Intelligent life sciences with automation

As life sciences organizations are pressed to lauch products as cost-effectively and quickly as possible, explore the advantages that intelligent automation (IA) can provide in reaching these goals.

Proactive talent management for the shifting workforce

Challenges facing the life sciences (LS) industry range from economic pressures and regulatory changes to emerging innovations and empowered patients. Some companies are integrating enhanced automation into their workforces to address these challenges. Those that are not, should be.

LS organizations are not only pressed to launch products as cost-effectively and quickly as possible, but must validate that the drugs and devices produced adequately and safely fulfill unmet patient needs, leading to better short- and long-term outcomes.

Intelligent automation (IA), such as robotic process automation and cognitive computing, represents a major transformation opportunity that can help organizations achieve these goals with advantages that include: more cost-efficient scaling of back-office IT; faster clinical trials and drug releases; more rapid regulatory compliance; increased accuracy in pharmacovigilance; andturbocharging big data.

Although there are evident opportunities to leverage IA to differentiate from a competitor, many organizations have shown resistance to adopting IA. Despite the many promises of IA, many LS professionals will experience automation anxiety.  It is true that the availability of powerful and inexpensive processing power on demand, coupled with advances in artificial intelligence, natural language processing, and exponential growth of data, has created an opportunity to substitute or augment human labor. But LS professionals can find comfort in knowing that, in reality, it is much more likely that advanced automation technology, like robots, will become adjuncts to the traditional workforce.

No matter what adoption pace a company takes, early strategic thinking needs to be applied to appropriately manage the change and talent implications of IA.  Leadership must consider what an optimized outsourcing model looks like for the organization, whether displaced internal workers can be reassigned or retrained, and how digital and human employees can effectively work together. To successfully incorporate IA within existing processes and teams, organizations must proactively address the impacts to their people and the overall organization in order to minimize business disruption and expedite the timing of benefits realization. Proactive talent management strategies that manage both the short-term workforce implications while addressing a forward-looking talent pipeline should ensure your IA strategy pays dividends, and the organization can scale going forward.

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