超市自助结账：方便背后的经济学启示

The parable of the supermarket self-checkout

超市自助结账的寓言故事

How imperfect technologies spread

不完美的技术是如何传播的

Imagine an invention that is worse at what it does than humans, threatens jobs and increases the potential for crime. You might think it would go nowhere fast. In fact, the supermarket self-checkout machine is a parable of technology adoption—how something can spread despite imperfections—and also one of management: how real-world trade-offs affect rates of change.

想象一下，有这样一项发明，它在其本职工作上做得不如人类，会威胁到就业，还会增加犯罪的可能性。你可能会认为它很快就会毫无进展。但事实上，超市自助结账机是一个关于技术采用的寓言——即便存在缺陷，某些事物也能得到普及——同时它也是一个关于管理的寓言：现实世界中的权衡取舍如何影响变革的速度。

Start with its spread. Before self-checkout came self-service. The Piggly-Wiggly grocery chain, which opened in Memphis, Tennessee in 1916, was the first in America to allow customers to pick items from the shelves for themselves rather than asking a clerk to fetch them. It took a while for American shoppers to be able to scan and pay for goods themselves. Kroger, another retailer, introduced self-checkout machines in 1986. It was not until this century that they became widespread.

先从它的普及说起。自助结账出现之前，先有了自助服务。1916年，Piggly-Wiggly杂货连锁店在田纳西州孟菲斯市开业，它是美国第一家允许顾客自己从货架上挑选商品，而不是让店员去取的商店。过了一段时间，美国的购物者才能够自己扫描商品并付款。另一家零售商克罗格（Kroger）在1986年推出了自助结账机。直到本世纪，这些机器才开始普及。

All new technologies must get over the problem of forcing people to change their behaviour. In Britain, initial encounters with self-scan machines involved a disembodied voice shouting “unexpected item in the baggage area” at you no matter what you did.

所有新技术都必须克服迫使人们改变行为习惯这一难题。在英国，人们最初使用自助扫描机时，无论做什么，都会听到一个没有实体的声音大喊“行李区出现异常物品”。

Even now, they bring their own very specific irritations—age-verification checks to buy alcohol even though you remember using faxes; a ten-step process to confirm that the yellow, waxy citrus fruit you put in your basket is a lemon. A cashier at an assisted lane can handle these thorny problems without having to think; skilled ones can also scan items much faster than customers.

即便到了现在，它们（自助结账机）仍会带来一些非常具体的烦心事——比如你明明记得以前还用过传真机，买酒时却还要进行年龄验证；又比如你放进购物篮里的那个黄色、表面光滑的柑橘类水果，却需要经过十个步骤来确认它是柠檬。人工辅助通道的收银员不用费脑筋就能处理这些棘手的问题；熟练的收银员扫描商品的速度也比顾客快得多。

Why then are self-service machines a fixture in most retailers? The big reason is economic: the ratio of staff to customers is much lower for self-checkout machines than it is on assisted lanes. The lure of cost savings in a highly competitive industry gave supermarkets a strong incentive to stick with them even as customers griped at doing something new. Persisting with them meant that shoppers became more used to self-checkout, and gave the technology a chance to improve.

那么，为什么自助服务机成了大多数零售商的固定设施呢？主要原因在于经济层面：自助结账机的员工与顾客比例远低于人工辅助通道。在竞争激烈的行业中，成本节约的诱惑让超市有强烈的动力坚持使用自助结账机，即便顾客对这种新事物颇有怨言。坚持使用这些机器意味着购物者会越来越习惯自助结账，也给了这项技术改进的机会。

It will, however, be a long time before assisted lanes disappear entirely. When queues build up and stores need to speed up transactions, human cashiers are better. And customers’ preferences vary greatly. Older folk still tend to like cashiers; younger ones are less keen. Chatty types might want a natter; introverts would prefer an acid bath.

