Author: Dr Will Venters

Lecturer in Information Systems, Department of Management, London School of Economics.

Cloud Expertise Report with Rackspace and Intel

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For a number of months I’ve been working with Rackspace and colleague Carsten Sorensen to undertake a study of the impact of skills and expertise on cloud computing. The report “the cost of cloud expertise” has just been published here. The headline figure is that $258m is lost a year through lack of cloud expertise.

Cost of cloud expertise report

In the press release I am quoted as saying; “Put simply, cloud technology is a victim of its own success. As the technology has become ubiquitous among large organizations – and helped them to wrestle back control of sprawling physical IT estates – it has also opened up a huge number of development and innovation opportunities. However, to fully realize these opportunities, organizations need to not only have the right expertise in place now, but also have a cloud skills development strategy to ensure they are constantly evolving their IT workforce and training procedures in parallel with the constantly evolving demands of cloud. Failure to do so will severely impede the future aspirations of businesses in an increasingly competitive digital market.”

The report also explores the requirements for cloud skills, and discusses the strategy businesses can adopt to mitigate the risks of the cloud skills shortages:

  • Split the IT function into separate streams – business focused and operation focused.
  • Develop a cloud-skills strategy.
  • Assess the cloud ecosystem and ensuring a balanced pool of skills.

Take a look!

https://blog.rackspace.com/258-million-year-cost-enterprises-lack-cloud-computing-expertise-says-rackspace

Some early press coverage below…

Only 29% of IT leaders have the skills needed to fully embrace the cloud TechRepublic Sep 21, 2017
Rackspace asked organization execs around the world about cloud IT — here’s what they found San Antonio Business Journal Sep 21, 2017
Cloud Skill Shortage Costs Large Enterprises $258 Million Each Year: Report Windows IT Pro Sep 21, 2017
Cloud skills shortage holding back some Aussie businesses CIO Australia
Is cloud computing a victim of its own success? Computer Business Review Sep 21, 2017
Two-thirds of businesses losing money over poor cloud skills Cloud Pro
Here’s what’s costing businesses a lot of money London Loves Business
UK organisations lose millions a year due to lack of cloud technology skills Bdaily
Lack of cloud expertise costing companies $258mn per year The Stack
UK businesses losing revenue due to lack of cloud expertise ITProPortal

The real cost of using the cloud – your help needed for research supported by Rackspace and Intel.

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It’s almost a given that cloud technology has the power to change the way organisations operate. Cost efficiency, increased business agility and time-saving are just some of the key associated benefits[1]. As cloud technology has matured, it’s likely not enough for businesses to simply have cloud platforms in place as part of their operations. The  optimisation and continual upgrading of the technology may be just as important over the long term. With that in mind, a central research question remains: how can global businesses maximise their use of the cloud? What are the key ingredients they need to maintain, manage and maximise their usage of cloud?

For instance, do enterprises have the technical expertise to roll out the major cloud projects that will reap the significant efficiencies and savings for their business? How can large enterprises ensure they have the right cloud expertise in place to capitalise on innovations in cloud technology and remain competitive? Finally, what are the cost implications of nurturing in-house cloud expertise vs harnessing those of a managed cloud service provider?

A colleague (Carsten Sorensen) and I are working with Rackspace® on a project (which is also sponsored by Intel®) to find out. But we would need some help from IT leaders like you?

How you can help

We’re looking to interview IT decision makers/leaders in some of the UK’s largest enterprises (those with more than 1,000 employees and with a minimum annual turnover of £500m) which use cloud technology in some form, to help guide the insights developed as part of this project.

The interviews will be no more than 30 mins long via telephone. Your participation in the project will also give you early access to the resulting report covering the initial key findings. We would also share subsequent academic articles with you. We follow research ethics guidelines and can ensure anonymity to yourself and your company (feel free to email confidentially to discuss this issue).

If this sounds like something you’d like to get involved in then please email me w.venters@lse.ac.uk

Best wishes,

Dr Will Venters,

Dr Carsten Sorensen,

and Dr Florian Allwein.

