Building a World Class Data Science Team

I have built data science and data research teams throughout the world since 2007.  I haven't always quite used that phrase, but in truth, the phrase data science simply didn't circulate much during those years.  Now as I am approaching a year of building a data science firm in Pittsburgh,  I am fortunate to find myself entrenched in a pool of top talent from elite universities and impressive industry backgrounds.  I've found that my experience doing this in war zones and refugee camps has given us an advantage regarding the role of human factors in data science, both internally and externally. My team is incredible and that is not an accident.

The Demand for Data Scientists

Data scientist is the number one professional in demand right now.  Recognized as America's coolest and among the best paying jobs, demand is expected to increase for many years ahead.  While this is great news for someone like myself who has worked in data science for over a decade, it nonetheless creates challenges for recruitment.  Most firms hire engineers, mathematicians, and physicists with good communication skills.  This makes sense, these are people with advanced quantitative skills who can do the data analysis - yet analysis skills alone are insufficient to maximize the value of such a team. 

Minds over Skills

My approach to hiring a data scientist is to go far beyond finding someone who can do the analysis. I specifically seek out people with interdisciplinary backgrounds and non-linear life histories. I seek out people who have degrees and educations in multiple fields but have synthesized this work with core data science specializations such as network analysis or natural language processing.  Hiring such persons his not easy - they are hard to find - but the difference is profound.  A great data scientist probably has more in common with a backpacker in foreign lands - continually probing at the social fabric, interpreting and learning about the complexities that support the data - than a lab researcher looking at a computer screen. 

The work of a data scientist is rarely as simple as doing math.  Companies rarely have their data easily accessible and compartmentalized. They rarely know what "insights" are the most important. The largest clients - typically the oldest - are sprawling with chaos and legacy systems, given the natural byproduct of employee churn and the constant injection of new ideas. Consequently, great data scientists the ability to seek out information within an organization, understand how that information flows and gets utilized, and then construct meaningful concepts about how data fits into the lives of the people doing the work. They understand that data is an abstraction and not every problem should be solved as a data problem.

Just last week, I met a man who worked as an auto mechanic for 15 years before going back to school to study computation and information systems. When I met him and heard his story, I was immediately interested, wanting to learn more about how he would approach a given problem.  He is a natural systems thinker, with a detective mindset, and the skills to do the work. Given my personal background in urban planning, I tend to default to geographic and spatial thinking, so I'm always curious to learn how others will approach the same problem in different ways.

Impact over Input

On my current team, I've hired and interviewed data scientists trained in political sciences, sociology, journalism, neuroscience, and mechanical engineering.  They are all skilled in programming languages and are adept technologists.  But they aren't merely "quants" and are instead, persons who can work with information simultaneously quantitative and qualitative.   They can make sense of the day-to-day chaos of complex organizations and social groups. They are comfortable talking about any subject and are great story tellers.  They also work well with other technical members of our team to translate their work into meaningful products through design and engineering.  The ability to do the math is top-notch - but that is not what defines the best data scientists.  It just happens to be the common thread among an expert team of problem solvers.

How to Reinvent the Electric Guitar via Design Research

Design Research inspired by Washington Post Coverage on Death of the Guitar Industry by Geoff Edgers, June 22 2017

Summary: The live music industry is a $40 Billion dollar market and recorded music is a $25 Billion dollar market, yet guitar sales are plummeting and guitar manufacturers are going out of business. If guitar companies are not selling guitars, it is not from lack of interest or vision, it is because these markets are changing faster than the manufacturers can adjust.  Design Research can generate an evidence based design strategy that is fast, flexible, and affordable to transform companies and drive new revenue streams. Design research drives corporate success with profits typically 220% ahead of competitors,  with 125% to 225% return on investment with 20% to 40% sales growth [1,2,3,4,5].  It can do all this and more for the guitar industry.

Improvisational Sitar, with drums, piano and violin added in production. Recorded on an iPhone and produced w/ Logic, in my living room in 2014, Pittsburgh PA

Intro
Most people know me as a designer and as a researcher.  Sure, I've used design to revive economies and shape the future role robotics in the world, but I am also a musician.  I have played the guitar and other stringed instruments for 25 years.  For the first 10 years of that journey, I was very serious. I have had multiple teachers (my favorite), taught multiple students, and studied a variety of styles from Yngwie-inspired 80s shred to finger plucked jazz and folk (a lot of Paul Simon).  I aggressively studied scales, modes, exotic chord constructions, and branched into Indian music theory in my early 20s, when I spent several months studying sitar in Varanassi.  Overall,  I can mostly anything on the guitar, but I don't talk about it or spend money on it, because it has nothing to do with the music I enjoy. I perceive the guitar as the instrument of my father's generation. As an instrument and as an industry, it is a constant point of frustration - primarily because I love it so much, that I expect more.

