What Great Data Can Do for Design

When designers think of great design, quantitative data rarely features in the imagination. Because experienced designers know that the most surprising and insightful moments will often come from some of the briefest and most nuanced interactions. They are weary of the potentially overpowering nature of quantitative data, with the knowledge that once people fall in love with numbers that go “up and to the right”, it can be particularly hard for them to break free.

By Geoff Lew

Designers have intuitively developed trust in their own design process – trust that comes from having faith in the research process, keeping an open mind, and being able to draw connections between the dots.

But this has also meant that designers have, somewhat unconsciously, chosen to drift away from incorporating quantitative data into their work. Designers are missing the opportunities for quantitative data to tell them something surprising, and are missing the opportunity to use it to talk more confidently and convincingly about what they know.

Designers today need to (re)learn how quantitative data can be incorporated into the design process. And they need to recognize that this will take a surprising amount of deliberate effort and focus, particularly as we often don’t know what data or metrics might be key at the start of a project. Like qualitative research, part of the process is to try and find a path to the right information.

To help designers (re)embarking on this journey, the following are three areas where quantitative data can reliably add to the design story.

Use quantitative data as a guide to finding the right questions

Quantitative data can help us to explore the tension between what people do, and what they say they do. Reality is rarely what we expect because most communication is by listening to stories. Great data can guide us to finding the outliers, to finding those fringe use cases, or to learn about something completely at odds with what we might be hearing.

Tandem7 once worked with a client to improve employee productivity, and in the interviews we consistently heard about the high adoption rates and improving user experience of the client’s internal processing system. However, it was not until taking a closer look at the adoption rates that we found that while the adoption of the system was increasing overall, it was not increasing evenly. There were some office locations that were frequently not using the system.

We eventually found that these were smaller offices which were not provided with sufficient training on how to use the systems. And, despite their complaints, were consistently overlooked as candidates for training due to their size. This meant that staff had to perform workarounds to compensate for what could not be done automatically, as well as relying on one or two staff to process the large backlog.

Using quantitative data helped us to challenge the stories we were hearing, and to seek out information in unexpected areas.

Use quantitative data to compare the incomparable

In the design process, it is always the context that matters. Both a blessing and a curse, one limitation of qualitative information is the ability to compare. It is by nature blunt, and biased towards the perspective of its source. Quantitative data allows us to better see and understand how things are changing, by showing us the patterns and meaning behind stories or feedback.

Methods such as surveys have commonly been used as a way to generate useable quantitative data, and  organizations are increasingly using surveys in simple, but novel ways. For example, Harvard Business Review[i] found that one organization tried to generate quantitative data around employee performance by asking managers to answer the same set of binary questions e.g. “This person is ready for promotion today. (Yes/No)”

Where organizations have traditionally struggled with objectively assessing and comparing employees, given the anecdotal nature of feedback, these binary responses gave the organization a powerful dataset to objectively compare performance.

Additionally, as more powerful analytics and artificial intelligence engines become available, designers will have quantitative data in areas where it was previously thought unavailable. For example, cloud based platforms like Dataminr, Sprinklr and Quip leverage social media and text analytics to help identify changes in customer sentiment in response to trigger events. These analytics help organizations analyze and compare customer reactions, and allow them to find new ways to enrich customer experiences.

Use quantitative data to illuminate the moments that mean the most

Quantitative data is only relevant if we are able to draw a line to how it relates to actions and stories of people. It needs to tangibly measure and relate to what people want to accomplish in the moments that matter in their journey.

Quantitative data is particularly powerful if it is used with precision, if it is used to identify the specific actions or change in behavior that would result from a movement in a metric. This forces the designer to define success in terms of the user’s journey.

At Tandem7, we enforce this discipline by linking metrics to the moments that matter in an individual’s journey –  whether it be the journey of an external customer or the journey of an internal employee. This explicit, and visual link, enabled through Cora Journey360 allows us to be extremely disciplined – it forces us to focus and measure the work we do through metrics that have a direct impact on the customer or employee. It allows us to transmute what can be complex and voluminous data into something relatively simple for all stakeholders to see. This ensures that the changes we are driving are meaningful to the user, and that actions are not taken just because the underlying data has changed.

Caption: View of an onboarding  journey within Cora Journey 360, with metrics measuring changes to the moments that matter in the customer’s experience

Designers need to continue refining their ability to make sense of data, and to use it in simple and meaningful ways. While the complexity of data in modern organizations may be increasingly prohibitive,  designers need to turn and embrace incorporating quantitative data in their work. Encouragingly, in some ways designers already have an intuition for applying great data to design, as they have been trained to focus on simplicity, and have an innate ability to filter out the noise.

When designers think of great design, quantitative data rarely features in the imagination. Because experienced designers know that the most surprising and insightful moments will often come from some of the briefest and most nuanced interactions. They are weary of the potentially overpowering nature of quantitative data, with the knowledge that once people fall in love with numbers that go “up and to the right”, it can be particularly hard for them to break free.

