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Last Updated on April 18, 2018

How to Avoid Micromanagement with Swarm Intelligence (Step-By-Step Guide )

How to Avoid Micromanagement with Swarm Intelligence (Step-By-Step Guide )

Have you ever wondered how a flock of birds interact so brilliantly? Or how ants and termites build fascinating colonies?

More importantly, have you ever wondered how your organization could mimic a flock of birds or an ant colony to create a thriving organization without having to micro-manage every little detail?

What is Swarm Intelligence?

First introduced by Gerardo Beni and Jing Wang in 1989, swarm intelligence is the collective behavior of decentralized, self-organized systems, for which social insects are one of the best examples.

    Swarm intelligence is an attempt to design algorithms or distributed problem-solving devices intended to mimic the collective behavior of social insect colonies.[1]

    Essentially, swarm intelligence improves our collective behaviors (our outputs).

    Derek and Laura Cabrera, systems theorists and professors at Cornell University compare this to a game of chess in Flock Not Clock,

    “The game of chess has simple enough rules for a child to master, yet there are 318 billion possible ways to play the first four moves. The behaviors (or outputs) of systems – be they a flock of starlings or biodiversity writ large, chess matches or organizations – are emergent properties of simple rules at the local level. By identifying, understanding, and applying these simple rules, we can make the outputs better.”

    Let’s look at an example of how these simple rules work for an ant colony:

    Simple rules outlined by the Cabrera’s allow social insects (such as ants) to become a superorganism. These simple rules are as follows:[2]

    1. Look for food. Ants randomly forage for food.
    2. If you find food, shoot pheromones. A few find food and communicate by leaving a pheromone trail increasing probability of collective action on food piles.
    3. Never cross a pheromone trail. Self-organizing behavior around simple rules produces collective intelligence.

    How to identify simple rules that work

    The Cabrera’s have defined four simple and deeply connected rules that apply in all types of organizations: Vision (V), Mission (M), Capacity (C), Learning (L).

    1. Vision (V): Your desired future state or goal (what do you see?). For example, ask the following: What do you see today? What should you see tomorrow?
    2. Mission (M): Repeatable actions that bring out the vision (what do you do?).
    3. Capacity (C): Systems that provide readiness to execute the mission (how do we align capacity?). Here you build capacity to do the mission.
    4. Learning (L): Continuous improvement of systems of capacity based on feedback from the external environment (love of learning). For example, the Cabrera’s explain that a big part of learning is making people aware of the lens through which they perceive reality.

    Why Swarm Intelligence matters to your team

      Dr. Louis Rosenberg (founder of Unanimous AI) informs us that we (as individuals) are smart, yet as a group we are even smarter – we are able to amplify our intelligence.

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      “A brain is a system of neurons so deeply interconnected that an intelligence forms. A swarm is a system of brains so deeply interconnected that a super-intelligence forms. Simply put, a swarm is a brain of brains and it can be smarter than any individual member.” – Dr. Louis Rosenberg

      In Human Swarming and the future of Collective Intelligence, Rosenberg discusses the potential of human swarming. He writes,[3]

      If we consider the leap in intelligence between an individual ant and a full ant colony working as one, can we expect the same level of amplification as we go from single individual humans to an elevated ‘hyper-mind’ that emerges from real-time human swarming?

      So, can humans swarm?

      Yes.

      How can humans swarm?

      According to Rosenberg, technology is the key. Humans can swarm only if we develop technologies that fill in missing pieces of evolution that hasn’t yet been provided.[4]

      Rosenberg developed a platform allowing swarms of online users to make decisions and answer questions together by moving a graphical puck. The puck is generated by a central server and modeled as a real-world physical system.

      Watch the following video to see how this platform works:

      How I Swarm the classroom (a case study)

      I have recently examined some of the innovative ways educators try to improve the learning environment. One such way is through “flipping the classroom.” This is a teaching pedagogy which reverses old classroom teaching through a form of blended learning using modern technology and practical application.[5]

      While a flipped classroom is an excellent approach to education, I feel as though we need to take it a step further and allow the classroom to “flip itself” and emerge on its own. Our classroom should be a complex adaptive system (CAS) with no set leader. It should use simple rules to guide it.

      I am currently using the following simple rules for an online course I teach at Fort Hays State University (FHSU) in Hays, Kansas: [6]

      Rule #1. Students interact locally with each other in a decentralized environment.