Several months ago I read a fantastic article on the death of the electric guitar.  I didn't realize that my boredom with the guitar reflects a broader trend. Guitar sales are dropping by 500,000 units a year.  Guitar companies are going bankrupt.  Baby boomers are shrinking in population and millennials don't care about the instrument (yep, my brother even makes fun of me for it).  Various theories abound on the cause of this - such as the lack of "guitar heroes" today. Guitar companies keep rolling out novel innovations or new product lines but haven't been able to succeed against the trend. I have my own personal bias, but as a design strategist, I wanted to probe deeper. I wanted to uncover problems and options.

So just for fun, I did some preliminary design research. I'm not going to provide all the insights or solutions here. Understanding the problem is not equal to understanding the solution. To understand the solution demands an additional layer of design research and exploratory prototyping. Yet from my cursory probing, below are some clear findings on the problem - it is not a hard one - and the most obvious opportunities.  Gibson and Fender are common examples in this blog because they are big and well known, but I looked at several companies and many shared similar problems. Ibanez, Yamaha, Schecter, Parker, and Peavey are not too different.


Kicking Off
I first reached out to some execs of various guitar companies to see if they were interested in getting some free insight from an established professional and the responses where hilarious.  My favorite response is below - this guy was a VP at Gibson. Obviously it does not take much to study corporate execution, the evidence is generated everyday by the outward choices in product design and deployment and marketing. Fnancial analysts do this all the time. Lesson one guys - please realize the industry is not a magical secret thing. If anything, deeply held beliefs like the one espoused mean you are becoming a prime target for disruption.

Situating People and Products
Every person approaches a problem with a deeply rooted perspective informed by previous experiences. If you work in digital marketing for 10 years and are asked by Fender to increase sales, most of your suggestions will be digital marketing solutions. If you are an architect, will will likewise have much to say about the design of the sales floor.   To understand these companies is to understand their teams. Notably I found no designers, no expertise in human centered design, and no expertise in user research. Sure, there were product strategists, but that is only sometimes aligned with expertise in methods and iterative execution.

I read deeply about what the various companies are doing, then used Linkedin to assess who they have hired, and where those teams are located. I made a spreadsheet of persons, expertise, and  I pulled up as much information as possible relations between persons, teams, and products on market. I assembled rough categories of product strategy for by location and expertise.  If and when there were gaps, I simply assigned unknown team members by location and then tracked the type of products to those locations. Within a few days, I could quickly see what kind of bias was informing new product lines.

For example, Gibson is trying to become an audio lifestyle brand similar to Beats. This idea is entirely rooted in situated expertise injected by outside individuals brought into the Gibson family.  Assumably these individuals held success in another aspect of the audio industry and this success was the basis to hire them. Yet success in another market is not necessarily the right metric to revive a brand. It merely informs the brand or pulls it into another direction. The new direction is possibly relevant but perhaps it is also arbitrary. The consequences of Gibson's action are reflected in the bizarre execution of their pro-audio offerings.

Gibson speakers do not fit the vision.

Pro-audio Example:  Maybe I'm on the market for some speakers. If I am going to spend a grand on speakers, then I must believe that these speakers are the solution between my current state as a musician and my ideal state as a musician.  Part of that ideal state is bound within the conditions of my music production - such as installation in a home studio, a reserved desk space, or a mobile backpack set up. I need speakers that not only sound good, but they solve my core problem (hearing music), and align to other goals (fit my home, lifestyle, etc). Also, what will I do with them? Cut a top 40 album or painstakingly craft youtube videos of my cat?

Gibson Solution: Expensive audio monitors with flamed maple facades (like Gibson guitars) that reference the heritage of the brand. Back-side supplies various EQ controls and ports for power and audio cables. Great design stationary use in a dedicated space. Although the maple finish is novel, it is also rather abrasive.  The speaker is entirely self referential. It is a beacon of great sound and a strong brand.

