UpFront
UpFront with Make the Dot
The First Mile: How Make the Dot Is Rethinking Apparel Product Development
By Joe Altieri, FIT Adjunct Professor, Mentor, Educator, and Trainer
For decades, the apparel industry has invested in improving manufacturing efficiency, developing global sourcing networks, and moving finished products through increasingly sophisticated distribution systems.
Yet one of the most important stages of the supply chain remains fragmented. It is the process that begins with a design concept and ends with a product that is ready to be manufactured.
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Emilie Ho, Co-founder and CEO of Make the Dot
This is where Emilie Ho, co-founder and CEO of Make the Dot, sees an opportunity to change the way the apparel industry operates. Ho describes this early stage as the “first mile” of the supply chain. While manufacturing and logistics have benefited from established processes and increasing levels of standardization, the work that takes place before production remains dependent on disconnected systems, manual communication, and brand-specific procedures.
The consequences are familiar to anyone who has worked in apparel manufacturing.
Designs change. Materials are substituted. Technical packages are revised. Samples are produced, reviewed, rejected, and produced again. Information moves between design teams, product developers, sourcing offices, and factories, often without a single, consistent record of the decisions that have been made.
By the time a product is ready for production, months may have passed.
Make the Dot is attempting to change that process by bringing design, product development, materials, sourcing, and technical information into a shared digital environment. But the more interesting question is not how quickly AI can generate a design. It is whether technology can help the industry make better decisions before those decisions become expensive manufacturing problems.
The Problem Begins Before Production
During my conversation with Emilie Ho, she described a product development process that can take 10 to 14 months from concept to market. Traditional development calendars, large minimum order quantities, and the uncertainty surrounding consumer demand create considerable commercial risk.
The problem is not simply that product development takes too long. It is that many important decisions must be made before a company has sufficient information to know whether those decisions are right.
A designer may select a fabric based on appearance without having complete information about its availability, cost, or suitability for the intended construction. A technical package may communicate the design intent without resolving every detail needed by the factory. A change in one component can affect the cost, construction, and timing of the entire product.
These issues are not new. What is changing is the ability to connect information that has traditionally been managed in separate parts of the organization.
Make the Dot provides a shared workspace where design teams can develop collections, explore variations, work with actual material libraries, and connect design choices to technical documentation.
During the demonstration, I watched as inspiration images were translated into visual design options and as those options were connected to garment details and construction callouts. Technical documents could be developed with AI assistance, while materials, trims, and other product information remained part of the same workflow.
Tasks that once required hours of manual work could be completed in seconds.
That is an impressive capability. But speed alone does not solve the first-mile problem.
The real opportunity is to reduce the number of disconnected decisions, make those decisions visible to the people who need them, and identify problems while there is still time to address them.
The Materials Library Is the Foundation
One of the most important aspects of Make the Dot is its library of product information.
The platform incorporates fabrics, trims, wash standards, prints, graphics, fit blocks, grading rules, and other reusable product assets. Historical technical packages can also provide a starting point for establishing specifications and developing new products.
This is where the connection between digital product development and manufacturing becomes important.
A digital image can communicate a design concept, but it cannot, by itself, establish whether a garment can be constructed efficiently, whether the selected material will perform as expected, or whether the finished product can meet its target cost.
Those decisions require technical knowledge and reliable information.
The platform's materials and sourcing layer provides a way to connect creative choices to the components and processes required to produce a garment. Brand-specific information can be incorporated into the workflow rather than assuming that every company follows the same development standards.
That is a practical approach to a problem that I have seen throughout my career.
The apparel industry has never operated according to one universal product development system. Brands maintain their own fit standards, construction preferences, grading rules, and approval processes. Even companies producing similar garments can approach their development differently.
Technology must accommodate those differences while improving the way information is managed and shared.
The value of the platform, therefore, is not simply its ability to generate design options. It is the opportunity to connect those options to the information required to turn them into products.
From Months to Weeks
Ho described the potential to reduce product development lead times to six to eight weeks for suitable programs supported by pre-sourced materials, pre-engineered processes, and coordinated production partners.
