Yesterday Innovation Writer, Ben Thompson, shared a piece about two scooter-sharing startups. I thought the piece was going to be a prediction about which startup would be acquired by Uber. Instead, the piece was about Uber and aggregation theory.
Aggregation theory is about how a company understands its goal. The theory distinguishes platforms from aggregators. If Uber only understood itself as a car-sharing platform, then its view of itself would be to provide car sharing services. As a platform, it would view the recent dent in car-share rides made by scooter-sharing as a threat. But if Uber, instead, sees itself as an aggregator of transport options, then they see the scooter-sharing space as an opportunity and thus they would work to acquire a scooter-sharing platform.
As the saying goes, the customer doesn’t want a drill, they want the hole in the wall. Aggregators who understand this have a monopolistic edge over silo-visioned platforms. But what does this mean for startups? Is the dream to get acquired by a huge aggregator and if so, what are the steps you have to take to get that dream? Or is the dream to carve out a niche, to be small but scalable and repeatable in your own space? And if so, how do you win at that?
The answers to questions about the types of dreams startups might have are personal and situational. But the answers to questions about how to achieve those dreams, whether going for an acquisition or planning to walk to the beat of your own drum are less clear. Is it about who you know? Charisma? Tech talent? There’s a lot at play.
Another question: Is aggregator the new word for monopoly and platform the new word for small? Or are there instances in which a startup that doesn’t want to be acquired can become an aggregator in their own right.
When a project has a lot of moving parts, sitting your butt down and making a spreadsheet can really help. Without one, it’s just too hard to keep track of WHAT needs to be done WHEN and by WHOM.
Your spreadsheet doesn’t have to be digital. If using a paper ledger or graph paper is a better fit for you, then go for it. Just be sure to use a pencil and not a pen because tasks evolve over the life of a project.
I was recently reminded of this quote from designer and educator, Allan Chochinov, from his 1000 Words on design.
“[Designers] think we are in the artifact business, but we are not; we’re in the consequence business.”
What attracted me to the field of design was the scalability and potential impact of that scalability. But as I got deeper into the field of design, it became clear to me that that scalability can also be terrifying. Because when a designer designs, it’s not just a one-up. If that thing goes into production, distribution, and sales, then that thing scales and makes an impact on the environment and culture. We have to be better about thinking that through. Because what we design has consequences.
People use the word “better” a lot. And I never know what they mean. When I can, I ask them. Asking what better means, and for whom, is something we should do more often. It helps us shed light on assumptions and biases.
I understand why it’s called that. Security is the feature that enables distributed ledger technology. But the word “crypto” is a description of the technology and says nothing about the user experience or its impact on the economy and society. The word “blockchain” is a description of the tech, too. Both words are so defensive. We need a name for crypto that is more about what the tech allows us to do that we couldn’t do before and less about how the tech works. What might that name be?
Jessi Baker is a technologist, designer, and founder of Provenance, a European startup that uses blockchain to track supply chain of products. Why is this kind of system valuable? It’s valuable for product companies in that it can help streamline supply chain issues. But more important, it’s valuable for customers who want transparency on where and how the companies they buy from source their materials.
Blockchain is a distributed ledger technology. Its killer feature is that it enables decentralized transactions. Example: You may have heard of Bitcoin. Bitcoin uses blockchain technology to facilitate financial transactions without banks.
There are blockchain experiments in journalism, like civil, that are exploring new business models in a field whose hierarchy was disrupted by the internet. There are experiments happening in about every sector: transportation, education, healthcare. If the internet disrupted command and control systems, then Blockchain, and it’s decentralized model, promises to be the solution to that disruption.
One application of that excites me is blockchains potential to track the social and environmental ethics that are embedded in supply chains. There’s a model in sustainable product design called “Life Cycle Assessment” or LCA. LCA can be used to measure the environmental and social impact of products and industrial systems. There are a lot of variations of LCA, but to give you a broad sense of what it tracks, we might look at the social and environmental impacts of how the raw materials for a gadget were mined; how they were manufactured; distributed;used; and in the end, reclaimed or recycled.
As you can imagine, one of the challenges in communicating LCA to decision makers (consumers, citizens, or policy makers) is that there’s a lot of variation in what and how things are measured with LCA models. The lack of universal standards is often pointed to as a challenge. But blockchain might turn that challenge into an opportunity. How might blockchain LCA be more dynamic and thus more appropriate for decision-makers? For example, in California a decision-maker might want to put more weight on how much water is wasted in a product’s LCA. Yet in upstate New York, where water is plentiful, this data point might carry less weight. Blockchain can accommodate this fine-tuning. Which can be scary if used to manufacture alternative facts. But can be quite powerful if used to make the social and environmental costs of products more visible than they are now.