West Elm is Aspirational

A Design Approach: Notably, as a consumer, I don't start the journey with the speaker as the point of reference - I make the purchase with the user's life and life goals as the point of reference.  The speakers need to somehow bridge the user's current life and his vision of a future life.  They need to solve a problem beyond great sound because lots of products sound good. So as a design researcher, I'd first build personas of those whom will buy these speakers. I'd build a persona to capture what is that person like. What are her values? Where does he shop? What else does he buy? What technologies are part of that person's life? How do speakers fit in the ecosystem of the person?

If the goal is to sell speakers to Millennials who have excess money - what do those people want? Do they even want pro-audio monitors? What do they spend that money on today? We know that urbanization is on an upswing, as are sales with Amazon, Apple products, Whole Foods, craft beer and good coffee.  What are the design aesthetics for such persons...probably something more like West Elm than Furniture Fair. Do these people have dedicated studios in their homes? Probably not. Will they use the speakers for more than recording - like listening to albums or streaming music from their iPhones? Definitely.

A Classic UX Persona

So as a 30-something who can afford to drink good coffee and might even care about audio quality, why purchase a bright cherry-burst, high-gloss speaker with weird mismatched attributes (the white and black is jarring)? Where would it go in the house? With a massive burden of student loans, how do I justify the cost to a spouse? I surely can't build a sound proof room in the basement. These are going in the living room or bedroom and will be multi-use.

If I want my my living room to look like West Elm (because that is a future tense of my values in daily living), then where does this speaker from Gibson fit?  Nowhere.  Furthermore, each speaker (as a pro audio monitor) requires a power cord, and a big long cable to fuse with a central console -usually a mixer. Why would I want to clutter my house with a bunch of gear and cords? I'm a serious musician and I don't want any of that. I'd rather go without it - and do.  I usually play an acoustic guitar. Done.

Takeaway: The speaker line says more about the teams that pushed the product than accessing a new customer base. These speakers are a great way to represent Gibson - the team clearly understands Gibson - but Gibson is not the current or desired customer.  The current customers (baby boomers) might buy these speakers, but the market is flush with similar options, so competition is stiff and the product offers nothing new except an ugly finish. It will be hard to disrupt current sales patterns. If Gibson wants generations M and Z to get onboard, then its time they reconfigure their teams to absorb knowledge, not diffuse it.


Rapid User Feedback Review via Social Media
To rapidly understand how current guitar players perceive current guitar offerings, I dug into the comment sections of Facebook, Youtube, and Twitter.  This was simple. Go to the Gibson facebook page, spreadsheet the types of information generated by Gibson (such as showcasing a $17,000 custom instrument) and list user comments ("I would never spend that much money on a guitar").  With some basic webscraping via Python (Beautiful Soup), there is enough data to rapidly build a massive spreadsheet comparing company message to user response en masse. There are also comments on the Gibson website and various chat groups online. The data pool is massive.

Some Key Findings:

Cost/Benefit. Millennials want more minimal instruments with higher quality construction (Explains why Martin and PRS are doing doing okay).

They need to design for experience over time. Sustainable design is about far more than recycled materials, as guitar companies need to think about how these instruments age.   Stop resurrecting classics (reissue lines) and manufacture instruments right now that will become classics. If the pick guard is going to fall off, can it do so in a way that is appealing?  For example, what if a beautiful engraving was was revealed only as the pick guard wore away?  What if the paint wears off to reveal another mindful layer of contrasting paint, show that the age of the instrument is an earned value? Design for returns on value over time.

Service integration. If I buy a Lexus, I get free oil changes from the dealer. If I buy an Apple, I get 1 year of Apple Care to take care of all my problems with no questions asked. So why is it so hard to get my $3,000 dollar guitar fixed, adjusted, cleaned, or tuned?  If I buy a guitar, I should also have an agreement that they support my ownership of this instrument and make it easy. My guitar should be evidence of a relationship not a meaningless object.

Interaction Matters.  Look at the comments below. There are thousands of comments on each guitar companies facebook page. Yet most of these companies don't interact with people. When Asaf complains that his pickguard peeled off, why isn't Gibson stating "sorry man, lets send you another pickguard!" or at least "Asaf, we hear you, and hope you will be interested in our new 2018 line."

Sample Comments from Gibson Facebook Page. Lively dialogues w no engagement from company.

Company Website Analysis

Lack of Care for Digital Experiences
I looked at the websites of companies like Martin, Gibson, PRS, Fender etc.  Most of these website are terribly designed.  The Washington Post article about the death of the guitar was better designed than the guitar company sites. Yet this is the cheapest thing a company can do to elicit massive returns. Lack of digital presentation tells me that they barely care about getting new customers who perhaps do not want to sit in Guitar Center.  This is a huge missed opportunity because the best way to secure a sale is to ensure the transaction seamless. A guitar should be easy to find, easy to assess, and easy to buy. Three steps.  Several of these sites are also not configured for mobile.  Please, fellas, start using BootStrap so I can look at your stuff while riding the metro.

