The Decision Strategist

When most people think of decision making, they are thinking of either business decisions like How to Compete Against Big Business or Motivating Employees and personal consumption decisions like Buying or Renting, Converting Your Car to Grease Fuel or How to Fight Advertising.

This is probably because these decisions are the easier decisions to make.

We really have no basis for how to go about making the harder decisions. Decisions about whether to leave an abusive spouse, or whether to find a new job if your old one is just ok, or what to do with your life, are much more difficult and messy.

The hardest decisions are ones between a mediocre or negative status quo and a change that would probably be positive, but requires a more negative hump to get over first.

In changing jobs, usually we stick with an unhappy situation far beyond what we would be willing to enter into. Getting a new job has quite a hump, and involves a lot of time, effort, and anxiety, so we are willing to put up with a lot.

In abusive relationships, and not just romantic relationships, but friendships, teacher-student relationships, family, etc… it can seem a lot easier to put up with a negative situation than to face the hump, largely emotional in this case, of speaking to the person and breaking off the relationship (or trying to change it). With relationships there is always the hope that next time it will be better.

The cost of change looks something like this:

(don’t laugh at my poor artwork)

These are the decisions we agonize over and are completely unsure of. They are also hard to make stick because we tend to be unsure about them in the beginning, but become more unsure as the cost of the hump begins to be felt, and we may try to back out.

They are also where we need the most help.

One of my favorite thoughts from Steve Pavlina is that we should not accept situations that we’d rate as mediocre to slightly positive. If we’d rate a situation 6 or 7 out of 10, then we should change it. The problem is that we tend to get complacent with situations that are mediocre, and never get to a situation we’d rate as a 10.

The real problem though is, as always, one of information. We might rate a current job at a 6 or 7, but who’s to say that it’s not actually a 9 and we just have unrealistic hopes for what a job should be? If our relationship is a 6 or 7 is that because of the relationship or because of years seeing media telling us what it should be?

In essence, how do we really know what the limit of possibilities is if we haven’t experienced it? Would we recognize it even if we did?

It reminds me of this question:

If you could have the best sex of your life tonight, knowing that for the rest of your life you’d be comparing every night to this night, would you do it?

We have a hard enough time dealing with decisions when we are facing uncertainty about our choices. In the messy world of personal decisions that have major impacts on our material and emotional lives, the cost hump involved with making changes makes these decisions even more difficult. How do we approach them? What is the right answer? Is there even a right answer?

-zot

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Technology is really about information, and our ability to interact and store information has been making some major changes for the past several decades.

Those of us who are researchers have been blessed in the past several years with an explosion of available information for examining nearly every topic we want to look at.

But at the same time, there has been a shift away from objective analysis toward studies completed by organizations with a vested interest in the outcome.

This has resulted, as noted at Overcoming Bias, in a crisis of faith in the use of statistics. No one believes any numbers that are released because they figure that the people who did the analysis have a hidden agenda. This is the most demoralizing aspect of being an analyst.

The problem is essentially that the analysis process is still closed. We don’t trust the numbers because we don’t know the process that went into obtaining them. Until the process of analysis is opened to a public that can understand and take part in a dialog about the methods, we can continue to write analytical work off as a waste of money and resources because someone else will always have a study saying the opposite.

We need the democratization of data analysis.

And I have high hopes for the future. One of my ideas has been to create an online data warehouse and analysis website, and a few groups such as Swivel and Many Eyes are doing just that.

The services are still fledgling, but in a fairly short time I think we’ll see the ability to perform analysis via the web, and to upload and share data. Hopefully this will result in the standardization of data sets and eliminate the monkey work of downloading a text file and formating it in excel.

I cry when I think how many people have done the very same thing with the very same data.

For a time there will be a lot of confusion, attacks, and some really bad work, but ultimately a community of devoted analysts performing essentially open and peer reviewed work will develop. Because it’s been through trial by fire from all sides of the issue, it will be the most objective approach to messy data analysis that we have ever obtained.

The new analytical hotshots will be the people who have weight with communities at Swivel and Many Eyes and others and are known for doing quality work. These people will engage in very public analysis and will be extremely valuable to everyone wanting analysis that can be seen as objective.

Hopefully that means that shoddy and lazy work will slip to the sides and we can regain confidence in numbers that we see.

I guess it could go the other way. That people don’t want objective analysis and we’ll shun those whose results we can’t know ahead of time. We’ll see even more extreme partisanship.

