Tim Phelan

More Focus More Profits

January 20, 2019 By Tim Phelan

Entrepreneurs have three things that loom largely in the back of their heads when thinking about their business. First, what is the next innovation or service that will add value to customers, attract new customers, and create competitive edge. Secondly, entrepreneurs know “cash is king.” It is critical that they ensure that there is adequate capital to pay people and bills while still investing as much as possible into growth. Thirdly, to reduce risk by containing and cutting costs.

The salesman in me wants to believe that we can always sell our way to the next goal. That sales mentality is risky because most salespeople have rose-colored glasses, and costs have a sneaky way of rising proportionally with sales. As a recovering accountant, I view cost containment essential to organizational health. Strong sales while containing costs enhances the ability to grow by investing profits, leveraging core competencies, and increasing velocity to GTM plans. Before you go sharpening your pencils and pouring over cell phone plans, I submit that one of the biggest, yet seemingly undetectable, business costs today are transition costs.

Transition costs are the time it takes to switch our focus and mindset from one task/topic to another. These add up. The more desperate the task/topics, particularly on the creative to pragmatic spectrum, the more time this takes. The American Psychological Association asserts that “even brief mental blocks created by shifting between tasks can cost as much as 40 percent of someone’s productive time” (“Multitasking: Switching costs”). In a business-world where being ADD is a badge of honor, there is conversely a simultaneous and tremendous impact in productivity and efficiency. Transition costs—wait, I just got a call from my son to discuss how badly Clemson beat Alabama in the National Championship game—so, what was I saying? Oh right, transition costs. Factors that increase transition costs on an individual level are the complexity/variety of activities required, span of control (the number of direct reports vying for attention), and also how well one takes care of themselves (proper rest, diet, etc.). The most insidious part of these transition costs is the difficulty quantifying the actual costs. Therefore, these costs are easy to overlook, shrug off, or ignore completely.

There are a number of fantastic resources and professionals that focus on assisting professionals in minimizing transition costs. and I have listed a few below. A few things that I have begrudgingly found effective are:

Batching Like Activities – Pretty simple, just arranging my schedule to do similar types of tasks in the same time slot.

The 1,440 “rule” – I read this somewhere. The notion is you only have 1,440 minutes in a day (24 hours), and only 480 minutes in an eight hour work day. With that perspective, I become more protective of my time, particularly when someone drops by saying “hey, can I run something by you for a few.” An excellent article on this topic is “What are You Doing with Your 1,440 Minutes? And Only 480 Minutes are in Your Eight Hour Day” by Jack Heimbigner

Do Not Disturb – I thought this was the most horrendous thing ever, and it took every ounce of willpower I had to start and stick to it. Cell phones have “do not disturb” functions where the user is not notified if a call or text comes in. Thankfully mine also has an exceptions list such as if a caller calls multiple times, or If a call/text comes from a specific person or group of people (instructions for the iPhone I use). Over time, do not disturb has become “my time” that I value and enjoy.

E-mail “times” – I have specific times in the day slotted to review and respond to e-mail. It takes discipline to do this and know that you will have to educate your less-patient folks on why they are not getting instantaneous responses. Yet, it has assisted me greatly in remaining focused and present. Of note: there is also a function in Outlook that I use that sends me a text if I receive an e-mail from certain people to whom I must be particularly responsive.

Curbing transition costs takes constant diligence. Think of it as life-hacking and make it fun. Like any other cost, if you spend the effort to minimize its impact, you will be amazed by the bottom-line results over time.

Resources:

Melissa Gratias PhD – Productivity Psychologist

LeadCrunch

IFTTT

StayFocusd

The Freelancer’s 6-Question Guide to Knowing When to Outsource

Blockchain – Antiquated as the Block and the Chain?

January 16, 2019 By Tim Phelan

Has blockchain lost its momentum? Have the promises made no longer within reach? Will blockchain now go down in the annuls as the want-to-be that was merely a now seemingly defunct cryptocurrency play? Many experts are saying just that, that the reality of blockchain will go down as hype. McKinsey & Company posits “Across its many applications, blockchain arguably remains stuck at stage 1 in the lifecycle (with a few exceptions). The vast majority of proofs of concept (POCs) are in pioneering mode (or being wound up) and many projects have failed to get to Series C funding rounds. We are still awaiting that promised technologic revolution.”

