The leadership challenges of homeworking.

Our notion of work and the office have changed forever. Whilst a positive experience for some, research shows we shouldn’t discount the benefits of an office environment. Will Venters and Enrico Rossi explain.

One lesson in leadership is not to make long-term decisions based on short-term experiences, while remaining ever mindful of world events. The last couple of months have provided many amazing examples of the success of homeworking and have certainly dispelled many criticisms. In the most part the technology works, we can meet people via Zoom and Microsoft Teams with relative ease (though we have also coined the term “Zoom-fatigue”) and most office work has continued well. But companies who see this as a tectonic shift towards a world where office-space is rendered unnecessary may be disappointed. While process and transactional work seems effective, the socialising, team building, learning and networking have been drastically reduced.

Our ongoing research has been examining how a very large global company’s high-level customer support staff went from being co-located in an office to all working from home. The lessons, based on numerous interviews, are stark with some staff hoping never to return to the office (often those with caring responsibilities at home, a long commute, or extensive experience), others desperate to get back (often those with small homes or partners also working from home, and with social or learning needs).

Not all workers enjoy the same conditions at home, and this can reintroduce disparities and injustices.

Two key changes are around learning and knowledge sharing. In offices, lots of knowledge is shared through serendipity; chance meetings in corridors or by the water cooler, the tea-break, the lunchtime chat[1]. These are crucial for knowledge sharing, generating new ideas, and bringing new staff into communities of shared practice and developing their identity as team-members[2-4]. Another form of informal efficient knowledge sharing is the “quick question”, where workers lean-back in their office chair and ask the people around them for help (a reason financial traders sit so closely together). These two forms of informal knowledge sharing have proved hard to replicate online. They are not however, always wanted in the office as they can be distracting (particularly for experienced staff who are constantly asked) and stressful (e.g. when managers constantly check their team). The transition to homeworking, and the consequential loss of informal knowledge sharing, was therefore perceived as a negative for some, but as a liberation for others.

Given this it was unsurprising that the very experienced staff we interviewed saw their productivity rise. One told us “I do more work at home… my workload has gone up massively” because in the office people were always coming up to her asking for help. Another told us “I am hitting targets more… without the office distractions…”,  “[in the office] I have nowhere to go because they ask face to face”. With homeworking, this person can choose which queries on the Instant Messenger app to answer and disengage herself whenever she feels the need to focus. Consequentially though, less skilled staff must spend more time finding the answer from the manuals and support tools which slows them down. As a junior person explained:

“[homeworking has] pushed me to educate myself more on what I don’t know… search for the information rather than just going ‘do you know this’…. It sinks in more if I have to find the knowledge myself”.

From a leadership perspective this feels very positive by fostering self-reliance, but the impact on new staff needs managing. More effort is needed to help them become part of the community at work. And, as online training proved less productive and harder to deliver, so more time is needed for training. Ideas like mentoring and regular-checkins seems sensible leadership responses here.

Our research also revealed the double-edge nature of digital technologies: they encourage people to share problems with a wider community (beyond their local desks) through platforms such as Microsoft Teams and Instant Messaging, but it also allowed workers to disengage and disconnect themselves from the wider social context by simply ignoring the chat, or putting it “in mute”- free riding on others. It was also harder for managers to keep track of staff – in particular, managers could not see the stress on people’s faces at home and so step in to help. And the lack of visibility increased pressure on some staff who felt the need to “prove something”, whist others were relieved and “liberated” from oversight.

Leaders should think about how to build a complex homeworking and office-working mix which maximises efficiency, equity and innovation.

Homeworking is also a great leveller – everyone had the same access to each other which proved a boon for staff who are usually located away from the main office. At the same time, not all workers enjoy the same conditions at home, and this can reintroduce disparities and injustices. Their work was impacted by different family and personal conditions (e.g. caring responsibilities, disabilities), different IT facilities (e.g. internet connection and hardware), but also physical facilities such as space for a desk, amounts of light, and whether other family members were trying to work from home at the same time. Leaders need to balance the disparity between equality of work for both office environments and homeworking. Consider, for example, the married couple we interviewed who are both now homeworking – the husband cooped up in the bedroom working for a bank, his wife downstairs in the open-plan living space. Neither could enter the room when the other was working and both worked long-shifts.

In summary, when designing physical office space architects consider balancing the need for efficient transactional work with socialised knowledge sharing and such design is linked to a wide range of factors such as the role and personality of the workers. For example, silicon-valley technology companies favour innovation over transactional work and so invest in fancy fun offices which foster interruption and informal gatherings and interaction. In contrast, many call-centres are physically organised to limit this kind of innovative interaction and focus staff on processing transactional work. When planning homeworking arrangements, the same thought for architecture, team-structures and support are needed. It is almost certainly not enough to simply replicate the same team and office structure online.

In the long-term, leaders should think about how to build a complex homeworking and office-working mix which maximises efficiency, equity and innovation, and should realise that this will vary considerably from individual to individual.

References

1. Fayard, A.-L. and J. Weeks, Photocopiers and Water-coolers: The Affordances of Informal Interaction. Organization Studies, 2007. 28(5): p. 605-634.

