Product, Service & Design Innovation
This Intelligent Database Could Be a One-Stop Shop for Sustainable Product Designers

Makersite is an all-in-one, open-source data platform for product design, costing and stewardship that product teams can use to analyze and collaborate on how things are made and improve the impacts of making them.

The platform includes dozens of apps tailored to various business, compliance, health and environmental evaluations that developers and designers can use to quickly explore the effects of different product configurations, such as climate change, eutrophication, carcinogenicity, RoHS and REACH compliance and production costs.

We caught up with CEO and co-founder Christoph Wilfert to find out more about this one-stop shop for sustainable product design.

When Makersite launched in 2017, it was billed as “the largest database on how products are made and the impacts, costs and risks of making them,” and it has only grown from there. How did the platform go about becoming a one-stop shop for all of its vastly different types of product data?

Christoph Wilfert: Well, decisions are only as good as the data that underpins them. We talked to a lot of people with open-source as well as commercial databases and everyone sees the benefits of having all the data in one place. Integration was a lot of work, but the result is impressive. At the moment, Makersite offers several million data points from more than 20 databases. In total, we natively include over 10,000 product models including their costs, 36,000 industrial processes, 80 million chemical substances and their properties, 70,000 materials, 600,000 environmental impacts and over 9,000 product regulations. And because we’ve already fused that data, teams don’t need to do that work anymore. They can add their internal data in a private space and focus on making decisions, instead of gathering data from all over the place.

In February, you launched your Dynamic Performance Modeling app, which allows product developers to view the effects of all potential materials and production processes, and reduce any impacts from there. What other features (existing or in progress) are you working on?

CW: At the heart of this was the idea to make data more “intelligent,” such as recommendations about what alternative material to use to minimize a certain impact. An improvement can be an environmental impact, costs, substitute plastics or whatever the need of a company is. We are still heading down that road, making it easy to solve problems with data and intelligence. The apps we build on top are just a certain view on the data. We can configure those views according to nearly any individual need.

Does Makersite learn from its users, as well (ex: can/do they share their analyses for the benefit of the database/other users)?

Learn more
in the
Good Growth Pavilion
SB'18 Vancouver!
CW: It is not really Makersite that learns from its users, but users that learn form other users if they choose to collaborate. Users can add their products to the system and make them public or not. Together, they can develop great new products. If you are a supplier and your products are compliant and sustainable, you can share that data, while protecting your intellectual property. Other users can see the performance data and Makersite can suggest it as a replacement for other, less well-performing products.

Who are the biggest users of Makersite? Where is the platform having the most impact so far?

CW: We see interest across a wide spectrum of businesses, the academic community, associations, public sector and NGOs. I think the benefit is highest for the three functions of product design and engineering, eco-design and sustainability, as well as procurement and supply chain. These teams are constantly looking for transparency and data to make trade-off decisions between alternatives.

What can attendees expect from Makersite in the Good Growth Pavilion at SB’18 Vancouver?

CW: We’re now at a point where we greatly simplify how to make, buy and sell sustainable products. The latest data and tools provide a completely interactive, human-managed and machine-aided modelling environment. This saves teams a lot of time. Evaluations which previously took months to complete can now be done within a couple of days.

We also built a showcase to compare the properties of products from different manufacturers quickly and easily. A user, such as a buyer or designer, can weigh the importance of requirements in three simple steps, such as ‘price vs performance.’ For demonstration purposes, we used boat paints as an example with data from a study conducted by Northwest Green Chemistry and Washington State's Department of Ecology. What we will demonstrate here for the first time is how to match a customer segmentation based on preference criteria to designing and buying the right product.


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