GENAI WILL CHANGE THE FOCUS OF ADVANCED ANALYTIC HIRING
At SENTIER we are deeply engaged in our deployments of VELOCITY for GenAI-based data mining. A critical success factor has risen to the top: the importance of business analysis skills in generating the best possible answers.
One could describe GenAI as a technology that diminishes the necessity for hardcore technical expertise, such as proficiency in SQL or Python. However, while large language models (LLMs) from leading providers like AWS, Microsoft, and Google offer immense capabilities, they lack the domain-specific training required to answer questions in life sciences.
Consider this scenario: You want to utilize GenAI to formulate SQL queries to analyze claims data. You provide table structures alongside the question, "What is the predominant line of treatment for my brand among the oncology specialty group?" Since the major provider LLMs have no prior training with claims data – and likely never will due to various constraints –the SQL generated and corresponding output will be garbage. How would the LLM discern that "HCP" corresponds to "NPI," decipher the concept of "line of treatment," or know the specific specialties that make up the oncology specialty group?
Where does the guidance necessary to yield accurate results come from? It comes from the expertise and experience of seasoned business analysts. They furnish extensive context through a prompt that is referenced each time a question is asked. This prompt lives outside the LLM and includes synonyms (e.g., HCP-Physician-Doctor), instructions outlining the LLM's role in generating SQL, and the business rules defining the KPIs.
GenAI is poised to become ubiquitous, drastically reducing the time required to obtain answers by removing the need to code by hand. However, for GenAI to fulfill its potential, it necessitates domain knowledge alongside its extensive capabilities. As companies consider their analytic hiring strategies for the coming years, business acumen, and the ability to translate that expertise into the context necessary to guide GenAI will become a top priority. The people hired will be called Prompt Engineers, but they will be business analysts at heart.
