Unifying Data Analytics & Experience Design: a 3rd Corner introduction

Joining two approaches

Over the past decade, two disciplines have grown in popularity and relevance — data analytics and human-centered design.

Their rise was largely tied to the fact that both helped us understand and unravel problems in new ways. This was, and is, a positive thing.

The less positive thing is that we created separate worlds for these two disciplines. We often viewed data analytics and human-centered design as separate approaches dealing with two different types of data, the quantitative and qualitative, respectively.

Quantitative data, that which:

• answers questions like “What are they doing?”, “How much?”, “How many?”, “How often?”.
• comes in the form of numbers, can be verified upon review and can be evaluated using mathematical techniques and statistical analysis.
• is collected via surveys, databases, Customer Relationship Management (CRM) data and behavioral analytics.
• has “consistency of measurement” — when the question is “how many apples do you have?”, the difference between 6 and 8 is easy and always the same.

Qualitative data, that which

• answers questions like “Why are they doing it?”, “How?”, “What type?”, “What for?”.
• is non-numerical and collected via interviews, contextual observations, focus groups, etc.
• approximates and characterizes how people feel about themselves and the properties of phenomena around them.
• often lacks “consistency of measurement” — when the question is “on a scale of 1–10, how much pain are you in?”, the difference between 6 and 8 is not so clear and rarely the same.

When tackling a problem, data analysts and data scientists often take a quantitative approach to build hypotheses, refine a point-of-view and offer solutions. This involves data preparation and exploration, model creation and insight generation, and finally, refinement, validation and embedding of actionable analyses.

Human-centered designers frequently look to do the same thing via a qualitative approach (the double diamond is a common reference). This takes the form of user research, insights and principles synthesis, point-of-view construction, ideation and prototyping, and finally pre-launch refinement of a service or experience.

Yes, data analysts/scientists and the human-centered designers represent two different disciplines. But at a closer look, the essence of their approaches is quite similar.

Both aim to organize, structure and present data so that it becomes useful information. Both explore context, develop hypotheses and points-of-view, and refine solutions to solve complex problems.

Yet, at large corporations and even startups, it is all too common for data analysts/scientists and human-centered designers to treat each other like service providers, to work divided, and to not collaborate holistically and consistently.

I do not want to imply that analysts or designers always choose one approach and ignore the other. I do not want to imply that I am the first person to propose a mixed quant-qual approach.

But I do want to propose the following: to build digital products, data analysts/scientists and designers need to leverage each other’s processes and work as a unit. This unit should research, empathize, hypothesize, synthesize, think of variables and model approaches, sketch and prototype together.

Many companies do not successfully balance and blend mindsets from the quantitative and qualitative worlds. Many more do not even try. But marrying these two mindsets is critical, even necessary, for us to appreciate and make calibrated decisions in our increasingly nuanced and data-rich existence.

The Whats. The Whys.
The numbers. The feelings.
Two types of data.
Together they improve how we approach daily activities, challenges, and conclusions.

This was the inspiration for 3rd Corner.

3rd Corner & the road ahead

In August 2019, I started 3rd Corner, a consultancy that helps clients blend the lenses of data analytics, data science and human-centered design to see and solve challenges with a new focus. We work with designers, data scientists and strategists to deliver this.

Understanding people and the world around them became a primary interest of mine while studying anthropology in my last two years of college. This interest not only pushed me to live in West Africa, Europe and Latin America but it also colored my professional pursuits. Years working with financial strategy and quantitative analysis, and then human-centered research and design strategy, helped me develop different tools with which to perceive the data all around me. The more opportunities I had to combine these tools, the more I saw the potential to blend experience design, data analytics and data science.

When orchestrated well, this blend brings the rigor, the creativity and the balance that is essential to our work at 3rd Corner.

