At the heart of a global information economy is an organising idea or principle: the network.
Networks are both a technical or social achievement.
By technical achievement I mean the ability to build telecommunication networks, the internet and digital computation that enables the collection, storage, transmission and processing of vast amounts of data across time and space.
By social achievement I mean the way that the network becomes an idea for organising society, workplaces and cultural life.
Apart from the enormous scale, look at the automated machines that sort and organise the books and household items that Amazon sell.
An individual consumer clicks on a website, through an information network that triggers a robot to go and fetch the book they requested in the ware house, scan it, package it, label it and send it to you.
This is a new kind of factory, one that can respond automatically and simultaneously to the requests of individual consumers.
Amazon prides itself on being a highly flexible and data-driven organisation.
Its founder Jeff Bezos insists that the corporation will not adopt bureaucratic processes, but rather will remain a lean and flexible data-processing machine. Amazon is organised as a networked series of teams, each team responsible for producing outcomes that it can demonstrate with evidence from data analysis.
We as consumers experience the results of data mining and analysis in the form of customer service. In conversation with Walt Mossberg at the 2016 Code Conference, Jeff Bezos describes their use of both flexible data processing and a networked manufacturing and delivery systems within the company:
Mossberg: Google knows a lot about you, Facebook knows a lot about you, you know a lot about what books people want to read, what things people want to buy. I don’t know, maybe you know some other things. Want to tell us domains in which you know…
Bezos: [laughs] I want to talk to you Walt, in particular.
Mossberg: What about privacy?
Bezos: One of the reasons we always want to greet you by nameon Amazon is so that as soon as you come to the site you see ‘Welcome back Jeff Bezos.’ You know you’re not anonymous on our site. And you know that in a way that would never be as clearly articulated by a set of terms and conditions. Because we’re greeting you by name, we’re showing you your past purchases. So to the degree to which you can arrange to have transparency combined with and explanation for what the consumer benefit is, that’s sort of the commercial piece. And then you get into the tension between privacy and national security, and that’s what you see. We’re very likeminded with Apple on this point, we filed an Amicus brief on their behalf. But I believe that this is an issue of our age, we as a citizen run democracy are going to half to deal with that.
In this interview, Bezos points to the persistent tension between data processing systems used as an extension of customer service and the privacy and security concerns of citizens in a networked society.
He also points to the casual way we encounter evidence of data mining, processing and analysis. When he describes customers being welcomed by name on Amazon’s website, he sees this as a form of transparency, one that is more clear of Amazon’s data use than a terms and conditions.
But what he also alludes to in this clip is that when we come across these clues of how our information is gathered and used on media platforms- being greeted by name, our past purchases- we are providing our consent. We consent to data processing systems when we continue to use platforms, apps, and services, and as consumers we are not particularly being duped. We are aware of that our data is collected and more and more view data collection as a kind of admission ticket to participate in a larger networked society.
Amazon is a huge and complicated operation, but because it is structured around an information and data-processing network: individuals, teams and management can manage it efficiently.
Amazon management don’t attempt to control the whole business, they instead set the parameters and systems of rewards, within which teams and employees compete with each other.
This makes for a ruthless, yet highly innovative and efficient workplace culture.
Jodi Kantor and David Streitfeld reported that:
To prod employees, Amazon has a powerful lever: more data than any retail operation in history. Its perpetual flow of real-time, ultradetailed metrics allows the company to measure nearly everything its customers do: what they put in their shopping carts, but do not buy; when readers reach the ‘abandon point’ in a Kindle book; and what they will stream based on previous purchases. It can also tell when engineers are not building pages that load quickly enough, or when a vendor manager does not have enough gardening gloves in stock.
Amazon employees are also encouraged to monitor and produce data about each other using an Anytime Feedback Tool. This feedback informs annual rankings of team members, those at the bottom of the rankings each year are eliminated.
In a networked and data driven organisation like Amazon employees are not told what to do from above, as much as they are given incentives to beat other colleagues and teams and provide data to demonstrate it. Only the best survive.
As much as this account of Amazon might be unsettling in terms of thinking about employee wellbeing and corporate culture, that’s not so much the point I want to emphasise here.
The point that matters to us is that you can only imagine, create and maintain a corporation like Amazon if you have networked information technology: the capacity to constantly monitor every aspect of the operation, produce detailed data about it, and determine which elements are functioning and which are not in real time.
Also important to note here is the way that networked information-driven organisations combine the best, or worst, depending on your perspective, of managerialist and networked approaches.
Just like Henry Ford's factory a century ago, Amazon monitors ‘warehouse employees with sophisticated electronic systems to ensure they are packing enough boxes per hour’.
While in its Seattle headquarters Amazon:
[Uses a] self-reinforcing set of management, data and psychological tools to spur its tens of thousands of white-collar employees to do more and more. ‘The company is running a continual performance improvement algorithm on its staff,’ said Amy Michaels, a former Kindle marketer.
There are three fundamental differences between the industrial managerial mode of production and the networked mode of production we see in a brutal form in Amazon. But, Amazon is no different to many important ways to other information and network driven corporations.
Firstly, where the managerialist set up hierarchies, issued commands, disseminated ideas and information, the global networker processes, networks, coordinates and controls flows of ideas and data.
Secondly, Where the managerialist directs and commands, the networker facilitates and steers.
Thirdly, where the managerialist controlled particular activities, the networker sets parameters or boundaries within which they encourage and exploit innovation and creativity.
If the assembly line was a symbol of the production methods of the industrial society, post-industrial societies are characterised by clean computer-driven factories, robots in the factors can adapt and retool to make different goods by reprogramming.
If the industrial factory was an engine for mass production: the same good produced over and over again.
The post-industrial computer-driven flexible factory is an engine for mass customisation: individually tailored goods and services depending on the changing demands of individual consumers or niche markets.