How Thinking Like a Product Designer Changed My Design Handoffs

Let me paint you a picture of Junior Me.

I’d whip up a design, slap together a shiny mockup, and send it off to the developers, feeling pretty damn proud of myself. I’d whip up a design, slap together a shiny mockup, and send it off to the developers, feeling pretty damn proud of myself.

Junior Me thought, “Hey, if it looks good, we’re good, right?”

Wrong. So very wrong.

Fast-forward to now, and my deliverables are unrecognizable compared to those plain mockups of the past. I’ve learned — sometimes the hard way — that the job doesn’t stop at making things look pretty.

As a product designer and now product manager, I’ve realized that great deliverables anticipate problems, answer questions, and make the dev team’s life a whole lot easier.

Here are five lessons I’ve learned about deliverables that Junior Me could’ve never imagined.

Fast-forward to now, and my deliverables are unrecognizable compared to those plain mockups of the past. I’ve learned — sometimes the hard way — that the job doesn’t stop at making things look pretty.

As a product designer and now product manager, I’ve realized that great deliverables anticipate problems, answer questions, and make the dev team’s life a whole lot easier.

Here are five lessons I’ve learned about deliverables that Junior Me could’ve never imagined.

Best practices for working with big data tables

Designing tables for large datasets is a whole different story. Big data tables need optimized designs and smart interactions to make sure users can navigate and analyze data efficiently. Here are some best practices to keep in mind when working with big data tables:

1. Enable advanced sorting and filtering

When you’re working with big data sets, it’s important to have effective ways to sift through all that information. Sorting and filtering are key tools for helping users find relevant data quickly.

• Multi-level sorting: Let users sort by multiple columns at the same time. For instance, users might want to sort first by department, then by revenue and then by date.
• Dynamic filters: give users the option to filter as they type or select options. Filters should be simple to understand, easy to use and flexible, so users can easily customize their views of the data.