By Geoff Lew

Designers have intuitively developed trust in their own design process – trust that comes from having faith in the research process, keeping an open mind, and being able to draw connections between the dots.

But this has also meant that designers have, somewhat unconsciously, chosen to drift away from incorporating quantitative data into their work. Designers are missing the opportunities for quantitative data to tell them something surprising, and are missing the opportunity to use it to talk more confidently and convincingly about what they know.

Designers today need to (re)learn how quantitative data can be incorporated into the design process. And they need to recognize that this will take a surprising amount of deliberate effort and focus, particularly as we often don’t know what data or metrics might be key at the start of a project. Like qualitative research, part of the process is to try and find a path to the right information.

To help designers (re)embarking on this journey, the following are three areas where quantitative data can reliably add to the design story.

Use quantitative data as a guide to finding the right questions

Quantitative data can help us to explore the tension between what people do, and what they say they do. Reality is rarely what we expect because most communication is by listening to stories. Great data can guide us to finding the outliers, to finding those fringe use cases, or to learn about something completely at odds with what we might be hearing.

Tandem7 once worked with a client to improve employee productivity, and in the interviews we consistently heard about the high adoption rates and improving user experience of the client’s internal processing system. However, it was not until taking a closer look at the adoption rates that we found that while the adoption of the system was increasing overall, it was not increasing evenly. There were some office locations that were frequently not using the system.

We eventually found that these were smaller offices which were not provided with sufficient training on how to use the systems. And, despite their complaints, were consistently overlooked as candidates for training due to their size. This meant that staff had to perform workarounds to compensate for what could not be done automatically, as well as relying on one or two staff to process the large backlog.

Using quantitative data helped us to challenge the stories we were hearing, and to seek out information in unexpected areas.

Use quantitative data to compare the incomparable

In the design process, it is always the context that matters. Both a blessing and a curse, one limitation of qualitative information is the ability to compare. It is by nature blunt, and biased towards the perspective of its source. Quantitative data allows us to better see and understand how things are changing, by showing us the patterns and meaning behind stories or feedback.

Methods such as surveys have commonly been used as a way to generate useable quantitative data, and  organizations are increasingly using surveys in simple, but novel ways. For example, Harvard Business Review[i] found that one organization tried to generate quantitative data around employee performance by asking managers to answer the same set of binary questions e.g. “This person is ready for promotion today. (Yes/No)”

Where organizations have traditionally struggled with objectively assessing and comparing employees, given the anecdotal nature of feedback, these binary responses gave the organization a powerful dataset to objectively compare performance.

Additionally, as more powerful analytics and artificial intelligence engines become available, designers will have quantitative data in areas where it was previously thought unavailable. For example, cloud based platforms like Dataminr, Sprinklr and Quip leverage social media and text analytics to help identify changes in customer sentiment in response to trigger events. These analytics help organizations analyze and compare customer reactions, and allow them to find new ways to enrich customer experiences.

Use quantitative data to illuminate the moments that mean the most

Quantitative data is only relevant if we are able to draw a line to how it relates to actions and stories of people. It needs to tangibly measure and relate to what people want to accomplish in the moments that matter in their journey.

Quantitative data is particularly powerful if it is used with precision, if it is used to identify the specific actions or change in behavior that would result from a movement in a metric. This forces the designer to define success in terms of the user’s journey.

At Tandem7, we enforce this discipline by linking metrics to the moments that matter in an individual’s journey –  whether it be the journey of an external customer or the journey of an internal employee. This explicit, and visual link, enabled through Cora Journey360 allows us to be extremely disciplined – it forces us to focus and measure the work we do through metrics that have a direct impact on the customer or employee. It allows us to transmute what can be complex and voluminous data into something relatively simple for all stakeholders to see. This ensures that the changes we are driving are meaningful to the user, and that actions are not taken just because the underlying data has changed.

Caption: View of an onboarding  journey within Cora Journey 360, with metrics measuring changes to the moments that matter in the customer’s experience

Designers need to continue refining their ability to make sense of data, and to use it in simple and meaningful ways. While the complexity of data in modern organizations may be increasingly prohibitive,  designers need to turn and embrace incorporating quantitative data in their work. Encouragingly, in some ways designers already have an intuition for applying great data to design, as they have been trained to focus on simplicity, and have an innate ability to filter out the noise.

Interested in partnering with us?

Send a message and we will work with you to understand your needs.

UX360 - Enterprise Journey Mapping Platform

Power Platform

UX360 - Enterprise Journey Mapping Platform
Related Insights from Our Experts

Related Consulting Solutions

Journey Mapping

Visualize your customer’s pain points and gaps, and create the future state customer journey. We put our tried and true journey mapping methodology to work to align your organization around your customer and use our UX360 platform to help create, store and share these assets.

Customer & User Research

Ground your CX initiatives on real insights uncovered via contextual inquiry.

2018-05-02T14:42:24+00:00