  1. Venters, W. and E. Whitley, A Critical Review of Cloud Computing: Researching Desires and Realities. Journal of Information Technology, 2012. 27(3): p. 179-197.

(Photo (cc) Damien Pollet with thanks!)

England’s Electronic Prescription Service: Infrastructure in an Institutional Setting

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Good friends in Oslo (Margunn Aanestad, Miria Grisot, Ole Hanseth and Polyxeni Vassilakopoulou) have just launched their edited a book on Information Infrastructure within European Health Care. The book is open-access meaning you can download it for free here.  

Infrastructure Book

Our team’s contribution is chapter 8 which discusses England’s Electronic Prescription Service that we evaluated for NPfIT over a number of years. This service moved UK GPs away from paper prescriptions (FP10s – the green form) to electronic messages sent directly to the pharmacy.  We examine the making of the EPS temporally by looking at:  (1) How existing technology (the installed base) and historical actions affect the project. (2) How the present practices and the wider NPfIT programme influenced. (3) How the desired future, reflected in policy goals and visions, influenced the present actions.

To go to our article directly click here.

England’s Electronic Prescription Service

Ralph Hibberd, Tony Cornford, Valentina Lichtner, Will Venters, Nick Barber.

Abstract

We describe the development of the Electronic Prescription Service (EPS), the solution for the electronic transmission of prescriptions adopted by the English NHS for primary care. The chapter is based on both an analysis of data collected as part of a nationally commissioned evaluation of EPS, and on reports of contemporary developments in the service. Drawing on the notion of an installed infrastructural base, we illustrate how EPS has been assembled within a rich institutional and organizational context including causal pasts, contemporary practices and policy visions. This process of assembly is traced using three perspectives; as the realization and negotiation of constraints found in the wider NHS context, as a response to inertia arising from limited resources and weak incentive structures, and as a purposive fidelity to the existing institutional cultures of the NHS. The chapter concludes by reflecting on the significance of this analysis for notions of an installed base.

Image (cc) Simon Harrod via Flickr with thanks!

Government as a Platform – an assessment framework

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I’m pleased that my paper with Alan Brown, Jerry Fishenden and Mark Thompson has been published in Government Information Quarterly today! The paper draws together our collective work on platforms and government IT to develop an assessment framework for GaaP (Government as a platform). We then evaluate recent UK government’s digital projects using the framework.

Cover image Government Information Quarterly

“Appraising the impact and role of platform models and Government as a Platform (GaaP) in UK Government public service reform: Towards a Platform Assessment Framework (PAF)”

Alan Brown, Jerry Fishenden, Mark Thompson, Will Venters

https://doi.org/10.1016/j.giq.2017.03.003

Abstract

The concept of “Government as a Platform” (GaaP) (O’Reilly, 2009) is coined frequently, but interpreted inconsistently: views of GaaP as being solely about technology and the building of technical components ignore GaaP’s radical and disruptive embrace of a new economic and organisational model with the potential to improve the way Government operates – helping resolve the binary political debate about centralised versus localised models of public service delivery. We offer a structured approach to the application of the platforms that underpin GaaP, encompassing not only their technical architecture, but also the other essential aspects of market dynamics and organisational form. Based on a review of information systems platforms literature, we develop a Platform Appraisal Framework (PAF) incorporating the various dimensions that characterise business models based on digital platforms. We propose this PAF as a general contribution to the strategy and audit of platform initiatives and more specifically as an assessment framework to provide consistency of thinking in GaaP initiatives. We demonstrate the utility of our PAF by applying it to UK Government platform initiatives over two distinct periods, 1999–2010 and 2010 to the present day, drawing practical conclusions concerning implementation of platforms within the unique and complex environment of the public sector.

Keywords

  • Platform;
  • Ecosystem;
  • Government as a Platform;
  • GaaP;
  • Digital Government

Image: Maurice via Flickr (CC BY) with thanks!

