Cracker takes inspiration from a framework described by bestselling authorJim Collins in the above interview. Collins there describes how value that can derived from three simple datapoints. This mixture of qualitative and quantitative data can be quite telling when properly analyzed. We've tested the framework and found value in it, which is why we want to make it accessible to all. Cracker is the solution we came up with. Your job is to enter the same three fields mentioned in the interview:

  • Overview: A record of your day no longer than a tweet. Anything that comes to mind is probably worth noting. Don't sweat the grammar here, just focus on the actions that defined your day
  • Number of creative hours: Keep track of the time you spend doing work that is new and creative
  • Rating: In retrospect, how do you feel about your day. +2 is excellent, -2 is bad, zero is “eh”

Once you've done so, your dashboard will be updated. The dashboard is a tool that enables you to visualize and step through your data. Jim mentioned that his motivation for starting this was to hold himself to the standard of doing 1000 hours of creative work per year. In the metrics section, we do the math and let you know how many hours you're on track to log this year. We also give you a count of each of the five ratings. You can pivot this section to be representative of the past 30, 60 or 90 days. The dashboard also helps you step through your cumulative overviews by providing a word cloud. This is a visual representation of the amount of times words come up in your data. Words that you used often will appear large in proportion to the number of times they were mentioned, and vice versa. This feature is interactive and allows you to investigate your use of specific words relative to the other two metrics you provide when using them.

These are the core features of Cracker that are designed to shed optimal on the incredibly simple data you've provided. On top of all that, we're also an AI platform. This app is a perfect use case to take advantage of textual analysis tools being rapidly developed in the AI community. We are currently leveraging Google's Natural Language API to identify sentences, tokens, and entities in your data and provide you with insights from the AI that can be found in the dashboard's additional tables. We plan to continue exploring new tools in the industry with the goal of providing our users the richest experience possible while analyzing their data. We believe this framework alone can change lives, and we plan to take it a step further with our software.

The Reflective Hour will always be transparent about our software architecture and the handling of our users' data.