i love you, lucy girl

when we’d open the door to our truck, lucy would jump in and pace until i lowered the back windows. she’d dive through to make sure she knew what was up, and how crisp the air felt on her flapping jowls.

when i was out of town for any period of time, lucy would sit at the window by our front door and wait and watch… wait and watch.

when i went through a terrible breakup, and didn’t want to leave my bed, lucy sensed my sadness and curled up next to me for the night. i whispered, “i love you, lucy girl” in her ear over and over, and in return she’d nuzzle up deeper between my cheek and pillow, wetting my face with her nose and an invariable lick.

she was my lucy girl.

when i’d yawn, lucy would lunge forward towards my mouth, as if she was attempting to crawl into my throat to be as close as possible to my soul. it was one part creepy, one part adorable.

when lucy got older, she’d vocalize every emotion she felt; from us trying to unlock the door to driving in unfamiliar territory. the noises she made were straight out of a jungle.

she was our monkey.

when she’d poo, she’d find cover behind a bush and spin in circles while constantly checking if it was working. she was both bashful and had a strong case of ADHD.

she was our lu lu

when she was a puppy, she’d lie in wait for houseflies to pass over her and BAM! snatch them out of thin air, one by one until word got around back at fly central that she wasn’t to be messed with

she was my miyagi

when i would make the mistake of leaving a bag of garbage in plain sight of lucy for more than a few hours, she would win that tussle. the garbage never stood a chance.

she was my lucyfur

when i’d take her off leash, she’d run in big or small circles, depending on the space available to her. around and around and around, and just as i’d come close to her, she’d juke one way, and go the other like a running back.

she was my little freeman

lucy couldn’t catch food for anything. SMACK! right off her nose; lucy was the pickiest eater ever; never once running to her bowl to chow down; lucy would nip everyone and guard the front door with purpose; lucy would stare at the couch, look at me, and wait however long it took for me to smack it before jumping up

lucy was a shelter dog as a three month old puppy, dominated by two larger dogs in her cage. she had a hole in one ear and a deep, fresh scar over her brow when i came upon her. the moment she walked towards me i was done for. if you ever decide to enrich your life with a dog, please save one.

lucy passed today and she was my heart. she was such a good girl…

i love you, lucy girl.

coffee & pedals


i once rode from here to there
back and forth
in-between and out-foreseen

feeling the moment of time slip
is the greatest motivation to slip

feeling the moment of time slip
is the muse to dig

feeling the moment of time slip
feels like nothing else
the fabric is textured
smooth to course
of course to plot
sitting on the beach with that shot we all shot

course reflection
metaphysical resurrection

. . .

if it takes a cycle to cycle through time
to unwind on a dime
to find that water and transform it to wine
then what the fuck is the rest of time for?
to slide through space just to pop through that door?
passing hallmark milestones while somehow expecting more?

the cycle through time
is just a metaphor
to breathe in deep and hold on evermore


Patterns And Asks Left And Right, With Innovative Iterations Kinda, Sorta, Somewhat In Sight

by Ben WisemanIllustration by Ben Wiseman

I published an article on Medium last week entitled, Understanding Snowflakes, Wheels, and Innovation.

The gist of the five-minute read is pretty straight-forward: smart modern day product teams aren’t slaving through 12 hour days within a high-cost, iterative gestation process in the pursuit of a “born perfect” entry to market; they’re most likely stitching together an experience based on a saturated market’s best practice patterns (think: regenerative braking in an electric car, or access to apps for smartphones).

Only once the business deems the market viable will a deep investment in major differentiators begin.

None of that is news to product teams, but what I’m discovering in my first B2B enterprise software rodeo is that the sales variable is much more influential than I had understood when breaking into the space six months ago. From shipping expectations to requirements definition to even the definition of the interaction model itself, sales greatly influences product across the board.

This reality has me attempting to work out an equation to immediately support ever-spawning sales profit arteries while nurturing an innovative and iterative product design culture, one that will have much more impact on our end users the farther we go down the line.

A brave new world. Interesting stuff.

Design, Post-Modern

For 20 years, I’ve been pining for the industry to consider interactive design as something far more than pushed pixels, first & foremost. Looks like even industrial design is becoming a second class citizen to the experience of things.

Has Jonathan Ive Designed Himself Out Of Existence?

[…] Think of massively linked datasets on user behavior, which allow your phone to guess what you want to do, when you want to do. Think of digital assistants able to parse even the vaguest commands and parcel out all the sub tasks to the right app—”Hey, can you make a reservation at one of my favorite restaurants this Friday, and make sure that my best friends get the invite too?”

These things are invisible. We can’t hold them, and the sense in which they are “designed” will be vastly different from any piece of hardware we have today, or even any piece of software, no matter how beautiful. […] The next great design monuments won’t be easily displayed in a design museum. They’ll instead be the systems and incentives that dissolve all the messiness of our whims into that simple bit of feedback that happens when your smartphone listens to whatever convoluted thing you’re asking about, and simply says, “Okay.”

