Chapter Thirteen

Conclusion

Where to from here?

The first rule is that you’ve got to have multiple models – because if you just have one or two that you’re using, the nature of human psychology is such that you’ll torture reality so that it fits your models …

And the models have to come from multiple disciplines because all the wisdom of the world is not to be found in one little academic department.

Charlie Munger79

WHERE TO FROM HERE?

We started working on The Decision Maker’s Playbook in 2014. It was in that year that Google acquired DeepMind, a leading Artificial Intelligence company. Two years later, algorithms dethroned the incumbent Go champion, and social-media technology platforms arguably played a pivotal role in the outcome of the US presidential election.

In recent decades, the environments in which we work and live have changed tremendously. A hundred years ago, even if you lived in affluent societies, your options were limited. You could only be hired by a handful employers, limited further by the number of companies and the distance required to commute to work. Labour-saving technologies were fairly basic. You almost certainly married someone who grew up in the same town or region as yourself.80

By the end of the twentieth century and into the new millennium, the opposite is true. We have too many options, and our major decision problems are centered on how to make the best choices given the range of possibilities. Enter any department store and you are overwhelmed by the sheer variety of different brands. Take Amazon, which stocks more than 500 million different products. A well-educated and mobile young professional can work in large international companies or organisations and start a family with someone who grew up 12,000 miles away from her. In this environment, making sense of these challenges requires a set of tools to help us reduce, focus and decide which among the countless options are the most useful.

THE AGE OF ALGORITHMIC DECISION MAKING

Today, algorithms and digital systems have come to the rescue and to help us make choices. They do this in a number of ways, but they primarily use our past behaviour and the revealed preferences of people similar to us to help filter our options. Take a review platform such as TripAdvisor. It’s nothing new that we follow the advice of our friends and visit the restaurant that most of them recommend. But the internet has made it orders of magnitudes easier to share and aggregate data such as reviews or recommendations. So even though we theoretically have many options, we end up booking the restaurant on top of the list.

Soon the world will be dominated by algorithms which predict fairly accurately what we want, prefer and do next. The more data these algorithms gather, the better their predictions will become. It’s not science fiction to suggest that, in the near future, algorithms will know which of our mental (and emotional) buttons to press in order to make us believe, want or do things. In itself, this is not necessarily bad. After all, we use these algorithms voluntarily because they offer us some kind of benefit. They take some load off our shoulders to sift through options and present us with the most suitable ones –or they present the pieces of information that we are most likely to latch on to. And they don’t have to do that perfectly. It’s enough for them to simply be better than what we can come up with ourselves. Google Maps’ routing feature occasionally leads us to blocked streets and we need to take a detour. But in the overwhelming majority of cases, it leads us the along the most time-efficient paths, saving us hours, days or even weeks of lifetime.

Remember the incentive systems from earlier in this book? It’s not hard to see that incentives may not be fully aligned. From the perspective of their owners, algorithms are tools to accomplish a goal, such as selling services or keeping us on a website so we can be exposed to ads. In solving these goals, such as profit maximisation, algorithms serve us suggestions, such as nuggets of news that are designed to stir outrage and polarisation. They may not be in line with the goals we set for ourselves if we are open-minded and weigh evidence of either side to form a balanced opinion. Our dependency on algorithms can make us subject to manipulation.

The more we use digital systems, the more data is collected. The more data collected, the better algorithmic models can be trained, and the more powerful the algorithms get. The more powerful these algorithms become, the more we delegate our decision-making authority to them. And this is where the problem lies. In doing so, we give up part of our autonomy, and we become dependent on algorithms. We become vulnerable against big tech, which is – thanks to large-scale effects of data – increasing the concentration of information and making it harder for us to opt out or switch. Just as Google Maps is better than a taxi driver at selecting the fastest route, we surrender to algorithms for much more important decisions: what we read, who we date, or who we vote for.

We are highlighting the potentially dangerous aspects of technology here, and the problems that are related to it: technological dependence, safety, biases, intransparency or ‘black boxes’. We don’t talk about the tremendous welfare gain that algorithms such as search engines have generated in the fields of logistics or healthcare. These achievements are clearly laudable, but they don’t take away from the risks.

