How do we get more from what we know?
How do we free the intelligence within our files so that it's available to everyone in our team?How do we get the answers we need from data we trust? And how do we work with technology to make it easy?
At Yopla we think files and folders are an outdated and inefficient way of working with information. They force us to think in rigid hierarchies, limit our creativity and obscure our insights. They make us dependent upon individual idiosyncrasies, shared understanding and limited bandwidth. They create silos and barriers between us and our data.
How often have you found yourself certain you are replicating work, or searching for a piece of information but getting nowhere?
Large language model enabled tools are beginning to liberate us from these limitations and frustrations. Allowing us to store our information in a more natural way. Empowering us to query our knowledge using natural language, without having to remember file names, locations or formats. These AI tools are helping us discover new insights and connections between our data.
We want to democratise data and decision making, and recognise that to do this we need to not just have data, but make sure everyone can find what they need, when they need it.
According to a study by the Wharton School of Business, teams that use collective intelligence methods outperform even the most productive individuals by 10% to 15%
Our data trail
Files, folders, tasks, notes, meetings, emails, transcripts. All the data we're encouraged to create as we go about our digital day. But have you ever wondered what happens when you save a file on your computer, upload it to your CRM or anywhere else where you save and forget?
In the moment you might think that you have made it easy to find your data and use it later. That training, documentation and it "being obvious" will enable anyone to find the results of your hard work. In reality, you are doing the opposite. Saving data in files means you are often burying it under layers of folders, menus, services, and icons, where it will be forgotten and ignored. You are dropping your files in a labyrinth that requires a map, training and dedication to navigate.
Data is one of the most valuable assets for any business. It can help teams to make better decisions, improve performance, and innovate new solutions. But this data is often a challenge to manage, especially when it is stored in files and folders that are scattered across different platforms, devices, and locations.
Sound familiar? Our team thought so. It was when we were thinking about this that we realised, "we are not saving files, we are archiving them."
Archiving is storing something for future reference, not for immediate use. It's like putting something in a box and hiding it in the attic. Useful for things with historical or sentimental value, not for practical or creative value. Archiving risks losing access to crucial insights and intelligence. Every file contains information that can help solve problems, generate ideas, or learn new skills. If you can't find it, you can't use it, wasting knowledge and opportunities.
Archiving data
These data archives lead to problems you will recognise, including:
- Data silos: Teams may not have access to the data they need, or may not be aware of the data that exists elsewhere in the organisation. This results in duplication of work, missed opportunities, and inconsistent information.
- Data overload: Teams may have too much data to process or may not be able to find the data they need quickly and easily. This causes information overload, confusion, and frustration.
- Data quality: Data may be outdated, incomplete, inaccurate, or irrelevant. This may effect the reliability and validity of the data analysis and the outcomes of the decision-making process.
So how do we respond to these challenges? Imagine a world where you don't have to waste time and energy looking for files and folders, where you can access all your data and insights with a simple query. Where you can unleash your creativity and intelligence without any constraints.
People + technology working together
Increasingly collective intelligence will include both human and computer intelligence, representing a paradigm shift in how the thought and cognitive industries go about their business. This shift will have an impact on everyone, and how well we understand the relationship between these two intelligences will have a profound impact on our organisations.
Human intelligence, with its capacity for creativity and empathy, should be complementing the computational power and efficiency of computer intelligence. Working in symbiosis, will enhance problem-solving, decision-making, and innovation.
A report by Nesta found that collective intelligence can help organisations understand problems, seek solutions, decide and act, and learn and adapt more effectively than traditional data management approaches.
Differences between Human and Machine Intelligence
Human intelligence is more:
- Flexible, creative, and adaptable
- Context-aware, emotionally intelligent, and ethically conscious
- Limited by cognitive biases, attention span, and memory capacity
- Able to learn from few examples
- Able to perform tasks that require natural language generation, machine vision, and natural language understanding
Machine intelligence is more:
- Consistent, efficient, and scalable
- Objective, rational, and data-driven
- Limited by data quality, algorithm design, and computational resources
- Able to learn from high-dimensional data
- Able to perform tasks that require speech and audio processing, predictions on structured data, and transformational creativity
Working together with AI to create and validate approved data sources creates a rich resource for providing near instant answers to your teams questions; it's this symbiotic approach that we are excited by. One where people and technology work together.
This future is what we call active data, it builds on the relationship between people and technology to empower your organisation.
Active data
Symbiotic AI tools are revolutionising the way we store, organise and retrieve information. Using natural language processing and artificial intelligence to understand our queries and generate relevant answers. They allow us to create rich, dynamic and verified documents that can link to other sources, embed media and interact with other apps.
These tools enable us to ask questions of the collective knowledge of every contributor. Mapped and created properly, they give your organisation superpowers.
A survey by Mural revealed that 86% of respondents agreed that collaborative intelligence improves team alignment, 82% agreed that it increases team productivity, and 79% agreed that it enhances team creativity.
This collective knowledge allows for realtime collaboration, asking questions of everyone, and everything's, knowledge to get an answer. Doing so overcomes our file and folder challenges, reorganising our data into a "collective memory" that can be queried, challenged and interpreted to suit the context and question being posed.
Active data achieves this by:
- Breaking data silos: Integrating data from different platforms, devices, and locations, and making it accessible to all authorised users. This helps teams to share data, collaborate, and leverage the collective intelligence of the organisation.
- Improving data quality: Using machine-learning algorithms to validate, enrich, and update data. Natural language processing (NLP) helps us to understand and extract data from unstructured sources, such as text, images, and audio. This enables teams to ensure that the data they use is relevant, accurate, and up-to-date.
- Reducing data overload: An AI knowledge base can use computer vision, speech and audio processing, and predictive models to analyse and visualise data. Using systems and distributed AI agents provides personalised and contextualised data suggestions. This allows teams to find the data they need faster and easier, while discovering new insights and connections.
Useful Tools for AI Knowledge Bases
So how do you get a glimpse of this future? The team at Yopla has tried out some great tools for creating AI knowledge bases. While each has its strengths, we have found that by carefully considering why we have data and what we want from it, we have been able to get some amazing results.
We recommend before you commit to any of these tools that you consider your organisation's data needs, the role data plays in your workflow's and processes, as well as your data privacy and security needs.
- GetGuru: A knowledge management platform that uses AI to capture, verify, and deliver knowledge across the organisation. It allows users to create and organise knowledge cards, sync data from various sources, and access knowledge from any device or application. Built in AI can suggest relevant knowledge, automate workflows, and measure knowledge impact.
- Notion: A collaboration platform that utilising AI to create and manage documents, notes, databases, and projects. Users can customise their workspace, embed various apps and media, and collaborate with others. The AI can organise and structure data, generate templates and summaries, and provide smart recommendations.
- Slite: An AI documentation tool to write and share documents, notes, and wikis. Users can create and edit documents, sync data from different tools, and collaborate with teammates. The AI will categorise and search data, create outlines and checklists, and track progress and feedback.
Conclusion
Hopefully, this article has given you a glimpse of the future of data and knowledge management.
At Yopla, we believe that collective intelligence is the key to unlocking the potential of our data and insights. We work with our clients to realise the potential of technology, including AI to create and share active data, breaking data silos, improve data quality, and reduce data overload. We want to empower you and your team to access, analyse, and act on your data with ease and confidence.
We would love you to join us in our mission to democratise data and decision making by building collective intelligence from active data. If you would like to find out more about how we structure our data or work with our clients to transform and empower their data, please do get in touch!