The Enterprise Kindergarten for our new AI Babies? Digital Leadership Forum.

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I am to be part of a panel at the Digital Leadership Forum event today discussing AI and the Enterprise.  In my opinion, the AI debate has become dominated by the AI technology and the arrival of products sold to Enterprise as “AI solutions” rather than the ecosystems and contexts in which AI algorithms will operate. It is to this that I intend to talk.

It’s ironic though that we should come see AI in this way – as a kind of “black-box” to be purchased and installed. If AI is about “learning” and “intelligence” then surely an enterprises “AI- Baby”, if it is to act sensibly, needs a carefully considered environment which is carefully controlled to help it learn? AI technology is about learning – nurturing even – to ensure the results are relevant. With human babies we spend time choosing the books they will learn from, making the nursery safe and secure, and allowing them to experience the world carefully in a controlled manner. But do enterprises think about investing similar effort in considering the training data for their new AI? And in particular considering the digital ecosystem (Kindergarten) which will provide such data? 

Examples of AI Success clearly demonstrate such a kindergarten approach. AlphaGo grew in a world of well understood problems (Go has logical rules) with data unequivocally relevant to that problem.  The team used experts in the game to hone its learning, and were on hand to drive its success.  Yet many AI solutions seem marketed as “plug-and-play” as though exposing the AI to companies’ messy, often ambiguous, and usually partial data will be fine.

So where should a CxO be spending their time when evaluating enterprise AI? I would argue they should seek to evaluate both the AI product and their organisation’s “AI kindergarten” in which the “AI product” will grow?

Thinking about this further we might recommend that:

  • CxOs should make sure that the data feeding AI represents the companies values and needs and is not biased or partial.
  • Ensure that the AI decisions are taken forward in a controlled way, and that there is human oversight. Ensure the organisation is comfortable with any AI decisions and that even when they are wrong (which AI sometimes will be) they do not harm the company.
  • Ensure that the data required to train the AI is available. As AI can require a huge amount of data to learn effectively so it may be uneconomic for a single company to seek to acquire that data (see UBERs woes in this).
  • Consider what would happen if the data-sources for AI degraded or changed (for example a sensor broke, a camera was changed, data-policy evolved or different types of data emerged). Who would be auditing the AI to ensure it continued to operate as required?
  • Finally, consider that the AI-baby will not live alone – they will be “social”. Partners or competitors might employ similar AI which, within the wider marketplace ecosystem, might affect the world in which the AI operates. (See my previous article on potential AI collusion). Famously the interacting algorithms of high-frequency traders created significant market turbulence dubbed the “flash-crash” with traders’ algorithms failed to understand the wider context of other algorithms interacting. Further, as AI often lacks transparency of its decision making, so this interacting network of AI may act unpredictably and in ways poorly understood.
Image Kassandra Bay (cc) Thanks

Digital infrastructures in organizational agility – Dr Florian Allwein

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It was a great pleasure to see Florian Allwein, my PhD student, successfully defend his PhD today. The thesis has significant lessons for practitioners interested in the role of their digital technology in promoting agility within large organisations.

The abstract of Dr Allwein’s thesis:

Organizational agility has received much attention from practitioners and researchers in Information Systems. Existing research, however, has been criticised for a lack of variety. Moreover, as a consequence of digitalization, information systems are turning from traditional, monolithic systems to open systems defined by characteristics like modularity and generativity. The concept of digital infrastructures captures this shift and stresses the evolving, socio-technical nature of such systems. This thesis sees IT in large companies as digital infrastructures and organizational agility as a performance within them. In order to explain how such infrastructures can support performances of agility, a focus on the interactions between IT, information and the user and design communities within them is proposed. A case study was conducted within Telco, a large telecommunications firm in the United Kingdom. It presents three projects employees regarded as agile. Data was collected through interviews, observations of work practices and documents. A critical realist ontology is applied in order to identify generative mechanisms for agility. The mechanism of agilization – making an organization more agile by cultivating digital infrastructures and minding flows of information to attain an appropriate level of agility – is proposed to explain the interactions between digital infrastructures and performances of agility. It is supported by the related mechanisms of informatization and infrastructuralization. Furthermore, the thesis finds that large organizations do not strive for agility unreservedly, instead aiming for bounded agility in well-defined areas that does not put the business at risk. This thesis contributes to the literature by developing the concept of agility as a performance and illustrating how it aligns with digital infrastructures. The proposed mechanisms contribute to an emerging mid-range theory of organizational agility that will also be useful for practitioners. The thesis also contributes clear definitions of the terms “information” and “data” and aligns them to the ontology of critical realism.

