Comms pro and tech enthusiast writing about blockchain, data, strategic communication, and business.
Since the advent of the modern age, people have used machines to save them time. Cars will get you places faster. Some refrigerators can write your shopping list for you. Most mediocre daily tasks can now be automated with a little bit of technology. This saves us time, but does it help us make better decisions as well?
Decision making is a resource that most people squander. Like energy, the ability to make a good decision is reduced throughout the day. In their book “Switch”, Chip and Dan Heath describe your ability to decide as an elephant, and a little person riding that elephant. Your brain is the rider, and the rider has a limited supply of energy to guide the elephant, and it is only through the careful application of strength that the rider is able to maintain the course.
There’s a hole in my bucket dear Liza, dear Liza…
As we make decisions throughout the day, we reduce this resource. And with each reduction, the rider gets tired while the elephant becomes increasingly willful. In the end, too many decisions lead to a losing battle, and the energy is gone before we come to the decisions that matter. At this point, all that’s left is a rampaging elephant, ignoring all queues and simply taking the path of least resistance.
In 1980 Richard E. Petty and John Cacioppo developed a model of persuasion that describes our decision-making process quite well. Instead of an elephant and a rider, they discovered two different routes people take when making a decision: the peripheral route (elephant), or the central route (rider).
The Peripheral route goes around the information and relies on cues and categories to assist in the decision. For example, if you are searching for a new computer, the brand name could be a cue, or the price, or the material it’s made out of. All of these paint a picture in your mind about the quality of the device without actually taking a deeper look at what is actually inside the computer.
“Your mind is a categorization machine, busy all the time taking in voluminous amounts of messy data and then simplifying and structuring it so that you can make sense of the world. This is one of the mind’s most important capabilities; it’s incredibly valuable to be able to tell at a glance whether something is a snake or a stick.” — Bart de Langhe and Philip Fernbach HBR
You recognize this when you hear people tell you that “Apple has higher quality computers.” Or that “iPhones are easier to use.” Through marketing, and by providing quality products, Apple as a brand became a cue many people use to decide which computer to get, or which mobile phone to buy. Most people using this cue are unlikely to conduct additional research on competing devices. Why would they? Their mind is already hardwired to take the path of least resistance which in this case is to buy an Apple device.
Our rider prefers the central route. In this route, the rider evaluates each bit of information to determine the best decision. Such an analysis is intense, and throughout the analysis the rider must keep the elephant at bay. This requires a massive amount of energy that eventually exhausts the rider. It is for this reason that most people let the elephant make most of their decisions, basing them on the cues and categories developed throughout their lifetime. Unfortunately, living by the whims of a willful elephant can result in poor decisions that may cause harm to ourselves or even those around us.
What’s the leaky bucket? You are. Throughout the day the average adult makes an average of 35,000 remotely conscious decisions. With so much to focus on, you can see why our decision making energy drips away throughout the day.
Well then fix it dear Henry, dear Henry…
Modern technology was once seen as a solution to this problem. Our mobile phones have hundreds of new apps, promising new ways to help you choose what to do next. Task management apps come with all sorts of prioritization tools attempting to give the rider rest. It’s a complete layout of your day, ready for you. Start at the top, go to the bottom. You don’t need to choose what to do next. It’s right there.
Unfortunately, apps treat the symptom, but not the problem itself. The symptom is a lack of productivity, indecision or poor decisions, while the problem is an exhausted rider. Essentially we keep looking for ways to fill up a bucket, without first patching the holes in the bucket.
What does your morning routine look like? Do you wake up, lie in your bed and wait for another alarm to go off? Or do you jump out of bed quickly to get through your morning exercise routine? Perhaps you meander from your bed to your kitchen, make yourself a cup of coffee and read the latest newspaper, blog, or news articles in your RSS feed. Whatever you do, it’s probably part of a daily routine.
Routines are predictable, that’s why we like them. In fact, by maintaining a routine, you keep your brain resources available to ponder more important decisions. To free up more decision making power, you can incorporate new routines into your life. For example, when do you decide what you’re going to wear?
Choosing what to wear is one of the first decisions a person makes in a day. They look at their wardrobe, trying to figure out which of their clean clothes will meet the needs of the day. This decision can be rather complex, especially if you have a lot of clothes.
Iyengar and Lepper discovered that the more options a person has, the more difficult it is to make a decision, and the more dissatisfied they are with the result. In fact, it is so difficult for the human mind, that the mind will often avoid making decisions with too many options. For most of us, putting on clothes is not an avoidable decision, so we push our way through it. Even something as simple as choosing what to wear reduces your decision-making abilities for the rest of the day.
To reduce this, you can set up an evening routine to pick and prepare your outfit for the next day. It sounds quite simple, but you’ll soon notice a difference the following day, and you may even be a little happier in the morning. Choosing your clothing the day before saves the rider’s strength, and allows that decision making power to be used for a more important decision later.