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      I use a free decision-making software called Loomio that allows my students to move past the typically discussion board thread. My students use Loomio as a launching point for the creation of systems diagrams/maps.

      I also use Loomio to build a complex adaptive syllabus by proposing or collaborating on decision tools within Loomio.

      Rule #2. Students analyze and synthesize concepts and share mental models, increasing the collective knowledge of the group.

      Using the Cabrera’s DSRP Theory -Distinctions, Systems, Relationships, and Perspectives, my students are able to break apart concepts and put them back together using two powerful platforms (also developed by the Cabrera’s!).

      First, my class uses Thinkquiry to help them develop and ask questions that penetrate deeper into a concept. They use these guiding questions to start breaking apart and rebuilding a concept.

      Second, my students then use Plectica to break apart and rebuild concepts. My students build concept maps using Plectica (free – I use it daily!) by visually organizing parts that can be combined and connected to each other to form a more complete picture.

      Rule #3. Students react and adapt to changes without asking for permission by forming systems with immediate Action-Feedback-Change (AFC) Loops.

        The most optimal way to improve is to intuitively act, recognize that we are constantly receiving feedback from reality when our mental models crash into reality, and change by forming new mental models.

        Thus, I developed the continuous Action-Feedback-Change (AFC) Loop designed to help me understand how we improve and adapt (as individuals and as a group).

        How to use Swarm Intelligence to make your team strive (Step-by-step guide)

        So, how can you use this information? How can you apply it as an individual or a group?

        It’s actually quite simple.

        1. Identify your goal

        Are you trying to improve the collective intelligence of a group? Or are you trying to improve yourself?

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        Think back to my discussion on how I use swarm intelligence in my classroom.

        2. Document reality

        What does the current state of your group looks like?

        Ask key questions such as:

        • How does your team or organization collaborate?
        • What systems does your team or organization use to collaborate?
        • Do you find that you have to micromanage your team or organization? If so, why?
        • What do you see today?
        • What would you like to see tomorrow?

        Ask yourself the following questions if you seek to improve yourself:

        • Are you overwhelmed? If so, list the reasons why?
        • How do you organize your tasks?
        • What systems do you use to organize your tasks?
        • What are the most important things in your life?
        • What do you see today?
        • What would you like to see tomorrow?

        3. Use simple rules to collaborate and automate

        Identify 3-4 simple rules to collaborate and automate as a group or individual.

        For example, use free collaboration tools such as Slack as a way to improve the collective intelligence of a group (allowing it to emerge). Slack (Searchable Log of All Conversation and Knowledge) is a cloud-based collaboration tool that you can use to allow your group to improve without the need to micromanage them.

        Slack is offered as a free and paid tool (I recommend sticking with the free version for most groups). Here’s what it offers:

        • Persistent chat rooms (channels) organized by topic.
        • Private groups and direct messaging.
        • All content within Slack is searchable (including files, conversations, and people).
        • Integrates third-party services and supports community-built integrations.
        • Major integrations services include the following: Google Drive, Trello, Dropbox, GitHub, Twitter, Google Calendar, Google+ Hangouts, IFTTT, RSS, Microsoft OneDrive, Box, and more.

        Let’s now look at an example of simple rules to use within Slack.

          • Rule #1: Your group interacts locally with each other in a decentralized environment. Slack is your launching point for discussion and collaboration.
            Action – Download Slack over the web and/or smartphone application.
          • Rule #2: Your group analyze and synthesize concepts and solve problems together increasing the collective knowledge of the group. Your group can easily create, upload, and share ideas/documents within Slack. Additionally, using apps within Slack (such as Trello) your group can track a project or concept from start to finish without ever leaving Slack.
            Action – Create a workspace and channels within Slack. Then add members of your group (very easy process).
          • Rule #3: Your group reacts and adapts to changes without asking for permission (or without the need for micromanagement) by collaborating with one another (think back to my discussion on the AFC Loop from earlier).
            Action – Find “the pass” within your group (discussed below). This is the optimal location where you can examine the collaboration of the group.

          Watch the following video for more information about Slack:

          Step 4. Use simple rules to collaborate and automate

          If you seek to improve yourself, let’s look at an example using IFTTT.

          IFTTT (If This Then That) is a free web-based and app service that creates chains of simple conditional statements called applets.