(c) Dr Florian Allwein

 

Image: (cc)Erick Pleitez (Thanks)

Anti-competitive Artificial Intelligence (AI) – [FT.com]

Dr Will Venters1 Comment

Yesterday’s FT provides a fascinating article (available here) on the role algorithms may increasingly plan in price-rigging and collusion. While previously humans have colluded to fix prices, today’s algorithms which seek profit maximization may end up colluding in a way which is hard to detect and difficult to stop. Indeed a recent OECD report states:

“Finding ways to prevent collusion between self-learning algorithms might be one of the biggest challenges that competition law enforcers have ever faced… [Algorithms and Big Data] “may pose serious challenges to competition authorities in the future, as it may be very difficult, if not impossible, to prove an intention to co-ordinate prices, at least using current antitrust tools”.

While algorithmic trading has proliferated in financial services (reported in many popular books such as “Dark Pools”), it is their increasing use in consumer marketplaces which concerns the article’s authors – airline booking, hotels, and online retailing.

The problem for regulation is that “All of the economic models are based on human incentives and what we think humans rationally will do.” (Terrell McSweeny US FTC) while an AI algorithm which “learns” that its most profitable course of action is price coordination are poorly represented in our understanding.

“What happens if the machines realise it is in their interest to systematically and quickly raise prices in a co-ordinated way without deviating?” (Terrell McSweeny)

Indeed we might ask whether an algorithm which uses huge databases of historical demand and supply data, and detailed data of the competitive marketplace, to arrive at its most profitable price in the milliseconds of a webpage loading is acting competitively in keeping with market principles or against the consumer (who could never undertake similar analysis and therefore faces huge information asymmetry challenges).

An interesting example in the article is an App to track petrol pricing whereby, because the app highlights instantly to competitors that a price has been cut (and they can match the price cut before demand shifts), so it removes the incentive for anyone to discount.

The article even states: “the availability of perfect information, a hallmark of free market theory, might harm rather than empower consumers”

 

(Image (cc) Keith Cooper – thanks)

Professorship in Information Systems at the LSE

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It’s exciting that the LSE Department of Management is recruiting another Professor in information systems… For details see…  http://bit.ly/LSEProfIS

“We welcome applicants with a successful research record in areas of digital innovation such as digital platforms, service innovation and e-business, social media and the digital economy, and information infrastructures and digital ecosystems. Scholarship on big data as a key component of digital innovation will be desirable. We expect research that demonstrates strong relevance for understanding the complexity of social or organizational processes and the institutional patterns within which digital innovation is embedded”

Artificial Intelligence and human work.

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The best computer is a man, and it’s the only one that can be mass-produced by unskilled labour.” (Wernher von Braun)

Last night I began to think further about the role of AI and humans in society while attending Future Advocacy’s launch of a report on “Maximising the opportunities and minimising the risks of artificial intelligence in the UK”. While a very useful contribution which I recommend, my friend Rose Luckin[1] (Prof in Education Technology @ UCL) rightly criticised the lack of specific focus on improving education and pointed out that our current education strategy centres around teaching children things computers do really well (basic maths, repetition, remembering things) rather than those AI will struggle with – creativity, critical thinking etc. This left me wondering what work humans are going to provide, and whether we really understand the skills requirement of a world with AI?

