iSChannel Journal – 10 Years of Information Systems writing.

Ten years ago a couple of students (Omer Tariq and Kabir Sehgal) entered my office with the idea of creating an academic journal to publish MSc and PhD students’ essays and articles on Information Systems. Today we have just published our 10th anniversary edition. I am extremely proud that something I pushed for during the first couple of years continues to thrive on its own, and I congratulate Gizdem Akdur, this year’s editor-in-chief and her team for their great work and enthusiasm!

http://lse.ac.uk/ischannel/

This is my editorial from this anniversary edition:

EDITORIAL – From the Faculty Editor

So the iSCHANNEL has made it to 10 years old. We should really celebrate with a cake with candles but that isn’t really in the spirit of this journal. If we are anything, we are forward looking. Our place is charting the future not the past and our regularly changing authors, reviewers and editors ensure this. Only myself – as so called Faculty editor – had remained around to steer the ship (though these days it mostly pilots itself and I simply pen these editorials).

This year’s articles reflect the iSCHANNEL’s forward-looking trend. Big data is reviewed by Maximilian Mende – though, reflecting our teaching here at the LSE, the focus is not on the hyperbole of this new trend, but on the limited rationality available to managers and the imposition of a technical rationality which remains inherently bounded. Also trailblazing is an article by Atta Addo on BitCoin– that most current of topics – exploring the entanglement of materiality, form and function. Drawing upon Prof. Kallinikos’ work, this article stands back to explore what currency is as a digital artefact of varying form. Similar questions are asked of cars in Tania Moser’s article which explores ubiquitous computing’s impact on transportation. This includes the famous quote “The most profound technologies are those that disappear. They weave themselves into the fabric of every day life, until they are indistinguishable from it” (Weiser, 1991).

What however excited me within this issue were two articles which rejected the inherent assumption of this quote, realising that while technology disappears for some, it becomes very much present for those it marginalises. Whether through economics, disability or location the brave new digital world is a barrier to many. It was therefore pleasing to see articles addressing the obstacles of old age in the adoption of telecare (in an article by Karolina Lukomska), and finally a paper by Matteo Ronzani on digital technology and its impact on replicating existing patterns of resource distribution which
support global inequality. These are topics of our time and it is wonderful to see this journal tackle them.
I very much wish the iSCHANNEL a productive second decade and hope our readership will continue to benefit from its insights.

Best wishes,

Dr. Will Venters
Faculty Editor

References
Weiser, M. (1991). The Computer for the 21st Century. Scientific American 265 (3): pp. 94-104.

Where next for UK government as a platform and GDS?

Mark Thompson provides a critical assessment of the UK’s GDS (Government Digital Services) questioning the desire to build systems as opposed to embrace the platform standardisation which should be central to a digital business strategy…

Where next for UK government as a platform and GDS?.

Why you should study Information Systems within a Management Degree.

The following is a lecture I gave to young people applying to study Management at the LSE. The aim of the lecture is to discuss why studying information systems is vital if we are to understand modern management practice. 

At the start of 2014 Erik Brynjolfsson and Andrew McAfee at Sloan Management School (MIT) published a book titled “The second machine age” (Brynjolfsson and McAfee 2014); a title drawn from the idea that information technology is progressing at such a speed that digital technology is likely to reinvent our economy – just as the industrial revolution and steam engine did in the first machine age. Picking up this books’ argument The Economist used a picture of a tornado ripping through offices to illustrate how in the near future information technology is likely to reinvent all aspects of work – including management jobs.

In some ways their thesis sounds like another tired outdated argument for how wonderful Information technology is and how it will change everything. Similar pronouncements were made in the 1960s as computers began to be used for banking and travel agencies; in the 1970s as computers began to be used for office work such as publishing; in the 1980s as the Personal Computer arrived on every desk and entered the home; in the 1990s as the Internet emerged as an “Information Superhighway” connecting the worlds information; then again in the 2000’s as eCommerce, Websites and Mobile telephony exploded.

What is different today? Should we accept these authors’ pronouncements and their hyperbolic claim of a “second-machine age” today? And if we do accept it what does that mean for the study of management?

Let’s begin by considering where we are with information technology in business today.

Within modern industrialised economies most businesses already rely on a suite of information technology applications to support their activity. We cannot conceive of businesses without IT to manage all the different information flows they need.

From a small shop’s stock management system and accounting package, to a large business running thousands of applications IT is everywhere. For example AstraZenica, a global pharmaceutical company runs 2144 applications for its 50,000 users.

