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Not all tech companies are startups.

We tend to equate them with tech companies, but fundamentally startups are businesses designed to grow quickly. To echo an oft-repeated truism: startup = growth.

Then why the free association between startups and tech? Over the past decade, the easiest way to grow quickly has been to acquire online users. The transitive equation has been: startup = growth = online users = tech.

In fact, we wrongfully equate startups with the tech industry. Startups are high-growth companies with large market potential. Tech reflects society's adaptation towards software automation tools, and spans culture, management, and technology.

Online experience is fundamentally fragmented.

We managed broad areas of our life across different platforms, all of which have incentives to keep fencing us off from each other. As collateral damage, we seem to have become inured to poor experience in important areas on the web:

  • task management.
  • writing.

“One community at a time”

That smaller cultural changes must accompany delivery system innovation is a truth already starting to take root among the largest institutions in health care. “All health care reform is local,” is a common saying among health care experts, and one of the key tenets in the mission statement for the Center for Medicare and Medicaid Innovation. In a speech on health system improvement given in early May, Kathleen Sebelius stated, “this transformation will happen one hospital and one community at a time. We can provide support and establish incentives, but you are the ones who will have to do the hard work of putting better systems into practice.”

In this way, the Partnership for Patients and the CMMI appear to be elegant solutions. The programs aim to encourage efficient, integrated care through a series of pilot programs and local interventions. Far from mandating top-down solutions, HHS is encouraging collaborations between hundreds of provider groups, hospitals, consumer groups,

“Look, doctor…”

The notion that local culture matters as much as any specific policy is not limited to health care. In fact, over the past few decades, organizational theorists have observed this phenomenon in companies across a range of high-reliability industries, from airlines to chemical plants to nuclear facilities. What is less clear is why or how this happens. After all, the academic and policy communities invest much effort researching the best interventions and piloting them across a variety of care sites. It is hardly apparent why shared values, in so many contexts, trumps carefully designed procedures; and even less clear how an abstract ideal is translated into tangible improvement.

The key may be in understanding industries whose work, like hospital medicine, naturally involves complex and unforeseen errors. In these environments, trial-and-error is not an available strategy for improvement: every trial is the consequence of a unique set of complications (think ER caseloads with a variety of

“Everybody has to be on the bandwagon”

The story of one of the most famous quality measures -- percentage of patients with acute myocardial infarction who receive a prescription for beta-blockers within seven days of hospital discharge -- is an example of how people fit together. Beta-blockers are a class of drugs that block the effects of adrenaline and slow down the heart rate. In 1982, results from a randomized controlled trial found that administering beta-blockers after heart attacks cut patients’ death rate by an astounding 40 percent. The results were so conclusive for all types of patients that within two years, they had been written into medical textbooks and featured in both medical journals and mainstream news media. By the end of the decade, the medical profession at large had come to understand the importance of a veritable “silver bullet” for heart attack care.

And yet, by the mid-1990s, only 34 percent of patients received beta-blockers after heart attacks. The policy response was an expans

II.

Friend-Driven Automation

On most days, Bill, a senior analyst, glided across the office sporting plaid button-downs tucked into comfortable khakis, armed with a laptop, a friendly wave, and a witty joke. He never turned down a conversation, always took extended lunches with coworkers, and then banged out a few hours of solid work. Speaking with him, I got the impression that his job was nothing more than a series of pleasant conversations and simple conclusions.

I was fooled.

My first month on the job, I was asked to do analyze the root causes behind poor customer experiences that caused high-dollar refunds. This involved talking with teams across the office: customer service, operations, sales, and finance.

Naturally, I sent out a slew of emails and set up a series of meetings over the next week. I felt important.

I.

Automate Your Job the Right Way.

If you're like me, there is a good chance your job won't exist in 20 years. We are not alone; earlier this year, Oxford researchers estimated that 47 percent of U.S. jobs are susceptible to computerized automation over the next two decades, in careers ranging from transportation and logistics to administrative support to customer service.

The business of automation is already pervading corporate consciousness. Early December, Amazon gave a preview of its drone delivery service - a concept so alien they had to clarify it wasn't a prank.

<iframe width="560" height="315" src="//www.youtube.com/embed/98BIu9dpwHU" frameborder="0" allowfullscreen></iframe>

The next morning, I listened on NPR to an altogether logical conversation: why couldn't Amazon Prime Air automate pizza delivery? Or laundry delivery? Or really the entirety of human log

#Building The Culture Stack.

Judging a company's culture by its office decor and happy hours is the equivalent of evaluating its technology by its homepage. Like technology, culture is a stack, and we can define it by spanning the lifetime of an employee: hiring practice, onboarding, business process, career mobility, marketing & PR, and social engagement.