She also reported that, for the majority of Make the Dot's customers, sampling can already be reduced to one or two rounds. In the fastest case she described, a collection was designed and developed in one week, and the entire collection was produced in eight weeks.
These are significant claims, but the conditions matter.
Such timelines depend on the availability of materials, the complexity of the product, the readiness of the technical information, and the ability of the production partners to execute the work. They should not be interpreted as a universal timetable for every apparel program.
Nevertheless, the underlying approach has important implications.
If a company can establish approved materials, fit blocks, and repeatable processes before a collection enters development, it can reduce the amount of work required to start each new product. If technical details are reviewed earlier, problems can be addressed before they move further into the production process.
The objective is not to eliminate product development. It is to remove avoidable delays from it.
Ho sees an additional opportunity in the way companies manage retail calendars. Shorter development cycles could allow brands to place smaller initial orders, observe consumer response, and repeat or adjust successful products during the same season.
This is the concept of a chase calendar: rather than committing all available inventory to a forecast made months in advance, a company can respond to sales information and customer feedback as the season progresses.
Such a model would require coordination across design, buying, sourcing, and production. Faster development technology alone cannot make a retail calendar more responsive if the organization continues to make decisions according to its traditional timetable.
The technology creates an opportunity. Management must be willing to change the way the business operates.
Testing the Difficult Details
One example that Ho shared illustrates why manufacturing expertise remains essential, even in a highly digital workflow.
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The project involved an embroidered denim design with laser-cut openings. The challenge was to establish a construction sequence that would deliver the intended appearance at an acceptable cost.
Rather than develop the entire garment before resolving the difficult construction, the team explored digital proposals and technical documentation, then tested the challenging detail on a smaller denim panel.
The physical test allowed the team to evaluate the technique, appearance, and cost before proceeding further. Once a workable version had been selected, the tested panel became a reference for updating the collection visuals and technical documents. This is an important distinction. Digital development does not mean that physical testing becomes unnecessary. It means that testing can be directed toward the areas of greatest uncertainty.
A difficult embroidery application, an unusual seam, a new bonding technique, or a material that behaves unpredictably may still require physical evaluation. The opportunity is to identify those risks earlier and avoid developing an entire product around an unproven assumption.
In manufacturing, a problem discovered early is usually less expensive to correct than one discovered after the product has progressed through multiple stages of development.
The lesson is straightforward: use digital tools to explore possibilities, use manufacturing knowledge to evaluate them, and use physical testing to establish what works.
The results should then return to the shared product record so that subsequent decisions are based on tested information rather than guesswork. Waste Is Often a Communication Problem The implications extend beyond lead time and cost. During our conversation, I raised an example shared by a graduate student who had described repeated sample production in a factory. In the scenario she reported, seven operators each produced ten rejected units in a day, amounting to 70 units that did not meet the required standard. Ho also recalled an experience from her time at Li & Fung, where she witnessed a room of wearable denim jeans scheduled for destruction following quality-control communication failures. These examples illustrate how waste can originate well before a factory begins bulk production. When design intent is unclear, specifications are incomplete, or changes are not communicated effectively, the consequences can include additional samples, unnecessary material consumption, repeated labor, and finished goods that cannot be sold as intended. Not every sample is waste. Sampling is a necessary part of validating fit, construction, appearance, and performance. The issue is the avoidable repetition that results when teams lack the information needed to make sound decisions. Better digital communication cannot eliminate every error, but it can help reduce unnecessary iterations and make product decisions more transparent. It can also make sustainability considerations part of the design process rather than an afterthought. Ho discussed an upcoming Coloro partnership intended to bring color feasibility and environmental impact information into the platform. The aim is to give designers additional information when making color decisions. The larger principle is important: when better information is available earlier, companies have more opportunity to consider cost, feasibility, and environmental consequences before committing to production. The Next Generation Still Needs the Fundamentals There is another issue that deserves attention: the implications for education. As an adjunct professor teaching production management at the Fashion Institute of Technology, I see the challenge facing fashion education. Students must develop