Large businesses like these will run applications for many different management tasks – to manage their key resources (staff, stock, warehousing etc); applications to manage their relationship with their customers (for example to manage call-centres, websites, online-orders, customer-email), supply chain management systems to manage suppliers and partners; and finance packages to undertake their accounting. They will also run specialist applications created for their particular business – for example the LSE has applications for timetabling all the classrooms and lecture halls, and applications to book halls of residences rooms for you.  These complex information tasks have existed for years –indeed the “computing department” predated the computer as shown in this photo – it was a department in a company responsible for processing information – so what is different today?

If these have existed for years the how then can Brynjolfsson and McAfee justify the argument that we are entering in a second machine age?

To consider this we need to think about the role of technology in our economy more generally.

The first machine age was when factories and machines (e.g. steam engines) were create in the “industrial revolution” and in a short period the entire economy evolved and changed.  Yet in 1976 Daniel Bell (Bell 1976) argued that we were a “post-industrial society” in which the number of employees in “first-machine-age” businesses were rapidly declining as computerised systems took over the role of people for repetitive manual labour (for example simple robots screwing nuts into the chassis of a car during its production). IT evolved and changed our industrial landscape during this period…

However at about the same time Peter Drucker (Drucker 1969)  (a famous management guru) coined the term “Knowledge worker”, describing how knowledge was the key economic resource and so showing that the human (as central to knowledge creation and application) would continue to rule supreme for knowledge work. The argument was that information-technology and machines might replace and mechanise simple repetitive jobs (making a more efficient first-machine-age) but knowledge-work would remain and would be vital for designing, building and supporting these machines.

While a PC might get rid of the typewriter and replace it with a wordprocessor application, or get rid of the calculator and replace it with an accounting application, the knowledge-worker would continue to direct and use these machines. They were supporting knowledge work not supplanting it. Knowledge Work wouldn’t be capable of mechanisation.

This view of knowledge-work also aligned with the shifting nature of economies as labour shifted from primary industry and secondary industry (e.g. Agriculture and manufacturing) to tertiary industries (like financial services) in which information technology was increasingly vital to support the knowledge work. Essentially knowledge-workers in tertiary industries – Lawyers, Financiers, Teachers, Doctors, Managers, Designers, Architects and (thankfully for me) Academics jobs’ were safe. Information Technology might support us in our work – and so make us more productive (and perhaps even more prosperous) – but ultimately we would still be needed!

Recently though we have seen a number of significant shifts in the way information technology is used in businesses and between businesses which might challenge this assumption.

To understand this though we need to stop talking about Information Technology – and begin to talk about Information systems. Because Information technology – computers, printers, applications, smartphones, networks – are only one part of an information system.

An information system is an organised system composed of technology and people which collects, organises and processes information. It is about how people are managed and coordinated to use information technology to do some task which is useful; whether it is a shop owner looking at their past-sales on a spreadsheet in order to make decisions on what stock to buy, or something more dynamic, globally distributed, and complex.

Take for example the Lotus Formula 1 racing team (which I had the pleasure of researching last summer). One of the crucial management tasks they face is to make decisions on racing strategy during a race. To do this they have a complex information system consisting of the driver, the car (which relays data about its performance from 150 sensors every 100th of a second) the pit-crew (who can see this data in real-time as it is processed by the 36 computers it keeps “Track-side” running specialist applications), and then a secondary crew sat in an office in Oxfordshire who see the same information as the pit-crew but also have access to all the engineers who designed the car, and another supercomputer to process this data. The information system then is all of this – the people, their expertise, the task (deciding what race strategy should be taken), the technology (the car, its instruments, the computers, software, the screens, the networking etc). The management decision on race strategy is effectively taken by all these components coordinating together and its success can have profound implications for the team’s financial performance.

Less extreme Information systems are everywhere… they got you into this lecture theatre this morning (remember the people with clipboards checking your name against a list), remember the Oyster-Card you used to get the tube here, remember the booking system you used to book the hotel.

What then might have changed recently to justify the name the second-machine age, and to justify why you need to study information systems within a degree on Management?

I would like to argue that two things might justify this argument today (these are drawn from my own research rather than from Brynjolfsson and McAfee’s book:  Digital Abundance and Connections and coordination.

1) Digital Abundance

Until quite recently business information systems managed information at a local level. Information was a scarce resource and mangers were employed to produce it (for example by getting people to walk around the shop floor counting things), analyse it (putting that data into a spreadsheet and deciding what was selling well) and act upon it (telling staff to order more of those things).