Mental tactics as presented in this book serve not only as effective tools, but also as means to reflect on our preconceptions, beliefs and biases. Taking this meta view can be an antidote, a shield against being hacked by algorithms.81 Even when we are still in the last instance of decision making (in autonomous systems, this is called ‘human in the loop’), we surrender our authority de facto to machines. While we still have the possibility to override the suggestions made by algorithms, we typically don’t do it.

Thinking and decision making have got some serious competition: machine algorithms. Your individual set of mental tactics serve as a check, back-up and corrective so that you can maintain your independence and critical thinking.

A MAP OF THE TERRITORY

Mental tactics, as you by now are aware, are models that aim to explain parts of reality, and provide a decision framework that helps you make better choices and drive the outcomes you intend. They are maps that aim to describe the territory (reality).82 A seafarer uses a map to locate his current position using various navigational instruments, dead reckoning (a navigational method calculating the current position based on known previous locations) and a triangulation of landmarks (mountain tops, harbours, buildings on land). He uses a map as a simplified copy of reality to simulate his position, and continuously compares the map against the observed reality.

Maps are necessarily reductionist. They de-emphasise data (observations or evidence) that isn’t relevant for the specific decision situation (many nautical maps don’t show elevations), and instead direct our focus and attention towards data that is relevant such as water depth. This is necessary, as our attention and time is scarce. Both creating and retrieving (reading/processing) complex maps is time-consuming and expensive.

REFLECTING ON YOUR EXISTING MODELS

All of us have already cultivated a number of existing mental tactics that we use on a daily basis. They might be simple or trivial. For example, you might put items that you frequently need, such as a pen, in the front of a drawer, and archive those that you don’t need as frequently in the back (such as tax invoices). Other mental tactics might be more complex, and uncertain, such as models about human behaviour or self-identity. You might hold the belief that humans are generally self-interested and have selfish reasons for everything they do, even seemingly selfless deeds. If that’s your map of the territory, you tend to think in terms of other’s individual motives, their benefits, gains and losses.

It’s important to be aware about your pre-existing maps and reflect on them frequently and consciously. Do they still hold up against the actual territory? By using them, are you able to make accurate forecasts about what’s going to happen? In our seafarer’s example, is the actual island that you discover recorded in the nautical maps? If it isn’t, should you lose confidence in the map, discard it and look for a different one that fits reality better? Or should you adjust the map? The same holds true for mental tactics. Test them frequently, and be honest with yourself. When is it time to adjust the mental tactic? When should you discard it and look for a new, more effective one?

A SUMMARY OF THE MENTAL TACTICS IN THIS BOOK

We have tried to provide you with our ‘best of’ selection of mental tactics. We sincerely hope they provide valuable shortcuts for your work and life. If you’ve read The Decision Maker’s Playbook chapter by chapter, you’ll now have a strong toolkit that allows you to collect evidence, connect the dots, craft the solution and complete the mission more thoughtfully and effectively. We hope that you continue to adapt and refine these tactics to improve your decision making under changing circumstances.

Here’s a short recap of the key insights in each chapter.

