大数据需要好设计

    许多公司一直相信大量囤积数据的好处，现在他们正在寻找能利用这些数据造福顾客的方法。大数据给各行各业的企业提供了一个变得更加透明、更值得信任，并在竞争中脱颖而出的机会，而且能让他们的用户在产品和服务上获得更加个性化的体验。

    大量的数据造成了巨大的复杂性，而设计的力量可以化繁为简，让这些数据能被普通人理解，因此设计在大数据上就有了用武之地。它的作用就是把信息变成人们可以使用的、有意义的观点，赋予冷冰冰的数据以生动的含义，同时把数据与我们居住的这个纷繁复杂的世界联系起来。那么企业应该如何更好地利用设计，使人们从“怕数据”变成“爱数据”呢？

    我们开始发现，在智能手机和其它联网设备的影响下，消费者的行为和预期正在发生变化。这些设备带来了海量的数据点，揭示出人们在任何特定时刻需要哪些信息，以及他们希望从哪里获得信息。消费者们已经意识到他们的数据是有价值的，因此他们可以期望、甚至是要求对方用某种价值来交换他们的数据。数据已经成了一种新的货币，企业也要从这个角度来看待数据。人们愿意拱手送上的信息越多，企业利用这些信息为消费者量身打造某种体验的潜力就越大。但是人们对于隐私问题的担忧却让这个过程变成了一个复杂的挑战。

    对于许多企业来说，如何让用户觉得自己在用一种很“酷”的方式使用他们的数据，而不是以一种鬼鬼祟祟、令人不自在的方法使用他们的数据，这是一个很难把握的平衡。设计师解决这个挑战的方法是建立一套貌似能神奇地对某个用户的习惯做出回应的系统。视频网站Netflix就是一个很好的例子。Netflix通过谨慎地利用用户的浏览数据，来向用户推荐他们可能喜欢的其它视频，让用户觉得这些视频都是为自己量身推荐的。移动社交网站Foursquare则已经转型成了一个推荐引擎，会根据用户的地理位置和一天中不同的时间，向用户推荐有用的信息和当地的优惠服务。只要企业把用户的数据当成一项服务来妥善使用，随着用户提供的信息越多，他们的体验就会越好，从而逐渐打消消费者对于企业可能泄露用户个人信息的疑虑。

    Companies that have long believed in the virtues of hoarding data are now looking for ways to use it to the benefit of their customers. Big data presents a massive opportunity for organizations across industries to become more transparent and trustworthy, get a leg up on the competition, and empower their users to have more personalized experiences with their products and services.

    But with great volumes of data comes great amounts of complexity. That's where design's power to simplify and make sense of data for ordinary individuals comes in. It's about turning information into meaningful insights people can use, giving data a human shape and a connection with the messy real world that we live in. So how can companies better use design to turn data dread into data delight?

    We're just beginning to see the extent to which smartphones and other connected objects are influencing a shift in consumer behavior and expectations. These devices are giving rise to a huge range of data points around what information people want at any given time and who they want it from. Consumers have now figured out that they can expect -- indeed demand -- value in exchange for "their" data. It's the new currency, and companies need to start treating it as such. The more information people are willing to give up, the more potential a company has to personalize an experience for them. But privacy concerns make this a complicated challenge.

    For many companies, getting the balance right between using data in ways that are cool rather than creepy can be difficult. Designers approach this challenge by creating intelligent systems that seem to magically respond to a user's habits. Netflix (NFLX) is a good example of this, carefully using viewing data to present recommendations that feel tailor-made. Foursquare has transformed itself into a recommendation engine, providing helpful information and local offers to users customized to their location and time of day. This savvy use of data as a service will likely reduce consumers' skepticism and fears around sharing personal information as the more they provide, the better their experience is.