What does it really mean to distribute manufacturing?

Last sept 8th the Danish Design Center held a Future Fabrication Summit in Copenhagen’s Carlsberg Byen. The event was part of many very exciting events that happened in the same city since the 5th to the 10th of September 2017 as part of the Techfestival 2017. The summit gathered academics, entrepreneurs, and professionals to discuss the implications of digital fabrication in the creation of self-sustainable cities.

One of the most attractive models for digital manufacturing implementation is distributed manufacturing. Digital manufacturing integrates fabrication processes around a computer. Through computerized control, we can increase the available complexity of the product we fabricate. Robot arms, CNC mills, Laser Cutters, Waterjets, and 3D printers, use digital models to create precise reproductions without molds or human aid. Moreover, information about the product like orders, materials, and designs, can be transmitted as data to remote locations that have the same fabrication equipment and achieve the same results. Distributed manufacturing implements these two advantages in a fabrication scheme where products could be produced in small digital fabrication sites instead of huge centralized facilities. This distributed model could reduce the environmental impact of huge supply chains that move raw materials and inventories around the world. It could also reduce the distance between manufacturers and consumers, creating a more immediate and local model for product fabrication.

By 1983~enwiki at English Wikipedia, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=53526868
By 1983~enwiki at English Wikipedia, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=53526868

Considering its benefits in sustainability, supply chain management, and product design, distributed manufacturing opens many opportunities for new business modeling. Pioneering projects have implemented distributed manufacturing in different modes that range from manufacturing “marketplaces” that connect designers to consumers, to open sourced repositories of models ready for production. Among them, we can find Opendesk, a furniture company that works with a network of manufacturers worldwide in what they call Open-Making. Opendesk designs furniture cut out from standard fiberboards 240×120 cm. Through their e-commerce platform, they allow the customer to select from a catalog focused on workspace furniture, worktables, chairs, bookshelves, and storage units. Images in different materials are available next to an estimated price in local currency. If selected, Opendesk sends a quote request to the associated makers in the network. The price is adjusted to local prices of material and distribution. The units payment is received through Opendesk who distributes all the payments between the designers, the platform, and the makers. The platform has been working since 2014, when they were successfully crowdfunded, adding designs in partnership with studios and including new manufacturers globally.

Opendesk workplace furniture
Opendesk workplace furniture

One of the most interested industries in applying distributed manufacturing on a large scale is the aerospace industry. According to the AirbusVoice Team in Forbes, the demand for spare parts for operating airliners is very slow and irregular. Considering the complexity of an aircraft, the variety of parts that need to be stored in replacement inventory for this uneven demand, implies that inventories today have to be huge. Additionally, available inventory has to be flown to the customer in charge of the replacement causing further delays. Since 2012 Airbus has been experimenting with the use of 3D printers to develop complex parts that can be produced on demand. Spare parts considered suitable for commercial 3D printing such as brackets, and seat lids, have been printed and are currently being tested in operating aircraft. Being able to fabricate on demand for a global industry also would allow Airbus to distribute or even outsource 3D printing of the spare parts. However, current technical requirements for aeronautic regulations have to be addressed in order to continue the development of the business model.

What means to distribute our manufacturing?

Both examples described above show promising opportunities for the creation of new businesses that implement distributed manufacturing. Yet, underlying both examples we can find a problem with product complexity. Complexity in product design and development can be described as a number of elements in a system, and the relationships among them. The more complex, the more parts and relationships they have therefore creating emergent behaviors and novelty. As a result, complex products need more prepared people and complex reliable equipment to be manufactured. Khajavi et al. describe this effect in an analysis of the distributed fabrication of fighter jet parts using additive manufacturing. In their conclusions, the current state of available 3D Printing requires a big investment in equipment and staff to be operational. This means that in order to successfully implement distributed manufacturing today, technology and education should become more accessible. We can see this happening in the examples described above. In the case of Opendesk, the available products are restricted to one method of fabrication and one specific range of materials. The complexity of the product and assemblies is restricted in order to reduce the difficulty in its fabrication. Contrary to Opendesk, aeronautic parts are more complex. Distributing manufacturing operations of an airplane part requires matching very specific technical requirements that make flying safe. Thus, if we want to distribute the fabrication of airliners’ spare parts we must upgrade each of the manufacturing sites to comply with all the technical standards. Then, we can say that distributed manufacturing needs of product complexity management to be successful. 