Today however data is everywhere and is usually created automatically (for example by shops Point of Sale (tills to you and me), supply chain management systems, and stock-tagging). Staff might walk around, but they would carry a computer and scanner and input this data directly into a huge database at head-office. But because computing storage and processing is extremely cheap today companies can go further to include other sources of information in making their decisions –  for example they can process internet sourced information (Facebook, Google, Twitter) to understand how people perceive a product or brand; they can process weather information to understand likely consumption patterns, they can process  all their past sales information, and they can even process data on customers – their buying patterns, habits, census data about where they live  – even how they walk around a store (using their smartphone wifi or CCTV).  Decision making has thus shifted from a scarcity of information to an abundance.

2) Connections and coordination

Management decision making is thus about dealing with this profusion of data and trying to identify causalities and inferences from the connections within it – and yet we are beginning to learn that this is often beyond the comprehension of humans. For example in some supermarkets Nappies and Beer are advertised together on Friday evenings.  Why? Because an information system with access to all sales data noted a direct correlation between the sale of nappies and beer on Friday evenings – and from this the head-office manager can infer that Men (mostly) are asked to collect nappies on the way home from work, and if prompted will probably buy beer at the same time. This decision however would probably only have been made through an information system analysing past sales data automatically.

But connection is also about extending information systems beyond a single enterprise. A new innovation termed “Cloud Computing” has shifted the IT used by many organisations outside their organisation and onto the Internet.  This has increasingly allowed them to create connections and networks between organisations, and build ever more profitable, and ever more complex, Information systems.

In a book I recently co-authored with two colleagues here at the LSE we termed this “moving to the cloud corporation” and describe a company called NewGrove who specialise in helping businesses by connecting and collating huge quantities of data from both within the organisation and from outside it and displaying this data as google-maps with colours, images and graphs showing how the business operated on a street by street basis. Managers with NewGrove’s information system can, arguably, make more informed decisions than competitors without such systems.

Connections and coordination are perhaps most evident at an airport – who flew here today – yesterday… How many of you didn’t really interact with a human being except at the departure gate (and perhaps the coffee stand)? Instead your passage through the airport was coordinated by a plethora of systems interacting and communicating together…  in the USA you put your frequent-flier or credit card into a machine and in those 3-4 seconds a conversation occurs between various machines – flight-status systems, Airlines systems, past-travel history, name with Transportation Security Administration, NSA (perhaps) , food providers, computers in the destination, connecting flights, weight distribution on the plane – what Brian Arthur (Arthur 2011) described as “ a second economy” alongside the visible economy. Throughout complex decisions and inferences are made by software that were previously made by human beings.

However as the software and computing power improves, as more IT is available through “cloud computing” shifts, and as more data is capable of processing, so the decisions and inferences can become more complex – and appear more like Peter Drucker’s “Knowledge Work”.

In 2010 IBM built a computer system called Watson capable of winning the complex gameshow “Jeopardy” against the shows two best ever players by keeping a gigantic database of information (taken from the internet) available in its memory- 200million pages of data.  Today Watson is being developed for sale as a management-support systems to work alongside physicians, lawyers, financial services and government. Note that since 2010 Watson improved its performance by 2300 percent and shrunk to the size of three pizza boxes[1]

However more importantly cloud computing allows large scale computing power to be available to any business paid-for with a credit card. The key lesson here then is not that these things are going to be amazing, but that they may become integrated into the mundane business systems central to every business today.

Finally these connections and their coordination change businesses and business models. Obviously music, TV, newspapers and photography have been fundamentally reconfigured by information technology. For example financial markets have been changed as companies harness similar data-abundance to produce computer systems that trade automatically… making complex financial decisions at huge speed through complex information systems which connect data from across the world.  This was made obvious on the 5th June 2010 at 2:45pm when 9% was wiped off the Dow Jones in about 5 minutes…. Within this time it was not human traders who were leading the volume of trades, but algorithmic trading systems created to play the market by making decisions based on vast quantities of data at speeds no human can match.

Now obviously the examples I have used in this talk so far might be classed as extreme – but they hopefully paint a picture. Information Technology are no longer simply tools used by managers – Information Systems are integrated, connected, coordinated systems with an abundance of data at their disposal which are making complex management decisions already.

Knowledge-Work is not longer, Brynjolfsson  and McAffee would argue, the preserve of the Human –and so we are entering a second machine age.

So what in conclusion I want to take away that:

1) Even if you don’t think you want to study computers you should ensure that you understand information systems at a basic level because they are as integral, pervasive and important as the people in a business – though often less visible. If we want to understand how businesses work from a financial or human resource perspective – we should probably do the same from an Information Systems perspectives.

2) Information Systems are part of what an organisation is and shape the way organisations evolve and change. We need to understand how to better design and build such systems, and how such systems constrain and shape businesses.