As art goes digital, it becomes easy to copy and remix. This is great in many ways. But it’s also important for artists to know that there are tools out there to help them communicate how they would like their work to be used.
Creative Commons (CC) licensing was founded in 2001 by lawyer and academic Laurence Lessig as he and the folks around him saw a need for a new kind of licensing in the digital age.
There are a few flavors of CC. Some give you permission to use and remix work with no boundaries at all while others have some requirements. From the CC web page:
Attribution CC BY. This license lets others distribute, remix, tweak, and build upon your work, even commercially, as long as they credit you for the original creation. This is the most accommodating of licenses offered. Recommended for maximum dissemination and use of licensed materials.
Attribution ShareAlike CC BY-SA. This license lets others remix, tweak, and build upon your work even for commercial purposes, as long as they credit you and license their new creations under the identical terms. This license is often compared to “copyleft” free and open source software licenses. All new works based on yours will carry the same license, so any derivatives will also allow commercial use. This is the license used by Wikipedia, and is recommended for materials that would benefit from incorporating content from Wikipedia and similarly licensed projects.
Attribution-NoDerivs CC BY-ND. This license allows for redistribution, commercial and non-commercial, as long as it is passed along unchanged and in whole, with credit to you.
Attribution-NonCommercial CC BY-NC. This license lets others remix, tweak, and build upon your work non-commercially, and although their new works must also acknowledge you and be non-commercial, they don’t have to license their derivative works on the same terms.
Attribution-NonCommercial-ShareAlike CC BY-NC-SA. This license lets others remix, tweak, and build upon your work non-commercially, as long as they credit you and license their new creations under the identical terms.
Attribution-NonCommercial-NoDerivs CC BY-NC-ND. This license is the most restrictive of our six main licenses, only allowing others to download your works and share them with others as long as they credit you, but they can’t change them in any way or use them commercially.
TAKE IT FURTHER
To see examples for each kind of CC and to download license tags for your own use, go here
At home, at work, and school we benefit from sharing spaces, tools, and resources. However, sharing resources is challenging because the responsibility for them is distributed. Shared spaces get messy. Shared tools get broken. And no one person is on the line to clean or fix them.
So when you use a shared space, leave the space better than you found it. Do something extra. Change that light bulb that’s been out for too long. Make and hang that sign that needs to be in place. Sweep those stairs that need sweeping. And when you contribute, don’t be a silent contributor. Let the group know what you’ve contributed. Your generosity will inspire others to make their own contributions.
The Internet of Things (IoT) is a category of products and systems that use computation and web connection. It’s a tough category to describe because computation and web connection enable so many different things. One thing is for sure, these aren’t the products of the 20th century. They are something new. And they behave differently. Whereas many products of the 20th century were stand alone and kind of static, 21st-century products work in systems and get smarter over time. Here are a few forms that you might see or imagine:
SOCIAL. Some IoT systems allow you to coordinate tasks with other people. Uber is essentially an IoT system: it allows drivers and people who need rides to coordinate their goals. Another social IoT system that does this is FitBit. They have a “challenge” feature that allows you to set competitive goals with the FitBit community.
GEO-SPATIAL. For some IoT systems, location really matters. If you are tracking air pollution with on-the-ground sensors, for example, you are going to want to see that data on a map. Autonomous vehicles need to sense and respond to geospatial data too.
HUB and SPOKE. Not every single object needs full computing power on board. That would be a waste of money and energy. Some systems work better in a hub and spoke model. Philips hue, for example, has a hub that communicates with multiple light bulbs throughout a home. Yesterday my students imagined a cattle tracking system that had a light sensor device on each animal, and that data from those sensors would be gathered by a mobile hub (a drone).
BIO-SENSING. We have sensors that can sense and track living things. Fitbit, mentioned above, is one. Other systems for human patients or herds of animals are emerging and enabling easier, and more effective tracking of vitals. “I’ve fallen and I can’t get up” wearables ought to be IoT enabled by now, yes?
SENSE and RESPOND. Mentioned above with autonomous vehicles, some systems not only gather data through sensing but enable the system to act on that data in real time. You could imagine a hydroponic farming system that can sense the temperature of the system and actuate heating and cooling as needed. If only the HVAC systems in office buildings worked as well!