Data-Driven Development
DDDM not only benefits businesses but also enables governments to make better policy decisions. For instance, DDDM can be utilized to uncover hidden patterns, unexpected relationships, and market trends or reveal preferences that may have been difficult to discover previously. Armed with this information, government entities can make better decisions about healthcare, infrastructure, and finances than they could before. Read this article from the Executive Summary through Chapter 2 to explore data-driven decision models, how data is changing development, and how data can fill the holes in policymaking.
Executive summary
Data Deluge
In a sample second in July 2018, it is estimated that some 2.7 million emails were sent and received, 74,860 YouTube videos watched, and 59,879 gigabytes of internet traffic carried.1 Clearly, we generate huge and growing volumes of data.
The digital economy has become more information intensive, and even traditional industries, such as oil and gas or financial services, are becoming data driven. By 2020, forecasts Cisco, global internet traffic will reach about 200 exabytes per month, or 127 times the volume of 2005, with much of the growth coming from video and smartphones (figure ES.1). And that data may hold huge value. McKinsey Global Institute estimates that crossborder data flows in 2014 were worth about US$2.8 trillion, up 45-fold in value since 2005.
Figure ES.1 The growing internet
The vast majority of the data that exists today was created in just the past few years. The challenge is to extract value from it and to put it to work – for firms, governments, and individuals. Every citizen is producing vast amounts of personal data that, under the right protective frameworks, can be of value for the public and private sectors. Firms are willing to pay everincreasing amounts for our attention on social media sites and to mine the data we produce. But even data that is produced unintentionally – a byproduct of other processes, known as "data exhaust," such as call data records or GPS coordinates – can have value when effectively analyzed. Both types of data, their potential uses, and associated risks are all growing exponentially. Figure ES.2 shows common sources of personal data.
Figure ES.2 Types of personal data
Source: World Bank, https://openknowledge.worldbank.org/handle/10986/30437
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