3, 2, 1… MedBridge.

surf's up

On May 5th, a Thursday, I heard back from the COO at MedBridge; my references had finally checked out, and their offer to join the team as their Product Design Manager was official. Just three days later, I found myself on a plane to Seattle and started work the very next day. To say the last month and a half has been an acclimation whirlwind would be the mother of understatements.

I’ve been somewhat of a lone wolf for the last eleven years, so it’s going to take me a while to wrap my head around what I can share that’s job specific, but I’ll figure all that out in due time. In the meantime, I’ll stick to posting a smorgasbord of product design thinking that’s been rattling around in my head.

As for MedBridge; what a great opportunity to do work that truly impacts people’s lives.

The company started five years ago with a focus on creating high quality online courses for physical therapists and a HEP platform to improve patient outcomes. Since then, they’ve invested in a production studio, and the product line has expanded to support enterprise solutions, along with continuous shifts towards the latest advancements in the field. As a bootstrapped company, we’re as agile of a business as you’ll find in our industry, which allows us to nimbly pivot to address immediate needs—whether cementing our strengths or addressing our shortcomings.

While the design challenges are deep and wide—from overhauling the existing interaction model to standardizing our patterns and visual language to impacting the next wave of products from the moment they become a directive—it’s the exact challenge that I’ve been looking for. The last time I had a similar opportunity, my team made some serious waves in the financial industry with the Apex platform.

Surf’s up.

Uber: Not Quite The Driver Friendly Business Model

uber app

In the midst of a post-job interview / project downtime stretch this past March, I decided to scratch an itch I’ve had for a while and test the overall experience of driving for Uber. I’ve always wondered about the product experience from a driver’s perspective, and hey, why not make a few bucks while finding out?

I was steeled for a lengthy process, but signing up was rather simplistic; I only had to upload images of my active insurance, registration and drivers license. As I waited to clear the Uber background check I detailed my Ford Escape, upped my mobile data plan, and within just a few days, I was on the road.

Since Uber launched a number of years back, I’ve had a rather conflicted perspective on the entire ride-sharing industry, unsure as to whether I found their disruption innovation to be of actual value to workers or an example of a tech firm taking advantage of an entire ecosystem of labor—the reality I experienced over three straight weeks of 30+ hours of driving leaned hard towards the latter.

Context Is King

Heading into this experiment, I realized there was going to be a drastic difference between driving within a saturated area such as New York City and my current home town of Greensboro, NC—from fare prices to Uber’s percentage cut to the degree of fare consistency, location makes a difference. So before I jump into my findings, let me provide some context regarding the environment I found myself navigating:

  • As a sprawling home to 270,000 people, Greensboro has a small downtown footprint—three blocks wide by six blocks long—surrounded by traditional suburbia and urban sprawl that extends out to a good number of office parks, gated communities and strip malls. It can take upwards of 30 minutes to drive from the northernmost to southernmost tip of its borders.
  • There’s one sporadically busy bus and train station downtown, and one small airport about 20 minutes away.
  • Five sprawling college campuses call Greensboro home, along with a host of technical and trade schools. The student population alone is close to 35,000.
  • Nearby major cities include High Point (20 mins), Winston-Salem (30 mins), Raleigh-Durham (1 hr) and Charlotte (1.5 hrs)
  • Sundays and Mondays are practically dead, with not many options for food or drink available after 9pm, if establishments are open at all.

Fares and Surge

As one might imagine, catching fares in such a vast physical space with limited activity can be a challenge. Aside from very particular hours of the day—from 8 to 9:30am and 5 to 6:30pm on weekdays, and from 10pm to 2am from Thursday through Saturday—consistency is severely lacking. The job becomes a crap shoot with so many neighborhoods and businesses to cover in guessing where fares will pop up, especially while competing with an unknown number of fellow Uber drivers chasing the same rabbit.

Whereas large cities have relatively consistent Surge™ zones over populated areas of both work and living activity, Greensboro drivers don’t enjoy such a luxury. The most recognizable Surge zone is found downtown, often later in the evening as people make their way home from clubs and restaurants. Every now and then a random Surge zone appears on the map, but it’s often during down times, and it seems to be literally based on a couple of fares vying for one or even zero drivers in the area. Uber markets Surge to the public as a feature designed to get more drivers on the road to service passengers with high wait times, but in reality, by the time an active driver (let alone someone at home or in a coffee shop) makes it across town to attempt to tap into an announced Surge it has already passed.

From a driver perspective in larger cities, Surge pricing is a nice-to-have in order to augment consistent fare activity in larger cities. In locations such as Greensboro, Surge is a core necessity in bringing hourly rates to even a semi-respectable level, much closer to how a waiter making $2.50 per hr relies on tips to pay the bills.

