Footwear Design & Smart Data, What’s Ahead?
Opportunities in Footwear Design with Creation & Adoption of New Technologies
Co-written by Alyssa Weitzman and Murray Vince
If the shoe doesn't fit, must we change the foot? Gloria Steinem
Footwear Market: Now & Projections
The footwear industry is dynamic and adopts new materials and technology to improve the fit, comfort, safety, performance, durability, reliability and sustainability of products. In 2017, the global footwear market was worth $246B with growth expected to reach $320B by 2021. In 2018 worldwide footwear production reached 24.2B pairs. This is an important global market occupied by some of the strongest, identifiable global consumer brands. There are at least 2 footwear companies ranked in the top 100 global consumer brands.
How do we apply and combine new 2020 state of the art technologies; sensors, visualization, digitization, miniaturization and artificial intelligence to supply a deeper, richer information flow for footwear design?
Footwear Design Feedback Data: What’s available and what can be improved?
Footwear design strives to embrace new ideas, technology and materials to improve comfort, safety, durability, performance and quality. Lab measurement informs designers about the effect of their designs, new materials and performance features. And user feedback helps but that is often finite from pre-production samples in a limited time frame, and can be either in controlled test environments or in field testing.
In terms of the practical effect due to production timing, that feedback is more likely to impact future footwear designs than the version being tested.
In some cases, footwear designers rely on feedback from footwear fit engineers and developers to tell them where there could be potential issues on a design in concept phase. Access to those resources isn’t always available and there can be lags between testing and reporting insight to the design team, so feedback and knowledge on general wear is necessary in the design process to be able to create better, more functional designs.
A designer can design around the data they are given but there are many variables after the sketch phase. For instance, designers select materials based on what they think will work best to achieve the best solution to the problem, but in technical products, there’s a lot of trial and error and testing that needs to be done to prove out the solution- that often takes valuable time in getting the product ready for market. When selecting materials, general testing is done for most of the materials that go into the shoes (i.e. abrasion, tear strength, etc.). That testing is done either in house or by the manufacturer. However, designers don’t always know how different components will perform together in a finished product. For example, an upper mesh may not perform the same way once backers, glues, etc. have been applied in construction of the shoe.
Also, footwear designers aren’t always designing the inside of the shoe, the construction. That can be at the discretion of developers and the factory. Seams, foams, and glues get added in that designers can’t always account for. Any issues due to construction should come up during a fit session, and during wider testing.
There are very few real time costing tools available that can analyze designs in the concept phase. Pushing design boundaries and designing to cost can be a challenge if the footwear design team doesn’t have upfront information on what the development process will cost to turn a sketch into a sample. It is possible for footwear designers to get a pre-cost at the initial design phase, but that’s usually based on existing data/previous models. That cost can change once a prototype is made: however, pattern complexity, vendor discretion on material pricing and factory overheads can affect the end cost. Re-designs and new details can change between product stages, and also contribute to cost changes. It would help the design process with a way to close the pricing gap between stages.
For reference there are applications like “Romans CAD” (a 3D/2D end-to-end program that has the functionality to pattern out a sketch, and provide costing) for designers in footwear, luggage and other industries. Still the library of data that designers can draw upon would need to be specific to the materials, manufacturing processes and designs of each specific footwear brand. Ideally an extensive database across brands on performance characteristics with alerts for desired and undesired design outcomes would be optimal.
What would a better solution look like for footwear designers?
Could smart data with rich visualization help even better inform designers or expert systems about the consequences of designs? Is there unrevealed data that could be harvested from broad field studies that would better inform the design process? And what is required to gather such insightful data?
Depending on the brand, a fit test occurs at the prototype phase and other stage gates, a larger wear test happens during pre-production phase. The ideal solution to provide timely input and insight for footwear designers would be more feedback on trial/pre-production designs or broader sampling of production designs with field data from users. A data flow that provides the fit engineers and designers with dynamic feedback on field trials would be helpful in providing real-time insight. A collaborative environment between engineering and design would improve dynamic feedback and accelerate testing cycles.
Technology that can help a designer visualize how the lines they have sketched or the materials they have selected will impact the wearer could create better designs. AI-powered prediction tools drawing on a library of diverse users and uses that analyzes a sketch and put it into motion-based simulations of on the foot movements are the type of resource that would be extremely helpful. Experienced designers or those who specialize in technical sports design generally know where issues with their designs could occur: however, capturing this empirically with a resource to measure design changes would help accelerate the time to market and could enhance fit, comfort and performance. Building on that knowledge base with ever-improving refinements would create a competitive quality edge for the footwear brands that adopt such a total quality management approach from design and development into manufacturing production.
Using foot avatars could be a very compelling way to get more real time data in early stage design. Avatar technology exists for apparel: the avatars use true motion and sense fit (i.e., if something is too tight). By creating a specialized avatar technology in footwear, with the addition of sensors to the avatars that measure performance and fit could be really unique. The avatars would be a compilation of deep data with a diverse library of users across gender, BMI, race, weight, height, activities, and terrain conditions (hot, cold, dry, wet, elevations) etc. The designer would be able to apply the design against the AI-driven avatar to test concepts and designs. The avatars are founded on deep data from field testing and an extensive library of known characteristics.