Lack of Concise Categories
Gibson had 84 guitars for its 2017 line.  Plus hardware and paint options. So they are manufacturing at least 150 different kinds of guitars in 2017, alongside pro audio speakers, cases, and more....Seriously?  I've been playing for 25 years and can name maybe 5 Gibson models. So really, there should be a maximum of maybe 18-20 instruments on market for 2017.  Maybe less... 10 is a good number. 10 Guitars (5 models, each with a high cost and a low cost version) with some customization options, meaning that production is a total of about 35 guitar models. Otherwise there is no way they can produce superior quality instruments on par with demand and not overshoot. The more they need to worry about warehousing and inventory the more they are just throwing money away. Also how is my guitar going to accrue value overtime if the market is saturated with every model possible? They could learn a thing or too from Zara.

Lack of Product Integration
Digital emulator amps are amazing. They don't sound as profoundly angelic as an all tube amp, but it by all other criteria it the best amp on the market. They can directly connect to a Mac for recording by USB.  They connect via bluetooth to listen to my music from a phone.  With 100 stock programs and full ability to tweak it all via a simple phone app - they have all the options needed. They even get software upgrades. Win.

So if Fender can make an amp like this (Mustang GT series) why hasn't Fender made their guitars accordingly? The amp has changed but the guitar has not. The amp and the guitar lines reflect different teams not a coherent vision for products. Fender clearly does not have a "Chief Design Officer" to unify the execution of verticals into a meaningful coherent vision.  So in the meanwhile, I still need a stupid guitar cord and my guitar is identical to something my grandfather bought in 1965. I use midi heavily, as do my music heroes, yet all the midi guitars on the market look like a child's toy. Lastly, thanks to new software solutions, there is less demand for my guitar to be made of expensive tone woods and weigh a thousand pounds.  My amp is lighter so why is my guitar  so heavy?  There is no symmetry.

First, there should be no more guitar cords. Also, guitars have knobs - this is great because, no touch screen is as good as a knob for manipulation - but right now all these knobs do is modify pickups. What if these knobs could do more? They could work as midi controllers, or could build custom relationships between pickups, piezos, and midi.  Better yet, what if the pickups could actually change the pickup as a source - shift it from sounding like a '57 LP to an 80s Dimarzio or a big fat SRV Texas-style single coil on the fly? That would be something... emulation guitars would be more powerful and interesting as the emulator amps.  They would offer a value symmetrical to the value of Ableton or Logic.

Notably, the solution to the guitar is not to simply "make it more high tech." Technology is not the answer (proven by Gibson's waste of $40 million dollars on automated tuning). Rather, the answer is found within mindful technology advancements to ensure the instruments are consistent with a robust vision for music production in the 21st century.  Either make the instrument raw and pure in wood and steel or make it fluid and elastic.

Lack of Product Service Systems
So I buy a guitar from a website... then what?  How do I get it set up, repaired, or modified?  Why do I need to rely on ad hoc service providers who have questionable degrees of recognition?  In the meanwhile, if I buy an item on Amazon, and there is a problem, I just print a label and take it to UPS. Done.

Bigger picture: If I buy a single Les Paul for 2,000 dollars, can't I just download and upgrade my Les Paul with new models over the years? Why not? After all, I buy a razor and pay a premium for razor blades to renew the value of my razor. I buy a laptop and extend its use via digital downloads of new operating systems. In the meanwhile my guitar is just a constant pain in the ass. It just sits there.  Simple wood and steel is sexy as hell... I love my Martin... but if I'm going beyond that, then I want something that can also evolve over the time of my musical journey.

Lack of Imagination

Dear Yamaha, I do not live in 1962, nor do my music heroes.

Tech companies are working hard on generating meaningful AR experiences. In the meanwhile, every guitar company is showing equipment that reflects bizarre remixes of the past.  Does any young musician alive today want to emulate rock guitar history? No. So please reconsider how your marketing connects with your product design. Better yet, stop marketing and be something pure and honest - show me a vision for the world to come and your role in it. Make me a believer.  Where is your AR version of Guitar Hero for real musicians?  I would love to rock out with Hendrix or Alice in Chains in my living room. What if I could swap beats for Jay-Z and we could perform  it live via AR?