2. Orr, J., Talking about Machines: An Ethnography of a Modern Job. 1996, Ithaca, NY: IRL Press.

3. Wenger, E., Communities of practice : Learning, meaning and identity. 1st ed. Learning in Doing: Social, Cognitive and Computational Perspectives, ed. R. Pea, J.S. Brown, and J. Hawkins. 1998, Cambridge: Cambridge University Press.

4. Wenger, E., Communities of Practice and Social Learning Systems. Organization, 2000. 7(2): p. 225-246.

Feature image by Annie Spratt on Unsplash

What automation can do for small businesses

What does automation mean for small businesses? And what processes can they automate today using current technologies?

Cloud computing provides small businesses with direct access to a huge range of automation solutions. But rather than automating their existing admin processes, small businesses may be better examining whether standardised processes already exist in the cloud through specialist tailored services.

Small businesses should be wary though as costs can escalate. Return on investment (ROI) analysis should be undertaken before committing, and automation services themselves need carefully managing. Small businesses must be particularly careful that they don’t end up locked-into a spaghetti like arrangement of different cloud services with escalating costs. One advantage of automation in the cloud however is that costs are linked to usage and thus scale as the business scales.

Where small businesses have existing processes that need automating, companies like AnotherMonday and UIPath have Robotic Process Automation (RPA) products targeting small business. Similarly, Low-Code providers like Mendix, Pega and even ZoHo support point and click application design. However, the skills needed to use these products are by no means trivial and the challenge is not just building the automation but maintaining and evolving it as business changes. Our own research suggests that many small businesses across Europe choose vendors based on the proximity of support staff during adoption[1].

Is the future of small business management creating entities to help owners/managers better run their businesses?

For decades small business managers have harnessed software such as spreadsheets to manage accounting or word-processors for mail-merges. The difference today is that new software is transforming processes allowing the integration of parts of the business using RPA, Low-Code development and AI. RPA automates robotic-human-processes in the sense that they are most capable of doing things which humans find robotic – the boring, repetitive, easy, precise work. Indeed since research suggests (Willcocks and Lacity 2016) companies do not fire staff when replacing their work with RPA but instead redeploy them to more value-added work, so many employees may welcome RPA as it frees them to do the exciting, interesting and value-creating work rather than the drudgery. I believe the future of small business is about focusing on core-capabilities (the stuff the business does best and adds value) and seeking to streamline the none-core capabilities through automation, cloud services and better organisation.

One way of achieving this streamlining is through collaboration. Small businesses should collaborate to automate capabilities which are not core and build ecosystems of connected services which adds value to all. For example, small UK businesses in a sector might collaborate to produce standard automation for a problem they all face (for example specific customs-related administration post Brexit). These businesses are well placed to understand the specific requirements for the automation solution for their sector and thus develop something which works for all. Government pump-priming support for such initiatives might also be helpful.

What are the key challenges facing the small and micro business owner wanting to use more automation? Isn’t AI and Machine Learning only for big businesses?

Advanced AI and automation are already available as cloud services from the likes of Amazon AWS, Google’s Tensorflow, and Microsoft Azure. While these obviously require some skills to exploit, they do not require a PhD in AI. Indeed, innovative small companies may be better placed to create innovative AI solution as they are unencumbered by legacy IT processes and can move quickly.

There are however five major issues: Data, skills, interfacing and bias:

  • Small businesses will struggle to acquire the data to train machine learning (ML) algorithms whereas big businesses often have data-lakes from which they can use ML to extract insight and value. It is these vast data-lakes which are driving the growth in AI. Small companies may struggle to have enough data to train the algorithms to work effectively.
  • Small businesses may struggle to find the skills even with todays cloud-AI framework. My own research (Venters, Sorensen et al. 2017) suggested 71% of IT departments have lost revenue due to lack of cloud skills alone. Building an AI automation solution requires cloud and AI skills as well as those of analysing the business problem being are automated. Maintenance of the application will also be needed over the long term. Small consulting practices and agencies will likely emerge which are better placed to assist specific types of small business in this work.
  • A solution to the skills and data challenges is interfacing: connecting small company’s systems together to pool the data they have, share the cost of innovation, and build system which, by connecting companies together, can complete with large enterprise. For example, firms within a supply chain might collectively (obviously within the limits of competition law) build automation which, through the collective sharing of production and usage data, improves the production processes of all of them. Managing this interfaced relationship will obviously require work (and is the focus of my own research[2]).
  • One of the significant challenges of AI is that it can only learn from historic data which may embed pre-existing biases, or fail to reflect current (and planned future) organisational realities. Keeping an open mind, examining critically and carefully calibrating AI solutions for today’s reality is vital. Given that organisations will change and evolve this final issue requires careful skills. It is easy to build a successful solution to yesterday’s problem.

Is a bot, or other Machine Learning-based entity, a small business’s next employee?

A bot or Machine-Learning based entity is not like an employee. But, for this very reason, they need carefully managing by human employees. Bots won’t question their work; they hold no ethical compass; they cannot easily explain how they arrived at a decision; and they cannot understand the biases they might be applying. Further, they work so quickly that the problems they cause can rapidly scale out of control. For this reason, managing bots requires frequent checks to ensure they are working in the company’s best interest and delivering a clear ROI.