New sources of data from new technologies (or existing technologies applied in new ways) would help reveal more insight for footwear design. This could help create a solution to generate a more customized fit, or find a new problem to solve. Insight into new sources of stress or pressure for the wearer could create new insights, new challenges and new opportunities in solving those challenges to better optimize the design. Can hidden data from surfaces like the sole and insole be captured and compiled across a diverse range of users (age, race, gender, weight, activity level, etc.) to provide intelligent dynamic sensing input for designers to help them even better predict the characteristics of a design before production? With the convergence of artificial intelligence and intelligent dynamic sensing technologies, we could unlock new observations to envision superior outcomes.
Can the technologists evolve field data and better integrate that into CAD design tools to provide feedback?
The programs most frequently used by footwear designers are from Adobe (Illustrator and Photoshop), as well as other programs like Sketchbook Pro. There are also 3D designers/modelers who use specific modeling software like Rhino, Maya, Modo and Romans CAD. 3D programs seem like a good place to integrate this feedback, but since not all designers use these programs, so it would be great to find a way to integrate into the commonly used programs or a new program in development.
Too much info can be overwhelming (if poorly presented) and could be contradictory to what we already know. Although shifting the paradigm with improved information could raise new levels of awareness in footwear design and development. New data and new ways of interpreting the data might challenge established practices. Professionals working in a specialized area can sustain certain paradigms that guide the approach to design and problem solving. However, at some point new data and problems with the paradigm cause an evolution in the paradigm as superior information is gathered, processed, understood and accepted. While the process is a transition for adherents of the old paradigm, the improved knowledge, science, technology and outcomes overall benefits the profession.
The adventuresome in footwear design and development, pioneering new sources of data and insight, will explore new ways to analyze a design during the concept phase that would point out potential wear, comfort, fit, durability, and safety issues.
If the designer knew the properties of a rubber sole material and had a broad library of the performance factors for the wearers, would that influence design? What kinds of dynamic data would be helpful in assessing performance of design alternatives?
Larger brands have an in-house library of materials from select vendors. In the case of selecting rubber outsole materials, many brands have proprietary rubber compounds that they’ve created. Outside vendors such as Vibram can provide specialty compounds. There are research engineers at some companies who can help with material performance and structural components. They will also need tools to gather footwear data as the source of engineering input for designers. The rubber choice should affect the design, it depends on materials. For example, if you have a soft rubber, the wrong lug shape could shear off after a few wears and compromise the performance of the shoe.
Same would apply to footwear components made of EVA, TPU or other compounds that can vary in hardness/softness. For example, if a heel stabilizer is being designed, the right shape, material and hardness needs to be applied. The shape of that part should be determined by performance data and how much stability one needs to solve for. There is often trial and error to get the best result along, as well as multiple fit sessions (sometimes the part isn’t made in the correct materials until after the initial prototype). A tool that could evaluate and visualize how a key technology or part designed will perform with the rest of the shoe in real time could help better inform the designer and get to the right solution quicker. Couple that with a deep database of diverse users and that can accelerate the design process for better outcomes.
Must Haves: What footwear designers want next in their digital tools
To compile the ideal wish list, there are several ideas that need to be brought together in new combinations of technology. Here’s an initial outline of the wish list:
Make the big data smart data and visually rich with instrumentation vs sheer numerical display; make it smart data to highlight performance/comfort/safety enhancements for designers and conversely detractors in the design
The data produced should be easily understandable/applicable to design and visually rich in a dashboard-type presentation: not tomes of numerical data
Get lab quality data in the field
Create digital libraries of diverse performance, comfort and safety data about users/wearers
Increase the diversity of input and build ever-improving data libraries of user experience
Apply collected data to expert design systems and design simulations to identify design deficiencies or optimizations
Enhanced visualization: reduction of smart data to easily highlight trends, and positives/negatives in concepts as a feedback for product designers
Improved battery life for sensors embedded in soles
Connectivity to provide always connected dynamic real time data to both the wearer and the design team
Create always connected beta test communities that provide new levels of diverse big data input that can be distilled as smart data
Footwear is a mature established market. The designers build on centuries of knowledge about humans and footwear. The skills, art and science involved are often passed down from the seasoned industry veterans to new designers.
Still there are gaps in the data available and desire by designers to even better understand the connections between design with wearability, fit, costs, performance of materials, performance of the entire design for a diverse range of wearers, durability, reliability, comfort and safety. As smart data, smart miniaturized sensors and artificial intelligence combine with wireless connectivity and rich data visualization, there are ample opportunities to improve on feedback for footwear design and development.
With input from skilled footwear designers and innovative technologists, this data gap will be bridged in the near term to usher in new levels of understanding for footwear designers, developers and engineers.
Smart technologists can provide better data and tools for footwear designers. We’re on the cusp of seeing new levels of resources for footwear design and development.
Alyssa Weitzman: Alyssa is a Lead Designer/Director and has worked at some of the most well-respected footwear companies in the industry such as Timberland, The North Face and Saucony. Most recently at Timberland, she headed up the team for influencer collaborations and special make ups. She volunteers her time locally in the Greater Boston area.
Murray Vince: Murray is Chief Strategy Officer at XSENSOR, the world’s leader in Intelligent Dynamic Sensing. He has also worked in strategic business development, intellectual property and executive leadership roles at Microsoft, Apple, Silicon Graphics and several startups (including one IPO). He is also active on the board of the Pink Boat Regatta, a 501(C)(3) organization that raises funds for breast cancer research.