Data doesn’t cause bad decisions, people with data cause bad decisions

One of the running themes from the past six months that I’ve been working on is the role of data in decision making. Historically, I’ve been one of the biggest advocates that it is hard to have too much data. Get the data together, test different ways of looking at it, then pick the best to drive decision making.

In the last half year, I have come to the conclusion that even basic data may do more harm than good many times. But the world is moving to more and more data you may exclaim. The trouble is, most people don’t understand numbers.

If you want to test the theory that most people don’t understand numbers, run a simple scenario by someone:

  • Can the price of a stock go down by more than 100%?
  • Can the price of a stock go up by more than 100%?

If you are reading this blog, you probably immediately responded No to the first, and Yes to the second. Stocks can’t go below $0 which means that, on a percentage basis, they can’t drop more than 100%. But a stock can increase to any imaginable number theoretically which means it can go up by as many hundreds or thousands of a percent as you’d like.

My guess, is you are going to be surprised by the number of people who get one or both of these wrong. Or who struggle to answer it. Or who don’t understand what you are asking. Even really smart people miss this.

If people struggle with basic percentages, what hope is there that they will be able to understand the relationship between square feet per person and square fee per desk. These numbers are often more together but projects can make them move in opposite directions. I’ve seen actuaries stop to think about it. Why would we think the majority will grasp it without first really understanding real estate fundamentals completely.

Data in the wrong hands can be damaging. If the person using it thinks they understand it but they really don’t, they can easily draw the absolute wrong conclusion. If they partially understand it, they can misuse it for something it doesn’t even address. Worse, if they pull data themselves, they may miss nuances around how it should be put together and get the wrong number entirely.


How willing are you to say “But I might be wrong”? #RiskManagement

Being wrong about something important sucks. I’m not talking about wrong in the sense of a math error in a presentation. That’s usually fixable. That’s an error. Wrong is arguing that you should put the new office in Alaska versus Texas. Wrong is taking a position that actually turns out to be a bad outcome.

When we make recommendations, we are expected to support them. The worst case scenario is to have a waffle recommendation doesn’t firmly state a position. If the answer is three different answers, it’s no answer at all. At a certain level, your job is to make decisions and drive forward. Part of that trade-off is that, sometimes, you will be wrong.

The worst part of wrong is when the decision maker is unwilling to take into account new information. This world is one of change. If you aren’t willing to accept the possibility that you could be wrong, you present a bigger risk than a simple non-optimal outcome. You become the risk yourself. People who continue to support bad positions have to start cherry-picking data and results. They become biased to a viewpoint.

Risk management is about understanding the nature of how things can go wrong. There are things that can go wrong today, tomorrow, or 5 years from now. There are controllable risks and uncontrollable risks. There are acceptable risks and unacceptable risks. The biggest risk of all is a flawed decision-making process that leads to a predetermined outcome.

If you are willing to say that you could be wrong, you are more likely to have a robust decision-making process that is appropriately reviewing data and new information. If you are open to correcting course, total risk is reduced. That’s not to say you may not be wrong, but the risk is lower.

An effective CRE strategy includes location, workforce, workplace, technology, culture, and (above all else) patience

It’s easy for those in the industry to fall into over-simplifying what corporate (or commercial) real estate is. This world we have chosen is extremely broad. It covers every industry that exists or used to exist. It covers retail, office, warehouse, and manufacturing. It covers big enterprise and mom and pop businesses. The business world happens because of CRE. If you don’t have a place to operate from, your business isn’t going to go far.

An effective CRE strategy (corporate or commercial) involves understanding what is important to you at both the time you are making any given decision and the times after that decision when you are stuck with it. Just because you are signing a 3-year lease doesn’t mean you aren’t making a 10+-year decision. It takes overcoming a lot of friction to pick up and move an existing site. Importantly, the things you worry about today often aren’t the things you will be worrying about tomorrow.

Now, tie in the fact that the decision has more than just a time-based impact. Your CRE decision making impacts how the on-going business will recruit, hire, find customers, and generally operate. The decision also dictates a large degree of the intra-office culture that will exist (offices in the ‘burbs have a different vibe than offices in a downtown). Get the decision wrong and you could negatively be impacting operational profitability.

Let’s step back from any given location decision. Managing a real estate portfolio, even one as small as just 30 locations, because a time consuming and complicated activity. If you miss one lease event, you could easily cost your company a lot of money and operational flexibility. If you aren’t familiar with your negotiated lease clauses, you could be spending money on something that is actually the landlord’s responsibility. Don’t keep your data up-to-date and it becomes surprisingly easy to forget about a location that you have somewhere.

It’s no surprise that CRE teams often roll-up to the finance organization. Understanding lease accounting rules and the impact of a lease on your cash versus GAAP reporting is complicated. That lease you are signing is essentially a financial instrument; if you don’t understand it’s financial qualities, you don’t understand the document at all. But at the same time, if you treat the decision as purely a financial one, you will quickly find yourself with a real estate portfolio that does not reflect or support your operational reality. Rolling up your CRE teams to HR or Operations doesn’t solve anything, it just leads to similar problems.

None of this even starts to address the problems with CRE technology. Let’s start with the fact that there is no equivalent to SAP for real estate. Sure, IBM Tririga and other platforms make a claim to being enterprise capable. But the reality is that operationally, these systems rarely live up to the hype. It’s no wonder why either. Real estate is the owner of no data except for leases (location, clauses, lease costs) and building plans (seats, space). They get data on headcount  (new hires, work-from-home, leavers, etc.) from HR. They get data on many of the financial aspects from Finance (non-lease costs including taxes, facilities operations, utilities, insurance). Getting all of that data to connect and talk correctly can be a significant ordeal.