In thinking about this I recalled the quote from Wernher von Braun, the German rocket scientist that “The best computer is a man, and it’s the only one that can be mass-produced by unskilled labour.”  Since the onset of the industrial revolution mechanisation has replaced human skill and as Prof Murray Shanahan[2] said last night, already replaced many jobs. After all, only around 5% of us work on agriculture today. It is therefore not a question of whether, but the degree to which new AI technology will replace jobs – and the economic efficiency of that replacement.

There are well-rehearsed arguments about the loss of jobs and plenty of books written on the subject[3]. Some jobs are clearly at risk such as professional driving in the face of self-driving technology[4]. Other jobs are safer as they involve complex unusual actions – plumbing, for example, is messy, contingent and complex (and Prof Shanahan argued this might be the last to go).

What is however lacking is a discussion of the new jobs that AI will create. Throughout history, we have underestimated the jobs created by digital technology. In 1943 IBM’s Thomas Watson predicted a worldwide-market of 5 computers, and in the 1980s people laughed at Bill Gates vision of a computer in every home.  Today we have spending forecasts for IT in the trillions[5]. With Bank of America anticipating that the “robots and AI solutions market will grow to US$153Bn by 2020” [6] it clear that disruptive innovation (Christensen, 1997) through these advanced algorithms will have a strong impact in creating new unimagined opportunity.

Since the rise of the industrial revolution we have created new jobs to replace those lost as people stopped working on farms and in factories: our grandparents would hardly imagine so many baristas, chefs, landscape gardeners, software engineering, financiers and marketers within modern society. What is interesting then is how AI might enhance and expand existing jobs, and create new ones. For instance, an AI supported lawyer might handle more cases so reducing the lawyer’s fees while maintaining their wages. This reduction may well mean more people can access the law rather than reducing the work for lawyers[7]. Similarly, we might imagine interior decorators “virtually” visiting our homes and recommending tasteful designs using AI and online stores. While I, like many others, are not currently prepared to pay designers fees for my small London home, if a store offered the service for a low fee I might well jump at the chance so creating new jobs in this area.

In this way, AI can offer huge efficiency savings which we should not necessarily be scared about. This is not however to downplay the risks to society – particularly as the distribution of this value may be inequitable with low-paid/low-skilled employees most at risk. If, however, we can ensure that those unable to capitalise on this opportunity aren’t left behind then I am cautiously optimistic.  We should also be aware that AI will likely create low-paid, low-skilled jobs as well. Someone will need to hold the 3d camera in my house for the AI designer to work. Someone will need to deliver parcels to my house for Amazon. Someone is needed to service the computers or clean up the data needed by the AI algorithm. And someone will need to make us all great coffee.

I am not trying to present a Utopian vision here – clearly there will be problems. But it is not the end of work either. After all, society has been very good at creating new work that involves sitting in front of computers shuffling files, writing text, and editing spreadsheets and PowerPoints – for people like me. Further, as Wernher von Braun’s quote reminds us – we humans are extremely good value in providing some extremely important intellegent activities: dealing with emotion and having empathy,  thinking creatively, interacting with other humans, understanding our human society and traditions. It will be a very long time, if even, before any AI can provide such intelligence. The problem is often that we underestimate the importance of these in modern work downplaying their significance in modern economic enterprise and thus overplaying the value technocratic automated AI might provide.

(This blog is an opinion piece based on personal musings rather than report on research)

CHRISTENSEN, C. M. 1997. The innovator’s dilemma: when new technologies cause great firms to fail, Harvard Business Press.

[1] https://iris.ucl.ac.uk/iris/browse/profile?upi=RLUCK37

[2] Prof Shanahan has a new book out which looks interesting:https://mitpress.mit.edu/books/technological-singularity

[3] E.g. The Rise of the Robots (Martin Ford)

[4] This is particularly pertinent for industrial driving such as farming and mining where self-driving technology is arriving already http://www.digitaltrends.com/cool-tech/self-driving-tractors/

[5] http://www.gartner.com/technology/research/it-spending-forecast/

[6]https://www.bofaml.com/content/dam/boamlimages/documents/PDFs/robotics_and_ai_condensed_primer.pdf

[7] For a full analysis of this debate read https://www.amazon.co.uk/Future-Professions-Technology-Transform-Experts/dp/0198713398  or listen to the podcast of their talk at the LSE

Image (cc) Rolf obermaier – thanks!

