Good science

Knowledge is the most addictive drug. As my AI course concludes I’m thrilled by how the acquired knowledge is expanding my perspective. My mental library now contains guidance on how to apply concepts such as decision trees, random forest and bootstrap aggregation to name just a few. What makes me happiest, though, is that what I have learned is universally applicable to life. The concepts, above all pruning, can be used to address any topic. This puts a big smile on my face. 

Today’s topics:

  • Science is not a religion
  • Normal distribution
  • NLP and customer engagement
  • Leadership: Appreciation and the value chain

Science is not a religion

Science is the pursuit of knowledge based on data. Good science requires an open mind, curiosity, and the humility to accept that what is true today may not be true tomorrow.  Great science, like coaching and consulting, requires us to be at the same time insatiably curious, and at ease with not knowing.

I have a medical degree, postgraduate training in translational research, was a postdoctoral fellow at the NCI, NIH. I have a diploma of advanced studies in pharmaceutical medicine, and trained in bioethics, personalised medicine, data analytics, market access and executive coaching among other things. I have worked with mRNA and DNA, designed plasmids, purified proteins, injected them into rabbits, and harvested antibodies. I still feel guilty about the rabbits. I have nurtured cell cultures, stained tissue sections and worked as a clinician treating patients. Then came the pharma years working in various roles locally, regionally, and globally. For the past ten years I have consulted and coached. I have a broad range of experience and training across disciplines, cultures and countries and an excellent memory and naturally all that  feeds into everything I do.

Yet, I think,  one of my biggest strengths, beyond being a pretty good cook,  is to be comfortable saying I do not know. I need more information.

I am prompted to write this, because I am concerned at how binary our world is becoming.  Especially in healthcare conversations, in many fields, there is the right path and the wrong path, the believers and the doubters. However, science is not religion. It is a data-based discipline based on current knowledge.

In science, and medicine, we can say “we do not know, the experiments have not been done yet, or the data is inconclusive”, we can say “this is current best practice, or this is my working hypothesis” we can even say, and as a scientist I really used to hate this, “we will treat the patient with this protocol, but we are not sure why it works, but we know it does”.  

In almost every situation the truth is expressed well by that sentence found at the end of every scientific publication “further research is needed” or in my words “science evolves“.

Key-takeaway: Science is data driven, biology is not binary: never or always have no place in scientific discourse, beware anyone who suggests otherwise. 

Normal distribution

I have always loved normal distributions. They apply to every area of life. Your general practitioner, your mechanic, or of course yourself. In a conversation with an HR professional many years ago, I was told that I am excellent at my job and highly productive, which seemed like a compliment, until she said “you do it on purpose to make other people feel bad.

Writing about it now makes me smile. My response centered on normal distributions  “There is a range for everything, where people sit within a range is generally just where they sit, it is not for or against anyone else”. 

Key take-aways: 1) Normal distributions are valuable when reflecting on everyday life situations  2) Not every piece of feedback you receive is valid 

NLP and customer engagement

I think about data. All the time. I always have. About different ways of using it, assessing it, benefiting from it, and using it to improve customer service. Since doing a No-code AI course, I have more ways of thinking about it.

One task we were given was to imagine an industry that could benefit from natural language processing. The first example that came to mind was the airline industry.

As a frequent flyer, I have engaged with airline helpdesks frequently over the years. I will read the FAQs, engage with the chatbot, wait on the phone for hours, and finally end up writing an email. The companies take weeks to respond. Often, the response is not helpful. I have never found the answer I need on the FAQ lists. Imagine, if an airline company categorised customer enquiries by financial impact, importance of customers, and whether a customer had tried to find the answer online. Imagine, if the company then assessed the customers complaints for keywords and hot topics and performed sentiment analysis on the text. And then imagine if they finally mapped out the key topics starting by order of business impact for example, enabling them to identify internal process improvements, update FAQ lists, and automate FAQ responses to submitted enquiries e.g. instead of the typical, we will get back to you in 2 weeks, sit tight, there might be more meat on the bone. In addition, knowing that customers reviewed online FAQs but still submitted an enquiry, will help identify which FAQs need revisions, updating or writing.

A well implemented system would improve resource use, reduce customer frustration, increase the value of phone conversations, when they do occur, and improve processes flows. Oh, and save copious amounts of money.

Imagine the improvements you could achieve if you could do that in a pharmaceutical company. Implementing new solutions is resource intense and whether it is feasible depends on many factors, if you wanted to investigate it from the business side, I’d love to discuss with you.

Key takeaways: Everything evolves, and new solutions are being born every minute.

Leadership: Appreciation and the value chain

As a consultant I have the pleasure of being involved in projects often from strategy to implementation. I stay in contact with teams after a project is finished and so I generally know how things went after I left.  I derive great satisfaction from seeing a plan come to life, from solving complex issues, and from my client’s appreciation for my support on the journey. Recently a client recommended me to a friend, which is the highest compliment a consultant can receive.

Most individuals are motivated by a mix of the following: a job that is meaningful, knowing where they fit in an organisation, the opportunity to grow, seeing that they have added to value creation, recognition, appreciation, praise and financial recompensation and titles.

While I do not believe it is a leaders job to motivate their team to do a good job, I do believe it is a leader’s responsibility to create an environment where employees can thrive. This includes ensuring employees are connected to the value chain, so that they understand, how the work they do benefits the company and the teams objectives as well as celebrating individual and team contributions. 

As a medical student I would manually assess all the EKGs that had been done the day before, I would put them in the resident’s cubby holes, that evening I would do it again. After a week I stopped. A resident said to me “why did you stop; you were doing so well?”. I said, “well there was no feedback, no training, I didn’t know if what I was doing was useful or not, so at some point I didn’t think to continue”.

Key takeaways: individuals who know that the work they do adds value, and why, are likely to find ways to do it better while being intrinsically motivated to contribute

I hope my writing provides you with useful insights if you have a project you need support with or are interested in coaching, please contact me to discuss whether I can support you. To find out what clients and coachees say about working with me, please follow this link.

I look forward to hearing from you,

Isabelle C. Widmer MD

Image credit: NIH