5 UX Rules Tech Startups Need To Master

It’s a challenge for any startup to get off the ground these days. The competition is tough and you need to consider a number of factors to stand out and make your project cut through the industry noise. And one of the crucial factors that are often ov…

It’s a challenge for any startup to get off the ground these days. The competition is tough and you need to consider a number of factors to stand out and make your project cut through the industry noise. And one of the crucial factors that are often overseen is ever-expanding customer expectation. That means understanding […]

The Role of Color in UX Design

One of the major factors driving choices of color in UX design is the psychological impact it has on the user. While a lot of people might deem a color choice to be an embellishment of sorts, every color has a specific mood and niche in the color palet…

One of the major factors driving choices of color in UX design is the psychological impact it has on the user. While a lot of people might deem a color choice to be an embellishment of sorts, every color has a specific mood and niche in the color palette in general. While a carefully curated […]

An Ultimate Guide To Write A UX Design Proposal

As a UX designer, you need to have great communication with the clients and stakeholders of the projects you’re handling. Whether you’re working on a website, mobile app, or a service, you and the clients must be on the same page. Why? Beca…

As a UX designer, you need to have great communication with the clients and stakeholders of the projects you’re handling. Whether you’re working on a website, mobile app, or a service, you and the clients must be on the same page. Why? Because you need to understand exactly what they need, and they need to […]

What Your Business Always Gets Wrong When It Comes to UX

What makes for a good user experience (UX) throughout your business model? UX is about more than just your website design, although that is a big part of the equation. How does your business make people feel each time they interact with you? Are your p…

What makes for a good user experience (UX) throughout your business model? UX is about more than just your website design, although that is a big part of the equation. How does your business make people feel each time they interact with you? Are your processes simple and intuitive to the customer’s needs? Studies show […]

Five UX Design Trends that will Impact Your UX Strategy

UX design is one area where you must be constantly evolving. You have to keep an eye on the latest picks, and learn them faster than the speed of light, to match the industry dynamism, and stay on top.

UX design is one area where you must be constantly evolving. You have to keep an eye on the latest picks, and learn them faster than the speed of light, to match the industry dynamism, and stay on top.

An Essential Guide to UX Measurement

UX (User Experience) has a great impact on how long visitors spend on your website and how they engage with it. When people land on your website, they instantly form many impressions that impact their behavior. If they don’t like what they see, or they…

UX (User Experience) has a great impact on how long visitors spend on your website and how they engage with it. When people land on your website, they instantly form many impressions that impact their behavior. If they don't like what they see, or they find the interface confusing or off-putting, they are unlikely to take action or return. In this article, we'll be covering some key UX variables to help you give your visitors a better experience.

Balancing UX with Security

Did you know that in the first half of 2020, the data breaches accounted for 36 billion records!? Well, that reflects the concern one should have for data security. Security is a must-include feature in UX design. However, it is a challenging task to b…

Did you know that in the first half of 2020, the data breaches accounted for 36 billion records!? Well, that reflects the concern one should have for data security. Security is a must-include feature in UX design. However, it is a challenging task to balance security and design. Challenges in UX design with Security UX […]

How to Create Human-Centered Websites with Your Clientele in Mind

Reaching users on a human level requires insight about who your target audience is and how best to serve them. Designers should start with site visitor demographics and branch out to psychographic, hitting all the points a person needs to make an infor…

Reaching users on a human level requires insight about who your target audience is and how best to serve them. Designers should start with site visitor demographics and branch out to psychographic, hitting all the points a person needs to make an informed decision about purchasing or converting into a lead. In a study of […]

The Application of Cognitive Psychology to User-Interface Design

Human beings have different perceptions of the same thing. We think, analyze, and create a picture in our minds. However, the thought-process responsible for the outcome goes unnoticed. This study is related to cognitive psychology. Today, every softwa…

Human beings have different perceptions of the same thing. We think, analyze, and create a picture in our minds. However, the thought-process responsible for the outcome goes unnoticed. This study is related to cognitive psychology. Today, every software company gives importance to cognitive psychology because of its essential role in human decision making. Cognitive Psychology […]

The Power of Exponential Growth | Data Viz to Simplify Complexity

There has been a lot of heartbreak around the world with the CV-19 pandemic. This chart, from NPR, illustrates some cause for optimism. It shows the 7-day average new cases per day across the world. It is crucial to acknowledge what’s hidden in the aggregated trend above: The impact on individual countries is variable. A […]

The post The Power of Exponential Growth | Data Viz to Simplify Complexity appeared first on Occam’s Razor by Avinash Kaushik.

