“If you can’t explain it simply, you don’t understand it well enough.” – Albert Einstein
I actually didn’t care much for consultants in the first part of my career. My experience was that people would come in, tell you what to do, and then leave victoriously while we were stuck trying to implement something that just wouldn’t work. It seemed that they made everything seem so complex – often as a way to justify their cost.
Then, I met a really amazing consultant who shared something valuable with me. He explained what he believed differentiated a true consultant from a contractor (something I wrote about a decade later in a Tech Republic article). He then made me aware of the Einstein quote above. This was one of those pivotal moments in my career.
Over the course of many years I have met many interesting people. Some seemed to try to intentionally obfuscate even the easiest things to try making themselves seem brilliant. Others took such a circuitous route that you sometimes forgot about what you were trying to understand and fix. And sometimes explanations were just so tangential that the main point was completely lost. There are likely many reasons for these experiences – some intentional and many not. The real lesson learned is that it wasn’t just consultants who have the ability to be incomprehensible, and that clear and comprehensible communication is key to effectiveness.
Just think about the power of a well crafted “elevator pitch” when you meet someone new, or the ability to quickly explain how your company differentiates itself from the competition (making you the better or safer choice in your prospect’s mind). Or, being able to articulate your business strategy in a way that people not only understand, but also so interests them enough where they want to learn more and be part of making that happen. This goes well beyond just having good communication skills.
The best consultants have this ability to explain something simply, as do the best employees, the best managers, the best executives, and the best business owners. While this is only one attribute of success (likability, powers of persuasion, integrity, luck, etc. are others), it is something that can be taught, developed, and consistently applied.
The power to “explain it simply” is the power to make a difference.
Whether you are a business owner, a manager, or a parent, finding the right way to motivate your team is important to maximize performance and results. Each person is a little bit different, is looking for something a little different, and once you figure out what is important you can get the most out of them. Not everyone wants to be a star – and that is usually OK (as long as they have the right attitude, skills and work ethic).
But, there are those exceptional people that want to be the best, are willing to take risks, work hard, and “think different” in order to succeed. These are the people who are self-motivated, and continue to raise the bar for the entire team as part of a high-performance culture. These are the people who move the dial.
I’ve had the pleasure of being taught by people like this, working with people like this, managing people like this, and helping a few people become people like this. Every once in a while you have a few of these special people working together, and that is when really amazing things happen. These people are generally curious and wonder “why not?” They are confident (not arrogant), intelligent, and passionate about being successful.
Back when I was funding research projects I had a trip scheduled to Philadelphia. I asked a friend at a local hospital to make an introduction to meet someone from “CHOP” (the Children’s Hospital of Philadelphia). They were always ranked as one of the top hospitals, and I wanted to see why. The introduction was made and a lunch meeting was scheduled. I was looking forward to the meeting, but had no real expectations for the meeting.
Much to my surprise, a half-dozen people in a large conference room with a catered lunch greeted me. They gave me presentations on their various projects (which was unusual as they did not know me, but did know I was involved with research projects at other facilities). Everyone in the room was amazing, and the department head (Dr. Terri Finkel) was one of the most impressive people that I had ever met.
After lunch was over I told Dr. Finkel that I appreciated the lunch, but wondered why they went to so much trouble when I never promised to do anything in return for them. She just smiled and replied, “We love what we do, and love having the opportunity to talk about our projects and passions to people who have similar interests.” That made a huge impression on me, and within about six months we were funding projects using a unique approach that Terri suggested in response to a question I had about getting the most “bang for my research dollars.”
Over the course of a few years this team did incredible things that had a tangible impact on Pediatric Rheumatology. There were many great researchers, but two of them really stood out (Drs. Sandy Burnham and Randy Cron – both continue to do amazing things to this day). The results of this team were so much better than everyone else that we supported. They provided a huge return on my investment, and I can take pride in knowing that in some small way I made a difference through these efforts.
To me it came back to the basics. Intelligent people who were passionate about making a difference, who were confident enough to be challenged, and who were led by a visionary person who saw an opportunity to motivate her team and help me achieve my goals. It’s the best type of win-win scenario possible.
These people moved the dial back then, and continue to move it today. It is a thing of beauty to watch stars like this perform. These are the people who shine twice as bright and guide others down the path to success. And, you can find them in every industry and every walk of life.
Two years ago I was assigned some of the product management and product marketing work for a new version of a database product we were releasing. To me this was the trifecta of bad fortune. I didn’t mind product marketing but knew it took a lot of work to do it well. I didn’t feel that product management was a real challenge (I was so wrong here), and I really didn’t want to have anything to do with maps.
I was so wrong in so many ways. I didn’t realize that real product management was just as much work as product marketing. And, I learned that geospatial was far more than just maps. It was quite an eye-opening experience for me – one that turned out to be very valuable as well.
First, let me start by saying that I now have a huge appreciation for Cartography. I never realized how complex mapmaking really is, and how there just as much art as there is science (a lot like programming). Maps can be so much more than just simple drawings.
I had a great teacher when it came to geospatial – Tyler Mitchell (@spatialguru). He showed me the power of overlaying tabular business data with common spatial data (addresses, zip / postal codes, coordinates) and presenting the “conglomeration of data” in layers that made things easier to understand. People buy easy, so that is good in my book.