To me one of the largest hurdles from the start was a lack of organization and unifying design principles for blockchain. Like many “open-source” software and technologies, the lack of these guiding principles create a double-edged sword: the beauty of unbridled creativity applied to addressing, overcoming, expanding and improving functionality, elegance, and effectiveness of a solution; the boundarylessness and lack of protocols that lead to chaos in the ecosystem, in-fighting amongst differing philosophies and approaches bringing chasms and diluted solution sets, and worst yet a loss of ability and belief in the technology ever making it to the initial visions of grandeur. I suppose we could always ask the Novell administrators or RedHat programmers their opinion! (Just for the record, I believe that regardless of market forces and technological piracy, Novell and its NDS Tree were the most elegant network structure and protocols ever copied and stolen)

Yet, the reports of blockchain’s death have been greatly exaggerated. (Mark Twain 1897). Interestingly today a VP of Technology for a $300M+ national firm asked me if I had any documentation or articles regarding a Tier-1 ERP and blockchain. I did. Maybe taking a 50,000-foot view of the benefits it was to have delivered would be worth a smell-test:”

Decentralized
Resilient
Scalable
Secure and Auditable
Autonomous
Transparent
Quick
Economic
Increased Capacity

See “BeingCrypto”

Like Samuel Clemens’ overstated death, blockchain is alive and kicking. Our Dubaian, grandeur-building, wealthy, trendsetters, and ultimate one-ups-men are aspiring to become the first blockchain powered city by 2020. In this article Dr. Aisha Bint Butti Bin Bishr shares “Dubai has established itself, and in record time, as a global destination for innovators and entrepreneurs in the Blockchain industry. Guided by the vision of our leadership, the emirate has become synonymous with bravely embracing avant-garde technologies and utilizing them to create an advanced, connected and seamless urban experience for its residents and visitors.”. Further, all major ERP/MRP/Financial Software Developers are planning the integration of blockchain because “the value achieved through integrating blockchain with ERP systems comes not by creating and porting new information into the distributed ledger, but by drawing existing data from enterprise systems and being able to tightly control with whom it is shared” per a COMPUTERWORLD report.

Rather than loss of momentum or a death spiral, maybe blockchain is morphing, adjusting, and potentially finding its initial niche that is beneficial, valuable, and sustainable. Or maybe it is as big of a fad as Al Gore’s Internet. Who knows???

Autistic Perspectives – Photo Shoot

January 7, 2019 By Tim Phelan

I love technology. As a father of an autistic young man, I keep up as best I can with the latest developments in Autism assistance and treatments, particularly those where technology can drive better diagnosis, assistance, or any type of help. Autism is a nebulous diagnosis that may include one or more of hundreds of demonstrated behaviors. Understanding the nature and what activities or environments that enrich and enable is mostly one of trial and error. I read and research. Every now and again I come up with an off-the-wall idea of my own to try…of course they involve technology! One idea I came up with provided interesting results. Of course, there is nothing at all scientific about this. However, because I know my son, yet I feel like it imparted some insights that I found enlightening.

Together, my son and I spend a few sessions teaching him how to take pictures with my Nikon D750 (an advanced camera). I made sure that we kept each time short so to not lose his attention or to make it less fun. He loved it. Once he felt comfortable, I sent him outside—to wherever he wanted to go—to take as many pictures as he wanted and of whatever he wanted. Off he went without me or his brothers. Alone to capture whatever interested him. He came back proud and asking for me to bring them up on the computer at least 200 times (it was Christmas and there were many things to attend to). Once I had time, I reviewed and printed out the clear pictures he took (many duplicates…more to come on that). Next, I sat down with him, excited and making it fun, and asked him to describe how each made him feel and to name each picture. I did have to explain the difference between the two many times and be encouraging. Here are the results:

Firstly, I was amazed by the quality of the pictures and how well he quickly shared his feelings and titles. Secondly, I gained insight into how he thinks from a broad perspective, some beckoning further questions:

All the pictures he took were of things he had a positive emotion towards – oh to see the world through that lens
He took 3-5 exact pictures of each – was he unsure, wanted to make sure he took the picture, or was it for some type of emphasis?
None of the descriptions included a possessive pronoun, only a name or literal description even though many contained subjects that normally would such as “my Christmas Tree”, “my dog”, etc. – I will address momentarily

With those observations alone, this was a great experience for both of us. He was proud of his work. I felt just a little more connected and hopefully better equipped to be a better parent to him. A couple of more detailed observations that I made:

Why “Fire” as the title on the first picture? While it is a broad landscape of a house and yard, the street lamp is the only one on the street with natural gas lights that are fire. I saw a scene, to him it was singly about the street lamp. Does he perceive details better as part of a larger context? I would have focused in tighter on the lamp (I did make sure that he knows how to zoom in/out with the camera). Furthermore, the picture “Love / For Quinn” contains many objects. Most interestingly, it also includes our other dog, Duke. Yet to him this was specific to just Quinn.
Revisiting the lack of possessive pronouns, he tended to use descriptors in their place. For instance, “Husky” instead of “my dog Duke” and “The House w Lights” instead of my house or home. Is this a unique gift, the ability to appreciate things for how they are now, and not the sentimentalism or reminiscing that shade our views of things.