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            An applet is something that is triggered by a change within a service (such as: Instagram, Gmail, or Facebook).

            IFTTT is a way for you (as an individual) to automate simple tasks in your life so you can focus on the more important things.

            IFTTT is also a way to automate or create what is called a “Recipe” to link services through a Trigger and an Action. You can automate just about anything using IFTTT.

            Let’s look at 10 examples of some of the best IFTTT Recipes:[7]

            1. Sync your Facebook and Twitter profiles.
            2. Send live updates from Twitter to a Slack Channel.
            3. Add scheduled events to Google Calendar.
            4. Automatically schedule daily or weekly recurring Trello Cards.
            5. Submit/automate expense reminder and/or spreadsheets.
            6. Track your work hours in Google Calendar.
            7. Receive e-mail digest of the week’s most popular business articles from the New York Times.
            8. Automatically e-mail yourself 10 Things to Know This Morning (just an example).
            9. Send weather updates to yourself at specific times of the day.
            10. Send notifications to yourself regarding the ideal travel times and routes.

            So, what are some simple rules you can use?

            Here we will apply Warren Buffet’s 5/25 Rule:

            • Rule #1: Identify your most important or top 25 goals in your life.
            • Rule #2: Circle the top 5 goals. These are your most important (big picture) goals for which you cannot automate. They must be your primary focus.
            • Rule #3: Use IFTTT to automate the remaining 20 goals.
            • Rule #4: Forget about anything else. Focus on your top 5 goals, automate the remaining 20 using IFTTT, then forget about anything else.

            Watch the following video for more information about IFTTT:

            Summing it up

            Finally, let’s conclude with one of my favorite learning/feedback examples discussed in Flock Not Clock – The best chef (the executive chef or CEO) doesn’t do any of the cooking:

            “Seems like a paradox, right? If she’s not cooking, what is she doing? She’s standing at the pass, expediting, prioritizing, and communicating orders as they come in; exercising quality control by ensuring that the fish isn’t overcooked, the side dish is ample, and the final plating of the dish is aesthetically pleasing. She monitors the plates as they are being bussed and returned – are they clean or barely touched? Are they returned with a complaint?

            Finally, the executive chef’s most important job is to ensure the sous, meat, sides, and pastry chefs learn. She knows that the safety of her stars rest not on her own ability to cook, but on her team’s ability to meet her exacting standards. When leaders focus on learning, they communicate that it’s an organizational priority and build and incentive a culture of learning.”

            So, how can you create a thriving organization using swarm intelligence?

            Simply follow the Cabrera’s advice and figure out what “the pass” looks like in your organization and lead from it.

            Featured photo credit: Unsplash via unsplash.com

            Reference

            [1]Eric Bonabeau, Marco Dorigo, and Guy Therauluz: Swarm Intelligence From Natural to Artificial Systems: Santa Fe Institute Studies in the Sciences of Complexity
            [2]Derek an Laura Cabrera: Flock Not Clock
            [3]Singularity: Human Swarming and the future of Collective Intelligence
            [4]Louis Rosenberg: Human Swarming and the future of Collective Intelligence
            [5]Balaji Alagurajan: Flipping the Classroom in ELT Context: International Journal of Scientific Research and Review
            [6]Schwandt: Swarming the Classroom
            [7]Harry Guinness: 15 Best IFTTT Recipes for Productive Business Automation

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            The Productivity Paradox: What Is It And How Can We Move Beyond It?

            The Productivity Paradox: What Is It And How Can We Move Beyond It?

            It’s a depressing adage we’ve all heard time and time again: An increase in technology does not necessarily translate to an increase in productivity.

            Put another way by Robert Solow, a Nobel laureate in economics,

            “You can see the computer age everywhere but in the productivity statistics.”

            In other words, just because our computers are getting faster, that doesn’t mean that that we will have an equivalent leap in productivity. In fact, the opposite may be true!

            New York Times writer Matt Richel wrote in an article for the paper back in 2008 that stated, “Statistical and anecdotal evidence mounts that the same technology tools that have led to improvements in productivity can be counterproductive if overused.”

            There’s a strange paradox when it comes to productivity. Rather than an exponential curve, our productivity will eventually reach a plateau, even with advances in technology.

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            So what does that mean for our personal levels of productivity? And what does this mean for our economy as a whole? Here’s what you should know about the productivity paradox, its causes, and what possible solutions we may have to combat it.