If such a simple change in routine helps one make better decisions. What happens when we automate processes with technology?
During this routine, you probably interact with specific pieces of technology. This might be your coffee machine, toaster or the device you use to consume your daily dose of media (iPad, smart speaker, radio, tv). Whatever these devices are, odds are that they are in some way connected. Your iPad uses WiFi or LTE. Smart speakers and smart TVs leverage your home WiFi network, while the radio continues to use those classic, reliable radio frequencies set aside decades ago.
These connections are there to provide a specific service to you. To feed that data to that device so that you can consume it. Leveraging them for so little is a sadistic waste of resources. What would happen if your morning alarm communicated with your coffee machine, telling it that you finally turned it off (instead of hitting the snooze switch) and you’re heading to the kitchen? It could certainly save you time, but does this simple automation help you make better decisions later in the day? Not really.
Sure you’ll have more energy, but time-saving isn’t the equivalent of saving your decision-making ability. We established that earlier. This is why modern technology, as it is, looks like it should help us, but actually ends up providing so many options that it slowly drains our rider throughout the day. There is a solution — and that is to develop smarter tech that helps us make better decisions. Not by telling us what to do, but by reducing the number of options based on the available data.
With what shall I fix it dear Liza, dear Liza, dear Liza?
Data, even personal data, isn’t the scary beast everyone puts it out to be. In fact, if you choose to leverage your own data, you could actually reduce the number of decisions you have to make each day. For example, your historical clothing preferences could be used to determine future outfits. In the future, we could even have “automated closets” that not only “distribute” your clothing in the morning, but also automatically sort, wash and press your clothing for its next use. Bring in the weather forecast to this process and suddenly you have weather appropriate attire automatically ready for you each day. This automated process not only reduces the amount of time it takes to take care of your clothing, but it also removes your need to make a decision about clothing. It sounds fantastic, doesn’t it? Something so simple has the potential to help you make smarter decisions. Imagine how many other non-critical decisions you make in your home. Would it be possible to automate those as well? Probably. What about non-critical decisions outside of your home?
Do you ride your bike to work? Do you leave at a different time if you know it’s going to rain or stop raining soon? How often was that prediction accurate? I remember the first day I rode my bike to work in Berlin (back when I didn’t have rain gear). I checked the weather forecast and everything looked perfect. Sadly that forecast changed midday, and it was possible it would rain on my ride home. After speaking with my cycling colleagues, they showed me the best places to find out when it would rain. Following their advice, I left the office at the best time to avoid the rain. As you can imagine, I still got soaked. Now there is a better way to do this.
If most of the buildings throughout Berlin had small weather stations able to predict and detect rain, that situation may have been avoidable. I would have been able to see where the rain was (exactly) and the pace at which it was moving across the city. One app using this information could tell me exactly the time I would need to leave to avoid getting wet. Not only would this be more accurate, but it would also remove the long consideration, and later decision. The app would decide for me.
There are a number of other ways data combined with automated analysis can reduce the number of non-critical decisions you have to make throughout the day. But for all of this to work, we need the data. It is only with this data that the systems can be built to save that rider’s energy, allowing him to make better decisions when the need arises.
With Data my dear Henry, dear Henry with Data
One solution to ensuring that enough data is available is to crowdsource the collection of data. That is, to allow people to enter data they’re collecting into a portal so that others can gain access to this data. Systems, like Waze, have been built for people to self-report data, however, these still rely on human interaction, and therefore cost the “reporter” time. An automated system would definitely be an improvement. This doesn’t exist today because it requires a financial investment. But as you’ve heard, data has value, and given the right tools, those wishing to source data may be able to make that initial investment back.
The MXC Foundation is building a platform that allows anyone to purchase a sensor, and list it in a data market. Instead of relying on the self-reporting methods, it takes advantage of low-cost sensors and uses blockchain technology to ensure that the data provided comes from a real sensor. Data listed in the data market will then be available to developers to integrate into smart applications, designed to reduce the number of decisions you need to make throughout the day. Naturally, developers pay for the data, which easily covers the cost of the sensor, and provides the sensor owner with a nice little stream of passive income. For full disclosure, I also work at MXC.
What’s incredible is that this hasn’t already been done. Our world already has a global network of sensors working on different projects. These may be specific to some scientific research, or even an everyday sensor as a functional element in a modern city. These are collecting data 24/7, and this data has the potential to improve lives all around the globe. Unfortunately, due to the closed nature of these projects, and lack of access or interoperability, this data isn’t available to the broader public.
This is why projects like MXC are needed today. It helps us bring all of this information together, making it useful for us while acting as a catalyst for global innovation.
Does tech help you make smarter decisions? Definitely — as long as it has access to enough data.
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