Clinical Expert Management's overview of KEE / KOL mapping 
Clinical Expert Management will be posting occasional blogs over the coming months, but for our first blog we thought that we would provide a summary of the various techniques and the reasons for performing a mapping project. If you would like more information, please use the ‘Contact’ page and we will endeavour to answer your query. 
There are various reasons for wanting to identify, profile and map Key External Experts (KKEEs) / Key Opinion Leaders (KOLs): 
Strategic advice: 
• Market entry advice 
• Market access advice 
• Regulatory/Approval body advice 
• Regional / Local clinical practice advice 
Tactical input: 
• Clinical trial involvement 
• Speaker engagements 
• Advisory board membership 
• Media engagements (if relevant) 
Techniques used to ‘map’ the External Experts: 
Peer recommendations – ‘old boy’ network 
Previous in-house experience – personal interactions 
Sales force / MSL recommendations – ‘local’ knowledge 
Data analysis – systematic examination of the KKEEs 
Peer recommendation 
• Relies on the recommendation of an External Expert by others 
• Identifies individuals with a high degree of visibility and influence 
• System is open to abuse and potentially introduces subjectivity 
• Takes no account of personality clashes and political bias 
• Introduces a trend towards the same faces being engaged with little ability to judge the reputation of the KKEEs 
• Lists of KKEEs tend to be refreshed on an infrequent basis as clients do not want to offend KKEEs who they think are key 
• Different clients engage with a small number of KKEEs with no competitive advantage 
• Lacks the ability to introduce fresh thinking and fresh idea 
Previous in-house experience: 
• Lists of KEEs are built from previous experience of working with an individual 
• Effective working relationships have already been established 
• Subjectivity is introduced as criteria used to select individuals may be applied inconsistently 
• Robust segmentation data may be missing or inconsistent 
• Strength of personal relationships/friendships may mean that unbiased input from the EE may be missing 
Field force recommendations: 
• Lists of KEEs are built from the ground up by field force (e.g. sales representatives, MSLs) 
• Rapport and a willingness to work with pharma has already been established 
• Subjectivity is introduced as different criteria may be used by the field force or the same criteria used differently 
• Data captured lacks consistency as errors inevitably arise 
• Information is often out of date by the time it is captured 
• Process is time consuming and takes field force away from core tasks 
• Direct or hidden costs may be high 
Data analysis: 
• Data sources may vary (e.g. publication data, clinical trial data, prescription data) 
• Choice of data and a complete understanding of its structure and attributes is important (e.g. hidden / latent patterns may be present but need sophisticated comprehension) 
• Care must be taken when combining data from more than one source due to assumptions about an EE’s identity being made (e.g. duplicate names and variations/inaccuracies need to be disambiguated) 
• Data needs to be quality controlled thoroughly 
• Limits of data analysis need to be considered (e.g. political / personal factor may need to be factored in)  
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