            What is the productivity paradox?

            There is a discrepancy between the investment in IT growth and the national level of productivity and productive output. The term “productivity paradox” became popularized after being used in the title of a 1993 paper by MIT’s Erik Brynjolfsson, a Professor of Management at the MIT Sloan School of Management, and the Director of the MIT Center for Digital Business.

            In his paper, Brynjolfsson argued that while there doesn’t seem to be a direct, measurable correlation between improvements in IT and improvements in output, this might be more of a reflection on how productive output is measured and tracked.[1]

            He wrote in his conclusion:

            “Intangibles such as better responsiveness to customers and increased coordination with suppliers do not always increase the amount or even intrinsic quality of output, but they do help make sure it arrives at the right time, at the right place, with the right attributes for each customer.

            Just as managers look beyond “productivity” for some of the benefits of IT, so must researchers be prepared to look beyond conventional productivity measurement techniques.”

            How do we measure productivity anyway?

            And this brings up a good point. How exactly is productivity measured?

            In the case of the US Bureau of Labor Statistics, productivity gain is measured as the percentage change in gross domestic product per hour of labor.

            But other publications such as US Today, argue that this is not the best way to track productivity, and instead use something called Total Factor Productivity (TFP). According to US Today, TFP “examines revenue per employee after subtracting productivity improvements that result from increases in capital assets, under the assumption that an investment in modern plants, equipment and technology automatically improves productivity.”[2]

            In other words, this method weighs productivity changes by how much improvement there is since the last time productivity stats were gathered.

            But if we can’t even agree on the best way to track productivity, then how can we know for certain if we’ve entered the productivity paradox?

            Possible causes of the productivity paradox

            Brynjolfsson argued that there are four probable causes for the paradox:

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            • Mis-measurement – The gains are real but our current measures miss them.
            • Redistribution – There are private gains, but they come at the expense of other firms and individuals, leaving little net gain.
            • Time lags – The gains take a long time to show up.
            • Mismanagement – There are no gains because of the unusual difficulties in managing IT or information itself.

            There seems to be some evidence to support the mis-measurement theory as shown above. Another promising candidate is the time lag, which is supported by the work of Paul David, an economist at Oxford University.

            According to an article in The Economist, his research has shown that productivity growth did not accelerate until 40 years after the introduction of electric power in the early 1880s.[3] This was partly because it took until 1920 for at least half of American industrial machinery to be powered by electricity.”

            Therefore, he argues, we won’t see major leaps in productivity until both the US and major global powers have all reached at least a 50% penetration rate for computer use. The US only hit that mark a decade ago, and many other countries are far behind that level of growth.

            The paradox and the recession

            The productivity paradox has another effect on the recession economy. According to Neil Irwin,[4]

            “Sky-high productivity has meant that business output has barely declined, making it less necessary to hire back laid-off workers…businesses are producing only 3 percent fewer goods and services than they were at the end of 2007, yet Americans are working nearly 10 percent fewer hours because of a mix of layoffs and cutbacks in the workweek.”

            This means that more and more companies are trying to do less with more, and that means squeezing two or three people’s worth of work from a single employee in some cases.

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            According to Irwin, “workers, frightened for their job security, squeezed more productivity out of every hour [in 2010].”

            Looking forward

            A recent article on Slate puts it all into perspective with one succinct observation:

            “Perhaps the Internet is just not as revolutionary as we think it is. Sure, people might derive endless pleasure from it—its tendency to improve people’s quality of life is undeniable. And sure, it might have revolutionized how we find, buy, and sell goods and services. But that still does not necessarily mean it is as transformative of an economy as, say, railroads were.”

            Still, Brynjolfsson argues that mismeasurement of productivity can really skew the results of people studying the paradox, perhaps more than any other factor.

            “Because you and I stopped buying CDs, the music industry has shrunk, according to revenues and GDP. But we’re not listening to less music. There’s more music consumed than before.

            On paper, the way GDP is calculated, the music industry is disappearing, but in reality it’s not disappearing. It is disappearing in revenue. It is not disappearing in terms of what you should care about, which is music.”

            Perhaps the paradox isn’t a death sentence for our productivity after all. Only time (and perhaps improved measuring techniques) will tell.

            Featured photo credit: Pexels via pexels.com

            Reference

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