When should you value specialized experience versus generalized experience?

Not all experience is created equal. In the real estate brokerage world, some end up specializing in a subset of their local market and other specialize in the general needs of a business. If you need to understand the exact nuances of the medical office building market in Alpharetta Georgia, you are going to have a small list to reach out to. If you want to understand the typical real estate needs of a Fortune 500 company, you would reach out to a different set of people.

Neither experience is better or worse than the other but the localized broker has developed a very specific and specialized experience. If they were to branch out into other areas they would suddenly have less time to devote to the constantly changing world they had just left but would gain an additional degree of generalization. This is specialized versus generalized experience.

Some problems that we need to solve may require a degree of both specialized and generalized experience. If I were plotting a data center strategy for a Fortune 500 company, I would start with company needs but quickly require more specialized knowledge as the strategy got more and more specific. This type of project requires both needs but it’s easy to see where to start.

If, however, you were starting by trying to determine a strategy for a specific site within the portfolio you could start with either specialized or generalized experience. Both are equally valuable for getting the final answer but would approach the problem very differently.

This difference in viewing the world is one of the most fundamental differences between the two groups. People with specialized experience deeply understand the problems and issues that impact their world but can often have difficulty elevating themselves from the weeds to understand the broader implications of a problem. Generalized experience can lead you down the road of understanding broad problems but can cause you to miss the details that will impact the on-going day-to-day. Not everyone fits this pattern, but generally, this is how each group would first approach a problem.

It’s important to understand the perspectives of the people solving your problems. Are they looking at the micro or macro level of the problem? Even if they are looking at both, are they giving each side the same weight? Should they be giving each side the same weight? Are they changing their view as the project goes on?

If you can balance this problem then you’ve started down the road of either leadership or Program Management, but that’s a discussion for another day.

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Most things in life are not binary (yes or no), most things exist on a spectrum.

I’ve been spending the last couple of weeks watching the cryptocurrency markets seemingly lose their mind. Bitcoin went from a high of almost $20,000 per coin to a low of $8,300 as I write this on February 2nd. This may seem like a bubble that popped (and I believe that it is) but that doesn’t mean that all original value suddenly disappeared.

Bitcoin first passed the $8,300 mark on November 24th – a grand total of 10 weeks ago. I remember it distinctly because I was surprised it had continued to rise to $8,300 at all. Somewhere in the last 90 days a grand delusion set in (or market manipulation which I’m giving a lot of credence to) that caused prices to rise like a rocket through December.

This isn’t meant to be a post on cryptocurrency, but it is what got me thinking. Just because there has been a short-term bubble, doesn’t mean that there is a fundamental problem. Just as when the housing bubble burst, it wasn’t a sign that houses had suddenly become a bad bet generally. It was an opportunity to step back and understand what the value should be based on.

Most things in life are not a simple yes or no, good or bad. Most things are on a spectrum with answers usually existing somewhere in the middle. This is what is known as nuance.

Any given 10-word answer may be right in substance but wrong in particulars. Any given 100,000-word treatise may be right in particulars but wrong in philosophy.

Thinking about the User Experience of CRE #ux

CRE is a complex area, trying to identify the user or customer in the decisions we make is not always simple. The most obvious users of a workplace environment are the employees that sit there. However, the reality is that it is designed based on the theories to increase productivity based on business definitions. The employees aren’t actually the customers of the design even though they are the ones who occupy it.

Similarly to building location decisions. One would think that the location is determined based on the employees who will occupy it, but here again, the business is the actual customer as they are trying to target a pool of potential labor. The commute of any given employee is a byproduct of the business’ selection rather than something that is being optimized for.

This may sound a bit anti-employee but in reality, it’s about balancing the needs of the many. The target user isn’t actually any given individual, it’s the ideal target which may be a combination of several different types of people.

Now, designing for the average and not the actual comes with many drawbacks. No one will ever have that “perfect” commute in. No one will ever find every aspect of their workstation right for them. No one has ever gotten everything they wanted from a system. The goal is to actually fit the needs, requirements, and wishlist of most while creating a degree of flexibility to allow as many as possible to make it work.

The user experience in real estate isn’t simple or straightforward. It takes a lot of thought and balancing of needs.

What qualities should you be looking for in a new HQ location?

Last week, Amazon announced their shortlist of 20 cities in the US for their HQ2. I personally think this process is just for show at this point. They needed no professional support to get to this list of cities. In fact, they could have gotten 90% of this list by simply cross-referencing NFL cities with international airports.