But that way lies certain death.

-zot, pretending to be a futurist.

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Anyone who has worked with statistics, models, or data of any form has probably run into the situation where someone wants a measure for something regardless of how useful that measure is.

Maybe it’s some version of the conjunction fallacy or other decision making error: A number gives us confidence regardless of how useful the number is.

Or maybe, like valuing the status quo over innovation, it’s a liability issue. Workers and managers want to be able to cover their own ass if something goes wrong. In such cases it’s always better to have some numbers, regardless of how applicable they are.

My bet is on the second reason, and it’s ruining the world.

Take an abysmal measure of inflation: the CPI. Granted inflation is a difficult thing to measure, but there are several bad problems that only make things worse.

The same goes for GDP, unemployment rates (or here or wikipedia) and basically any other measure of economic activity.

But maybe other disciplines aren’t like that? Don’t bet on it.

A friend of mine who is an accountant says that there is enough error and flexibility in accounting rules to make most balance sheets suspect. Consider the value of goodwill and brand value (look at that equation).

Measures of worker efficiency, political polls and statistics in scientific research all have regular problems.

Earlier I was talking about ourreference and discuss our tendency to slap a measure on everything, but the effect is that it causes us to shift our focus to maximizing the measure rather than what we really want.

As a policy analyst, I run into the ‘a garbage number is better than no number’ mind frame regularly. Government officials and big companies, the havens of bureaucracy need a number to justify their decisions. They need something to protect themselves if something goes wrong.

The problem isn’t really that we want to rely on numbers. It’s that we’re making big, important decisions based on numbers that have high measures of error at best or are just plain irrelevant at worst.

Our desire to cover our own ass is causing us to make bad decisions. In complex, important decisions the situation is always more nuanced than the reduction to measures indicates. But we can’t cover our ass if we make a decision based on a judgment call after considering all the complexities of the situation. That is an opinion and is open to dispute.

Yet what do we miss by relying on approximations so heavily? We miss all the subtle implications of the situation that can’t be measured easily or that get lost in the aggregation of data.

We often forego the time and effort of gaining a deeper understanding of a decision in the name of cost and efficiency. For small decisions it might be worth it to search less and ignore more information. But for large policy decisions it is almost certainly worth the effort of getting more information.

So to conclude this long rant (my apologies), lets reflect a bit on the importance of considering things that can’t be quantified, interactions that can’t be written down in a list, and factors that may only be known to us subconsciously.

Our reliance on numbers as the ultimate truth is ultimately misguided.

-zot

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If you are like me, you have a million different things you are interested in, but you never pursue any of them to completion. I float from one project to another as it grabs my interest. This is great for generating ideas, and I think remaining curious is an essential aspect of enjoying life. It’s not so good for bringing projects to fruition.

The typical process goes something like this:

1. Get excited about an idea.
2. Research the idea compulsively to the detriment of other aspects of my life.
3. Work on the project in all of my spare time (and some not spare time).
4. Get disrupted, reach something I can’t figure out, or have to deal with real life.
5. Become discouraged and try to force myself to work on the project.
6. After a few weeks of doing nothing, get excited about a new idea.

It’s a vicious cycle not unlike the problem-solving cycle.

I seem to be doing well on my current project decyder though. I think the difference is due to momentum. How am I creating momentum? Here are three major ways:

The Decision Strategist

This blog is peripheral to decyder, but keeps me thinking about how decision making works in the real world, an idea that is directly relevant to decyder. Though writing for The Decision Strategist takes up a significant amount of time, it keeps me involved and provides an important alternative when I’m sick of working on decyder.

Public Deadlines

The Ycombinator application is due October 11th. I’d like to get a demo of decyder working before then, so I have a very real deadline. Deadlines are great, but hard to enforce without some kind of public commitment.

Making Progress

Making progress is key to building momentum. With past projects I’ve spent an excessive amount of time brainstorming and planning. These are fun activities that get my imagination going, but don’t produce much else. Eventually I lose interest.

This time I decided to basically wing it. Thoughts from Paul Graham, Steve Pavlina, Seth Godin, and others seem to coincide on the value of execution over imagination, so I try and keep my planning to a minimum.

The upshot is that I am accomplishing my goals and feeling less overwhelmed. Instead of having a huge list of tasks, I have only the next few steps. This keeps my goals small and as they say, the thousand mile journey begins with a single step.

Good luck to all of you who are struggling to bring your ideas to life.

-zot

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