The more I thought about this technology – simple points, lines, and area combined with powerful functions, the more I began to think about other uses. I realized that you could use it to correlate very different data sets and graphically show relationships that would otherwise extremely difficult to make.
Think about having access to population data, demographic data, business and housing data, crime data, health / disease data, etc. Now, think about a simple and easy to use graphical dashboard that lets you overlay as many of those data sets as you wanted. Within seconds you see very specific clusters of data that is correlated geographically.
Some data may only be granular to a zip code or city, but other data will allow you to identify patterns down to specific streets and neighborhoods. Just think of how something so simple can help you make decisions that are so much better. The interesting thing is how few businesses are really taking advantage of this cost-effective technology.
If that wasn’t enough, just think about location aware applications, the proliferation of smart devices that completely lend themselves to so many helpful and lucrative mobile applications. Even more than that, they make those devices more helpful and user friendly. Just think about how easy it is to find the nearest Indian restaurant when the thought of curry for lunch hits you. And these things are just the tip of the iceberg.
What a lucky day it was for me when I was assigned this work that I did not want. Little did I know that it would change the way that I think about so many things. That’s just the way things work out sometimes.
Ever since I worked on redesigning a risk management system at an insurance company (1994-1995) I was impressed at how you could make better decisions with more data – assuming it was the right data. The concept of, “What is the right data?” has intrigued me for years, as what may seem common sense today could have been unknown 5-10 years ago, and may be completely passe 5-10 years from now. Context becomes very important because of the variability of data over time.
And this is what makes Big Data interesting. There really is no right or wrong answer or definition. Having a framework to define, categorize, and use that data is important. And at some point being able to refer to the data in-context will be very important as well. Just think about how challenging it could be to compare scenarios or events from 5 years ago with those of today. It’s not apples-to-apples but could certainly be done. It is pretty cool stuff.
The way I think of Big Data is similar to a water tributary system. Water gets into the system many ways – rains from the clouds, sprinkles from private and public supplies, runoff and overflow, etc. It also has many interesting dimensions, such as quality / purity (not necessarily the same due to different aspects of need), velocity, depth, capacity, and so forth. Not all water gets into the tributary system (e.g., some is absorbed into the groundwater tables, and some evaporates), so data loss is expected. If you think in terms of streams, ponds, rivers, lakes, reservoirs, deltas, etc. there are many relevant analogies that can be made. And just like the course of a river may change over time, data in our water tributary system could also change over time.
Another part of my thinking is based on an experience I had about a decade ago (2002 – 2003 timeframe) working on a project for a Nanotech company. In their labs they were testing various things. There were particles that changed reflectivity based on temperature that were embedded in shingles and paint. There were very small batteries that could be recharged tens of thousands of times, were light, and had more capacity than a 12-volt car battery. And, there was a section where they were doing “biometric testing” for the military. I have since read articles about things like smart fabrics that could monitor the health of a soldier, and do things like apply basic first aid when a problem was detected. This company felt that by 2020 advanced nanotechnology would be widely used by the military, and by 2025 it would be in wide commercial use. Is that still a possibility? Who knows…
Much of what you read today is about the exponential growth of data. I agree with that, but also believe that the nature of and sources of that data will change significantly. For example, nano-particles in engine oil will provide information about temperature, engine speed and load, and even things like rapid changes in movement (fast take-off or stops, quick turns). The nanoparticles in the paint will provide weather conditions. The nanoparticles on the seat upholstery will provide information about occupants (number, size, weight). Sort of like the “sensor web,” from the original Kevin Delin perspective. A lot of data will be generated, but then what?
I believe that time will become an important aspect of every piece of data, and that location (X, Y, and Z coordinates) will be just as important. But, not every sensor will collect location. I believe there will be multiple data aggregators in common use at common points (your car, your house, your watch). Those aggregators will package the available data in something akin to an XML object, which allows flexibility. From my perspective this is where things become very interesting.
Currently companies like Google make a lot of money from aggregating data from multiple sources, correlating it to a variety of attributes, and then selling knowledge derived from that plethora of data. I believe that there will be opportunities for individuals to use “data exchanges” to manage, sell, and directly benefit from their own data. The more interesting their data, the more value it has and the more benefit it provides to the person selling it. This could have a huge economic impact, and that would foster both the use and expansion of various commercial ecosystems required to manage the commercial and privacy aspects of this technology.
The next logical step in this vision is “smart everything.” For example, you could buy a shirt that is just a shirt. But, for an extra cost you could turn-on medical monitoring or refractive heating / cooling. And, if you felt there was a market for extra dimensions of data that could benefit you financially, then you could enable those sensors as well. Just think of the potential impact that technology would make to commerce in this scenario.
This is what I personally believe will happen within the next decade or so. This won’t be the only type or use of big data. Rather, there will be many valid types and uses of data – some complementary and some completely discrete. It has the potential to become a confusing mess. But, people will find ways to ingest and correlate that data to identify value in it – today or in the future, and decide to store it (potentially forever). Utilizing that data will become a competitive advantage for people and companies knowing how to do something interesting with it. Who knows what will be viewed as valuable data 5-10 years from now, but it will likely be different than what we view as valuable data today.
So, what are your thoughts? Can we predict the future, or simply create platforms that are powerful enough, flexible enough, and extensible enough to change as our perspective of what is important changes? Either way it will be fun!