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Analytics
What’s Your Data Strategy?
Leandro DalleMule and Thomas H. Davenport
page 074
Although the ability to manage torrents ofdata has become crucial to companies’ success, most organizations remain badlybehind the curve. More than 70% of employees have access to data they shouldnot. Data breaches are common, rogue data sets propagate in silos, andcompanies’ data technology often isn’t up to the demands put on it.
In this article the authors describe aframework for building a robust data strategy that can be applied acrossindustries and levels of data maturity. The framework will help managersclarify the primary purpose of their data, whether “defensive” or “offensive.”Data defense is about minimizing downside risk: ensuring compliance withregulations, using analytics to detect and limit fraud, and building systems toprevent theft. Data offense focuses on supporting business objectives such asincreasing revenue, profitability, and customer satisfaction.
Using this approach, managers can designtheir data-management activities to support their company’s overall strategy.
HBR Reprint R1703H
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Economics & society
The World’s Next Great Manufacturing Center
Irene Yuan Sun | page 086
An industrial revolution in Africa is nolonger a far-fetched notion.
According to data from the Chinese Ministryof Commerce, privately owned Chinese companies are making more than 150investments a year in Africa’s manufacturing sector, up from only two in 2000.These companies are having a major impact: They smelt steel in Nigeria to fuelits construction boom; they’ve made the clothing industry the largest economicsector in Lesotho; and the board of Humanwell, a Chinese pharmaceuticalcompany, has approved an eventual investment of $100 million in Ethiopia.
These and other investments aretransforming Africa’s economy and society by providing millions of Africanswith formal employment for the first time, fostering a generation of Africanentrepreneurs, and inspiring African institutions to support vibrantmanufacturing clusters.
HBR Reprint R1703J
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Operations
Linear Thinking in a Nonlinear World
Bart de Langhe, Stefano Puntoni, andRichard Larrick | page 096
The human brain likes simple straightlines. As a result, people tend to expect that relationships between variablesand outcomes will be linear. Often this is the case: The amount of data an iPadwill hold increases at the same rate as its storage capacity. But frequentlyrelationships are not linear: The time savings from upgrading a broadbandconnection get smaller and smaller as download speed increases.
Would it surprise you to know thatupgrading a car from 10 MPG to 20 MPG saves more gas than upgrading from 20 MPGto 50 MPG? Because it does. As fuel efficiency increases, gas consumption fallssharply at first and then more gradually. This is just one of four nonlinear patternsthe authors identify in their article.
Nonlinear phenomena are all around inbusiness: in the relationship between price, volume, and profits; betweenretention rate and customer lifetime value; between search rankings and sales.If you don’t recognize when they’re in play, you’re likely to make poordecisions. But if you map out relationships in data visualizations, you canactually see whether they are nonlinear and how—and then make choices thatmaximize your desired outcome.
HBR Reprint R1703K