I am thinking of ways to expand on this. Regardless of the insights—true or false—my son and I both enjoyed it. If anyone has suggestions, I graciously ask for them.

This is a positive experience and writing for me. I write it with a sense of duty and the heaviest of hearts for my dear friend Ralph. On Thanksgiving Day, his autistic angel Dante passed unexpectantly and unexplainably. I am blessed to have my son. I am confident Dante’s blessings continue from above. I am humbled, forlorn, and at the same time inspired by Ralph and his family’s resilience. I dedicate this writing of my uplifting experience with my son to Dante and Ralph…ALWAYS in my heart and mind…

Personal Artificial Intelligence Nexus (PAIN)

November 3, 2017 By Tim Phelan

What a great topic of science fiction from my childhood with the menacing H.A.L. 9000 killing the crew of the space ship in 2001: A Space Odyssey. In fiction, Artificial Intelligence (AI) is a computer or robot thinking for itself and typically trying to destroy all humankind. While wonderful stories, AI is the ability for computers to process data, analyze trends, and make predictive to accurate communications or actions through the processing and analysis of massive amounts of data. AI and machine learning (ML) surround us daily: from Alexa or Siri learning our voice patterns, to Google Maps or Waze predictively choosing the best route home, to spam filters, and even to the emergence of self-driving cars such as the Tesla (and George Jetson thought he had a monopoly). Gone is the villainous killing-machines, and the days of time-savings, convenience, and great accuracy are growing exponentially via AI.

Many business applications already make use of AI in their work. But, think of a platform (computer, mobile device, tablet, voice-activated service, etc.) that assimilated all your household calendars for each person, had stock off all the food in your home, trended preferences over time, and had the family’s health data and dietary restrictions stored and cross referenced. What if it was then tied into a recipe service, a super market delivery service, and of course your financial budget data for meals. Every Saturday you would receive the “menus” for each meal, skipping of course that night you are dining out for Jamie’s birthday. With a click of a button, mouse, or a verbal “make it so number one,” the groceries would arrive the next day with quick meals of PB&J before the ball game, and health/time/cost appropriate foods for the next week.

One that would rock for me would be the next time I pull out my mobile device to pay for something at Best Buy (a severe vice of my tech obsession), it forecasts the financial impact of the purchase by processing my buying trends, upcoming birthdays, holidays, travel, predictive medical expenses, and a myriad of other data. I hear via my Bluetooth earbud, “Tim, you may want to reconsider this purchase as your son has applied to only private colleges and your savings will need to increase dramatically.” Whether I listen or not is another story better suited to the American Journal of Psychology.

As our minds race thinking of the limitless applications of AI—as do the minds of this generation’s entrepreneurs—there are a few critical constraints to keep in mind:

Privacy – the amount and varied data sources would each have a scary amount of data on us. Is that an invasion of privacy? Can this be regulated? How amazingly valuable would that data be to marketers (ask Google and Facebook)?
Profitability – no technology or technological service comes without someone financially gaining on the efforts to make it work and take it to market. Just because I would enjoy a piece of AI that told me when my camera needed to be serviced based on the model, number of pictures, and the environments where I took pictures, there may not be a big enough market to warrant the data collection and analytical programming necessary to make it happen.
Personal organization and documentation – there must be data to analyze before it can be linked to other data sources and processed appropriately. Further, that data must be accessible, and it must be “good data.” Thus, my written list of things to do today that is always 4 times more than I can accomplish will not due. In fact, Dr. Melissa Gratias, a Productivity Psychologist, shared that “too many people spend as much time trying to figure out what they are supposed to do instead of actually doing the work. They either do not have a system to effectively and realistically track tasks, or they have too many different systems that conflict with each other.” Not only is that a powerful message to get organized, it also means my grand AI project is not going to happen until I become organized!

Personal Artificial Intelligence is the ultimate high-tech hack. Big business, big data, and Wall Street are all relying on it. It is coming, and I am ready…well mostly for the cool stuff and maybe not quite as much as the stuff I will have to do to make it viable for me.

Big Data – The Final Frontier

October 1, 2016 By Tim Phelan

It sounds like a drive through meal, why should I care?

If you join the ranks of those entering the world of the technology religion…er, I mean industry, or technological exploration and invention, or are just a hobbyist there seem to be two prerequisites:

You must love, love, love, love, and dream in acronyms
If you name something, make it so generic as to leave it completely open to any conversation, application or ability.