Managing product complexity is in itself an important business matter. According to the theory of incomplete contracts, firms try to include inside themselves the transactions that they can’t control through a contract with other entities. A complex product, such as a new technology, or an ad-hoc solution cannot be completely split and described between two partners and as such, it must remain in control of the company that has invested in its creation. Again, this shows the difference between the two examples above. While making furniture does not deal with state of the art technology, Opendesk is able to share the information with their suppliers. Every partner can clearly understand where their responsibility starts and ends as much as how much they are being paid. In the airplane spare parts example, the complexity of the parts would make a huge deal if distributed because processes such as titanium 3D printing have many variables such as controlled atmospheres, and low-dimensional tolerances. Hence, the communication between two parties (inside a company or between two companies) would be very complicated to manage. A company just like Airbus would have a hard time sharing information with distributed partners. Subsequently, the problem of distributed manufacturing is not only a technological problem, is a management one too. Unfortunately, this management problem is poorly addressed when we discuss digital fabrication with the general public, and when we offer it as an alternative to existing business models.


More complexity brings more components and relationships between them. (Lego 42055 BUCKET WHEEL EXCAVATOR)


Back in the future fabrication summit in Copenhagen, Nat Hunter Strategic Director of the Machines Room stressed the role of the designer as an actor of this new production model. Many other authors highlight this as an effect of digital technologies that combine the roles of designer and the manufacturer. We can see how digital technologies bring together activities that before were split into planning and building thanks to advances in simulation and the precision and speed of these new fabrication methods. We have shown above how product complexity management is one of these activities in planning that needs to be addressed if we are going to implement digital manufacturing in a distributed model successfully. Maybe it means that managers need to bring designers close or even become designers in order to create new ways of going around the problem of product complexity in distributed models.

Questions for the future

Considering managers as designers would open very interesting questions that can push the implementation of distributed manufacturing forward. What is the role of design in enterprise management software? How can we manifest product complexity in ways that facilitate talking about it and sharing? How do roles inside a digital manufacturing enterprise should evolve to accommodate distributed manufacturing? Which is the place of product design inside management and entrepreneurship? However, the main question that we have to answer is the question of innovation. Innovation is the main differentiator of new businesses, it makes space for them to survive and create new market opportunities. As mentioned above, novelty is commonly related to product complexity. Hence, novel businesses are usually complex as a result of their innovative solution. Does this mean that there can’t be new product development through distributed manufacturing? Are distributed manufacturing models only possible if we manufacture simple products? More work is needed in order to answer these questions. Luckily, projects such as the FabCity prototype in Poblenou, Barcelona and the Maker Mile in London will throw some clues that will help us evaluate if distributed manufacturing is a viable alternative for new business making.



Change weather — Why innovation can’t be instrumentalized?

(This article was originally published in Antonio Esparza’s Medium profile, 3 August 2016)

Being serious about innovation and change

The more I study, the more I am convinced that today, the circumstances for successful business performance are more difficult than the ones in our parent’s generation. In all possible levels, we are threatened by the uncertainty of the surrounding complexity in society. Technology changes in an unprecedented way out dating our everyday practices while we still try to catch on the means that we control. Moreover, as if it was not enough, social environments become more unstable and precarious. All the former fueled by people’s restricted working conditions and the fear of people whose jobs are threatened by Artificial Intelligence (AI) and automation.

The easiest way to describe this uncertain environment is to list the rise and fall of industries or the scenario of the 2008 financial crisis. Nevertheless, examples of these micro level symptoms of collapsing macro structurescan be felt in more subtle events in everyday business. Just to mention few examples; the value of our productive assets diminishes, the value of intellectual property rises at the expense of our ability to leverage and protect it, and workers do not engage seriously with productivity and avoid compromise with their environments. Facing these scenarios, our most obvious answer is scaling up. Only through the multiplication of business we can reach profitability. And only through heavy infrastructure investment we can multiply business. In conclusion, such uncertain environment only forces us to acquire more capital.

It is in the middle of this volatile and complex context that innovation became a top priority concern for management. Just as “total quality management” in the 80’s and 90’s, novel ways of understanding the “exploration” of new opportunities were extracted from the study of the ones who have managed to stay relevant inside their industries. Tools like “business model innovation canvas”, “open innovation”, “disruptive innovation strategies”, and “design thinking” are now the new repository of an army of specialists in charge of building a vessel that can help us navigate through all this turmoil.