Informal Sector Analysis
So how are people modifying their guitars today?  How are people solving the problems the big companies don't even see? What are they trying to accomplish.? This was by far the best part of the design research.  People are generating tons of different experiments and building products on Kickstarter with little money.  Youtube is full of DIY mods.

Now guitars are lighter, more durable (carbon graphite), and more flexible with deep midi integration.  Many additional accessories are to integrate phones and HD cameras.  The innovations matter less than the underlying use cases.

People clearly are using guitars as an interface into a computer and in relation to other media than sound.  I love the fact that my fender amp allows me to import amp/effect settings created by others - I only wish such an effect could be easily shared P2P with a friend (or bandmate perhaps) rather than an entire community. The current design reflects boardroom strategy not field research.

It is also clear from informal sector analysis that no one is going to buy the Cadellic of instruments or amps everyday.  Our music heroes are people who write music - I love Kanye's production - not guitar solos (snooze).  My instrument and any other stuff should help me write more compelling and forward thinking music. Software can help more than hardware because its cheaper, faster, and more adaptable.

Deep User Interviews for Validation
To validate the broad spectrum research, I also sought out guitarists and did deep interviews about what they play, how they play, and where they play. I found some people on the border between GenX and Millenial generations who are passionate about their guitars.  They all used to have big MesaBoogie Amps.  Now they also have small emulators. Some have bands. Everyone has Ableton.  One guy just had an emulator foot controller - no speakers at all - and is an active musician who plays bars on the weekends. 

I found lots of musicians but no other hard focussed guitar players except a 12 year old in Pennsylvania with a love for the 90s metal band Pantera.  This kid fits the current guitar consumer profile, except he doesn't have any money and is a poor market target.  The guy with the foot pedal who plays bars recently dropped about 5k on equipment, including a new PRS guitar.  Obviously he is the better option. He also had a lot to say...  maybe its time the guitar companies start to listen.

Is AI/Robotics the Next Humanitarian Crisis?

I am not afraid of technology.  To make technology is to be human. Technology and humanity are inseparable. My concern rests on the agility of our leading global institutions to engage technology in a manner that does not understand other forms of human organization. Technology is human, but it is not innately social. 

Nearly everyday an apocalyptic statement graces the headlines, announcing the threat of robotics to the global economy and patterns of day-to-day living. Supposedly by 2025, one of every three people will lose his job and become replaced by a robot. Five years later, in 2029, robots will have intelligence equal to humans. Artificial intelligence is the “biggest existential threat” to humanity.

These pronouncements do more to demonstrate a poor comprehension of the technologies and a complete disregard for economic history. Thousands of years of evidence highlight technological change is a healthy thing for labor markets. The counter argument is that emerging developments in robotics concerning automation, computer vision, data analysis, and machine learning are giving rise to a new kind of technology that is different from previous developments concerning hardware or information processing. 

The debate on the integration of computation and human society is as old as computation itself, and contemporary arguments remain rooted in the 20th-century invention of cybernetics, an experimental epistemology concerning the effective organization and communication of integrated social and environmental systems. Norbert Wiener’s theories on systems feed back and interactions with technology were situated within concerns of human ecology and governance. Weiner also projected the eventual creation of the machine a’ governor, a robot government designed to solve any problems to emerge within the government-human economy. In consequence, humans would be free to spend time at leisure while the machines replicated themselves, taught themselves, and effectively solved all possible problems for humans. All hail the machine.

According to roboticist Illah Nourbakhsh, in his book Robot Ethics, the critical difference is that while the developments of the 20th century provided the ability to simultaneously engage and manage multiple streams of information, but the advancement of robotics provides the capability to now distribute multiple forms of action. More significantly, the ability for robots to network, sense, choose, and automate with other robots will eventually lead to strange unpredictable configurations of technology that will blur currently held conceptions of social identity and accountability. To render this probability in the context of advanced capitalism, established modes of socio-economic production are at risk of obsolesce. It will be necessary to invent new modes of value production in society or human beings will be useless.

Wiener’s visions were not unique but predicated John Maynard Keynes' Economic Possibilities for our Grandchildren. Economist John Maynard Keynes predicted a technologically advanced future relegating the necessity of human labor to a mere 15 hours a week. There was some plausibility to Keynes' vision, as more efficiency in labor does not replace the need for human labor, but rather elevates the value of human labor relative to the demand for production. Of course, if there is a change in demand, and production is not sufficiently responsive to that change, then human labor is devalued. In the case of robotics, it is imaginable that vast networks of robots producing goods in relation to the algorithmic demands of big data would be more responsive to market changes than humans. Already this is evidenced by the application of algorithmic trading in stock markets. Humans can’t compete with networked, data driven, robots on mere market efficiency. The need for human supplied labor is replaced. The externalities are severe. 

