Technology
Genetics, Genomics, Nanotechnology, and more
Science has interested me for most of my life, but it wasn’t until my first child was born that I shifted from “interested” to “involved.” My eldest daughter was diagnosed with Systemic Onset Juvenile Idiopathic Arthritis (SoJIA – originally called Juvenile Rheumatoid Arthritis, or JRA) when she was 15 months old, which also happened to be about six months into the start of my Consulting company, all while we were in the middle of a very critical Y2K ERP system upgrade and rehosting project. It was definitely a challenging time in my life.
At the time, there was very little research on JRA because it was estimated that only 30,000 children were affected by the disease, and the implication was that funding research would not have a positive ROI. The economics of medical research were eye-opening to me. This was also a few years before major breakthroughs like Enbrel for children.
One of the things that I learned was that this disease could be horribly debilitating. Children often had physical deformities as a result of this disease. Even worse, the systemic type that my daughter has could result in premature death. As a first-time parent, imagining that type of life for your child was extremely difficult.
Luckily, the company I had just started was taking off, so I decided to find ways to make a tangible difference for all children with this disease. We decided to donate 50% of our net profits to fund medical research. Our goal was to fund $1 million in research and find a cure for Juvenile Arthritis within the next 5-7 years.
As someone new to “major gifts” and philanthropy, I quickly learned that some gifting vehicles were more beneficial than others. While most organizations wanted you to start a fund (which we did), the impact tended to be more long-term, supportive, and much less immediate. Later, I met someone passionate, knowledgeable, and successful in her field who showed me a different, better approach (here’s a post that describes it in more detail).
I no longer wanted to blindly give money and hope it was used quickly and properly. Rather, I wanted to treat these donations like investments in a near-term cure. To be successful, I needed to understand research from both medical and scientific perspectives in these areas. That began a new phase in medical research and an independent learning journey in areas where I had limited understanding and expertise.
A lot was happening in Genetics and Genomics at the time (here’s a good explanation of the difference between the two). My interest and efforts in this area led to a position on the Medical and Scientific Advisory Committee with the Arthritis Foundation. Except for me, the other members were talented, successful physicians who were also involved in medical research. We met quarterly, and I asked questions and made suggestions that made a difference. But unlike everyone else on the committee, I needed to study 40+ hours for each call to ensure I understood enough to add value and not be a distraction. Every quarter, I earned my seat at that table, and soon, most of the other members respected me for that (i.e., “not a typical donor”).
A few years later, we did work for a Nanotechnology company (more info here). The Chief Scientist wasn’t interested in explaining what they did until I described some of our research projects on gene expression. He then went into great detail about what they were doing and how he believed it would change what we do in the future. I saw that and agreed. That started my thinking about the potential of leveraging advanced nanotechnology in medicine.
While driving today, I was listening to the “TED Radio Hour” and heard a segment about entrepreneur Richard Resnick. It was exciting because it got me thinking about this again – a topic I haven’t thought about for the past few years (the last time, I was contemplating how new analytics products could be useful in this space).
There are efforts today with custom, personalized medicines that target only specific genes for a specific outcome. The genetic modifications being performed on plants today will likely be performed on humans in the near future (I would guess within 10-15 years as gene editing becomes more mainstream), possibly even performed by some type of robots. Because the body is an incredibly adaptive organism, it may be very challenging to implement anything consequential that is consistently safe and effective long-term. But that day will come.
It’s not a huge leap from genetically modified “treatment cells” to true nanotechnology (not just extremely small particles). Just think, machines that can be designed to work independently within us to do what they are programmed to do and, more importantly, identify and understand adaptations (i.e., artificial intelligence) as they occur and alter their approach and treatment plan accordingly based on findings and changes. This is extremely exciting. From my perspective, being able to do things that positively impact the quality of life for children and their families is a worthy goal.
My advice is to keep learning, stay open-minded, and do what you can to make a difference. You will never know what is possible unless you try. It will also be interesting to see how technologies evolve and work together to create an even greater impact.
Profitability through Operational Efficiency
In my last post, I discussed the importance of proper pricing for profitability and success. As most people know, you increase profitability by increasing revenue and/or decreasing costs. However, cost reduction does not necessarily mean slashing headcount, wages, benefits, or other factors that often hurt morale and cascade into lower quality and customer satisfaction. There is often a better way.