Nevertheless, my point in this essay is that the idea of tooling and instrumentalizing innovation and change goes against the nature of change itself. Coding such a volatile environment requires the homogenization of different terms and techniques for the purpose of scale distribution. These actions hijack the definition of what “ought to be” thereby restricting our chances to create something different. In addition, coding such procedures implies expected successful results misleading us from reality. Finally, technology forecasts and trend analysis tools give us a sense of linearunderstanding of the environment while in reality we struggle with exponential effects. Contrary to these perspectives, a critic approach to design science as a way to determine what “ought to be”, clearly shows that the architecture of the future can’t be easily defined and tamed beyond heuristic approaches. Accordingly, when Herbert Simon discusses the ontology of artificial sciences in “ The science of design: creating the artificial” he points out that such practices are extremely difficult to define since future domains are constantly changingCoding a deterministic approach to innovation may help our anxiety as decision makers, but certainly it will not guarantee the success of our enterprises.

In this moment it is important to clarify that I am not against the homogenization of practices that help us improve our performance. I only make a difference with innovation and change where homologization is nonsense. My guess for the diffusion of this practices is our despair facing uncertainty and the responsibility of our own agency. It has always being better to trust the experts and follow the best practices in order to minimize perceived risk of failure. In my opinion, such unease towards ambiguity comes from the foundational metaphor behind our manager stance. As decision makers we are responsible to guide our organization through a competitive landscape to achieve profitability as if it was some kind of boat or spaceship with a navigation computer that can bring us from A to B. Under this paradigm, it is understandable to expect deterministic tools that bring us from A to B. But if the actual socio-technological landscape cannot be mapped, risks can’t be calculated either and forecasts become as valid as mere guessing. Then, what are we supposed to do to guide our vessel?

In order to look for a metaphor, I focused on my current research. As part of my studies in Auckland University of Technology, I struggle a lot with the definition of design and entrepreneurship. Within that context I found a very coherent definition for entrepreneurship by Per Davidsson who describes it as “the micro level phenomenon of a macro level change”. This definition highlights the mechanics of change stressing the complexity that actual change brings at different levels and the relationship between all of them without being deterministic in the effects of our actions. While discussing this post with my supervisor he pointed out how this definition was similar to the study of attractors in dynamical systems. In such simulations, complex systems are simplified to study its performance in a “toy model”. An attractor is the set of values in a complex system that despite its variability always attracts the values to a certain plotted shape. In such simulations, little variations in the initial conditions create great differences of final performancenevertheless all those different results, are attracted to the same set. If we plot those systems we get very interesting shapes that show us the dynamical relationship of the involved variables without losing its complexity and unpredictability. Such models were born with the study of weather, a super complex system where every single layer of molecules has a different set of physical properties. Its discovery coined the term “butterfly effect” in a conference paper by Edward Lorenz in 1972. Clearly, the complexity of the actual landscape, could be described by an “attractor set” where slight differences in the initial circumstances can create huge and complex results in the whole system. In such complex scenario, we are not in charge of creating a strong vessel and a convincing road map, we are atmospheric molecules that perform in a micro level as part of a macro ecology of events. Therefore, the Lorenz Attractor of atmospheric simulation clearly resembles a metaphor that in my opinion, describes our role as decision makers in the middle of complexity.

Lorenz attractor spreading into chaos

Conceiving ourselves as individual molecules in an atmospheric scenario might even aggravate our sense of agency. Nevertheless with this perspective, new opportunities arise since small changes in the initial state can create enormous differences in the overall system. Research around the decision making processes of expert entrepreneurs by Sara Sarasvathy, found out that more than planning and forecasting, successful founders rely on themselves and their means at hand to build their ventures. Sarasvathy calls this effectuative logic, a stance where “to the extent that we can control the future, we don’t need to predict it”. Sarasvathy’s entrepreneurs innovate by considering their means at hand and effectuating the circumstances and stakeholders to get more means or higher goals. In this sense, being a lone entity inside a complex ecology of entities becomes an opportunity to innovate through effectuation.

To understand more of this alternative perspective of innovation and change we must push the effectuation logic even further in our relationships within our weather model. We have already mentioned how our landscapes cannot be described only in terms of categories, sectors and industries and how this fact restricts not only our perception of the environment but our agency. In this regard, Anne Burdick proposes a critical approach that makes use of future speculation where the interaction of artefacts, products, services, firms, etc. coexist with users altering each other and creating futures that are more complex than actual Utopian technology forecasting. Similarly, the Hyperstition project proposes a philosophical approach where narrative itself is in charge of future building. Both perspectives stress the importance of future building through critical reflection of our socio-technologicalreality and the narratives that we have today. Therefore, creating an image of a future that we build instead of one that we have hope to catch up.

