Communicating Data: Is Your Transmitter Faulty?

May 8, 2015
The Column

Volume 11, Issue 9

Page Number: 13–14

Communicating Data: Is Your Transmitter Faulty?

Incognito sends out his/her latest transmission. Are you on the correct frequency?

 

You may be the best chromatographer with the best instruments and resources, but if you are unable to properly communicate your results, you may as well not bother.   I’ve seen it so many times - brilliant minds that just cannot properly explain how data has been derived, never mind the contextual inference of the result that has been generated. To be a top analytical scientist you have to be able to communicate “information” in a manner that your client (internal or external) can understand and that takes them forward. If reasonable people fail to understand the data you produce, then you have failed to communicate it properly.   This communication can take place in a multitude of different settings including via telephone, face-to-face meetings, in your office, in the laboratory, by the water cooler, or in formal presentations. But no matter what the setting, the principles that apply to good teaching and learning, those critical communication skills necessary to convey information in an understandable manner, still apply. These principles and skills are relatively straightforward and simple to adopt if you’re willing to accept that even a telephone call to explain your latest findings is worthy of being done properly.   How do you communicate most effectively? Well your learning style is generally well-aligned with your teaching (communication) style, which can be broadly classified as visual (seeing), auditory (listening), or kinaesthetic (moving and doing) (VAK), or a mix of these styles in which one will probably dominate. There are a number of on-line resources that help you to assess your learning style. (1,2). I’d recommend that you find out your own style because it will really help to inform the way in which you teach. And yes, explaining results to someone is teaching.   Once you have assessed your teaching style, you can help to stay true to it by arranging your sessions to match it. Auditory teachers may like to explain in detail in meetings or via the telephone, visual teachers should be using chromatograms and diagrams for explanation, and kinaesthetic teachers should be getting straight into the laboratory and pointing to the instrument and clicking through the data system.   You should get to know as much about your audience as you can. First, what is their learning style? Ridiculous to even suggest that we undertake this exercise for merely explaining our data to the customer? Well maybe that’s where you’re going wrong. This can be done as simply as asking how the “student” would like to discuss the data - on the telephone, in my office, or would you like to pop down to the laboratory. They will know their own preference, but you won’t unless you ask! Secondly, always take time to ask what they already know. Most people hate to be patronized and hate being baffled even more. When was the last time you bothered to understand your customers level of understanding before you embarked on demonstrating how clever you are and how great your data is?    Your session should have a solid start, middle, and end and there’s a pretty famous teaching plan that goes:

  • Tell them what you’re going to tell them.

  • Tell them.

  • Tell them what you told them.

I’ve used this many times to make sure that the main points of my data, or their inference, are properly conveyed.    In carrying out Step 1 above, you might want to make notes on some learning objectives, which should always be measureable so don’t write “Understand that the results have indicated the formation of methyl-ester by‑product within the reaction mixture” because you’re not explaining how you’re going to measure if the learning objective has been met. It would be much better to write “Can explain an appreciation of methyl-ester by-product formation to me by drawing up a proposed reaction scheme” OR “Can suggest that the M+14 peak within the spectrum is potentially a result of the formation of a methylated homolog of the desired reaction product.”   For those who are sceptical at the need for this level of rigour prior to a call to explain experimental results, remember that other age‑old rule of the 5 P’s: Proper Preparation Prevents Poor Performance. However, there is also a vital part missing from the three-point plan above: 4. Ask them to tell you what you just told them.  

  • Essentially this is assessment. If you can’t or don’t assess whether someone has understood the data or its inference in the context of their own work, then you might as well have not done the analysis at all. I’ve heard so many meetings and calls end with questions like:

  • Is that OK?

  • Do you understand?

  • So are you OK with that?

  All of these are “closed” questions and will elicit “yes” as a response because most folks won’t want to appear dumb and this will not help you to understand if the person really does understand the results. Consider using the following types of question, which are not patronizing but will still help to assess understanding: 

  • How will these results affect your next steps?

  • How do these results differ from what you expected and what does this mean?

  • What do these results mean to you in the context of your work?

These are all questions that allow your customer to consider your data in the context of their work and will help you to assess whether they have understood the information you are giving to them.
I’m going to conclude with some tips, tricks, and facts that have helped me to more effectively communicate my data in various situations, from simple telephone calls to formal presentations to a room full of people.   In a learning situation people retain: (3)

  • 10% of what they read.

  • 20% of what they hear.

  • 30% of what they see.

  • 50% of what they see and hear.

  • 70% of what they talk over with others.

  • 80% of what they use and do in their working situation.

  • 95% of what they teach someone else to do.

This basically tells you that the best way to explain your data is to send them it and arrange a session in which they explain it back to you. I can promise you that the most useful sessions I’ve ever had were done in this manner. It takes more work from both parties, but it’s highly successful.   Remember that “Death by PowerPoint” isn’t PowerPoint’s fault. This is the world’s most widely used teaching tool, so make sure you know how to use it!   The use of collaborative teaching tools has revolutionized the way in which you can communicate data. Screen and desktop sharing tools which can be set up very quickly (www.join.me is a terrific example) can be used to point, click, share control of systems, and highlight various aspects of pictorial data. It’s absolutely terrific for appealing to all of the different teaching and learning styles. So, the next time you find yourself saying “Those chemists are really dumb” or “Sam really doesn’t get it” or “That’s not what I told them, why have they gone and done that?” - ask yourself if the problem is really with the receiver or could it be that the transmitter wasn’t working as well as it could have!  

References

  1. http://www.educationplanner.org/students/self-assessments/learning-styles-quiz.shtml
  2. http://vark-learn.com/the-vark-questionnaire/
  3. Motorola University: Creating Mindware for the 21st Century, Corporate University Xchange 2(3), (1996).

Contact author: Incognito E-mail: admin@chromatographyonline.com

   

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