Talent retention, combined with a talent shortage, is becoming a big problem for life sciences. Companies are using many strategies such as structured onboarding, flexible working and career development training in a bid to find and keep their top people.
Thinking style can now be added as a strategy. Thinking style or cognitive style refers to the variety of ways in which individuals perceive, think, reason, and solve problems; it is less visible than, for example, age, ethnicity, and gender diversity. Its on continuum on which people’s thinking style is a range from a preference to “do things better” to a preference for doing things differently.
Think of Jeff Bezos for doing things better (using traditional ropes to climb the mountain) and Elon Musk for doing things differently (using a hot air balloon). No style is better than the either and people have a preference which is set by their late teens and remains stable throughout life. The continuum goes from an adaptive thinking style which is more internal looking, respecting the existing system and uses a structured approach to solving problems via incremental change to innovative thinking which is more globally focused, unstructured and challenges the current system.
The style can be complementary or if opposed they can clash, and this is what can cause retention and motivational challenges. Especially if there is a big gap between two individuals they see problems differently. People leave jobs because they don't feel valued, miss a sense of belonging or don't feel their contributions are being considered.
Companies should work to ensure that recruitment and retention processes support cognitive diversity within leadership. Starting with the job descriptions being written and candidates interviewed through a lens to attract the leader with the style appropriate to the task.
Cognitive diversity in the era of AI
The pivotal use of AI with life sciences underscores the need for awareness and application of cognitive diversity. This underscores the value of cognitive diversity in teams. A broad spectrum of perspectives leads to innovative AI solutions. Diverse teams can minimize biases in AI algorithms, curate richer training data, and ensure a user-centric design. They're also better equipped for problem-solving, often outperforming homogenous teams when faced with the intricacies of AI challenges. In response to these challenges and the changing landscape, life science companies must recalibrate their talent acquisition strategies. Beyond fostering a positive company culture and offering competitive benefits, understanding the creative climate within a company becomes paramount. Considering the problem-solving styles that would best complement an organization's culture can pave the way for success, especially in AI-centric roles.
In this White Paper, we share a talent acquisition and retention approach that helps align hard and soft skills for specific leadership positions. PM Jennifer Chase or Nick Hicks, if you are interested in learning more.