Lost human jobs equates to a reduced tax base, reduced social services, lower quality education, reduced social capital, deteriorating communities, crumbling infrastructure, and stunted generational access to social and personal mobility alongside increased depression and substance abuse. To let this possible future, arise anywhere in the world is unconscionable. Surely this can’t happen of course because humans are capable and responsive. New markets can be created. 

Keyne’s argued that the remedy to competition with technology relies on the ability for humans to acquire the sufficient skills to make use of the technology. Keyne’s highlighted this problem as a “temporary maladjustment:, which might require several years for a labor force to catch up to the technology”. But what if the pace of technological advancement is faster than the ability for humans to learn? To close the gap is an ineffective a pointless conquest. In some places – existing urban concentrations of wealth and opportunity like New York City, San Francisco, Tokyo, or Istanbul – this will be true and educated people who inherited rich social assets will make use of the technology. But no one else will ever have a chance to compete.

Clearly, there is a bigger concern that does not emerge in these conversations on robotic futures: Is a world in which day-to-day livelihoods remain under constant threat of technology a desirable world? As the systems of production, exchange, and valuation that drive the technology are the choices and actions of humans, why then could the long term future of the world be one outside of our own choosing? Obviously, systems magnify behaviors, and complex adaptive social systems are virulent landscapes to contain. The complementary mechanisms and conditions of the global economy, such as systems of governance and human security, have struggled to keep pace with socio-economic demand and it is clear that this trend will only get worse.

There have been tremendous strides in the global economy in the last 100 years. International institutions have been founded to advance regulatory measures for human interests. Less people have died of illness or war. More people in the world have accessed education and social mobility than any century in human history. I am confident in those strides and those institutions. My concern rests on the agility of those institutions to engage a technological threat. The problem of Keyne’s “temporary maladjustment” continues to repeat itself ad infinitum, and when the world places blind faith in the advancement of technology, the learning curve becomes painfully steep.

The international humanitarian and human rights regimes are not contemplating this future impact of robotics. Grass roots organizations and urban planning departments are busy replicating the status quo. In the meanwhile, cybernetics hasn’t died in the minds of military engineers and industrial capitalists remain quick to take advantage of grand visions of a perfectly automated society. We are sold conveniences but in exchange purchase longterm economic servitude.  There is a demand for another approach, other ways for thinking and acting are essential to guide the advancement of human living. Buried beneath the layers of ideology and intent, our globally distributed modes of production and exchange all contain a shared thread and this thread elicits a new possibility for design.

Design Comes First for High Tech Entrepreneurs: Quantum Computing, Robotics, Artificial Intelligence, BioComputing, Machine Learning

While the design is increasingly central to the operations of established technology companies, it remains overlooked within research teams pursuing initial research of those same technologies. This is due to the lack of understanding held by high tech entrepreneurs about the role of design. They think it is decoration - when in truth - it is the fundamental process to transform abstract ideas into new realities. Design is the cornerstone to successful entrepreneurship.

In the last few weeks, I have had conversations with dozens of high tech startups that have one foot in the lab and one foot on the path to a new market. Interplanetary robotics, quantum computing, and super intelligent machines are exciting new domains described at length in business and technology magazines alike, yet these ventures struggle to overcome the leap from research in unstructured domains to generating meaningful human-product experiences and viable companies. They struggle to think and work like designers.

How Design Serves Advanced Technology Companies

Computers are everywhere. As more of our lives are inundated with computers - cars, planes, banks, security, government - the software on those computers is getting very sophisticated and difficult to test. It is also difficult to build to ensure that it is testable. Think of the complexity to manage all air flights in a country, the testing of that software is critical to everyone's safety - but with so many airplanes, airports, satellites and so on - how do you test it?

In my engagement with machine learning companies throughout Silicon Valley and Pittsburgh, I found one that has solved this problem. They build tools to help other big companies build reliable software for complex systems.  They can even predict if your company is going to create a bug before it happens. It is incredible.

The company does amazing work and is profitable. Yet they have a terrible website. They know it. Their tools do not really have a user interface that users enjoy using or easily understand. Their software is very advanced and difficult to communicate.  It is challenging to hire for this company. They see every market as possible and yet are not sure how to access them. Their work is in such high demand they are doing well... but will this always be the case?  What are the limits of their current market? How do they know?