3) We must understand how we can prepare for the information systems created by others (be they competitors, partners or government) –Uber’s[2] impact on taxi-firms, TripAdvisor[3] on Hotel chains, Flikr and Facebook’s on Kodak, Amazon on retail and publishing, Google on mapping and search. When managers ignore the impact of information systems on their business, they are taking fundamental risks with their organisations future.

Thank you,

Will Venters.

New Name, New Look, New direction – BinaryBlurring.com

Dear Readers,
After 5 years of blogging under the uninspiring title of “Utility and Cloud Computing” I’ve finally decided to “rebrand”. As cloud has become central (and assumed) in computing the old title made little sense and grew to inhibit me from writing about wider issues in computing and digital technology.

So BinaryBlurring.com … I would love to say that I hired a team of crack marketing and PR executives who exhausted plantations of coffee in concocting it while sat mostly on bean-bags … but no I just spent an hour trying to find something that (a) captured the spirit of my work,  but more importantly (b) was available!!!

I think BinaryBlurring kind of works. My research has always been about how digital technology’s binary approach becomes problematic, challenging and more interesting when it hits the analogue world of people, organisations and work practice.

I will continue to write on this topic over the coming months… and I very much hope you will continue to read.Let me know what you think!

Best wishes,

Will Venters

Software For The Full-Stack Era | TechCrunch

Alan Brown at Surrey alerted me to the following article from Tech Crunch charting the rise of “no-stack technology” – organisations that do not build their underlying technology stacks at all – instead relying on “API-based micro-services that package up a lot of underlying capability”. 

via Software For The Full-Stack Era | TechCrunch.

For me this reminds me of the desires of Component Based Software Engineering but with a realisation that the components here are far more complete, isolated and self-managing and that this enables complex business processes to be automated without the overhead of a complex stack.

BBC micro:bit computer.

The BBC is planning to distribute 7 million micro:bit computers to children in the UK with the aim of building a generation of tech pioneers. While the aim is clearly laudable and the technology is exciting, particularly the ability to connect to lots of devices and sensors, I am very worried.

Almost nobody is critical of this initiative. Yet this is a public monopoly wading into the tech space which already has a competitive marketplace with raspberry pi and Arduino etc. Sure the BBC version maybe more technically sophisticated (it had better be with the assurance of 7million ‘sales’) but my concern is the significant impact this will have on the emerging marketplace for technology. While I am not an economist (despite working at the LSE) such a move may well stifle innovation and lead to a standard emerging which it suboptimal for the market. Sure everyone in the UK will be trained in micro:bit and Python (which it comes with) but this is a monopoly decision that the kids didn’t decide upon. Without this intervention perhaps the kids would choose something else. Perhaps kids in other countries are choosing something else and that choice will become the new standard. Who knows.

I raise this as a kid of the 80s when the BBC last did something like this. The BBC Micro become the de facto standard because of the BBC intervention and acorn became huge. While the machine was wonderful it was also really expensive for a kid like me. The focus was on making the best machine for schools not the cheapest. So when I got my first computer it was a Sinclair spectrum and I was alone. The teachers all knew about the BBC, the school library was full of books on the BBC, the TV was full of programs about the BBC micro, but none of that was much use to me. Then along came the Atari ST and Commodore Amega and the UK micro computer industry foundered. I would love someone to critically assess the impact the BBC had on this demise by stifling competition through restricting the market to an expensive standard  (if they have let me know). 

Anyway I really do wish the BBC well with this new initiative and I hope we create a new generation of techies, but be warned that I am part of this industry despite the BBCs efforts in the 80s not because of it.

Talking coordination at BT next week.

I’m at BT’s Adastral Park giving a ‘Thought Leadership’ talk (available to all BT staff online) next week. It should be exciting and I plan to give them an idea of my current and future thinking on dynamic digital infrastructure. In particular I am keen to extend our thinking on how such infrastructure (constructed with cloud provided modular services and platforms) create new forms of coordination  which extend beyond existing either technical, managerial or social coordination. I am keen to discuss how such coordination extends beyond traditional institutions (such as the firm) through cloud services limiting the power of existing institutional arrangements (e.g. The CTO) to control how their digital infrastructure is coordinated and dynamically evolves into the future. Obviously thoug I will also try to make it an enjoyable and fun talk without too many of these technical terms!

Looking forward to the “Researching Digitisation workshop next week @LSE!

RESEARCHING DIGITALIZATION

via Delivering Digital Drugs (D3) – D3-Workshop May 2015.

Indicative topics include:

  • Digital materiality
  • Assemblage theories
  • Co-consumption and Personalization
  • Digital practices
  • Business models and value architectures
  • Platforms, Services and Servitization
  • Research data services and Big Data
  • Digital supply chains
  • Research methods and research practices for digitalization