When expanding into cities with low population density, high degrees of urban sprawl and a limited adoption of technology, it’s abundantly clear to me that Uber can’t just roll out the same program.

(Not) Sharing The Load

In January, Uber reduced the passenger rate in the Piedmont-Triad area by 20%. This price point reduction was rolled out to help grow the Uber passenger base, which is an understandable approach and one that would help drivers as well. The problem is that while Uber passed such a significant savings to passengers, they didn’t supplement the loss of income for drivers, as they kept their 25% overall take of driver earnings in effect.

Essentially, drivers in non-dense, growth markets are paying for Uber to expand their market, while the company keeps raking in the profits. If I were making solid money over those three weeks, I wouldn’t care much. So how was my pay? Here’s the breakdown:

Week One: 32.18 hours driving
Fares: $487.92
Surge: $73.27
25% Uber fee: ($142.80)
Gas & carwash: ($100)
Total Income: $328.39 [$10.19 per hour]

Week Two: 30.92 hours driving
Fares: $380.25
Surge: $19.66
25% Uber fee: ($99.96)
Gas & carwash: ($100)
Total Income: $199.95 [$6.47 per hour]

Week Three: 36.12 hours driving
Fares: $530.11
Surge: $33.68
25% Uber fee: ($140.92)
Gas & carwash: ($100)
Total Income: $322.87 [$8.94 per hour]

Over the course of three weeks, working an average of 33.07 hours, I only made $8.58 per hour—not to mention the cost of taxes (10%) or the depreciation of my vehicle by putting an average of 1,000 miles per week. Unless I had zero other options to earn, why would I continue driving for Uber when in order to meet a living wage threshold in my area, I’d have to make at least $10.53 per hour?

The Longtail Of Drivers

Aside from drivers who have limited options to earn income, you have to wonder why anyone would commit to a full-time schedule picking up fares. Maybe my three weeks doesn’t accurately represent the opportunities of all drivers. Or maybe Uber didn’t design their service with full-time drivers in mind, and are shifting the focus away from their more traditional employees.

Uber portrays their archetypical driver in the following commercial:

The service is framed as beneficial to each person’s life based on the flexibility that Uber provides; not based on the amount they can make while driving. Uber has tapped into a workforce version of what Chris Anderson coined The Long Tail well over a decade ago.

In an online retail environment, The Long Tail represents product that might never see the light of day on a brick & mortar shelf. Think Amazon, and the millions of books available to you, regardless of the size of the print run. The web makes such product availability possible, as the concept of physical shelves is replaced by a singular coded product template that represents each and every book in stock.

Most importantly, when you stack the long tail on end, overall sales will equal or surpass the big ticket items; the “popular” head of the tail. While such a definition doesn’t match the actual results of part-time vs. full-time Uber driver productivity, it doesn’t need to, as new long-tail drivers are constantly replacing the attrition of fellow moonlighters.

Uber’s business model is steeped in the surface notion that the tail is what matters; that people moonlight with Uber to make ends meet, so the traditional definition of an “employee”—and every labor expectation that comes with it—shouldn’t apply. And with the constant turnover that occurs in the < 10 hours per week driver class, Uber benefits by having a turnstile of new drivers willing to forgo basic labor rights, such as a minimum wage or benefits. This becomes the overarching approach to classifying Uber drivers, as they redirect attention to the moonlighters while full-time drivers aren’t treated any differently.

Noah Zatz makes a similar point in his post at OnLabor:

[…] the much-touted majority of Uber drivers working very few hours per week are performing far less than the majority of the work. And the seemingly marginal group of full-time drivers actually are doing about half the work, far more than those driving the fewest hours. The precise numbers are sensitive to how one subdivides the drivers (using 1-10, 11-29, 30-44, and 45+ hours per week might look worse for Uber) and to the distribution within each bracket, but the basic point is robust.

Uber has created a worker ecosystem that “benefits” those who need to occasionally earn and doesn’t reward those who invest the most amount of time catching fares.

Driver Improvements

There are a few interaction model changes that would positively impact the ability for drivers to make more money:

  1. Expose predictive patterns – I’m not sure what percentage of riders use Uber in the same way either daily or weekly, but expose pick-up patterns to allow drivers to cruise areas well prior to Surge zones being presented. It may not matter in a huge city, but it would make a difference across all of the mid-sized cities in play.
  2. Allow for tipping – Lyft already has tipping in play. I can’t tell you how many of my riders wanted to hook me up but didn’t have cash on hand. Uber, if you’re not going to reduce your 25% take, then make it easier for drivers to make a living—it’s only right.

At the end of the day, Uber is creating a brand off the backs of gig workers. It’s not a sustainable employment model, and at some point the pool of desperate drivers is going to limit the possibility of future growth. Time will tell how long the novelty lasts.