The 5 stages of Data + Design

Written by Mustefa Jo'shen

July 19, 2016

Designing with Data for enterprise startups

Our 5 stage model. It’s your model too.

Who’s afraid of the big bad wolf?

Not us. Read along to learn how you should start thinking about data design.

But who’s afraid of the Big Bad Wolf?

We generally encounter data-design when we work with companies solving complex problems using…‘big data’.

The biggest problem isn’t big-data design, but when designers, product folks, or founders find themselves wanting to visualize data without a purpose– just for the sake of the pretty data.

And if you dive too deep in big-data design, you can drown in it. And so it’s our job to recognize the 5 stages of data design.

I want you to save yourself time and draw a roadmap for data & design in your services or products through 5 stages.

Plot it out in your head or on a paper as you read along.

Stage 1: Data + Tables:

Where it all starts. I love living here: CSVs, Excel, & Sheets. You can even create your own table UI that’s clear and easy to use to navigate big data-sets. Here’s an example of work we did with ThinkData Works on their Namara platform.

a CSV image.
Data in tables can be pretty to look at, and navigate…

It’s pretty stellar data design, and they’ve done some great work on the evolution of the platform, being used with Thompson Routers. 💥

Just presenting data in standardized tables and making them highly usable and accessible. Simple ideas, major keys.

But tables still don’t scale in usability within enterprise applications (esp. for non pro-users and stakeholders). Which brings us to charts.

Stage 2: Charts

Hockey sticks, trends, and pie 🎂

We use legends to explain what we’re trying to show with the charts. They show relativity of data for our interpretation of it. The data helps us make decisions to take actions.

But charts present limited amounts of data sets, and you need lots and lots of charts to explain complex relational databases of content. That’s not fun to build, let alone use and navigate.

Charts are data @ the communication stage, but still needs a presenter to help make sense of it.

Stage 3: Data Visualization

This is where things get fun, and is our first chance to try to impact user perspectives through rich & interactive data.

Communicating large sets of data.. with some insight…

With Akindi we used graphs, data visualization, and we even summarized it. We even gave some insights through conversational sentences to help users understand what they’re looking at.

A lot of us stop here when designing and building web and mobile applications. Even when providing our services.

Impactful design with data is about going the extra mile. And that’s our job. It’s applicable in everything that we put our efforts into, so why not how we dig up and deliver data to people?

But this is just scratching the surface.

And it’s not a groundbreaking concept: but there’s more to presenting data than visualization. that’s where we dive into really thinking about the users’ experience– not for the sake of the app experience.

DJ scratching from scratch?

Once we’ve mastered understanding our fundamental understanding of interacting and leveraging data sets in product design, we move beyond the interfaces of data and into the intelligence and meta-data that it holds.

Intense, I know, just read…

Stage 4: Insights & Recommendations

I call this “there is no spoon” data.

Insights are where you want to live because you add value to someone looking at your data-sets and UI. You want to do some work for them, answering the question of “why am I looking at this data? What am I going to use it for?”. If we can answer those questions for our users without them looking at fancy visualizations, we’ve done our job.

With recommendations, we’re finally using data to to proactively piece together what you’re going to do with insights…

& here’s where we’re most excited in working right now, in creating Critical Thinking programs that works with you to uncover the value that you’re looking for in interacting with tech.

Data-Value is a big deal & it’s where you need to start with data design

Bridge the gap and switch your mindset from this conversation:

Q: After I give you insights into your data, what are you going to do?

A: I’m going to decide on variables to change that will help me achieve my goals…

… to this conversation with your users.:

“Good morning, based on X & Y, you need to change variables 1, 2, 3 for the product you’re selling to hit an expected result based on this, that, and the third goals”. 🔑

This is where our users and customers have an opportunity to deep-dive from stage 5 all the way to stage 1 to validate your insights and recommendations through the data itself: see insights, data visualizations, charts, and raw source data.

Now you’re partying with data.

Two more things + a recap:

Thing #1. We’re talking about funnels

The higher in the funnel you are, the less you are able to scale dealing with your data…

The more you visualize and present conclusions, the higher your value.

Until you get to the ultimate value of intelligent narratives in product design.

Where are you on the value chain?

Thing #2: We’re really talking about cycles…

What are the right recommendations that will prompt the right actions that create new data so that we can get the right actions to CREATE A STRONG CYCLE…

Data -> Action and back again.

What data will drive us to take the right action? & at what stage of data design is it appropriate to invest in communicating the data that will deliver the most impact?

I hope this 30,000 ft. overview helped give you insight into how you’re dealing with data.

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Ci. a User Experience & Design Thinking Agency in Toronto. Our studio solves complex problems & designs digital products and services for organizations to help them grow.

Want to work together? Connect with Mustefa of LinkedIn or email