But Amazon’s process raises a good question for other businesses that use their HQ location as a strategic advantage: what attributes should you look for in an HQ location?

Amazon’s process has done one thing perfectly: it has created a demand for them. No matter what else happens between now and their operational go-live, they will have more job applicants than a typical new company to a market. They will also have an enormous pile of goodwill (unless they screw this up royally and it turns out that they are simply in it for incentive money). These two elements are critical to a business’ long-term success in a market.

Much of a business’ success is dictated by the quality of the talent you can recruit. Good talent reduces your overall cost of delivery because one great finance person is worth three poor finance people (and far less than the cost of those three). The larger your talent and recruiting pools, the more likely you are to land those in-demand A players.

This is a lot of exposition to get to the list of attributes you should look for in an HQ location but it’s important because the selection of a new HQ is as much art as science. Here’s the recipe for success:

  • A talent pool that aligns with your overall organizational needs. You want people that understand your business, not just the back office.
  • A market that is hospitable to your type of business. A financial company in an industrial town will always feel a bit out of place.
  • A cost structure that fits your needs. Don’t go to New York if you aren’t willing to pay for the expensive real estate required to keep up with the Joneses. Don’t go to Huntsville, Alabama if there are no buildings that reflect the type of operation you want to run.
  • Do not sacrifice your culture. If you don’t want a Silicon Valley mentality in your workforce, don’t go to Silicon Valley.
  • Do not pick a market that is too small. Some companies can get away with dominating a market (Walmart!) but most cannot get away with it. Make sure you have some room to grow even if that means leaving room for competitors to come in behind you.

It’s not a math problem but you can largely model many of these. There’s an art to this process but it requires you to think it all through.

Embrace the unknown to enhance your solutions.

It is impossible to know everything. It is even difficult to accurately model or simulate those things that you actually do know. The very nature of the future means that it is impossible to predict.

Unknowns are not a negative in a solution. Instead, they are an opportunity that should be embraced. Unknowns present the chance for improvement and change. Choosing how you handle the unknown can often determine whether your solution is bad, good, or great.

For example, when you are determining the length of a lease term there are many unknowns to consider:

  • What is going to happen to the local economy?
  • How will the business perform against growth estimates?
  • What M&A activity could happen during the term of the lease?
  • Changes to business products and delivery?
  • How will the operation perform against revenue forecasts?

Sensitivity modeling is the act of understanding how your solution performs given various outcomes within the unknown categories. Performing sensitivity modeling can add a lot of complexity to a model and, if done wrong, can actually lead to worse outcomes. But when done correctly, it can give you incredible insights into what aspects of a decision actually matter.

When negotiating a lease, sensitivity modeling can help you understand the relative value of an earlier break option versus simply taking additional square footage. It can help you understand whether it is better to have a single large office or several smaller offices. It can help you take into account the various confidence levels that stakeholders have around their forecasts.

I can’t tell you how badly I wish I had written this article: Data shouldn’t drive all your decisions

Quartz just published a phenomenal article titled Data shouldn’t drive all of your decisions. Go read it first because I can’t find a single thing I disagree with in it. It hits all of my favorite topics on innovation and decision making.

Go ahead, I’ll still be here after you finish reading it.

Done? Good! Because there’s some summary to unpack:

  • When solving new problems, yesterday’s data isn’t going to give you the answers.
  • Data is best used in story form, not in charts and tables.
  • Just because most of the data says one thing, that doesn’t mean your conclusion won’t be something else entirely.
  • Sometimes experience isn’t everything and can lead you down the wrong path.

Check your ego before you start the day.

All of us experience swings in our ego and confidence from day-to-day. When we are on a winning streak, it’s easy for the head to start to inflate. When we’ve hit a few roadblocks and things aren’t quite going our way, it’s easy to fall into a pattern of worry and quiet. Neither is ideal for operations.

I used to be bad about letting my ego do the talking for me. I’d focus on what things meant to me personally instead of just getting on with the job. It’s an easy thing to do when you think you know more about a topic than anyone else. Problem is, operating like that leads down the path of ego vs. ego instead of getting things done.

My current process is to try and stick to just the facts. If you remove ego entirely from the decision-making process, you allow everything to be driven based on the known information. At the end of the day, getting the job done is why we each have a job. If ego is more likely to cause problems than simplify the solution process, why let it influence what is going on?