Upon offering to help with the website, I've since had multiple conversations with the founder of this company. I understand the technical details of their software. As a researcher, I am equipped to study and understand the problems they face. I also am a designer so I am able to communicate it to people who do not understand.  Consequently, as a designer, I also have methods to rapidly TEST & LEARN from the range of possible consumers on how to tailor the language, the product, and the transaction. We do not, consequently, have to worry about marketing or even business development. With design, we can KNOW and VALIDATE our language, our image, our transaction, and our team to transform machine learning into highly needed customer solutions. With Design, we can better engineer success, not just software.

This is Different than The Current Business Models and Operations

At each startup, the conversation unfolds the same way every time.  I ask about the product and the CEO demonstrates or describes the product. I ask about the business and they display a prepared document or slide deck on the business strategy and organizational shape.  I ask about financing and they tell me about early mistakes made impacting future financing for the negative. I ask about the distinction between the market they set out to pursue vs the market opportunity they have discovered - and they start to get depressed.  I ask about new market or growth opportunities, and they say "we hope to figure that out soon... " and perhaps "if only we could hire the right person for business development."

Hire the right person for business development?

Certainly, the most important aspect of building a company is the team. Yet to assume that the success of the business - to align internal operations to market demand - is the job of a solo individual is misguided.  MBA programs tout the ability to transform graduates into such beings - and there are many times this person can hold an instrumental role - but for highly sophisticated technologies, there is no evidence that a traditional business approach will always work.  To make the assumption is high risk.

In addition, when I ask "do you have a designer?" - the CEO confuses my question, thinking I asked: "Do you have someone to make this pretty?"  They say no or "that is important, but we aren't there yet" or "we know it needs to be attractive so we outsource that, we have someone make it look good." The worst ones point to their current success and say "we don't need a designer, we are doing just fine" and months later are panicking because they had all along been meeting the needs of only one or two clients and could not actually scale their business. By their definition, to have a designer on the team is expensive and the person would sit around most the time with nothing to do. If they learn their lesson - it is often too late.

Design Driven Business is an Optimized Transaction

Every company requires some basic components - they need the product, they need an efficient way to generate the product, they need a clear path to connect to the consumers for the product, they need a very simple mechanism to exchange the product for capital, and they need the ability to do this over and over again.  If this process is well tuned, the capital acquired will outweigh the capital exhausted and the company can flourish.

Nothing in this product demands marketing, or branding, or financial planning. There is no need to hire agile coaches or communications consultants. I also mentioned nothing about aesthetic design. These things - these tasks - are simply tools to help solve the core problem: the material transaction. The material transaction is made possible by the optimized movement of information. It is possible to invest in these things to make that transaction happen, but within an unknown market for an untested product, operating on the thresholds of possibility... it is difficult to measure the effectiveness of these tools. Marketing language, targetted advertising, and agile product development are all just attempts to optimize the movement of information. Yet with advanced technologies, early wins are just as likely events of luck. There is no way to know.

Design is the Process to Optimize Transactions

Designers are specialized in the art of communication. This communication may take place through graphic text, plastic form, or even through the process of a work itself (this is where the post-its come into use). Optimized communication within a team will increase efficiency, to transform a team from thinkers to doers but with less technical debt.  Optimized communication to external consumers will get the two groups together faster for the transaction to take place.

Optimized design of the transaction itself - a form of communication - will result in high satisfaction for everyone.  If transactions are fast and positive, and communication from the buyer can connect to the team (who internally is optimized to leverage it by communicating), the transaction will take place again.

You can call this stuff strategy, marketing, team building, communications, - whatever you want. But to get from lab to market - you are better off to optimize your business by starting with Design.

The Demand for Fuzzy Science and Explicit Design: Rationalism is Not Universal

Whenever I explain Design to non-designers, I essentially describe the scientific method - observe, hypothesize, test, repeat. Many designers work this way, although they might think creativity is something more magical, and are less inclined to describe their work as sequenced trial and error via prototyping.  Also, let's face it, clients will pay for magic but not for experimentation. The differences between science and design are more cultural than procedural. Science is better tuned to the needs of validation and design facilitates more generative insight, but the largest difference is that the scientific method is often stuck in the culture of science - we tend to think of the scientific method within fields like biology or physics, and thus resort to reasoning and intuition for day-to-day matters. Thus we think we use the scientific method all the time, but actually, we rely mostly on the power to reason.  