PARTCHAPTERTHE BOTTOM LINE
 Zero
What’s your problem?		Problems don’t just exist, we actively choose and frame them. Good decision makers ask the ‘Question Zero’ first: What’s my problem? Reflect on the framing of the problem: Who framed it? What are their underlying interests? And then think hard: Would this problem benefit from reframing? Should it be solved at all? Immediately? By me?
1 One
lluminate your blind spots: Admit what you don’t know and correct your wrong beliefs		Humans don’t have a built-in mechanism to detect false beliefs, or to be good at acknowledging what we don’t know. Instead, we typically look for evidence to confirm our biases, and make up satisfying stories to fill in the gaps. To be a good problem solver, it is paramount to regularly review your belief system, calibrate confidence levels and actively practise humility.
Two
Bust your biases: See through the games your brain plays		Our minds use a lot of shortcuts to help us navigate the world. The problem is that most of these shortcuts are adapted for an environment that is long gone, and lead to biases in modern social settings. As far as gathering data and evidence is concerned, three types of biases are particularly relevant. First, simplification and stereotyping. Second, accepting stories that seem to make sense too quickly. Third, the inherent stickiness of the beliefs we hold. Actively de-biasing yourself takes time, but can be learned. It all starts with acknowledging the various distortions, being mindful and aware, as well as practising ways to deliberately shift down into System 2.
Three
Explore your data: Gather, scrutinise and visualise information to discover insights		The data you use to kick off your analysis will determine how useful your results are – and whether they are useful at all. Make sure that your data is good quality, and form hypotheses to make sense of your information. Always look for ways to go beyond the average and see the full picture of your data (by looking at descriptive statistics and forming views about the underlying distribution of your data). That’s where the real insight is.
2Four
Drill down: Use tree diagrams to deconstruct any problem		Problems and data are often complex and messy. Tree diagrams provide a useful way to add structure to your thinking and give you a useful means of communication. Trees help you break down a trend or dynamic into their drivers, de-average aggregated numbers, find the root cause of a problem, or structure a presentation, project or vacation. Tree diagrams require you to think MECE (mutually exclusive, collectively exhaustive), and allow you to understand problems and data in a much deeper and clearer way.
Five
Move the needle: Anticipate regression to the mean		We are programmed to automatically look for patterns in data. But we often impose patterns on what is, in fact, random. Establishing rules that work reliably is difficult, particularly if you only have a few observations to build on, and if luck plays its part as well. To overcome regression to the mean, think about how much the success you are observing could be due to chance, hone counterfactual reasoning (what could have happened but didn’t), and try to find more historical data points.
Six
See the big picture: Practise systems thinking		Systems are groups of interdependent actors or items forming an integrated whole. The environment, social groups and companies are all examples of systems. When mapping out systems, one typically starts by identifying causal chains such as A leads to B leads to C. Whenever C has an effect (directly or indirectly) on A, we call them feedback loops. Feedback loops result in emergent behaviour such as exponential growth (reinforcing feedback loops) or convergence (balancing feedback loops). Depending on your aim, you typically try to create, change or stop causal loops. The systems thinking mental tactic lets you analyse loops and find the most effective points of intervention.
3Seven
Think on the margin: Focus on the next unit		When we make decisions, we often take into account irrelevant factors such as costs incurred in the past. We often fall into the all or nothing trap in which we consider all the benefits and all the costs of a decision situation, which makes decision problems complex and unwieldy. Contrast that with marginal thinking. It requires you to only take into account variables pertinent to your current situation. In its core, marginal thinking is economic thinking, as it always assumes that decisions are made by weighing additional costs against additional benefits. Marginal thinking provides the foundation for rational decision making.
Eight
Score points: Articulate your criteria and make sound trade-offs		Many choices are not as straightforward as they seem at first. Equally, many decisions that appear complex or stressful can be radically simplified. Every option has a different set of advantages and disadvantages and often it’s hard to pick the right one. A structured scoring model allows you to deliberately reflect on criteria, weights and scores, and provides you with a rigorous assessment approach. Using scoring models makes it easy to communicate and discuss choices and allows you to reach the most beneficial solution.
Nine
Walk the talk: Run experiments to test your solutions in the real world		How do you know if your solution actually works? How can we make sure that our actions have the effect we intend? When it comes to understanding causal relationships, we typically revert to speculation, mimicking others or best practices. But the results often disappoint, because best practices may work in one situation but not in others. Experiments allow you to test your solutions and find out if they survive the crash with reality. Use randomised control trials (such as A/B tests) if you can randomise and have a large enough sample size for both control and treatment groups. Or apply n=1 experiments for situations with only one subject.
4Ten
Multiply your possibilities: Use real options to improve your odds of success		Having the option (but not the obligation) to act in the future is valuable, particularly in environments that change quickly and unpredictably, and that are hard to shape or influence. Options are everywhere you look. Understanding and valuing options is an important skill to hedge for future contingencies. Your goal should be to create and use them wisely to enable optimal decision making in the future. Remember, a truly valuable option hardly ever comes for free. Start thinking about your future choices as today’s options, each with a value attached.
Eleven
Engineer incentives: Energise everyone to be their best		Incentives are tools to motivate individuals to perform actions. Misaligned incentives are one of the major causes of conflict and lost productivity in our world. However, careful up-front thought about the desired outcome, the relevant inputs and incentive system design can help anticipate and avoid common issues such as moral hazard, principal-agent and coordination problems. Pay attention to ineffective incentive systems and remember that intrinsic motivations may help you to change performance for the better, and for longer.
Twelve
Make it happen: Anticipate, execute and improve		Big things don’t just happen. But with a little pre-planning, attention to action and post-action reflection, your most important projects can fall into place. The ability to plan and execute is a learned skill. It improves over time and with practice. Teams, individuals and groups increase their odds of success by putting in place techniques to plan effectively, execute well and reflect appropriately, such as the critical-path method, the pre-mortem and the decision audit.