foundational skills in garment construction and manufacturing while also learning to work with increasingly sophisticated digital tools. There is limited room in a curriculum, and every new technology creates pressure to add something else. But adding technology without maintaining the fundamentals would be a mistake. A student who can generate a convincing digital garment must still understand how that garment is constructed. The student needs to recognize whether the proposed seams, materials, reinforcements, and other details are appropriate, and whether the product can be made consistently at the required cost and quality level. Otherwise, the ability to generate more designs simply creates more designs that may not be suitable for production. Ho recognizes the importance of this foundation. She described Make the Dot's work with the Savannah College of Art and Design, where students develop basic sketching and physical garment construction skills before the platform is introduced. That sequence makes sense. The purpose of AI in education should not be to replace the development of technical judgment. It should give students additional tools with which to apply that judgment. As technology takes over some repetitive tasks, the ability to evaluate its output, identify problems, and make informed decisions becomes even more important. The Hardest Part May Be Changing the Organization The apparel industry is not short of new technologies. The challenge is getting organizations to adopt them effectively. A platform that connects design, product development, and sourcing changes more than the tools employees use. It can change when decisions are made, which departments participate, what information must be available, and who is responsible for approving a product. Design, merchandising, sourcing, and production cannot continue operating as isolated functions if a company wants to realize the full benefit of a connected workflow. Management must support the change, employees must understand the new process, and the company must be prepared to reconsider established practices. This is particularly important as the next generation enters the workforce. Students may be comfortable using digital applications, but familiarity with technology does not automatically translate into the ability to apply it in a manufacturing environment. The industry needs people who understand both. Make the Dot's approach offers one example of how technology developers and educational institutions can begin addressing that gap. Continued dialogue between industry and education will be necessary to ensure that students understand not only the tools available to them but also the manufacturing principles that make those tools useful. Rethinking the First Mile Make the Dot is working to address a part of the apparel supply chain that has too often been treated as a series of separate activities. Its approach brings design, materials, sourcing information, and technical development into a shared digital environment, with the potential to shorten development calendars, reduce unnecessary sampling, and give companies greater flexibility in responding to the market. But the broader lesson goes beyond one platform. The apparel industry does not need technology simply to produce more designs or generate technical documents more quickly. It needs better ways to connect creative decisions to the practical requirements of manufacturing. The first mile determines much of what follows. Decisions made during product development affect material selection, construction, costing, quality, production timing, and ultimately the commercial success of a garment. Improving that stage can have consequences throughout the supply chain. After more than four decades working in apparel manufacturing and production management, I see digital product development as an opportunity to bring creative and technical disciplines closer together. The objective is not to make manufacturing knowledge less important. It is to put that knowledge to work earlier, when it can have the greatest impact. AI can accelerate the process. A connected platform can make information more accessible. But people still need to understand the product, the materials, and the manufacturing process. The next evolution of apparel will depend on how effectively the industry combines those capabilities. The first mile may be where the transformation begins. What happens next will depend on whether brands, manufacturers, and educators are prepared to change the way they work.
Rather than develop the entire garment before resolving the difficult construction, the team explored digital proposals and technical documentation, then tested the challenging detail on a smaller denim panel.
The physical test allowed the team to evaluate the technique, appearance, and cost before proceeding further. Once a workable version had been selected, the tested panel became a reference for updating the collection visuals and technical documents. This is an important distinction. Digital development does not mean that physical testing becomes unnecessary. It means that testing can be directed toward the areas of greatest uncertainty.
A difficult embroidery application, an unusual seam, a new bonding technique, or a material that behaves unpredictably may still require physical evaluation. The opportunity is to identify those risks earlier and avoid developing an entire product around an unproven assumption.
In manufacturing, a problem discovered early is usually less expensive to correct than one discovered after the product has progressed through multiple stages of development.
The lesson is straightforward: use digital tools to explore possibilities, use manufacturing knowledge to evaluate them, and use physical testing to establish what works.