At the Thresholds of Reason

Unfortunately, human reasoning is not universal. Rather, it is situated in disciplines, as each discipline enforces a particular kind of language and patterns of cognition. The lawyer does not interpret the world the same way as the doctor or the engineer. Yet if forced to work together on a worldly problem, they will each insist on using reason (common sense) to engage problems of magnitude. Yet as each person in the room is attuned to a different way to frame and engage a given problem, it seems that direct experimentation would be more valuable. So why the fear to experiment for results? 

There is a widespread predisposition to assign the scientific method to the profession of science, wherein science is only for science-y things, and likewise,  we assign design methods to the design professions like architecture. Why is the method of science only reserved for biology but not for daily action? By extension, we are prone to work through other disciplinary problems in discipline-centric methods- and those methods are all the same, but get diluted by disciplinary language and habit - so why don't we step outside of our discipline with our methods? Most MBAs for example, never do scientific experimentation, although it is the premise of all worldly knowledge. They might embrace a design workshop (as business has to embrace superficial elements of design), which is a good way to synthesize ideas and create opportunities, but it also is a high-risk endeavor because it lacks any direct role for validation - it is a synthesis of assumptions. In contrast to generating learning opportunities, we rely upon the idea of the "expert" who has knowledge based on previous experience and we expect that knowledge to cross over. 

In contrast, we resort to rationalism and rationalism relies heavily upon our subjective interpretation of previous experiences - and our memories are not the best way to record the world because memory is highly subjective. Design is an approach to understanding the world through observation and experimentation, yet it also considers and takes advantage of personal subjectivity, cultural patterns, and the emergent outcomes of group interaction.  It does not merely accept the implicit assumptions and detriments of subjective memory. Design attempts to leverage those things actively avoided within Science. We could all probably use more science in our lives.

Dangers of Expertise
Dropping expertise within approaching a problem is important because expertise is really the opposite of science and design.  Expertise makes the assumption that experimentation is no longer necessary because the expert has all the necessary information already or can quickly filter available information.  Experts supposedly already did all the hard work to understand a particular worldly pattern. Expertise can be reasonable - in any given problem, we all find a point in which additional experimentation is redundant, and an outlier result will have little statistical significance. Yet what happens when we combine this statistical argument with the psychology of a group? In this context, the value of expertise is diminished because of a necessity to all reach a common understanding. Without a process of experimentation, people will talk about things they understand as individuals with poor translation to others. They will impose known patterns upon new problems. They will fail to experiment.

Patterns of Cognition: Habits
Later, studying robotics at Carnegie Mellon University, this way of thinking was entirely beneficial to advance the state of human robot interaction.  How do you build stronger human relationships with technology? It takes more than mere manipulation of pixels or a human factors design assessment. Yet when I was a graduate student in economics and law, this way of thinking was not helpful.  In fact, economics never touches the same time of reasoning. Economists are looking regularly at the circulation and balance of inputs and outputs - a far more linear and sequential type of thinking. Law likewise was a headache to study, as legal reasoning relies more upon the accounting of evidence to identify conflicts of logic. The reasoning of pattern relations - whatever they teach in art school - has far less to do with sequencing or logic. These different paths to engage and interpret the world establish radically different understandings of a given problem.

The notion of "patterns of reason for knowledge construction" is perhaps a critical element in how we all approach problems. When I was an art student at the Art Academy of Cincinnati, I developed a way to see and understand the world that was not explicitly rational or empirical. It was more akin to pattern recognition at large, the ability to identify and symmetries/asymmetries amid abstract collections of information.  Studying historical and contemporary art, I became attuned to the relationship between cognition and body mechanics and to the relationship between physical materials and economic production. I learned to look at the associative relationship between materials and ideas.  For example, I recall seeing a photo with a dogwood tree, and by association bring up a legend about how the dogwood tree is cursed by God to grow crooked. This story implies personal meaning, and thus as an artist, I am inclined to use the tree to indirectly communicate something about religion. Compared to basic arithmetic, this way of thinking makes no sense, and yet, moving through the world by association is an important part of the human experience. 

Scientists attempt to identify and negate their values, yet there is sufficient evidence that all science is situated in the subjectivity of the scientist.  Many scientists accept this.  Good designers also take stronger responsibility for their own values and situated knowledge. Yet both can also discover other paths of inquiry and reason.  In the end, the only ones who fail to adapt to new problems are those who rely explicitly on their own situated reason.  The world is too complex for experts.