There has been a lot of heartbreak around the world with the CV-19 pandemic.

This chart, from NPR, illustrates some cause for optimism. It shows the 7-day average new cases per day across the world.

Covid 19 Global cases over time

It is crucial to acknowledge what’s hidden in the aggregated trend above: The impact on individual countries is variable.

A large percentage of humans on the planet remain under threat. We don’t nearly have enough vaccines finding arms. We have to remain vigilant, and commit to getting the entire planet vaccinated.

Recent worries about Covid were increased by the proliferation of virus variants around the world. Variant B.1.1.7 was first identified in the UK. Variant B.1.351 was first identified in South Africa. Variant P.1 in Brazil has 17 unique mutations. The variant identified in India, B.1.617.2, had a particularly devastating impact (see the blue spike above). There are multiple "variants of interest" in the United States, Philippines, Vietnam, and other countries.

A particularly dangerous thing about variants is that they are highly transmissible (evolution, sadly, in action).

Some journalists rush to point out, hey, the death rate remains the same.

I believe this is a mistake. It imprecisely minimizes the danger, and results in some of our fellow humans feeling a false sense of hope. This is possibly due to a lack of mathematical savvy.

As Analysts, you can appreciate that a lay individual might not quite understand the complexity behind infection rates, and the impact on death rates. At the same time all of us, journalists and Analysts have to figure out how to communicate this type of insight in a way that everyone can understand.

This reality is similar to what we face in our business environment every single day. We have too much data. It is complicated. There are a lot of things happening below the surface. We somehow have to figure out how to preserve the complexity, but be able to communicate it simply.

Inspired by the work done by Adam Kucharski, mathematician, epidemiologist, and Mona Chalabi, Data Editor at Guardian US, I want to showcase how we can simplify complexity – in this case using Covid data, but the lessons apply across multiple use cases for Analysts.


The Problem.

Let’s simplify the challenge of explaining the problem we face with these variants down to these two scenarios:

Which of these is more dangerous:

1. A variant that’s 50% more deadly?

Or

2. A variant with 50% increase in transmission?

Take a pause with everything you know about Covid and math.

Ponder the problem, and what do you think the answer is?

Get a Post-It. Do some rough computations. Note your assumptions.

Did you choose #1 or #2?

Ready?

The Answer.

Have you heard someone say humans are not wired to understand the impact of compounding interest?

Applies here as well.

As Adam explained:

An increase in something that grows exponentially (transmission, in this case) can have far more effect than the same proportional increase in something that just scales an outcome.

Or, in English, as I suspect you all already noted above: #2 is the worse scenario.

It is far worse if the new virus variant is 50% more transmissible.


The Answer in Equations.

R represents the reproduction number. Let’s assume R to be 1.1.

This means that every 10 people who are infected will infect another 11 people.

[You can assume whatever R, math still works.]

F represents the fatality rate. Let’s assume F to be 0.8%.

This means that 8 out of every 1,000 people who get the virus will die.

G represents generation time. Let’s assume G to be 6 days.

This means that from the time that someone is exposed, it takes around 6 days for them to infect the next person. So each month, the virus can generate about 5 times. (30/6=5)

One final assumption, let’s assume 1,000 people were infected.

Scenario Normal

1,000 x (1.1^5) x (0.8%) = 12.9 fatalities after 1 month.

[For extreme clarity: 1.1^5 denotes 1.1 to the power of 5.]

Scenario 50% More Deadly

1,000 x (1.1^5) x  (0.8% x 1.5) = 19.3 fatalities after 1 month.

A sad increase for sure. But. Wait.

Scenario 50% More Transmissible

1,000 x ((1.1 x 1.5)^5) x 0.8% = 97.8 fatalities after 1 month.

OMG.

12.9 to 97.8.

This is why all the scientists, and ultimately Boris J as well, got so freaked out about a variant that was 50% to 75% more transmissible.

The math is scary at the higher end of that range.

If folks in your circle are less well versed in exponential growth (in their bank account, in loss in retail stores, or pandemics), do please take a moment to illustrate that for them.

You’ll be helping them think smarter.

Analysts typically feel that they are done at this stage. They got the data. They got the formula. they did the math. It is all so clear.

And, they are right. It is clear. But. It is not yet as accessible as it could be.

I urge you to think about accessibility of your work.


The Answer Visualized.

The “problem”, if I may use that ugly word, with the formulas above, is that they are a little bit dry.

Well. Maybe, it is more accurate to say: They are not quite as accessible.

A lot of people have a natural aversion to math. Even simple formulas like the one above can seem intimidating.

In life, and at work, perhaps the #1 job we have as Analysts is to be able explain data in a way that’ll be understood.

This is where Mona stepped in to help. She built on Adam’s excellent insights and explanation, and sketched some pictures that made the analysis potentially accessible to everyone on the planet.

Let’s do the exercise again.

Scenario Normal.

You’ll recall from above, the normal Covid scenario was:

1,000 x (1.1^5) x (0.8%) = 12.9 fatalities after 1 month.

Here’s Mona’s simplified visualization to make the formula a ton more accessible to all humans of the planet:

Covid 19 transmission - normal scenario

Isn't it more accessible compared to the formula?

Of course it is.

We all have this opprotunity in our day to day business work (in addition to an opportunity for all journalists who have to make this, literally, life and death data more accessible).

Let's keep going.

Scenario 50% More Deadly.

The challenge is to simply visualize this formula:

1,000 x (1.1^5) x  (0.8% x 1.5) = 19.3 fatalities after 1 month.

Here’s the visual:

Covid 19 transmission - more deadly scenario

Simple. Effective.

And now to our final scenario.

Scenario 50% More Transmissible

Our formula for the impact of 50% more transmissible:

1,000 x ((1.1 x 1.5)^5) x 0.8% = 97.8 fatalities after 1 month.

Mona’s visual to illustrate the impact:

Covid 19 transmission - more transmissible scenario

The simple visualizations, (possibly hand drawn?), make the data exponentially (there’s that word again) accessible.

While the data is heartbreaking, I had a momentary smile from appreciation for Mona and Adam for this timely and accessible lesson for all of us.


The Answer Visualized, Try 2.

There are many other ways to illustrate this data.

One thought I had was, I wonder if we should have three boxes?.

One for 1,000 infected. A second one for the increase in infections (huge in scenario three).

A third one for the unfortunate increase in deaths.

More information to sketch, I’m so wary of clutter in these cases. Something to sketch and see how it comes out.

My friend Kaiser Fung illustrated an alternative approach in a recent post on his excellent, and I really mean excellent, blog Junk Charts.

For a (poor) visualization used in a video published in Germany, showing the danger posed by new variants, Kaiser whipped up R = 1.0 and R = 1.4.

[Note: Being 50% to 70% more transmissible means the reproduction rate goes from 1 to 1.4.]

Here’s R = 1.0.

Kaiser Fung - R 1.1 visual

A very different approach to simplifying the complexity in the data, and a very different approach from the ones earlier in this post.

All in all, such an interesting visual.

I like that in a way it captures the haphazardness / randomness of the actual spread.

And here’s what happens when R = 1.4.

Kaiser Fung - R 1.4 visual

It depicts something truly heartbreaking, but does so in a mesmerizing way.

[I grew up in India, R1.4 reminds me of a mandala.]

More infections obviously mean more deaths (holding deaths constant as above).

The super nerd in me loves Kaiser’s version. There is an organic chemistry virusy nature of the visual that holds a certain appeal.

My experience would suggest that Mona’s is unquestionably more accessible. I would use something like Kaiser’s for certain audiences.

I wanted to share Adam's formulas, Mona's visuals and Kaiser's mandalas to highlight the diversity in the paths we can take on the quest for data accessibility.


Bottom line.

In the quest to communicate your insights more clearly, you can pick the path that works optimally for your audience knowing that there are multiple paths for simplifying complexity.

However you choose to do it, I urge you to figure out how to convert your numbers, assumptions, and formulas into a visual story that’ll make your insights more accessible.

Good for you. Good for the audience. Good for your company/planet.

Carpe diem!

As always, it is your turn now.

Please share your critique, reflections, and your lessons from the approaches you have taken in your quest to simplify data’s complesity. Thank you.

The post The Power of Exponential Growth | Data Viz to Simplify Complexity appeared first on Occam's Razor by Avinash Kaushik.