I have been in the line of teaching data science and data analytics for a long while, since 2007 till now. I always get this question and that is
"Can you customize the case study to my industry/company use case?"
I want to use this article to discuss this question.
For any courses, there are certain learning objectives that need to be reached. The focus for my courses has always been, regardless of whether the materials are prepared by me or not, I want to ensure my participants learn concepts and skills that will make them gainfully employed as long as possible. What does this mean? I will focus on imparting to my participants evergreen concepts that they can bring back to their workplace and be applied to a VARIETY of problems.
With the objective of imparting knowledge that can be applied to various problem, there will be specific characteristics of the datasets trainers are looking for so that the learning objectives can be impressed easily. Looking for datasets that can meet learning objectives and they are "real" is NEVER EASY and there is a search and curation cost to it. It is one of the reason why I asked for a fee to conduct such search and curation if the company desperately needs a 'relevant' use case for the course, and I will be upfront here, I charge an arm and leg for it because such work does not add much value to me and I will show it in a while that the participants also do not gain much from it as well.
Assuming I do the customized case study and possibly sacrificing learning objectives (that helps the organization to create a thinking workforce), there is a very good chance the participants will FOCUS solely on how to solve that SPECIFIC problem, learn the steps and hoping to repeat it back at their work. This translates to the fact that the course will only be training employees that solve Problem A and nothing else or to be more precise, trained employees will not be able to solve Problem A' (A Prime) or any similar problem because there is NO INCENTIVE to learn more than that. How I know this? Because after finishing a case study, I get another FAQ, "Can you list/state down the steps to solve these problems for my reference?"
Now if you are from the L&D team in your organization, I am pretty sure you'll want to train up an innovative and thinking workforce for the organization. From the above, having a customised case study, do you think that will support your cause? As mentioned the "trained" workforce cannot transfer what they have learned to other problems that they have, you have trained a group of "human software" that can do the steps to solve a very specific problem and nothing else. My next question is why not replace these folks with an automation software instead, that can do the task 24/7 without any human emotions and temperament in the equation? Is it not cheaper, better and perhaps even faster than human?
Besides the fees paid to the course provider, organizations also put in the time-cost of its employees to be skilled up in the course. From a capitalism perspective, you will want get the biggest bang for your buck, meaning training up an innovative and thinking workforce that can solve a VARIETY of problems rather than a specific problem. If your organization think otherwise, please let me know. I will love to draw a large salary while only solve one specific problem and any deviation to be handled by others. :)
In conclusion, I am never supportive of doing customised case study because
1) You'll trained a workforce that follow steps only and not able to innovate and solve a variety of problem.
2) You'll have paid a large monetary and time cost to have your workforce trained to solve a VERY VERY specific problem and nothing more. They do not have the incentive or even opportunity to think about the knowledge and skills learned can be applied to other challenges.
3) Perhaps an automation software might be a better choice rather.
What are your thoughts on this?
If your organization is interested to train a workforce that can solve a variety of challenges with data, reach out to me on LinkedIn! :)