Source: The Framing of the Developer | svese, by Stephan Schmidt
“In the social sciences, framing comprises a set of concepts and theoretical perspectives on how individuals, groups, and societies, organize, perceive, and communicate about reality.” Wikipedia
Framing is intentionally and unintentionally used in discussions and environments. A frame shapes the discussion and makes some things thinkable and some other things unthinkable. Frames have friends that go with them.
We have a dominant frame in development. Software development as a “backlog”. Features are put in a backlog by a product manager – the product owner – and by different departments. According to the Cambridge dictionary a backlog is “a large number of things that you should have done before and must do now”. The word backlog makes you think you are always behind finishing things. The frame says: Finishing means success. If we work from the backlog, we’ll have success. If we complete all the things I as a product owner have in my vision, we will have success.
Companies today need a frame of impact. In this world view success is defined by impact. Do product and technology develop products and features that have impact? Impact means impact for the company and impact for the customers. For the company this feature, or product moves the needle. For customers it changes their behavior.
The impact frame helps to focus on the important things. If success is defined by throughput and finishing a backlog, the more things you do the more successful you are – which leads to many features developed that are not important to customers. Backlog success is input driven product development. It focuses on the input. Impact development is outcome driven. It focuses on outcome. … This means we need to do things that have impact and no longer focus on things that have no impact. … Failure is when we don’t have impact. In this frame it becomes crucial to choose things that have impact and not work on things that do not have impact. It is key to throw away most of the ideas you have and only stick with the very few that will change your customer or the market. … Also throw out ideas that are already in development. You’ve put time, energy and money into something and learned that it will not have impact? Stop! Throw it out.
Source: The illusion of certainty, by Rory Sutherland
at stake is the difference between deterministic and probabilistic improvement. If you engage engineers, you don’t know what you are going to get. You may be unlucky and get nothing. Or their solution may be so outlandish that it is hard to compare with other competing solutions. On average, though, what you get will be more valuable than the gains produced by some tedious restructuring enshrined in a fat PowerPoint deck.
But in business, let alone in government, it is only in crises that people find a budget for probabilistic interventions of this kind (in peacetime, nobody would have given Barnes Wallis the time of day). The reason is that both bureaucrats and business people are heavily attracted to the illusion of certainty. Standard cost-cutting ‘efficiencies’ can usually be ‘proven’ to work in advance; more interesting lines of enquiry come with career-threatening unknowability.
One problem with this pretense of certainty is that cost-savings are more easily quantified than potential gains
for a long time, the ratio between ‘explore’ and ‘exploit’ has been badly out of whack.
use [an] ‘evidence-based’ data-model up to a point, but correct for the fact that it is incomplete, temporary and weighted to the past. Institutionalised humans obtain a false sense of certainty by assuming … that what is optimal in a one-off transaction in a certain present is also optimal at scale, in an uncertain, long-term future.
Source: S&P 500 Buybacks Now Outpace All R&D Spending in the US | The Sounding Line, by Taps Coogan
The United States engaged in roughly $608 billion worth of research and development in 2018. That figure includes R&D by all entities in the US, from universities to private and public corporations. During the same year, corporations in the S&P 500 spent $806 billion buying back their own stock. In other words, the 500 largest companies in the US are now spending 33% more on their stock buyback programs than the entire country is investing in R&D.
Source: Economists are rethinking the numbers on inequality | The Economist
Yet just as ideas about inequality have completed their march from the academy to the frontlines of politics, researchers have begun to look again. And some are wondering whether inequality has in fact risen as much as claimed—or, by some measures, at all. It is fiendishly complicated to calculate how much people earn in a year or the value of the assets under their control, and thus a country’s level of income or wealth inequality.
The conventional wisdom to have emerged from [recent wealth and income research] revolves around four main points. First, over a period of four to five decades the incomes of the top 1% have soared. Second, the incomes of middle-earners have stagnated. Third, wages have barely risen even though productivity has done so, meaning that an increasing share of GDP has gone to investors in the form of interest, dividends and capital gains, rather than to labour in the form of wages. Fourth, the rich have reinvested the fruits of their success, such that inequality of wealth (ie, the stock of assets less liabilities such as mortgage debt) has risen, too.
Each argument has always had its doubters. But they have grown in number as a series of new papers have called the existing estimates of inequality into question.
Few dispute that wealth shares at the top have risen in America, nor that the increase is driven by fortunes at the very top, among people who really can be considered an elite. The question, instead, is by just how much. … Proposals for much heavier taxes on high earners, or a tax on net wealth, or the far more radical plans outlined in Mr Piketty’s latest book, are responses to a problem that is only partially understood.
Source: The Real Class War – American Affairs Journal, By Julius Krein
The socioeconomic divide that will determine the future of politics, particularly in the United States, is not between the top 30 percent or 10 percent and the rest, nor even between the 1 percent and the 99 percent. The real class war is between the 0.1 percent and (at most) the 10 percent—or, more precisely, between elites primarily dependent on capital gains and those primarily dependent on professional labor.
While the top 5 or 10 percent may not deserve public sympathy, their underperformance relative to the top 0.1 percent will be more politically significant than the hollowing out of the working or lower-middle classes. Unlike the working class, the professional managerial class is still capable of, and required for, wielding political power.
Members of the top 5 or 10 percent have done better than the middle and working classes in recent decades, but this masks their dramatic underperformance relative to the top 1 percent (and especially the top 0.1 percent).
the costs of maintaining elite status—and passing it on to one’s children—have risen disproportionately for the top 5 or 10 percent. The ongoing decline of the middle and working classes may have reinforced the top 10 percent’s sense of elite status, but it also means that any backsliding would be catastrophic. These pressures have converged in two key areas in particular: real estate and education.
This underappreciated reality at least partially explains one of the apparent puzzles of American politics in recent years: namely, that members of the elite often seem far more radical than the working class, both in their candidate choices and overall outlook. … Many of the most aggressive proposals associated with the Left—such as student loan forgiveness and “free college”—are targeted at the top 30 percent, if not higher. Even Medicare for All could potentially benefit households earning between $100,000 and $200,000 the most; cohorts below that are already subsidized.
The purposelessness of many professional careers in the capital accumulation economy starkly contrasts with the growing number of unaddressed needs in the public sector. The legions of finance drones making utterly pointless discounted cash flow models could be far better employed designing a serious industrial policy. The engineers currently laboring over algorithms to make social media more addictive should be funded to focus on more productive technological advances. All the effort now devoted to coming up with new pricing strategies for old drugs could be directed at real medical problems, like increasing resistance to antibiotics. The vast resources invested in unprofitable ride-hailing apps and real estate arbitrage could have been used to solve America’s ever-increasing public infrastructure and housing challenges.