TURNING IDEAS INTO ACTION

As we conclude this book, we’re incredibly excited for you. We hope you had at least a few of the ‘aha’ moments we’ve enjoyed while collecting and refining these mental tactics over the years. Maybe you’ve learned about a mental tactic that you have witnessed in your work or life but didn’t know how ubiquitous it was. Or, during reading, you realised how these models apply to problems you have experienced in the past.

The next step is to use these mental tactics in your future work and life. We write this as an invitation to start applying these concepts from today. To get you started, we want to offer the following suggestions:

  • Over the next four weeks, use new problems as a trigger to slow down and consult this book. We typically rush into problem-solving mode, rather than stepping back and deliberately thinking about which mental tactics would best apply. Make the pledge to consciously use mental tactics, at least for a limited time – give them a chance.
  • Take time to review and reflect on the mental tactic used in a particular situation. Did it serve as intended? Did it help to render your beliefs more accurately? Did it support you in spotting regressions to the mean? Did it help you focus on what makes the marginal difference?
  • Find an accountability partner. Approach someone who’s as invested in improving their problem-solving and decision-making skills as you are. Talk through problems together, and share new mental tactics with each other.
  • Take our recommendations for other books and blogs to read on this subject. Please also see the suggested resources at the end of this book – they have all helped us tremendously.

This is only the beginning of the journey. Connecting and building mental tactics is a lifelong endeavour – worthwhile but demanding. We hope that you will start to build your own collection of ideas, concepts, frameworks and tools that help you make sense of this VUCA world. In doing that, aim for general fluency in selecting, reflecting and discarding mental tactics, not comprehensiveness. And keep on experimenting.

As we said at the beginning, this book can be read from start to finish, or as a reference guide, or a field manual, or an introductory text to concepts that we think are vitally important. It can also be re-read in any of these ways. We hope that you’ll pick it up again and again – before a big meeting, at an inflection point in your life or when something happens that tickles your brain with a reminder of one or more of these mental tactics.

DON’T BE A STRANGER

The most meaningful part of our work is hearing from people who’ve put mental tactics into practice – how they use options to think about future decisions, their approach to calibrating their beliefs and their meta sense in thinking about problems. You are a part of that community now – the growing number of people who are fluent with these mental tactics and are passionate about applying them in work and life. Welcome to the club – we are delighted that you are here.

Please visit us online at MentalTactics.com and follow us on Twitter (@MentalTactics). We can’t wait to hear where you take these ideas. Tell us:

  • which of the concepts in this volume really resonated with you
  • which ones you have put into practice and how you did it
  • who you have shared these ideas with
  • which experiments didn’t work for you and any n=1 experiments that don’t work out too (it is all data after all)
  • which mental tactics not listed in this book you use on a frequent basis.

As you go out into the world, we make this invitation and request: think clearly, analyse rigorously, decide carefully, act boldly.

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