The Work

Some of the challenges we have worked on / are working on in our first year (client specifics are currently confidential):

• We are leading a quantified user insights initiative for a platform that aims to democratize investing. We are implementing a process that quantifies user behavior, characteristics, and journeys as well as identifies actionable data in user clusters. We are setting the groundwork for multidisciplinary data science and design teams to leverage quant and qual data to prioritize value and problem-solving efforts.
• We collaborated with an Artificial Intelligence (AI) firm to help a medical network use Natural Language Processing (NLP) to extract meaningful information from language data. We recognized that while AI is a powerful tool, alone it cannot determine which human problems to tackle. Thus, to best leverage NLP, we designed data ideation workshops and mapped data workflows to strategically enhance doctor, administrative and patient experiences.
• We are coaching product designers and data analysts at a financial services company to establish data-driven Design Research Operations. At its core, this involves developing quant/qual research tools relevant to all phases of the product lifecycle — discovery, development and delivery. We believe this will enhance how exploratory and strategic research improve company-wide product decisions.
• We are leading a fashion design company in the implementation of agile-inspired routines. Our goal is to improve how data flows from collection-to-use across analytics and design squads, as well as how experiment with a focus on iterative measurement.
• We worked with a sustainability-focused agency to help them strategize the prototyping of new business models as well as how to creatively think about new metrics and data collection.
• We advised a digital media company aiming to enhance their qualitative research by collecting new types of data via quantitative methods.

Why Now

We realize that companies vary in their ability to blend the efforts of designers, data analysts and data scientists. But this does not stop us from helping clients understand why joining these disciplines is relevant now.

1. It turns out that opposites attract. Over the last decade, human-centered designers and data scientists and analysts have become the popular kids at school. Unfortunately they are often on different, if not opposite, sides of problem-solving and decision processes. But by bringing them together into collaboration units, designers and data scientists and analysts can unlock new insights born out of leveraging their differences: data-informed ideation, machine learning segmentation and outlier-inspired research, prototypes that consume and produce analyzable data, etc.

2. Alone, traditional needs-focused UX work is less and less differentiating. Good User Experience (UX) patterns are no longer secrets; the “design thinker” explosion means in-depth interviews and empathy maps are the norm. As a result, we should not expect differentiation to solely come from how emotionally in-touch, contextual or beautiful our digital services are.

Because many of these services are (at least partially) “fueled” by data that users provide (via direct responses, trigger events, inference of behaviors, etc.) it is increasingly critical to tie the data to the user in actionable ways. Differentiation will come from how we combine contextual empathy work with an understanding of quantitative variables that approximate human sentiment and behavior. This way our products can manifest an understanding of how the data implies intentions, aspirations and desires of individuals.

3. The abundance of quantitative data demands more considered, empathetic treatment. “More data, more problems” becomes our reality if we are careless. Technical capacity to track and ingest rich, large sets of data is only worth so much if we are not considerate about how we select, transform and display it. Consistent collaboration between analysts, scientists and designers helps us ask better questions to filter and frame this data, aligning powerful systems with human needs.

This collaboration also helps us design products with “data journeys” better suited to receive, share, and leverage users' data in ways that solve functional needs as well as respect privacy and transparency.

4. We are increasingly aware of the real complexity of challenges. Whether it is increasing employment for low-income workers via an app or educating young parents about child development via a service, the challenges we face are nuanced. Individuals have more access to opinions, emotions, facts, and numbers than ever before. Implicitly, many individuals expect “problem-solvers” to synthesize these multiple sources and perspectives.

If data analysts, data scientists and human-centered designers work as a unit, we get closer to reaching the expectation for more holistic solutions to complex challenges.

We look forward to the challenges ahead.

Reach Out and Stay Tuned

If you are interested in learning more, reach out at contact@3rdcorner.studio

And watch for future posts about how we think, what we are doing, and what we are learning.

A sincere thanks is owed to several people for their support, collaboration, feedback, and edits: Talita Di Iorio, Noah Norman, Dave Zaretsky, Will Heidrich, Muamer Cisija, Rafael Fernandes.