Outsourcing the management of clinical trials, manufacturing, and packaging, as well as (to a limited extent) data management and sales operations, is fairly commonplace in the world of pharma. However, companies are showing themselves to be even more adventurous in trying on for size the outsourcing of analytic functions.
GETTY IMAGES / DIETER SPANNKNEBEL
Ideally, outsourcing enables organizations to improve operational effectiveness and gain improved insights, freeing resources to focus on decision making (see Figure 1). The conventional wisdom is that these efficiencies can in turn put companies on the fast track to greater insight—an "aha!" moment, if you will—that can propel them toward greater commercial success.
Figure 1: The Resources Shift
Weighing the Options
To date, knowledge-based outsourcing has been limited to a reliance on partners for incentive compensation, sales reporting, and some data management. While the amount of spending has been significant, it is concentrated on single processes and individual needs.
Many companies in the industry are in an assessment phase to determine which activities and processes they should hold on to from a strategic standpoint versus those that might benefit from outsourcing. Advice and frameworks in the area abound, and making the wrong decision can be detrimental, especially as the industry moves from piecemeal initiatives to large-scale outsourcing efforts (see Figure 2).
Figure 2: The Value Chain—Outsourcing Information-Intensive Processes
At best, knowledge-based outsourcing can drive commercial excellence and cost efficiencies within and across commercial support functions by offering:
» More effective and adaptable decision support for sales, marketing, and managed markets operations;
» Improved processes, stemming from wider exposure to methodologies that lead to the adoption of best practices in sales force effectiveness, sales and marketing analytics, multichannel marketing, and information management, for example;
» Higher-quality data interpretation, owing to a broader perspective;
» Greater staffing flexibility and access to critical expertise through peaks of demand (during launches, for instance) plus variability in cost structures as the need wanes. IT functions have benefited from utility computing—the notion that capacity is scalable and available on demand—and the same approach can work for knowledge-based activities;
» Lower operational costs (tracked as being reduced by as much as 20 percent to 30 percent);
» Global consistency and standardization;
» Adherence to changing regulatory, privacy, and security requirements; and lastly
» Freedom from the costs associated with training and retaining knowledge experts.