Edge cases are the key to understanding system behavior. First, we should start by defining what an edge case is for those not up on systems. An edge case is any scenario where the state changes.
For example in travel, traveling a highway has multiple scenarios:
- Travelling between cities in the same area (soft edges)
- Travelling across state lines (soft edges)
- Travelling between countries (hard edge)
Edges are anything that causes the conditions of operations to change. It’s easy to test static conditions: does this system work on Windows XP, 7, 10, MacOS, ChromeOS, iOS and Android? That’s a yes/no condition. Understanding whether the system still works on each of those while switching internet connections between providers and resubmitting credentials is a much harder scenario to test.
In real estate, we have a few common edge cases that are important to think about:
- How do you operate your largest and smallest offices? It’s easy to manage the average office, the ones on the extreme are more difficult.
- How do you handle your highest growth office?
- Are your processes different for offices where the CEO sits?
- Do offices perform better when closer to the business or further away?
- Which day of the week has peak occupancy of your offices?
Thinking through what happens at these boundary conditions allows you to pressure test your solutions. Have you really thought through everything you need to? Are you handling your risks appropriately? Do you have a plan for dealing with best case/worst case scenarios?
Everyone likes to think they can see the world clearly and as it is. That we can remove our rose-tinted glasses when we choose and correctly set the measure of what is happening around us. Objectivity is that wonderful state of removing your feelings and biases to evaluate what is happening.
On many things, this can be possible. Our emotions don’t rise to the level of bias on most things. Cats versus dogs – biased. Beige versus tan – objective. Objectivity comes from the ability to set aside emotions and experience to understand something as it is in that moment separate from yourself. As humans, the most difficult thing for any of us to do is to set aside ourselves.
When we make judgments or decisions, it’s important to realize that we aren’t doing so objectively. If we cannot realize our biases, preferences, failings, weaknesses, limited experiences, and occasional bad decisions, we cannot understand the impact of our decisions. Self-reflection is all about understanding how we can be wrong.
I love being a little crazy and out there. There are fewer better rushes than proposes a wild hare idea and seeing what the team does with it. A little madness goes a long way.
Madness is how greatness often manifests. Proposing to build an iPhone was madness. Proposing the internet was madness. Building any brand new product is often madness. Traveling the world has a touch of madness. Quitting your job without a fall back is madness. Starting your own business is madness.
The world moves forward through madness. Progress is entropy. Madness and entropy are the stuff that make us smile.
This post came about because I watched the HBO documentary on Robin Williams titled “Come Inside my Mind.” It was a startling look at a life and career built on being different from everyone else – at being better at being funny from moment to moment than everyone else. It all stems from Robin Williams understanding the nature of madness. Adopting madness as his muse. Taking out the filter we all have that is intended to strip out madness.
Steve Jobs was a bit mad. Elon Musk certainly seems a bit mad. Reading through those sentences, it seems like a negative. But in fact, it’s the madness that gave them their bursts of inspiration and ability to push people further than the bounds of their imagination. Who could have dreamed of a reusable rocket, let alone turned it into reality? Only someone with a touch of madness.
I respect people who dream of audaciousness. I tend to be risk-averse when it comes to my own life but I strive to keep the madness in so that I am still taking chances. Hopefully, all of you seek to do the same.
One of the blessings of doing data analytics on real estate/workplace data is that you get to see some truly unique datasets and trends. One of the curses of doing data analytics on real estate/workplace data is that you have to figure out how to explain what those trends mean to people who don’t love data as much as you do.
One of the best examples of needing to explain real estate data is around the concept of “peak day.” When designing a workplace, you design for the theoretical “peak day” which is the day of highest occupancy. Depending on the nature of the work in the office and the region of the world you are in, this day will vary in both occurrence and magnitude. Many offices I’ve studied have a peak day that is 20 to 30% greater than the average occupancy and it occurs every 2 to 3 months. Meaning, if you design for average you will dramatically come up short on seats. If you design one seat for every person that could be there on a peak day, your average occupancy rate will appear low. It’s seemingly a no win data analytics problem.
Here’s the thing about data, it doesn’t provide answers on its own. Data is a tool that can help you test hypotheses, predict operational behaviors, and measure solution risk. Data cannot tell you the “right” answer. Two people looking at the same dataset could easily draw opposite conclusions on how to move forward. It happens every day with every dataset. Some believe you design for the worst day, others believe you design for just shy of the peak day, still others say to build “flex” seats to accommodate the peak day. The data can justify any of those directions.
The real test is in the detail of the solution and the processes in place to help make the solution a success.
I love when companies decide to pretend their marketing claims are real. Recently, I came back across several where companies that were leading a traditional industry decided to say the equivalent of “We’re not a [pick an industry] company, we’re a technology company.” I have to hold back my laughter every time.
Let’s start off by acknowledging that no large company can succeed without investing in technology. That includes the traditional day-to-day, do-your-work technology that every needs but also includes the specialty stuff that you need to keep up with/ahead of your competitors. This is table stakes to being a leading company in any industry. There’s nothing special here.
Just because you put $100m into new or proprietary technology, you do not suddenly become a technology company. You are simply a company doing the smart thing and using technology as a differentiator. Unless 90% of your customer interactions are through your tech, take a deep breath and stop letting your marketing department run wild.
Being a technology company is about more than just having a lot of money dumped into systems. It’s about living and breathing by those systems. It’s about your entire future being bet on the success of those systems. It’s about being aggressively invested into that technology being the future of your company. Only if you do that can you be a tech company.
So please stop letting your marketing groups drive you to making silly claims.
I have an ego. There’s no sense denying it because it comes through pretty clearly to people. My wife and family joke (I think it’s joking) that it’s good the people I work with keep my head from growing to big.
Over the past decade, I’ve worked hard to develop a good working relationship with my ego. I can think clearly of some times where it started running and I ended up saying some things I really shouldn’t have in hindsight. But I can also look back at many more examples where it put me in positions where I succeeded where I wouldn’t have without it.
Much like your experience, knowledge, and relationships, your ego is a tool that you should lean on and learn to use. Leaving it outside the door to the room does no one any good. Knowing when to keep it locked away helps everyone.
Where egos have developed a bad reputation is where people use them to run roughshod over others. People who think they know best and no one else is worthy of an opinion are simply bad people. Blame their ego if you want, but there’s more going on there. Just like unchecked power corrupts, so does an unchecked ego. Managing it is the key.
Figuring out the right way to display your data is an important part of any project. Bar, line, and waterfall charts can bring certain assumptions. Tables can be difficult to read. Scatter plots may be accurate but imply risk or uncertainty
This may feel like a trivial problem, but it isn’t. Difficult to understand data analysis leads to faulty decisions which cost companies money.
How do you get it right? Through two questions:
- Does the data, as displayed, answer the question without an explanation being required?
- Can someone unfamiliar with the data and problem quickly understand what is being shown?
If the answer to either of those questions is no or maybe then you have done data visualization wrong and you need to try again. Yes, there will be problems where it is difficult to get to yes on these questions. Where that occurs, you generally are asking multiple questions at a time. Charts and graphs are usually able to answer one question at a time, don’t ask them to do more than they can.