I mentioned the changing decision environment above but it comes back here because on-going changes to business operations impact the overall management of the real estate portfolio. If you are shifting to more work-from-home, you need less space. Suddenly decide to bring all those people back in, you need to have somewhere to put them. Consolidating back-office locations is a great idea but can increase operational risk. Move back-office support back into multiple hubs puts you in a position of mixing types of space all over again.

CRE is often like the tides. Everything changes on approximately 3-year cycles. Expand, contract. Risk mitigation, operational aggression. Focus on the culture, focus on cost. Up economy, down economy. Something is always changing and CRE is always at the front of it for execution but rarely in terms of really understanding what the business is trying to do.

Pareto was right. The world operates at 80/20.

Striving for perfection is the opposite of operating perfectly. Getting to 100% has a cost disproportionate to the added value – 80% is usually more than enough.

Look around at what you do. How often does something new get released that can answer every single question around it with perfection? There are always grey areas that can’t be known before you hit the start button. Trying to know everything before you hit go only adds time and doesn’t really reduce risk much.

Most people try to get to perfect in order to mitigate their concept of risk. Surely the more they know, the less risk they have. The problem is that this assumes you can know everything you need to know. It’s simply not possible. Experience in the real world always leads to new and unexpected knowledge.

The reality is, even Pareto saw this trend of 80/20 in populations, decisions, and groups of highly generalized things. 20% of your time generates 80% of your profits. 80% of your time is occupied by only 20% of the things you need to work on.

Are you spending your time right?

It’s the circle of risk management!

With the election of Donald Trump, I have seen an associated uptick in the number of consultants talking about the increasing need for risk management. Everywhere I look I’m seeing “risk management.”

But talking about risk now is like trying to sell fire insurance after your house has burned down. It may be on top of people’s minds but the right time to talk about risk management is always. But especially prior to surprising events like Brexit and the election of President Trump. Risk management should be part of the everyday playbook in how problems get solved.

Consultants, as a group, are very good about selling for the situation in front of us today or that occurred yesterday. Like clockwork:

  • If the stock market takes a hit you will see all kinds of mentions about aligning strategy with EPS and EBITDA.
  • If something unexpected happens in the world they will bring up Risk Management.
  • If unemployment starts going up they will talk about aligning your workforce to the next three years.
  • If a treaty is about to be signed addressing climate change or the cost of carbon you will see them going hard after sustainable initiatives.

Anyone focused on yesterday or today is not really looking out for your best interests – as they say on Wall Street, buy low/sell high! When unemployment is going up they should be talking to you about how you can leverage the opportunity to get new customers. When your earnings are strong, you should be paying even closer attention to aligning strategy with financials.

When everyone thinks the same and acts the same you end up with these recurring cycles that strike everywhere at once. Groupthink is very pervasive and can occur even when you don’t know you are part of the group.

Being skeptical of statistics is rational. Rejecting all statistics is irrational.

Statistics is a tricky subject. To some, it seems like the ultimate in waffling – why can’t you just say what the right answer is after all? To others, it’s the ultimate in risk mitigation – but what if these 15 things were to happen. With the recent election forecasting, renewed debate over climate change data, economic modeling and any number of difficult topics, statistics has been taking a very public beating.

Here’s the thing about statistics and data modeling: it’s simply a tool. Like a gun, it can be used for good, evil or any range of grey areas in between. Like people holding guns, some know to use the safety while others wave it loaded around in the air like it’s a toy. The problem with statistics is you typically only see the outcome of a process and not what went into getting it. Essentially you get the target with holes in it but don’t see how the shooter put them there.

To carry the analogy forward, sometimes shooters get lucky and cluster 3 shots right in the middle of a target even though they would never be able to do it again. Sometimes a previously used target is placed up and the shooter only pretends to have accomplished the feat. Sometimes you have a skilled shooter that actually knows what they are doing but has a bad day and misses. Things happen.

Judging performance of statistics in hindsight is useful to be able to understand the tolerances and error associated with a given model. But even then, past performance is not always an indicator of future performance. It’s important to understand the role that statistics and data modeling should play in your decision making process but throwing them out completely is taking a very powerful tool (often perfect for the task) and choosing to never use it because it wasn’t used properly by amateurs in the past or a customer was unhappy even though the product was technically correct.

All tools that you used should be evaluated regularly to understand their best roles and uses, where they work and where they don’t, what can go right and what can go wrong. Statistics is powerful but with that power comes inherent risks that you should always keep in mind.

Trust but verify. It’s even true with math.

The quality of a decision is directly related to the degree risk is accounted for in it.

Risk mitigation and decision making are two topics that go hand-in-hand. You can’t make good decisions without understanding the risks that come with the various choices.

Risk is not always a negative consequence. A lot of time risk goes by another name: opportunity cost. Risk can often be best described as the downside difference of potential outcomes. The greater the best to worst potential outcomes (even if all outcomes are good), the greater the risk.

Sometimes we get thrown off by the word Risk. It has a negative connotation to it. Maybe it comes from all the awful hours spent playing the painful board game of the same name. Maybe it is simply that the association of risk in our minds is tied to the idea of losing money. Regardless, risk is something that exists in all decisions.

There is risk to every post I write. If I publish as-is am I leaving readers out that wanted something shorter? If I don’t spend more time editing do I hurt my credibility through the use of bad grammar? Is this really a topic that is worth posting here? These are all risks – every, ordinary, daily risks.

Thinking through the downside is how good decisions are made – even when the downside is still a good outcome. Maximizing upside is always worthwhile.