The Dual Path of Feedback

A little more than a year ago, 'Data Literacy in Practice' (https://a.co/d/a5umZJ7) was launched by Packt . It was a journey my dear friend Kevin Hanegan and I began, and will never be forgotten!

Reviews and feedback (the good and the bad) are important elements in selling books through various channels. The main point here is that we can learn from feedback when it's given in a way that allows us to grow and learn from it. But writing feedback effectively, whether in an organizational context or as the author of a book, requires a thoughtful approach that balances critical analysis with constructive suggestions. Let's have a look at both worlds.

Feedback for Data and Insights within an Organization, your colleague has presented a report on customer satisfaction trends.

Noticing trends with curiosity. As an example: In Table 3, I saw that customer satisfaction dropped in Q2. This caught my attention. Do we know if other areas like sales also showed similar trends during this time?

Asking for context. As an example: I’m trying to better understand our data. How does this customer satisfaction trend fit with our overall objectives?

Proposing to look a bit further. As an example: Would examining the specific customer feedback from that quarter help us understand this trend better? I think it might be interesting to see their comments."

Expressing the eagerness to learn. As an example: The analysis you've done is quite thorough. I'd like to learn more about how you think customer satisfaction and sales data are connected or not.

Encouraging Discussion. I'm keen to learn more from your perspective on these findings. Maybe there’s something I haven’t thought of?

Show willingness to help and learn. As an example: I find the reasons behind this satisfaction trend really intriguing. If there's any way I can assist in exploring this further, please let me know."

Being Mindful of Privacy. As an example: I realize handling individual customer feedback can be sensitive. What are our usual practices for maintaining privacy in these cases?

Feedback for a colleague that is writing a book about Data Literacy book and he (or she) asks for feedback on the first draft, we need to take care of the following points:

Observation and curiosity. As an example: when you’re discussing data visualization techniques, I found the examples really helpful. Could you maybe include more case studies or real-world examples to illustrate these concepts?

Seeking for clarification. As an example: I'm still learning about data literacy myself, so could you clarify the section on statistical misconceptions? Some parts were a bit complex for beginners like me, maybe you could add this?

Encourage for further investigation. As an example: Have you considered adding a chapter or a section dedicated to common mistakes beginners make in data analysis? I think that would be incredibly useful for new learners.

Adopting the learner's perspective. As an example: Your explanation of big data was insightful. I'm curious, how would you suggest beginners approach this vast topic without feeling overwhelmed?

Invite to create a dialogue. As an example: The example in Chapter 6 was intriguing. Could we discuss it further? I’d like to understand more about the thought process behind choosing this particular example.

Focus on Learning / development. As an example: The book seems really comprehensive, but I wonder if there could be a way to make it more accessible to those who are completely new to data literacy. Perhaps a glossary of terms or a 'beginner's guide' section?

Respecting expertise. As an example: I appreciate the depth of knowledge you have in data literacy, and I'm learning a lot from your book. Your expertise really shines through, especially in the more advanced topics.

Honest, respectful and open. As an example: As someone who is relatively new to this field, I find some sections challenging but very educational. Your book has been a great resource in demystifying complex data concepts for me.

To conclude

Showing respect for the data analysts or an author's expertise while also providing insights into how the book or analysis might be received by its intended audience.

When we look at both contexts, the key is to be respectful, clear, and focused on improvement. Whether dealing with data or creative writing, effective feedback can be a powerful tool for growth and development.

Stay safe, be kind and help each other to learn!

Angelika Klidas

Challenger, Advisor & Trainer at Business Data Challengers

[email protected]

+31621944524