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Data is information waiting to happen, but today's global pharmaceutical companies are riddled with data—so much that their
numerous functions and disparate systems struggle to know what to do with all of it. Worse still, these data are usually disconnected,
duplicated and, all too often, inaccurate.
Data is generated by the day-to-day activities that take place in each department. Regulatory operations personnel, for example,
produce documents, develop submissions and file them in for approval. However, a submission begins long before the documents
themselves are created. The process commences with the generation of concepts that get encapsulated into documents, which
ultimately form the regulatory submission. Submissions become part of a portfolio across multiple nations, with concomitant
licences that must be managed. In most cases, data gathering is managed locally, with regulatory departments drawing on the
minimal amount of information needed to adhere to requirements or to track commitments. What is often missing is the ability
to aggregate information across the enterprise so that it can be used to conduct more predictive work, such as project planning
across the portfolio, resource planning, and pre- and post-marketing activities. In so doing, companies can manage their activities
more holistically.
Other industries have been quicker to grasp the importance of information management. Perhaps one of the best examples is
the automobile industry; for example, when problems arise with a particular model, the manufacturer can respond quickly by
linking manufacturing information with warranty information. When a manufacturer spots a trend, such as a faulty part, it
can both ensure that its dealers are ready with the new parts and send out relevant recall letters, thereby helping to minimise
any escalation in cost.
Information overload
Pharmaceutical companies are aware of the data they generate and capture. According to a survey by the consulting group Ovum
(1), the pharmaceutical industry is ahead of other industries when it comes to adopting enterprise applications, such as customer
relationship management (CRM) and enterprise resource planning (ERP) solutions, but lags behind with business intelligence
solutions such as regulatory tracking and management systems that can harness data productively.
Poor information management can create a bottleneck for companies on multiple levels, as well as add unnecessary cost burdens.
Take the cost of storage, for example; failing to manage data results in the retention of redundant information and records,
which occupy storage space within a system. Then there's the time cost associated with chasing information needed to meet
regulatory requirements or to make a business or strategic decision.
