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Getting a clear view of business performance can be cumbersome, time-consuming and even nigh-on impossible.
Business success relies heavily on the ability to make strategic decisions faster than the competition. Turning the data flowing in and around the business into reliable, accurate and timely information on which to base crucial decisions is a challenging task in any sector. However, the huge volumes of data handled by pharmaceutical companies, coupled with globalization, and a highly competitive and severely regulated market, make it particularly daunting.
It's a challenge that pharmaceutical companies aren't shirking. In 2006, the US 'Big Pharma' sector spent approximately $181 million on business intelligence (BI) software and services with the US biotech industry alone outlaying $33 million, according to analyst firm Datamonitor. But pharma needs to spend carefully: throwing money at expensive BI solutions won't necessarily solve the specific problem of obtaining and exploiting management information drawn from a plethora of source systems.
Getting a clear view of business performance can be cumbersome, time-consuming and even nigh-on impossible. Most companies attempt to 'construct' an accurate view, but it's often a mix of volatile data from unknown times and places that has been pieced together. This is understandable: departmental, regional or country differences in any large pharmaceutical company often translate to diverse operating models, reporting structures and coding. In this highly regulated market, pharmaceutical companies face even greater challenges than most companies as they try to conform to, bend and obey the myriad of different regulatory standards around the world. Similar to any other sizeable businesses, large pharmaceutical companies run many disparate data systems. In pharma's case, these might track data generated by global discovery projects, clinical trials, manufacturing and operations, and post-marketing activities. With no relationship to data held in other systems, there isn't an easy way to highlight trends or draw correlations to make critical decisions. Transaction systems can adequately track and store 'facts', such as a patient's results from a clinical trial, all of which are easily recoverable, but to equip executives with the knowledge they need, these facts must be combined with other data and analysed to transform them into 'information'.
As a first step, companies must change their mindset to acknowledge that information is 'active', and deploy tools and processes that allow a high degree of flexibility — tools that can adapt to the speed of a constantly changing market, rather than the speed of the underlying information architecture. Standardization or reconfiguration of source systems is often cited as a potential solution, but is expensive, time-consuming and usually ineffective. Executives should be able to easily manage and manipulate data without corrupting it, avoiding interference with the source systems and ensuring that data stay pure throughout unavoidable constant changes.
Companies need solutions that can rapidly iterate, evolve and adapt to changing business conditions without consuming time or bringing the need for custom programming. If correctly implemented, such business-oriented solutions can provide the highly-prized accurate, clear view needed by senior executives.
In addition to the improved insight into business performance, true business intelligence solutions also reduce risk by capturing and recording every change to the information, providing a trustworthy audit trail for regulatory compliance and governance, which is crucial in the pharmaceutical industry.
An effective information management system is also, critically, agnostic of vendor technologies. Pharmaceutical companies need the flexibility to select the best source systems for their business. In addition, pharmaceutical companies often rely on third-party, external data that have not been standardized with internal standards. Such a business-focused strategy demands flexibility and heterogeneity of source systems — and an information management infrastructure that can support it. Of course, quicker development and deployment of IT systems also mean cost savings for the IT department and rapid access to information — for management rather than IT employees — which leads to better decision making.