“Big Data” falls into that latter to the proportion of the “smart phone” (what the heck does that mean???). This inability of the technology industry to intuitively name anything that self-describes in this case is tragic because of the wide-ranging implications and potentialities of Big Data. In fairness, none of us were English majors! What is Big Data in simple terms? Here is a non-PhD explanation of Big Data and why it is truly one of the last exciting frontiers, albeit not in a completely physical sense.

In our infancy of exploration of the scientific method, business, fitness, marketing, and almost any arena big or small, we started with siloed data. In other words, a business had accounting numbers; marketing had demographic data; and science had measurements beyond my comprehension. The goal was simple, to bring this information specific to a process or entity and make sense of it to make decisions, assumptions, valuations, or whatever was the pertinent decision point. We humans, in our inherent need to organize things, created data organized in columns and rows which brought the data together into “information” which we in a moment of utter lack of a comprehensive vocabulary, called reports. By sorting the data in in linear and even multi-dimensional formats, these reports enabled measurement of profitability, scalability, probability, etc.… Today this is still the widest used decision-making technique from household budgets to probabilities of orbital change affecting global temperature.

After years, actually decades, of analyzing reports to assist in decision-making someone asserted that this process of looking at formatted data that gave insightful information and then making decision missed a quintessential question: “what if?” After all, that leaves a great deal to interpretation and “gut feel.” By tracing both good and bad causal effects across information, modern computing could provide models by which we could look for predictive trends. In essence, by breaking down the silos of data, and joining them with other silos, technology could produce more accurate, and more actionable, information. In addition, models could then be manipulated to see where and how it impacted business, health, molecular generation, oil prices…you get the idea. The advent of relational databases made this sort of data storage, configuration, indexing and results available. Hence, the oxymoron term “business intelligence” (BI) was born because technology could now relate data to other data, with very minute variables in common.

The scientific industries and big business fueled the growth of what is now a several billion dollar a year business of BI. Technological advances with computing power and data storage and retrieval continued to make this type of analysis more accessible. Once the professional industries (consultants) joined in with their specific theories and understandings, beautiful modeling techniques such as Key Performance Indicators (KPI’s), benchmarks, acceptable tolerances, sprouted up across every industry. In the simplest forms, many organizations use Excel with pivot tables to accomplish this task at a high level. Yet even in 2016, only a small portion of private organizations take full advantage of these capabilities. The major hurdles, which are slowly coming down, are the cost to deploy technologically, the expertise to ensure the models are actually sound (and not biased to the desired results), and the cost to adapt to each individual data set and configuration of decision trees which is a costly venture in consulting fees alone. Frankly, it has become a battle between the cost savings of proven models versus the innovation of out of the box thinking that brings an entire new set of variables into the mix. Undoubtedly, BI is today one of the most powerful analysis tools available, and it is just now starting to be deployed outside fo the fortune 5,000 and academia.

So, what is left? And, why Big Data? We broke down the data silos very intentionally, joining data with commonalities so technology could give us some predictive results on the question of “what if.” What is next, and more appropriately, why is it big? Simply, Big Data can look at tremendously vast data sets across seemingly unrelated data sets—more than the Library of Congress to the third power of ten hypothetically. This is only possible because computing power has exponentially risen and the cost of storage diminished. There are challenges as well, mind you: cooperation, collaboration, anonymity to name a few. A final frontier for technologists—programmers, analysts, subject-matter experts, and the experiences of past data joining—is coming together to create programs that systematically look for the “joins” instead of the answer in a universe of unlimited data. In short, we are tasking the massive computing power to actually find the relevant causal effects, no matter how distant they may be. Tell me: 42 year old humans living between the 40-43^rd parallel of the earth with chromosome 19 at 1,450 genes…what are material circumstances, outcomes, effects, trends, etc.… Except in this case, subject matter experts are only giving potential variables and the computing power takes over the rest, looking for trends, and other material variables. Imagine finding the correlation between potable water elements of a region and the effects on scientific exploration from those hailing from that region. The trends and how things may relate are limitless.

This is important because it does not give us all the answers. Rather, we are now finding and identifying connections between things we would have never imagined. None of this answers “why am I here.” Nor, will it create immediate change or cures. What it will do is expand our thinking—computers are just machines keep in mind…Artificial Intelligence (AI) is another giant technological leap. Big Data can deliver significant insights into the relevance and relation of organisms, people, ideas, environments, outcomes, tendencies to each other. Those results will lead to more “ologies” than we already know, and certainly to a new era of thought, philosophy, understanding, and connection.

In short to me, the only way to truly describe Big Data’s potential is taking a giant step towards technological wisdom. Out of that will sprout the next generation of entrepreneurial ventures and innovations that touch every aspect of our lives.

Here are a few interesting resources: