How Data Will Drive The Next Big Design Trends
Summary
TLDRThis video explores the growing trend of data-driven design in product development. Highlighting Microsoft's HoloLens 2 as a case study, it demonstrates how analyzing millions of data points can lead to innovative, comfortable, and competitive products. The video also discusses the ethical considerations of data collection, emphasizing the importance of transparency and customer benefit. It concludes by stressing the need for a balance between leveraging data for innovation and respecting privacy.
Takeaways
- 📊 Data-driven design is becoming increasingly important in the 2020s and will likely continue to be a significant trend in product design.
- 🧠 Data refers to facts and statistics collected for analysis, and its use in product design is not new, but the scale and impact of big data are transforming the field.
- 🎯 Microsoft's HoloLens 2 is an example of how data was used to create a one-size-fits-most design, accommodating the diverse shapes and sizes of human heads.
- 🔥 The use of a digital twin in the design process of HoloLens 2 allowed for thousands of trials and tests to manage heat dissipation efficiently, leading to a more comfortable product.
- 🛠️ Data can provide a competitive advantage in product design, but it's essential to use it smartly and understand when diminishing returns set in.
- 🏥 Insight Surgical uses computer vision and data to improve patient safety in the operating room, demonstrating the life-saving potential of accurate data collection.
- 🤖 The difficulty in obtaining certain types of data, like medical records, can create a barrier to entry for competitors, thus enhancing the value of the data collected.
- 🏎️ Companies like Zinger use data to optimize their products, such as the strength-to-weight ratio in their hypercars, through computer simulations.
- 👟 Nike leverages data to customize athletic gear, like outsoles for shoes, to enhance performance, which contributed to their athletes' success in the 2016 Rio Olympics.
- 👗 Shein, a fashion brand, exemplifies how data from social media and trending searches can rapidly inform product decisions and disrupt the fast fashion market.
- 🤔 Ethical considerations around data collection are crucial; companies must balance the benefits of data-driven design with the privacy and consent of their users.
Q & A
What is the main focus of the video script?
-The video script focuses on the importance of data-driven design in product development, its impact on innovation, and the ethical considerations around data collection.
Why is data-driven design considered a significant trend for the 2020s and beyond?
-Data-driven design is significant because it allows for the collection and analysis of vast amounts of data, informing product decisions and enabling innovations that were previously impossible.
What was Microsoft's approach to designing the HoloLens 2 headset?
-Microsoft scanned thousands of people's heads to gather data on head shapes and sizes, which helped them create a 'one size fits most' design for the HoloLens 2 headset.
How did Microsoft address the issue of heat management in the HoloLens 2 design?
-Microsoft used a digital twin, a computer simulation of the physical device, to conduct thousands of trials and tests, ultimately finding a solution to effectively diffuse heat away from the user's face.
What is a digital twin and how was it utilized in the design of HoloLens?
-A digital twin is a digital clone of a physical product. In the case of HoloLens, it was used to simulate the product's performance, allowing for rapid iteration and testing of design solutions.
How does data-driven design provide a competitive advantage?
-Data-driven design provides a competitive advantage by enabling companies to make more informed decisions, create more effective and personalized products, and stay ahead of competitors through continuous improvement.
What ethical considerations are mentioned in the script regarding data collection?
-The script discusses the importance of collecting data in an ethical way, such as ensuring anonymity and transparency with users about what data is collected and how it's used.
Can you provide an example of a company using data to improve product design in the medical field?
-Insight Surgical is an example of a company using computer vision and data to identify tools in the operating room, aiming to prevent accidents like leaving a gauze pad inside a patient.
How does data influence the design and what to design in the context of the fashion industry?
-In the fashion industry, companies like Shein use data from social media and trending search terms to quickly produce and test new garments, responding to trends faster than traditional fast fashion brands.
What are the potential downsides of data-driven design mentioned in the script?
-The script mentions that while data-driven design can lead to innovation, it can also lead to ethical concerns around privacy, potential misuse of data, and the risk of companies collecting more data than necessary.
How can companies ensure they are collecting data ethically and beneficially for their customers?
-Companies can ensure ethical data collection by asking if the data benefits the customer, being transparent about what data is collected and how it's used, and seeking customer consent in a clear and straightforward manner.
Outlines
📊 Data-Driven Design: The Future of Product Innovation
The video script discusses the growing importance of data in product design, emphasizing its role as a key trend for the 2020s and beyond. It highlights how data collection, especially at a massive scale, is transforming the way products are designed. The script uses Microsoft's HoloLens 2 as a case study, illustrating how data on head shapes and sizes was crucial in creating a comfortable, one-size-fits-most headset. It also touches on the use of digital twins for heat management in the device, showcasing the competitive advantage gained through data-driven design. The summary underscores the impact of emerging technologies like cloud computing and machine learning in making data analysis more accessible and powerful for product innovation.
🔍 Ethical Considerations and Competitive Advantage in Data Usage
This paragraph delves into the ethical controversies and competitive advantages associated with data collection and usage. It contrasts the accessible yet easily replicable data of Microsoft's headscans with the more exclusive and difficult-to-obtain medical data used by Insight Surgical, which has a significant impact on patient safety. The script also discusses the challenges of obtaining medical data due to strict regulations and the importance of collecting data ethically. It further explores how data can be quickly copied by competitors, diminishing its long-term value, and provides examples of other companies like Zinger and Nike using data for product optimization and performance enhancement. The summary also addresses the ethical implications of data collection, privacy issues, and the importance of transparency with users regarding data usage.
📈 Data's Role in Shaping Business Strategies and Consumer Experiences
The final paragraph examines how data is not only informing the design process but also driving what products are created. It presents Shein, a fashion brand leveraging social media data for rapid market response, as an example of a company using data to understand and capitalize on trends quickly. The script critiques fast fashion's questionable ethics, including copying designs and environmental concerns, while acknowledging Shein's successful data-driven strategy. It also discusses the broader implications of data collection for businesses, including the potential negative impact on consumer trust and the importance of collecting data that benefits the customer. The summary concludes with a call for companies to be mindful of the balance between business advantage and customer benefit in their data strategies.
Mindmap
Keywords
💡Data-Driven Design
💡Data Collection
💡Digital Twin
💡Heat Diffusion
💡Competitive Advantage
💡Computer Vision
💡Customizability and Personalization
💡Ethical Controversies
💡Fast Fashion
💡Data Privacy
💡Cloud Computing
Highlights
Data-driven design is becoming a crucial trend in the 2020s, influencing product design through the use of vast amounts of data.
Microsoft's HoloLens 2 project exemplifies the use of data in product design, overcoming challenges in creating a universally comfortable headset.
Data collection allowed Microsoft to scan thousands of heads to determine the ideal shape for the HoloLens 2, ensuring comfort for a wide range of users.
Heat management in the HoloLens 2 was addressed using a digital twin, a digital replica of the device for simulation and testing.
The digital twin facilitated rapid prototyping and testing, leading to a more effective heat diffusion design in the HoloLens 2.
Data-driven design provides a competitive advantage, as seen with HoloLens being one of the most comfortable headsets on the market.
Data collection must be done smartly to avoid diminishing returns and maintain its value in product design strategy.
Insight Surgical uses computer vision and data to prevent surgical complications, emphasizing the life-saving potential of accurate data.
Ethical data collection, as demonstrated by Insight Surgical, ensures patient benefits without compromising privacy.
Data can be easily copied, as competitors can mimic product designs, but the initial advantage remains with the innovator.
Zinger uses data-driven simulations to optimize the strength-to-weight ratio in their hypercar, showcasing the role of data in innovation.
Nike leverages data to customize outsoles for athletes, contributing to their success in the 2016 Rio Olympics.
Data is increasingly guiding not just the design process, but also the decision of what to design, as seen with fashion brand Shein.
Shein's data-heavy strategy allows for rapid response to trends, impacting the fast fashion market significantly.
Data collection raises privacy concerns, with some companies collecting more data than necessary and using it unethically.
Apple's feature allowing users to control app data tracking has impacted companies like Facebook, highlighting the importance of ethical data use.
Companies should assess whether their data collection benefits the customer or solely their business, promoting transparency and ethical practices.
Transcripts
one thing i've been noticing with many
of my clients is a heavy emphasis on
data driven design i think it's going to
be one of the most important design
trends of the 2020s and beyond this
video will give you a better
understanding of why data will be so
important to designing the products we
make the ethical controversies around
data collection and why some types of
data are much more valuable than others
[Music]
so first of all data are just facts and
statistics collected for reference or
analysis everyone uses data to make
decisions all the time that's nothing
new but within the context of this video
i'm talking about millions or even
billions of data points collected and
used to inform product decisions this
somewhat recent phenomenon is allowing
us to do things that were impossible
even as recently as a few years ago
pretty much all major innovations in
design are a direct result of emerging
technology and this trend towards big
data and the designs that will result
from it are no exception when designing
the hollow lens 2 microsoft had to
figure out how to make a headset that
would fit on everyone's head comfortably
the hololens 2 weighs about 580 grams
and that's basically the equivalent of
strapping a loaf of bread to the front
of your forehead and wearing it for
several hours i tested it so you don't
have to it's very uncomfortable but this
task gets even more difficult when you
factor in the radically different shapes
and sizes of people's heads it's
basically like trying to make a
one-size-fits-all shoe individuals have
radically different facial features as
well so if you're designing a headset
that's supposed to fit over your eyes
it's not going to be easy if one
person's brow ridge is zero millimeters
and another's is 15 millimeters so
microsoft had to scan thousands upon
thousands of people's heads in order to
determine the ideal shape for their
headset design this gave them the
necessary data to make proper decisions
in making a one size fits most design
without that data microsoft would have
ended up with a far less comfortable
headset for anyone who's worn a vr or ar
headset that's clunky and uncomfortable
you know how much it takes you out of
the experience
the hololens team also had to deal with
heat so when you have a computer
strapped to your face it's not only
important to make sure that it's
comfortable in terms of not hitting any
pressure points but it also needs to
direct the heat away from your head
testing this with physical prototypes
would have taken forever so instead they
created a digital twin and a digital
twin is basically exactly what it sounds
like it's just a digital clone of
whatever you're trying to make in real
life so in the case of hololens they
probably gathered all of the relevant
data about the product material
compositions component arrangement
material distribution thickness and
types and various heat diffusion
features they put all this in a computer
simulation that was a replica of the
physical device and placed that digital
twin through thousands of trials and
tests until the ai was able to come up
with a solution that successfully
diffused the heat that's how they came
up with this component configuration and
it's probably how they came up with the
channels along the top of the hololens
which helped to cool the device by
guiding the heat upward and away from
the person's face
the digital twin didn't give them a
perfect finished product it was just
sort of a model for them but it got them
close enough to the final design so that
they could move more quickly the data
that the hololens team used to create
this design gave them a very distinct
competitive advantage and you're going
to see more of this data-driven design
as these tools become more accessible
for everyone to use new cloud computing
and machine learning tools allow
companies to sift through this data in a
way that used to be difficult or
impossible hololens is one of the most
comfortable headsets on the market right
now and i can't stress enough how hard
it is to make a 580 gram computer
strapped to your head be comfortable and
microsoft did it with the help of data
now data is going to be incredibly
important to creating a competitive
advantage in product design but only if
it's done in a smart way so if we
continue to use hololens as an example
their data on facial scans is hard to
access they can probably continue to
improve it as they collect more data and
therefore improve the actual final
product but eventually it's going to
lead to diminishing returns so if the
designers and engineers manage to make
the headset fit 100 of people and
everyone can wear it with no issues for
18 hours making the headset even more
comfortable after that point is going to
sort of become unnecessary if the data
you're collecting stops being useful
after a certain point it's not as
valuable of course there's nothing wrong
with this necessarily you just need to
think about this as you formulate a
design strategy as it relates to data
you can contrast this with a client that
i've worked with in the medical field
called insight surgical they're using
computer vision to identify all of the
tools in the operating room so that
something like a gauze pad doesn't
accidentally end up inside of the
patient after an operation and yes this
actually does happen if that data
becomes even 0.1 percent more accurate
it could save lives so there's a huge
benefit to collecting more data in this
case it also makes it harder and harder
for other competitors to catch up so if
one solution is 90 effective at
identifying these surgical complications
just because they have more data to rely
on and another competitor comes up and
it's only eighty percent as effective
it's pretty obvious which one you're
going to choose on top of that getting
access to medical data is extremely
difficult because there are all sorts of
regulations around how medical records
and patient data are shared this data
can't be bought and it's very very hard
to obtain so insight surgical doesn't
keep any of the video footage and they
use computer vision to blur out the name