The results should then return to the shared product record so that subsequent decisions are based on tested information rather than guesswork. Waste Is Often a Communication Problem The implications extend beyond lead time and cost. During our conversation, I raised an example shared by a graduate student who had described repeated sample production in a factory. In the scenario she reported, seven operators each produced ten rejected units in a day, amounting to 70 units that did not meet the required standard. Ho also recalled an experience from her time at Li & Fung, where she witnessed a room of wearable denim jeans scheduled for destruction following quality-control communication failures. These examples illustrate how waste can originate well before a factory begins bulk production. When design intent is unclear, specifications are incomplete, or changes are not communicated effectively, the consequences can include additional samples, unnecessary material consumption, repeated labor, and finished goods that cannot be sold as intended. Not every sample is waste. Sampling is a necessary part of validating fit, construction, appearance, and performance. The issue is the avoidable repetition that results when teams lack the information needed to make sound decisions. Better digital communication cannot eliminate every error, but it can help reduce unnecessary iterations and make product decisions more transparent. It can also make sustainability considerations part of the design process rather than an afterthought. Ho discussed an upcoming Coloro partnership intended to bring color feasibility and environmental impact information into the platform. The aim is to give designers additional information when making color decisions. The larger principle is important: when better information is available earlier, companies have more opportunity to consider cost, feasibility, and environmental consequences before committing to production. The Next Generation Still Needs the Fundamentals There is another issue that deserves attention: the implications for education. As an adjunct professor teaching production management at the Fashion Institute of Technology, I see the challenge facing fashion education. Students must develop foundational skills in garment construction and manufacturing while also learning to work with increasingly sophisticated digital tools. There is limited room in a curriculum, and every new technology creates pressure to add something else. But adding technology without maintaining the fundamentals would be a mistake. A student who can generate a convincing digital garment must still understand how that garment is constructed. The student needs to recognize whether the proposed seams, materials, reinforcements, and other details are appropriate, and whether the product can be made consistently at the required cost and quality level. Otherwise, the ability to generate more designs simply creates more designs that may not be suitable for production. Ho recognizes the importance of this foundation. She described Make the Dot's work with the Savannah College of Art and Design, where students develop basic sketching and physical garment construction skills before the platform is introduced. That sequence makes sense. The purpose of AI in education should not be to replace the development of technical judgment. It should give students additional tools with which to apply that judgment. As technology takes over some repetitive tasks, the ability to evaluate its output, identify problems, and make informed decisions becomes even more important. The Hardest Part May Be Changing the Organization The apparel industry is not short of new technologies. The challenge is getting organizations to adopt them effectively. A platform that connects design, product development, and sourcing changes more than the tools employees use. It can change when decisions are made, which departments participate, what information must be available, and who is responsible for approving a product. Design, merchandising, sourcing, and production cannot continue operating as isolated functions if a company wants to realize the full benefit of a connected workflow. Management must support the change, employees must understand the new process, and the company must be prepared to reconsider established practices. This is particularly important as the next generation enters the workforce. Students may be comfortable using digital applications, but familiarity with technology does not automatically translate into the ability to apply it in a manufacturing environment. The industry needs people who understand both. Make the Dot's approach offers one example of how technology developers and educational institutions can begin addressing that gap. Continued dialogue between industry and education will be necessary to ensure that students understand not only the tools available to them but also the manufacturing principles that make those tools useful. Rethinking the First Mile Make the Dot is working to address a part of the apparel supply chain that has too often been treated as a series of separate activities. Its approach brings design, materials, sourcing information, and technical development into a shared digital environment, with the potential to shorten development calendars, reduce unnecessary sampling, and give companies greater flexibility in responding to the market. But the broader lesson goes beyond one platform. The apparel industry does not need technology simply to produce more designs or generate technical documents more quickly. It needs better ways to connect creative decisions to the practical requirements of manufacturing. The first mile determines much of what follows. Decisions made during product development affect material selection, construction, costing, quality, production timing, and ultimately the commercial success of a garment. Improving that stage can have consequences throughout the supply chain. After more than four decades working in apparel manufacturing and production management, I see digital product development as an opportunity to bring creative and technical disciplines closer together. The objective is not to make manufacturing knowledge less important. It is to put that knowledge to work earlier, when it can have the greatest impact. AI can accelerate the process. A connected platform can make information more accessible. But people still need to understand the product, the materials, and the manufacturing process. The next evolution of apparel will depend on how effectively the industry combines those capabilities. The first mile may be where the transformation begins. What happens next will depend on whether brands, manufacturers, and educators are prepared to change the way they work.
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