Building Mobility-as-a-Service in Berlin: The rhythms of information infrastructure coordination for smart cities

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[The following article was jointly written with my PhD Student Ayesha Khanna. The article was published today on LSE Business Review http://blogs.lse.ac.uk/businessreview/ and is syndicated here with their agreement]

The 21st century has seen a growing recognition of the important of cities in the world: not only does over half of humanity live in cities, but cities contribute 60 per cent of global GDP, consume 75 per cent of the world’s resources and generate 75 per cent of its carbon emissions. There is little doubt that the enlarging footprint of cities, with the rapid rate of urbanization in the developing world, will be where “the battle for sustainability will be won or lost” and, for those engaged in “smart-cities” initiatives, the focus of winning this battle is through the use of digital technology to efficiently manage resources. One of the key sectors for such smart cities initiatives is transportation.

Transportation infrastructures today rely heavily on private car ownership, which is powered by fossil fuels, and public transportation, both of which operate independently of each other. Policy makers believe radical innovation in this sector is needed to move it to a more sustainable system of mobility.

To achieve the goal of sustainable, seamless, and efficient mobility, an infrastructure would be required that would allow residents to move away from private ownership to a combination of car-sharing and public transport. For example, such an intermodal chain of mobility might include taking a rented bicycle to the bus station, a bus to a stop near the office, and then a car-sharing service to the office, covering every step from origin to the last mile. Powered by renewable energy, electric vehicles could make this journey entirely green.

In order to create such a mobility infrastructure, all the services offered (buses, trains, car-sharing systems, charging stations, and payments) would have to be integrated using digital technology in order to provide an urban resident with an easy way to map and take an intermodal journey using her smartphone. This change would transform transportation as we know it today to Mobility-as-a-Service but requires considerable innovation in the various heterogeneous digital computer-based systems (what we might term the information infrastructures), underpinning the physical transportation infrastructure. (For a more detailed account of the ideas of information infrastructure see Hanseth, O. and E. Monteiro, 1998)

Framing an Academic Project

Academic research on how such mobility information infrastructures would grow from the constituent disparate systems that currently exist in silos has been nascent, especially on the topic of the coordination efforts required. Part of the reason is that many required elements of such infrastructures do not currently exist, and that cities are only just beginning to prototype them.

In our research, we use a theory of digital infrastructure coordination as a framework to unravel the forces that influence the development of a mobility focused information infrastructure, extending it to focus particularly on the influence of temporal rhythms within the coordination. Understanding this has important implications for policy makers seeking to better support smart-cities initiatives. Our research took us to Berlin and a project which was prototyping an integrated sustainable mobility system there.

The BeMobility Case Study

The BeMobility project, which lasted from September 2009 to March 2014, was started as part of a concerted effort by the German government to become a market leader and innovator in electric mobility. A public-private partnership between the government and over 30 private and academic sector stakeholders, the goal of BeMobility was to prototype an integrated mobility services infrastructure that would be efficient, sustainable and seamless for Berlin residents. The largest railways operator Deutsche Bahn was chosen as the lead partner of the project, with the think-do tank InnoZ (an institute focused on future mobility research) as the project coordinator and intermediary. Organizations participating in the project ranged from energy providers like Vattenfall to car manufacturers such as Daimler to technical scientists provided by Technical University of Berlin.

The project, despite facing many challenges, was able to prototype a transportation infrastructure which integrated electric car sharing with Berlin’s existing public transport system. In the second phase of the project, it further integrated this infrastructure with a micro-smart power-grid, providing insights into how such mobility services could be powered by renewable energies. While the integration effort was both at the hardware and software levels, our research studied the coordination efforts related to information infrastructure in particular.