tags and faces of everyone in the
operating room so it's totally anonymous
i think it's important to mention this
because it's a great example of
collecting data in an ethical way that
ultimately benefits the patient and the
hospital staff another thing is that
while the data that microsoft has on
headscans is not especially easy to
access the resulting product that came
out of that data is not hard to copy so
any competing company can just sort of
get a hololens and copy the way the
weight is distributed copy the materials
and padding placement and copy the way
that the heat is diffused a competitor
could get the benefits of all of the
research that the microsoft team did
without having to do any of the work so
while the data does give them an initial
competitive advantage it can quickly be
copied it's still worth it for microsoft
and other companies in the long run
because they're always going to be one
step ahead of the competition but it's
not quite as valuable as the data that
insight surgical has for their computer
vision anyway if you made it this far
into the video you should totally
subscribe it's free it helps me out and
you can always change your mind later on
to the rest of the video
zinger is another company that runs
thousands of simulations in order to
optimize the strength to weight ratio of
various components for their hyper car
this hyper car is built using several
computer generated simulations that rely
heavily on data this allows the
engineers and designers to come up with
shapes that a human probably would never
have thought of nike is another company
that's investing heavily in data to
determine the outsole structure and
pattern for some of their highest
performing shoes data will enable more
customizability and personalization for
each user nike made a customized outsole
for each of their athletes unique foot
shapes and running event and it helped
their team win 45 medals during the 2016
rio olympics it's getting to a point
where data not only informs how to
design something but also what to design
in the first place so xi'an is a great
example of this they're the biggest
fashion brand that you've never heard of
unless you're their target demographic
of teenage girls which pretty much none
of my viewers are the company is
currently valued at about 15 billion
dollars their strategy is super data
heavy and as a result they're
aggressively taking market share from
the big fast fashion players like zara h
m and forever 21. they do this by
analyzing data from social media and
other trending search terms so if a
video goes viral of a girl wearing a
stylish outfit or top sheen will
immediately contact one of their
factories to make a copy of the garment
the factory will do a limited run of 100
units and see how the sales go based on
how fast the first few units sell they
decide whether or not to create more of
them other companies do this too zara is
a big one but to be fair there are a lot
of issues with xi'an's business model
and pretty much any fast fashion brand
they often copy other designers work
without compensating them they have
questionable quality and safety
standards in their factories there's a
massive amount of environmental waste
that comes from these brands the ethics
of xi'an as a company are definitely
questionable don't get me wrong but they
clearly have developed a system that's
really really heavily data driven and i
think it's a great case study on how
data can inform product design decisions
the way that xian collects data is also
very controversial and it's hard to talk
about data without talking about privacy
issues this is usually good for the
business but it's not always good for
the end customer a lot of companies are
taking more data than they need to and
even selling to third parties or using
it to influence your decisions and
purchasing habits in a negative way
without your knowledge or permission
more recently apple created a new
feature on their phones where you can
decide whether it's okay for certain
apps to collect track and sell your
usage habits this totally destroyed
facebook's revenue and data tracking
capabilities because they rely very very
heavily on this information
not only did facebook lose a ton of
money on this but their stock price
plummeted about 26 percent after it was
reported that fewer people are using
facebook now there are a lot of reasons
why fewer people are using facebook but
the issues they've had with data
collection is definitely no small part
of that the same data collection methods
that turn them into one of the biggest
companies in the world is finally
catching up to them the lesson here is
that companies really need to be careful
about how the data they collect affects
their customers so how do you know if
you've taken your data collection too
far as a company well i think a good
starting point would be to ask my users
and myself two questions number one is
the data that i'm collecting benefiting
the customer or is it really only
benefiting my business's bottom line
if it's not explicitly benefiting the
user's experience in some way you
probably shouldn't do it it might work
out in the short term but you run the
risk of having the same issue that
facebook has recently had and number two
just tell your user what kind of data
you're collecting and how you're using
it in a transparent way and ask him if
they're okay with it and i don't mean in
a dense privacy policy that nobody reads
i mean in real human simple terms data
collection can be unethical but it's
just a tool and it's a powerful tool
that's not going away so rather than
trying to demonize it we should instead
focus on how we can collect data that
actually benefits the end customer
anyway thanks for checking out the video
don't forget to subscribe and hit the
little bell icon to get notified about
when i post my next video and don't
forget to smash that like button and all
the other youtube cliches that youtubers
say but really all that stuff really
does help me out so i appreciate you
have a great day
[Music]
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