This surely looks as dreadful as unknown, but in the appreciation of a broader picture and a different metaphor we open up more opportunities for autonomous and successful future making instead of homogenized and partial forecasts. A very interesting example are the concepts of the blockchain (the technology behind bitcoin), artificial intelligence and 3d printing. From a “vessel” point of view, all of them fit perfectly in a linear future road map. We all have read how “bitcoin will disrupt the financial sector”, “how 3D printing will enable localized production” or “how AI impacts marketing data collection” but all this scenarios are situated in a vessel metaphor. A “weather model forecast” would also show us how the blockchain can create wealth in new and more dynamic economies. Or how AI could be used to personify complex environments such as crops and make them easier to manage. Finally how 3D printing can increase the available complexity in product architecture to the extent that bodies can be altered through new categories of prosthetics. Contrary to a linear approach, a complex weather one lets us imagine products and services outside our vessel that could not be envisioned before. Which products can we envision within this different economies/environments/bodies?

The proposal of this essay calls for a more serious understanding of innovation and change, one represented by the weather metaphorrecognizing the real complexity of the challenges that we face today. Only in this mode we can make critical use of the tools that we are given according to our unique position respecting the complete socio-technological scenario that we face. My belief is that in the verge of a deep structural change business creation will find a way to create and capture value outside the actual reigning system. Creating multi-dimensional businesses that foster growth in holistic ways apart from the monetary paradigm. Therefore no only surviving the difficult weather but building one that is more suitable for everybody.

There was once a product…

If you are starting a business you know that DESIGN should be a priority for you. A good User Experience Design (UX) is important for you to deliver seamless value propositions for your customers. Good  User Interaction Design (UI) can also help your product to go beyond aesthetics and function as intended. By implementing Strategic Design (SD) we can also portray innovative solutions and future roadmaps for our organizations to follow. Design is the contact surface between your organization, the future and your market (or more design centered, USERS). As a result, when we start businesses with our users in mind, we build relevant value propositions that resemble a future promise embodied in coherent products.

The Firm and the Product are traditionally thought to work together as two separated entities.

But who are the users of the product? Research in Product Architecture suggests that the products we make also have users inside our organizations. As a result, they also shape the way the organizations are built through time. Researchers Lyra Colfer and Carliss Baldwin describe that the way we solve problems through the design of product components shapes the relationships between the people who are involved in its creation. In their research, they also describe how this configuration does not only shape the configuration of a company but can also extend to partners and industries. Their observations coincide with research that has been widely validated since the 90’s demonstrating that the way we design our products has a huge impact in the performance of our businesses. Therefore, when we design our product we are actually designing the future of our businesses too.

Asset 30@2x
The mirroring process between products and services by Colfer & Baldwin (2017)

But how does this happen? Colfer & Baldwin call this the mirroring process. They describe a process using a technical dependency matrix and an organizational ties matrix. We are going to describe the model in 4 main steps:

  1. Product design – When we design products we deal with complex problem solving. To deal with them more efficiently, we split the problem in little parts that we can solve individually. This little parts are the product components. Components can be related to the solution of one or more functions which relates them to other components. The researchers use an example with a product that has 3 components, A, B, and C. In the technical dependency matrix you can see that some components are interrelated as shown by the dashed boxes. A and B work together just like B & C.
  2. The projection of activities – Arranging the product in components means that the person or team in charge of developing component A (Sam) will negotiate its definition with component B (Anna). At the same time, Component B (Anna) will have communication with both A and C (Sam & Pete). While C (Pete will only negotiate with b (Anna).  As a consequence, when de business grows, the existing relationships will grow as well. The performance of the product will be evaluated according to the values that these teams negotiate. At the same time Sam and Pete will not develop channels and tools to collaborate.
  3. The projection of products – The developed team has created something that Clayton Christensen calls “the value network“. This is an underlying structure that describes what the product “is” and how it “should perform”. Through this value network, the organization designs products that are aligned to the possibilities of the organization, ideas, and performance that were shaped by the very first product configuration. This value network extends to all the business supliers and partners since they all interact with a part of the product.
  4. The mirroring trap – When the surrounding environment changes and the organization is forced to innovate, the teams are constrained by the first product configuration that shaped them in the first place. Colfer & Baldwin call this “the mirroring trap” and is one of the explanations for the death of businesses whose markets are being disrupted.
We can say that product and firm are closely related as two parts of one object rather than two entities themselves.

As we can see, through the design of our first value proposition (product or service) we are actually creating a roadmap for our business to follow. If we look around we can see this mirroring process everywhere. Mobile phones all look just like iPhones because its design has shaped not only its organization but the industry itself. Consoles look like PlayStations and Electric Cars look like Priuses. The problem is that we are all trained to force the same business template to all businesses just like all startups have the C – level executives. Considering this, we should start questioning if the way we start our businesses separated from product design is right. Can we create a unified process that considers the mirroring process from the beginning? Because as the title of this post says, there was once a product… that shaped an entire industry.