Naps in the Huawei office – perhaps the secret of China’s digital success?

We have just spent a week visiting Shenzhen, China to see the headquarters of one of the world’s most innovative and fastest growing companies – Huawei. Since its founding in 1987, Huawei has grown to become one of the world’s largest telecom’s companies with revenue of $75Bn[1]. Globally it employs 180,000 with nearly 60,000 of these based at the Shenzhen campus. 768px-Huawei.svg

Our overall aim is to understand their global innovation practices[2]. We want to understand how management and governance arrangements support the demand for concurrently tightly knit, yet open, innovation networks. In particular we are interested in how they harness digital platforms in support of this global innovation practice. Understanding this is particularly important since Chinese firms must successful harness capital and talent beyond their borders (Fuller 2016) and since, given the diversity, scale, and adoption-willingness of the Chinese home market, innovation networks outside China will be attracted to take advantage of the “world’s biggest Petri dish for breeding world-class competition” (Yip and McKern 2016).

So how does Huawei achieve its amazing growth and success?

It was amazing to spend time digging into the practices of this fast-growing successful Chinese technology company. Away from our intense research activity, we became mindful of stark differences between Huawei and other Silicon Valley technology companies we have visited. We noted two things which we thought particularly interesting (acknowledging that many others have provided much more detailed analysis of Huawei’s management practices (e.g. Tao et al. 2016) which we do not aim to repeat or claim to validate).

Firstly, like many others across China, the employees of Huawei take naps at lunchtime[3]. They have lunch in huge canteens[4] then return to their cubicles, roll out camp beds kept hidden under their desks, and go to sleep (with the office lights turned out and blinds drawn). The whole company knows not to call between 1pm and 2pm, and so sleep is uninterrupted. Talking to an expatriate who now works there it is “like taking a shower” – refreshing and revitalising everyone ready for the afternoon. A downside is clearly that it extends the day in the office, though for many this would also allow them to travel outside commuter hours. But it provides a natural pause in the day, with time to reflect, pause and concentrate on afternoons tasks by reducing the mid-afternoon productivity slump. Naps might also be helped by the focus on tea rather than sleep-depriving espressos and flat-whites!

Secondly, alongside naps, was an overall general lack of overt hubris and self-aggrandising. In the USA and Europe tech-companies invest in amazing offices with slides, banners, bright colours, ping-pong tables, foosball tables etc. At Huawei, the offices felt much more like a university of young clever people – the furniture functional but personal with each workstation organised with bags of tea, pot-plants, posters and the roll-beds. Rather than amazing (like Google’s offices) it felt homely, welcoming and personal. Plastic fruit and cheap toys hung from the ceiling as decoration – presumably put up by the employees themselves rather than interior-designers. Chairs were comfortable rather than “designer” and the focus was upon working efficiently rather than “jerking around” or having fun. It felt efficient, focused, and much more like the university campus’ that tech-companies work so hard to try to emulate. Huawei in Shenzhen was clearly a friendly enjoyable place to work – albeit to work very hard.

* Our research is funded by Huawei’s HIRP Open funding programme.

Will Venters and Carsten Sorensen.

Fuller, D.B. 2016. Paper Tigers, Hidden Dragons: Firms and the Political Economy of China’s Technological Development. OUP, Oxford.

Tao, T., D. De Cremer, W. Chunbo. 2016. Huawei: Leadership, Culture, and Connectivity. SAGE Publications India.

Yip, G.S., B. McKern. 2016. China’s Next Strategic Advantage: From Imitation to Innovation. MIT Press, Cambridge, MA.

[1] http://www.huawei.com/en/about-huawei

[2] Our research is funded by Huawei’s HIRP Open funding programme: http://innovationresearch.huawei.com/IPD/hirp/portal/hirp/hirp-open.html

[3] http://www.goabroadchina.com/Why-Chinese-People-Always-Take-a-Noon-Time-Nap_b70#.WcjoC0yZPOY

[4] http://money.cnn.com/2016/05/20/technology/china-tech-huawei-campus-life/index.html

 

Image (c) Huawei – used with permission and thanks

Cloud Expertise Report with Rackspace and Intel

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.

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

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 HibberdTony 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

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.

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

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)