies have installed enterprise resource planning (ERP) systems, but few companies have taken full advantage of them. The fact that a central source in the organization often funds the early implementation of an ERP system suggests that the goal is integration, but the software rarely is integrated with existing tools at the plant level, which typically has many planning tools and other automation already in place. The result is many orphaned systems and processes, disjointed data sources, and more integration with headquarters than with the business processes that make operations possible.

Deviation management is a case in point. The process for handling deviations should focus on gathering information, identifying the root cause of the problem, resolving it, and closing it out as efficiently as possible. Many manufacturing lines still process deviations manually, using their systems support (i.e., ERP, quality-management, or issue-tracking systems) only to document decisions. ERP systems often include unused integration capabilities even though incorporating deviation management into the systems can improve workflow, management, and understanding. These integration capabilities tend to be overlooked simply because the ERP was put in place for different reasons.


Automated deviation entry, classification, and support for closure are commonplace in other industries. Automated investigation support ensures that deviation-management processes are complete. Depending on the size and scope of a plant, automation can help cut costs significantly and save thousands of hours of effort. Furthermore, automated processing, when well defined, is embraced by regulatory authorities. Often, all that is lacking to take advantage of these benefits is sufficient training at the plant level.

Increasing integration and expanding capabilities
In the laboratory and manufacturing plant, and in other areas as well, the case for change is compelling. Strategic data management can increase a company’s leverage in buying technology, quicken and improve all phases of the product life cycle, and yield the business advantages that result from operating as a single, unified organization.

Greater integration can help a company expand its capabilities. For example, increasing pressures for financial improvements and improved productivity in life-science companies are leading pharmaceutical manufacturers to outsource more of their activities. Current practices in management, security, data sharing, and other support capabilities hamper the rapid formation and dissolution of partnerships. Many partnerships require a level of permanence and investment before they begin to show promise. The comprehensive management of information flow, information requirements, and business interactions between organizations is critical to successful partnerships.

Coordinated IT, data-management planning, and investment across the drug-development and manufacturing life cycle can help companies take greater advantage of systems they already have in place and ensure that future investments yield acceptable returns. Better coordination can improve products, help bring them to market more quickly, identify product concerns early, and mitigate the difficulties of working with outside partners.

1. A. Bartels et al., US IT Budget Benchmarks—Preparing For 2010 (Forrester Research, Cambridge, MA, 2010).

Gregory T. Plante is a principal at Tunnell Consulting, 900 East Eighth Ave., Suite 106, King of Prussia, PA 19406, tel. 610.337.0820, [email protected].