“Integration of all this information is what we now call Mobility-as-a-Service. BeMobility was  one of the first projects in the world to attempt to do it.” – Member of BeMobility Project

Findings and Discussion

Our analysis showed that individuals and organizations respond to coordination efforts based on a combination of historical cycles of funding, product development and market structures, and anticipated patterns of technology disruption, innovation plans and consumer behaviour. Peoples’ actions in contributing to an integrated infrastructure are tempered not only by these past and future rhythms, but also by the limits of the technologies they encounter. Some of these limitations are physical in nature, such as the inability to integrate data due to lack of specific computing interfaces, and some are political, such as blocked access to databases due to concerns about competitive espionage and customer privacy.

Our findings also surfaced the power of the intermediary as coordinator. Contrary to the limited perception of a coordinator as a project manager and accountant for a government funded project, we saw InnoZ emerge as a key driver of the information infrastructure integration. One of the most powerful tools for the intermediary was its role in mapping future rhythms of technology development. It achieved this by showcasing prototypes of different types of electric vehicles, charging stations, solar panels, and software systems, at InnoZ’s campus.

This campus itself acted as a mini-prototype where both hardware and software integration could be first implemented and tested. The ability to physically demonstrate how the micro-smart grid could connect with the car-sharing system to enable sustainable energy for electric cars, for example, both surprised and motivated other stakeholders to take the imminent possibility of a sustainable mobility infrastructure more seriously.

Ultimately, business stakeholders were especially concerned about the commercial viability of such radical innovation. Here too the intermediary proactively shaped their thinking by conducting its own extensive social science research on the behavioural patterns of current and future users. For example, by showing that young urban residents were more interested in car-sharing than private ownership of cars, InnoZ made a strong case for why an integrated infrastructure could also be a good business investment.

Implications

As more cities experiment with Mobility-as-a-Service, understanding the influence of rhythms on coordinating information infrastructure is helpful for policymakers. Insights that would be useful to policymakers include:

  • Keeping a budget for building an innovation lab where cutting edge technologies can be tested and integration efforts can be showcased will lead to more engagement with stakeholders.
  • Working more closely with the intermediary to conduct social research on the mobility habits of millennial urban dwellers will incentivise stakeholders as it will prove a market for the smart infrastructure.
  • Anticipating the disciplinary inertia imposed by legacy systems and organizational practices, and countering it by including stakeholders in the working group whose temporal rhythms include innovative product cycles more in line with the goals of the integrated infrastructure.

This study also contributes to the academic literature on information infrastructure development by providing insights on the role of time in coordinating integration efforts. It responds to a gap in the understanding of the evolution of large-scale multi-organizational infrastructures, specifically as they relate to mobility.

♣♣♣

Notes:

Will Venters is an Assistant Professor within the Department of Management at the London School of Economics and Political Sciences. His research focuses on the distributed development of widely distributed computing systems. His recent research has focused on digital infrastructure, cloud computing and knowledge management systems. He has researched various organisations including government-related organisations, the construction industry, telecoms, financial services, health, and the Large Hadron Collider at CERN. He has undertaken consultancy for a wide range of organisations, and has published articles in top journals including the Journal of Management Studies, MIS Quarterly, Information Systems Journal, Journal of Information Technology and Information Technology and People (where he is also an associated editor).  http://www.willventers.com

Ayesha Khanna is a digital technology and product strategy expert advising governments and companies on smart cities, future skills, and fintech. She spent more than a decade on Wall Street advising product innovation teams developing large scale trading, risk management and data analytics systems. Ayesha is CEO of LionLabs, a software engineering and design firm based in Singapore. She has a BA (honors) in Economics from Harvard University, an MS in Operations Research from Columbia University and is completing her PhD on smart city infrastructures at the London School of Economics.

Photo by Mueller felix (CC- thanks)