然而，自助通道要完全消失还需要很长一段时间。当排队队伍变长，商店需要加快交易速度时，人工收银员会更有优势。而且顾客的偏好差异很大。老年人通常还是喜欢有收银员服务；年轻人则没那么热衷。爱聊天的人可能想闲聊几句；内向的人则宁愿（与他人）保持距离。

Levino Perrucci of NCR-Voyix, an American company which develops self-checkout technology, says that users fall into several categories. “Tech-enabled shoppers” will seek out the whizziest checkout, for example; “necessity shoppers” will pick the option that enables them to get in and out of the store as quickly as possible. Most supermarkets must cater to them all.

开发自助结账技术的美国公司NCR - Voyix的莱维诺·佩鲁奇表示，用户可分为几类。例如，“科技型购物者”会寻找最先进的结账方式；“务实型购物者”会选择能让他们最快进出商店的选项。大多数超市必须满足所有这些人的需求。

Self-checkout machines are themselves designed to negotiate several trade-offs. Employers want lower costs. But they also need to provide a decent customer experience and control “shrink”, the name that retailers give to lost stock when shoppers—inadvertently or maliciously—fail to pay for things.

自助结账机本身的设计就需要权衡多个方面。雇主希望降低成本，但他们也需要提供良好的客户体验，并控制“损耗”——这是零售商对库存损失的称呼，这种损失发生在购物者无意或故意不付款的时候。

These goals do not line up neatly. Employing fewer cashiers cuts costs, for example, but also opens the door to more shrink. So lots of self-checkout machines have weight-sensitive surfaces where you have to place each scanned item before proceeding to the next one; some retailers install exit gates that only open for people who have paid. Measures like these deter shoplifters, but at the cost of slowing down customers.

这些目标并非完美契合。例如，减少收银员的数量能降低成本，但也会增加损耗。因此，许多自助结账机都设有重量感应台面，你必须在继续扫描下一件商品前，将每件已扫描的商品放在台面上；一些零售商还安装了出口闸机，只有已付款的人才能通过。诸如此类的措施能起到震慑 shoplifter 的作用，但代价是拖慢了顾客的结账速度。

These same trade-offs explain why checkout nirvana is so difficult to achieve. In theory, Amazon Go, a sensor-packed store where customers can just walk out without going anywhere near a checkout, offers a perfect customer experience and a way to reduce shrink to nothing.

同样的权衡取舍解释了为什么完美的结账体验如此难以实现。从理论上讲，亚马逊无人便利店（Amazon Go）——一家布满传感器的商店，顾客无需靠近收银台，直接走出去即可完成购物——不仅能提供完美的客户体验，还能将损耗降至零。

In practice, industry observers say that it is extremely expensive to track every item in a shop digitally (and consumers are still required to learn strange new behaviour). RFID tags do work beautifully for higher-margin products like clothes, but the sums don’t add up in the cut-throat world of cheap groceries.

实际上，行业观察人士表示，对商店里的每一件商品进行数字化追踪成本极高（而且消费者还得学习陌生的新行为）。射频识别标签在服装等利润率较高的产品上确实效果很好，但在竞争激烈的廉价杂货领域，这样做并不划算。

Real-world constraints mean that technologies often take small steps rather than great leaps. Self-checkout technology is no different. In the offices of NCR-Voyix in Atlanta, Mr Perrucci’s team is working on machines with overhead cameras which use AI to identify items without the need for scanning. These machines can still get confused if items are piled on top of each other. But they fit into existing consumer behaviour. They should also be better at identifying that bloody lemon.

现实世界的限制意味着技术往往是小步前进，而非大步跨越。自助结账技术也不例外。在亚特兰大NCR - Voyix公司的办公室里，佩鲁奇先生的团队正在研发配备头顶摄像头的机器，这些机器利用人工智能来识别商品，无需扫描。不过，如果商品堆叠在一起，这些机器还是会识别出错。但它们符合现有的消费者行为习惯，而且在识别那个棘手的柠檬时，表现也应该会更好。