The best businesses generally focus on repeatability and reliability, realizing that the more you do something, the better you get at doing it well. You develop a compelling selling story based on past successes, build a solid reference base, and identify the sweet spot from a pricing perspective. People keep buying what you are selling, and if your pricing is right, money is available at the end of the month to fund organic growth and operational efficiency efforts.
Finding ways to increase operational efficiency is the ideal way to reduce costs, but it takes time and effort. Sometimes this happens through increased experience and skill. But, often optimization occurs through standardization and automation. Develop a system that works well, apply it consistently, measure and analyze the results, and then make changes to improve the process. An added benefit is that this approach increases quality, making your offering even more attractive.
Metrics should be collected at a “work package” level or lower (e.g., task level), which means they are related tasks at the lowest level that produce a discrete deliverable. This project management concept works whether you are manufacturing something (although a Bill of Materials may be a better analogy in this segment), building something, or creating something. This allows you to accurately create and validate cost and time estimates. At this level of detail, it becomes easier to identify ways to simplify or automate the process.
When I ran my company, we used this approach to win more business with competitive fixed-price project bids that provided healthy profit margins while minimizing risk for our clients. Higher profit margins let us invest in our own growth and success by funding ongoing employee training and education, innovation efforts, and international expansion, as well as experimenting with new things (products, technology, methodology, etc.) that were fun and often taught us something valuable.
Those growth activities were only possible because we focused on doing everything as efficiently and effectively as possible, learning from everything we did – good and bad – and having a tangible way to measure and prove that we were constantly improving.
Think like a CEO, act like a COO, and measure like a CFO. Do this and make a real difference in your own business!
A missed opportunity for Geospatial
I have a Corvette that I like to work on for fun and relaxation. It gives me an excuse to learn something new and an opportunity to hone my troubleshooting skills. It can be a fun way to spend a few hours on a weekend.
A few weekends ago, I was looking for a few parts for a small project. This was spur-of-the-moment and didn’t need to be done right away (as the car will be stored soon for the winter). I found the parts I needed from a single company, but then something strange happened.
The website had my address and knew the two parts I wanted, but the process was not easy and almost cost them the sale. This company forced me to manually check five different store locations to see if they had both parts. In this case, two of the five did. One store was about 5 miles from my house and the other about 20 miles away.
It would have been helpful if this website used the available data (inventory and locations) to present me with two options, or, better yet, default to the closest store and note the other store as an option. Using spatial features, this would be extremely easy to implement. It’s the equivalent of the “Easy Button” that one office supply company uses in their commercials.
Now, let’s take this example one step further. The website makes things quick and easy, leaving me with a very pleasant shopping experience. It could then recommend related items (it did, but by that time I had wasted more time than necessary and was questioning whether or not I should start that project that day). The website could also create a simple package offer (e.g., auto wax and polishing supplies) to increase my cart value while leaving me impressed with the convenience. While this last portion isn’t spatial, it is complementary technology that enhances the value provided by spatial technology.
All simple things that would generate more money through increased sales and larger sales. It is easy to justify from both a business and technical perspective, assuming the company is aware of this issue.
I frequently tell my team that, “People buy easy.” Help them understand what they need to accomplish their goals, price it fairly, demonstrate the value, and they make the rest of the sales process easy. This makes happy customers and leads to referrals. It makes good business sense.
So, while geospatial technology might not be the solution to all problems, this is a specific use case where it would. The power of computing systems and applications today is that so much can be done so fast, often with reasonably low technology investment. The first step is to ask yourself, “How could we be making this process easier for our customers?”
A little extra effort and insight can pay off big for your business.
To Measure is to Know
Lord William Thomson Kelvin was a pretty smart guy who lived in the 1800s. He didn’t get everything right (e.g., he supposedly stated, “X-rays will prove to be a hoax.”), but his success ratio was far better than most, so he possessed useful insight. I’m a fan of his quote, “If you can not measure it, you can not improve it.”
Business Intelligence (BI) systems can be very powerful, but only when embraced as a catalyst for change. What you often find in practice is that the systems are not actively used or do not track the “right” metrics (i.e., those that highlight something important – ideally something leading – that you have the ability to adjust and impact the results), or provide the right information – only too late to make a difference.
