8HRS is our platform to optimise efficiency in life and work that adapts to include the ideas and practices you want to implement in your life. It adapts and improves itself by gathering analytics on how you live while maintaining your control over your data.
For the past decade I have been fascinated with how data can be used in the process of lifestyle design to work and study more effectively, while also maintaining a good work-life balance. During this time, I have used virtually every productivity tool available, read hundreds of books and searched for philosophies of living from Stoicism to China’s Warring States philosophers.
The productivity industry has also vastly expanded during this time offering us a broad range of tools that help us to track our tasks more effectively, manage projects, monitor our time and even build no-code custom applications on tools like Notion.
The field of personal improvement and efficiency is one of the most crowded and getting more so every day. Why is there a need for yet more tools and analytics to help us work more effectively?
The demand for tools to help us organise and improve our chaotic lives highlights that this problem is far from being solved. Additionally, as we begin to adopt a wide variety tools, we encounter difficulties in navigating between information silos that each perform specific functions in our lives. For instance, I am drafting this article in Typora using a plan written on Milanote with notes I made on Evernote according to a timeline I manage in Notion. While I might be an extreme example, many of us managing increasingly complex workflows to produce our best work.
More broadly, tools tend to focus on niche areas of work, which has its advantages when it comes to focusing the functionality of tools and ensuring a clear roadmap of what to develop. The problem is, without a contextual understanding of where a tool fits into the bigger picture, it cannot adapt effectively to our lifestyles.
Another major problem that many of us encounter is the implementation gap. Every day we consume vast amounts of content whether this is through browsing sites like Medium or our favourite blogs (perhaps helpfully curated by Feedly). Alternatively, we may be a fan of podcasts, audiobooks or good old-fashioned paperbacks. However, many of the insights we come across in this form get lost. We may have a vague notion that we should be implementing the ideas that we discover, but the concrete steps, principles and metrics are difficult to define. As a result, we drift between half-implementing new strategies and techniques which disappear as they quickly fade from our short-term memory.
So, what we need is a tool that can adapt itself to fit around how we work best without taking us away from other areas of our lives that matter to us. It needs to give us feedback on how we’re doing, and smart interventions to guide us when we go off track. For this to work, it needs to make use of data about our lifestyle (such as sleep, daily steps/exercise) as well as our productive time and progress towards goals. However, accessing this data is obstructed by two major barriers, firstly the difficulty of collecting useful information and secondly the privacy concerns associated with data collection.
The first problem can be seen with the failure of the quantified-self movement to capture mainstream interest. This movement enjoyed a brief period of popularity which soon gave way to a broad cynicism about the usefulness of data collected. It was hard to take any action on information collected and it was rarely reviewed, like the thousands of photos I’ve taken on past holidays only to never look at them again. Additionally, any kind of travel or disruption to life quickly brings an end to data collection routines leading to gaps and strange exceptions in the data. The complexity of the data collection process meant that it was highly liable to the forces of entropy.
The second problem relates to concerns over privacy. Not only might we be concerned with the use and misuse of our data by third parties now, but as Google’s attempted acquisition of Fitbit shows, we have no idea where ultimate control of our data may ultimately reside. While it’s true that Google have offered reassurances about the autonomy of Fitbit and its data from the advertising mothership, these concerns only partially alleviate worries about just how much data technology companies already have on us.
All these concerns together mean that current systems for life improvement have serious shortcomings. Tools have promised to solve some of these issues by drawing on the possibilities offered by Blockchain data storage however still fall short on addressing many of these issues.
We recognise that solving the above problems will not be easy. It is not currently possible to develop a single application that addresses all these concerns with one swift, magic-bullet solution. What is instead is required is an understanding of the true nature of the problem as well as the technologies that are being developed that could address it. What we are building at Octocol is solutions to the problem as we understand it, and they will only be partial. But we are in this for the long-haul and we believe through frequent iterations we will begin to develop solutions that work.
These solutions are likely to have several key characteristics:
- Core platform open source platform. Opaque data collection systems controlled by a single entity are not fit for purpose when helping us with something as important as managing our lives. Startup companies are, by their nature, fragile when compared to the length of a human life. They cannot deliver on the promise of longevity. Startups which fail to plan for their demise and offer adequate solutions for what should happen when they are no longer around are not truly providing the service to users that they claim. As a result, Octocol’s core platform will be open source and available to users who want to talk their data with them or expand and build out functionality.
- Sustainable business model. Octocol will have a sustainable business model for tools built on top of the open source platform. The predominant practice for most self-improvement tools has been to offer free or heavily discounted services to build up a user base. This approach might work in periods of growth however eventually requires restrictions of features. Evernote began by offering a powerful free plan in the beginning, however, later began to restrict functionality and failed to increase storage space as file sizes continued to grow. Ensuring that the costs of operation are covered by users who truly find the service valuable helps to ensure that the platform is scalable and can continue to operate as long as people still find the tools helpful. There are excellent examples of this in practice with the most notable of course being the relationship between Automattic and WordPress
- Heavily customisable. Users have shown that they are unwilling to put up with tools that cannot adapt to unique workflows. The reality is that we use a wide range of tools for distinct reasons often with functionality that closely overlaps. Startups should not pretend that their tools are the only game in town and must integrate with APIs that allow a free flow of data and information to pass between them, when authorised by the user.
- User control of information, to the maximum possible extent. GDPR and similar regulations in California and elsewhere left companies scrambling to find solutions that allow them to live up to the letter, if not the spirit, of the law. Data privacy should not be fixed by workarounds. In contrast, there are sufficient technologies and tools available to minimise the possibilities of misuse by aplatform. Whether this comes from encryption, blockchain storage using services such as Blockstack (which is implemented very effectively on habit and data tracking app Nomie) or by allowing information to be stored on user’s physical devices or online cloud storage platforms, there are ways to ensure that user has radically more control over their information.
- Highly flexible. Many tools seem to assume that everything will always be perfect, that we will always have a strong, stable internet connection or access to certain devices. In the real world, things break down servers go offline, and internet disconnects. As a result, systems should be highly flexible with ways to compromise and have limited functionality even in the most desperate of situations. One effective way of doing that is to ensure when cross-combability with other applications as well as ensuring that basic functionality is available across devices. Alternatively, if there is no access to technology, ways of understanding what happened after the fact and can bring users back up to speed if they missed out.
All this sounds great but implementing all of these is of course a massive challenge. At present, we are testing a prototype of the 8HRS platform alongside a small group of other beta testers. You can get access to tests by signing up on the website before it is rolled out more broadly. If you are working on tools that have similar principles and goals, then I would be interested to hear from you.