In 1983, the UN gave China and India awards for their efforts to control the population. The recipient for India was its then prime minister, Indira Gandhi. She famously pushed for a compulsory sterilisation campaign and even suspended elections in order to enforce it. Her programme failed miserably, and one of its enduring effects is a pervasive distrust of India’s health care system, which still plagues public health efforts today.
By contrast, China’s one-child policy was in place for 35 years until this October, when the government announced a shift to a “one couple, two children” policy.
The contrast in duration between the Chinese and Indian population control policies cannot be sharper, and it is this, among other differences, that prompted some Western observers to argue that the authoritarian Chinese system is more capable of enforcing politically tough but economically rational policies.
The reality is much more complicated. It is true that India has a higher fertility rate than China and it is also true that India could not enforce population controls as effectively as China has. But there are many other differences between China and India that would account for a lower fertility rate in China, regardless of policies. Chinese women enjoy a higher socio-economic status than Indian women. Chinese basic education and public health are far superior to those in India. All these factors would have led to a declining fertility rate in China even if China did not have the one-child policy in place.
The media landscape has changed tremendously over the past year, and as we look ahead to 2016 a big question is: What is the future of TV? Television has long been the leading medium when it comes to American video consumption, but the landscape is quickly changing. Traditional TV is seeing competition from video streaming providers like Netflix and Amazon, Over-The-Top (OTT) devices such as Chromecast and Roku, and streaming content on a myriad of personal devices.
While big data is a powerful tool, it hasn’t yet unseated TV from its place at the head of the pack. A Nielsen Total Audience Report for Q2 2015 shows that adults 18+ spend more than 32 hours a week watching television, giving TV a 95% share of all video viewing. As for advertising, TV is where we see the majority of spending. It’s a $72 billion-a-year industry in the U.S., compared to $50 billion for digital advertising. However, if TV is going to stay the leader amid this digital disruption, it needs to make some changes – and make them fast.
Not surprisingly, we’re starting to see TV experiment with alternate data collection methods. The traditional means to obtain data about television viewership has long been the Nielsen rating system. That is based on a panel of roughly 25,000 homes in the U.S. and collects data once every minute. However, it really only tells us what is on the TV screen in that home. It doesn’t show if anyone is actually in the room watching the TV, or, if they are in the room, whether they are attentive to the program. Yet Nielsen has long set the standard for telling us what Americans are supposedly watching, which sets the pricing for TV advertising.
Many people find asking to be paid more money awkward. How will your request be perceived? Will you look greedy or demanding? Are you sure you’re really worth what you’re asking for? The key to answering these questions and reaching a successful outcome is preparation. Fortunately, it’s not difficult to prepare for a salary negotiation. It just takes a few simple steps.
1. Think about timing.
The first step in preparing for a salary discussion is to consider timing. In general, it’s better to discuss salary after you receive a job offer rather than once you start a position. Companies generally expect there will be some negotiations before a person formally accepts a position, and assuming you have done your market research, you should be comfortable knowing the salary range and typical benefits for your position and in your location.
However, many people decide to have this conversation when they have been in a job for a time and desire a raise. If this is the case, look at whether you’ve had changes in job responsibilities. Have you taken on new roles or tasks? Or have you recently completed a successful project? If so, this would be an appropriate time to ask for an increase.
Another rule of thumb is that it’s better to ask for a raise when you’re happy in your job, versus feeling dissatisfied. You want to bring a positive attitude to the negotiating table, because that suggests you are committed to the company and are in for the long haul. After all, who wants to reward a disgruntled employee?
It’s also helpful to look at how the company is doing. If it just announced layoffs, don’t ask for a raise. On the other hand, it reported a 15% increase in profits over the last quarter, that is probably a better time.
It’s well known that mobile phones are changing every day life in the developing world — particularly in sub-Saharan Africa. The spread of cell phones coupled with the ease and efficiency of text messaging helps people save, spend, and investtheir money more wisely. Text messages and mobile apps improve health outcomes by teaching people about nutrition and reminding patients to take their medication. They also further education by helping students learn more effectively through virtual tutoring.
We now have evidence that text messages improve civic engagement in emerging countries by encouraging people to vote. A recent study I conducted in Kenya with Benjamin Marx, an economist at MIT, and Vincent Pons, of Harvard Business School, found that get-out-the-vote text messages increased Election Day turnout by as much as 2 percentage points. This increased participation in democracy comes with a condition, however. If voters perceive that elections aren’t free and fair, they lose trust. Put another way: when voters willingly place their faith in electoral institutions — the very essence of voting — those institutions had better make good on their promises.
Democracy in the developing world is a fragile thing. Corruption and fraud are common features of elections and understandably, voters feel disillusioned and angry. In Kenya’s 2007 election, that anger turned to bloodshed. After Kenya’s election commission ignored evidence of vote rigging that kept the ruling government in power, the country erupted into violence and hundreds of people were killed.
The following year, Kenya’s government worked to rebuild trust. The country adopted political reforms and created a new constitution. It also replaced its old electoral commission with a new one: the Independent Electoral and Boundaries Commission (IEBC), tasked with creating a new register of voters across the country. Before the 2013 election, the IEBC purchased biometric voter registration kits, based on fingerprint technology, to mitigate identification issues at polling stations.
Kristina McElheran, MIT Initiative on the Digital Economy Visiting Scholar
Professor of Information Technology, Director, The MIT Initiative on the Digital Economy
From Harvard Business Review
Growing opportunities to collect and leverage digital information have led many managers to change how they make decisions – relying less on intuition and more on data. As Jim Barksdale, the former CEO of Netscape quipped, “If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” Following pathbreakers such as Caesar’s CEO Gary Loveman – who attributes his firm’s success to the use of databases and cutting-edge analytical tools – managers at many levels are now consuming data and analytical output in unprecedented ways.
This should come as no surprise. At their most fundamental level, all organizations can be thought of as “information processors” that rely on the technologies of hierarchy, specialization, and human perception to collect, disseminate, and act on insights. Therefore, it’s only natural that technologies delivering faster, cheaper, more accurate information create opportunities to re-invent the managerial machinery.
At the same time, large corporations are not always nimble creatures. How quickly are managers actually making the investments and process changes required to embrace decision-making practices rooted in objective data? And should all firms jump on this latest managerial bandwagon?