The goal of any business is to develop a profitable business model and execute extremely well. So, you need to have something people want, deliver high-quality goods and/or services, and finally make sure you can do that profitably (it’s amazing how many businesses fail to understand this last part). Developing a systematic approach that allows for repeatable success is extremely important. Pricing at a competitive level with a healthy profit margin provides the means for sustainable growth.
Every business is systemic in nature. Outputs from one area (such as a steady flow of qualified leads from Marketing) become inputs to another (Sales). Closed deals feed project teams, development teams, support teams, etc. Great jobs by those teams will generate referrals, expansion, and other growth – and the cycle continues. This is an important concept because problems or deficiencies in one area can negatively affect others.
Next, the understanding of cause and effect is important. For example, if your website is not getting traffic, is it because of poor search engine optimization or bad messaging and/or presentation? If people visit your website but don’t stay long, do you know what they are doing? Some formatting is better for printing than reading on a screen (such as multi-column pages), so people tend to print and go. And external links that do not open in a new window can hurt the “stickiness” of a website. Cause and effect are not always as simple as they seem, but having data on as many areas as possible will help you identify which ones are important.
When I had my company, we gathered metrics on everything. We even had “efficiency factors” for every Consultant. That helped with estimating, pricing, and scheduling. We would break work down into repeatable components for estimating purposes. Over time we found that our estimates ranged between 4% under and 5% over the actual time required for nearly every work package within a project. This allowed us to profitably fix bid projects, which in turn created confidence for new customers. Our pricing was lean (we usually came in about the middle of the pack from a price perspective, but a critical difference was that we could guarantee delivery at that price). More importantly, it allowed us to maintain a healthy profit margin to hire the best people, treat them well, invest in our business, and create sustainable profitability.
There are many standard metrics for all aspects of a business. Getting started can be as simple as creating sample data based on estimates, “working the model” with that data, and seeing if this provides additional insight into business processes. Then ask, “When and where could I have made a change to positively impact the results?” Keep working until you have something that seems to work, then gather real data and validate (or fix) the model. You don’t need fancy dashboards (yet). When getting started, it is best to focus on the data, not the flash.
Within a few days, it is often possible to identify and validate the Key Performance Indicators (KPIs) that are most relevant to your business. Then, start consistently gathering data, systematically analyzing it, and then work on presenting it in a way that is easy to understand and drill-into in a timely manner. To measure the right things really is to know.
Spurious Correlations – What they are and Why they Matter
In an earlier post, I mentioned that one of the big benefits of geospatial technology is its ability to show connections between complex and often disparate data sets. As you work with Big Data, you tend to see the value of these multi-layered, often multi-dimensional perspectives on a trend or event. While that can lead to incredible results, it can also lead to spurious data correlations.
First, I am not a Data Scientist or Statistician, and there are definitely people far more expert on this topic than I am. But, if you are like the majority of companies out there experimenting with geospatial and big data, it is likely that your company doesn’t have these experts on staff. So, a little awareness, understanding, and caution can go a long way in this scenario.
Before we dig into that more, let’s think about what your goal is:
- Do you want to be able to identify and understand a particular trend – reinforcing actions and/or behavior? –OR–
- Do you want to understand what triggers a specific event – initiating a specific behavior?
Both are important, but they’re different. My focus has been identifying trends so that you can leverage or exploit them for commercial gain. While that may sound a bit ominous, it is really what business is all about.
A popular saying goes, “Correlation does not imply causation.” A common example is that you may see many fire trucks for a large fire. There is a correlation, but it does not imply that fire trucks cause fires. Now, extending this analogy, let’s assume that the probability of a fire starting in a multi-tenant building in a major city is relatively high. Since it is a big city, most of those apartments or condos likely have WiFi hotspots. A spurious correlation would be to imply that WiFi hotspots cause fires.
As you can see, there is definitely the potential to misunderstand the results of correlated data. A more logical analysis would lead you to see the relationships between the type of building (multi-tenant residential housing) and technology (WiFi) or income (middle-class or higher). Taking the next step to understand the findings, rather than accepting them at face value, is very important.
Once you have what looks to be an interesting correlation, there are many fun and interesting things you can do to validate, refine, or refute your hypothesis. Even without high-caliber data experts and specialists, you can likely identify correlations and trends that can give you and your company a competitive advantage. Don’t let the potential complexity become an excuse for not getting started. As you can see, gaining insight and creating value with a little effort and simple analysis is possible.
Where Ideas, Experiences, and Lessons Learned Intersect 