Since my last post about Decision Stories. posted here, I received some feedback about the usefulness of Decision Stories as a product. The main critique is about the ease of use and adoption of this tool. First, it’s not easy to use. As in people need to invest too much effort in thinking about how they made decisions before. And sometimes it’s not easy for the person to recall how they made the decision. They might not be aware the process even if they try to recall. So there needs to be processes to guide for the user to think about how they make those decisions. I will expand these ideas in a later post.
What I want to talk in this post is about is the second point and possible pivots. And that is not a lot of people are making life changing decisions in their personal life. If not many people are using the product on a daily basis, it’s even harder for them to justify the initial investment of effort to record their decisions.
One of the suggestions is to use this tool to help mid-level managers to make everyday decisions, so they can spend more time on other tasks such as personal and employee development. There are potential benefits to this approach. Most decisions made by mid-level managers involve technical decisions that have data to back it up. These decisions are more quantifiable and involve less “gut feeling”. It’s easier for the model to pick up quantifiable features and make reliable predictions.
The type of decisions made by mid-level managers are more homogenous. For example, a customer service call center manger generally worries about the average handle time of calls, and don’t worry about marketing strategies of product lines. Whereas an executive manager needs to think about how the change in product line will impact the type of customer service changes in call centers branch of the customer service organization. And since a consistent decision type will more likely generate accurate decision predictions, this is more likely to work for mid-level managers and not executive levels.
A bonus for the mid-level managers to have consistent decisions is clarity in management expectations. If the managers are comfortable to share the predictions, it could be used to manage expectations within their department. For example, if the employees knows exact how their manager is going to react to a specific scenario, they could adjust their expectations accordingly and synchronize efforts to maximize results. This of course needs trust building between the manager and their direct reports prior to deployment. Ironically, well trusted teams probably already have clear expectations between team members. It’s the new team members that need help the most.
And of course we have to mention that any model prediction involving human decisions requires sanity checks. Blindly trusting a model decision without thinking about consequences invites disasters. Before people start using this more or less automatically, both the manager and their direct reports needs to understand the risk. And if they don’t feel comfortable using the tool, they should be compelled to use it.
I’m interested in what other pros and cons about this application people can think of. I would love to hear any suggestions!
Here is a pitch deck for the product.