As significant may be that the a small-businesses’ future customers may be AI-led bots that negotiate and place orders automatically with complex market analysis. This may change the way small businesses transact their businesses and derive profit.

Will some freelancers and micro business eventually be competing against AI-based services?

It’s easy to overplay the success of AI-services compared to a human. AI suffers from the frame problem (Boden 2016) in that they cannot understand what it is to be human and make human-decisions – they can only apply robotic action or make inferences from existing limited data. The most likely emerging reality then is not that a bot or AI will replace employees, but that employees’ capabilities will be drastically improved by working alongside AI and technology. Seeing human and machine as entwined rather than opposed is a more productive perspective.

What’s somewhat more interesting is how many micro-businesses today are becoming human-intelligence based services (forms of mechanical turks[3]) provided to large AI-reliant platform companies. Consider Uber; for the “micro-business” person driving the car their “company” is entirely controlled by the Uber algorithm which allocates their piece-work contracts to drive. All traditional business functions – marketing, quality-control, advertising, sales etc. that a small mini-cab company might have provided are subsumed into the Uber platform leaving the drive-business reduced to just the intelligent driving skill. Ubers seem closer to self-driving cars than to mini-cab-firms in that the human only provides the driving-intelligence. Similarly, eBay and Amazon Marketplace have reduced retail to mere product acquisition.

What does small business automation look like in 2025?

I think many small businesses will prove highly efficient as their administrative overhead reduces allowing them to complete more easily and efficiently with larger companies. As small business automation matures so the cost of doing business will be reduced allowing more exciting and innovative businesses emerge which are both efficient and agile. The rise of Harry’s Razor for example shows how a plucky start-up harnessing online tools in marketing can build a business to complete with global multinationals.

It would be great to see government departments focused on supporting this innovation. For example, if they used next five years to focus on producing standardised APIs that allow small businesses to easily comply with “red-tape” rather than through mountains of form-filling. This would require considerable change in the way Government built and used their IT[4].

We should also not underestimate the growth of blockchain alongside automation. By providing mechanisms for establishing trust the technology could allow small businesses to collaborate more fluidly with greater safety. Smart contracts, for example, might ensure that payments happen immediately and automatically once a product is shipped.

Physical robots are also rapidly improving and may form part of physical-automation processes alongside digital ones. For example, robots, like the early Baxter, can now safely work alongside humans and are easily trained for repeated activities. If coupled with a process automation application one can envisage such robots undertaken key tasks (e.g. picking, boxing and labelling) unaided. Further out, as robotics takes the place of humans, so the economics of manufacturing may shift in favour of producing closer to the consumer rather than overseas – a move which may benefit small business.

Finally, once automation becomes accepted within the small business community, I think we will see the rise of ecosystems of small businesses working together to take on larger enterprise. By drastically reducing the transaction costs involved in collaborating there is little reason such ecosystems cannot outcompete.

References

Boden, M. A. (2016). AI: Its nature and future, Oxford University Press.

  • Venters, D. W., C. Sorensen and Rackspace (2017). The Cost of Cloud Expertise, Rackspace and Intel.
  • Willcocks, L. and M. C. Lacity (2016). Service Automation: Robots and the future of work. Warwickshire, UK, Steve Brookes Publishing.

[1] Polyviou, Pouloudi and Venters, (Forthcoming),” Sensemaking and proximity in cloud adoption decisions” (Working paper).

[2] https://binaryblurring.com/2017/12/04/win-of-6-million-to-research-digital-interfacing/

[3] https://en.wikipedia.org/wiki/The_Turk also https://en.wikipedia.org/wiki/Amazon_Mechanical_Turk

[4] Fishenden, J., M. Thompson and W. Venters (2018). Better Public Services: The Green Paper accompanying Better Public Services, A Manifesto. Launched at the Institute for Government on 27th March 2018.

Feature image by James Pond on Unsplash. (With thanks).

The World Turned Upside Down … The future of digital innovation research post COVID-19

To register (free) via eventbrite click here!

25th June from 1:00pm (BST – UK Summer time) until 5:30 pm (includes a 1hr break from around 2:30-3:30)

As part of the The Digital Infrastructure, Innovation and Economy Series London (DIIESL.org) which I co-run I would like to announce a seminar on the 25th June 2020.

In 2020 the world turned upside down: one particular consequence has been the most marked shift to digital forms of social interaction we are likely to see in our lifetimes. We would like to hold a workshop to explore how research in Information Systems and related fields might (and perhaps should) change in response, by bringing together a range of information systems researchers to engage in reflection and futurology.

Dr Will Venters
Chairperson:
Dr Will Venters – LSE

We will not dwell on COVID, choosing to focus instead on imagining what sort of changes may ensue – and speculating on how these are likely to affect our disciplines. The workshop will be informed by futures research (Chiasson, Davidson et al. 2018) and consist of short presentations on imagined changes, followed by structured discussion and debate.

.

.

.

Speakers

Prof. Michael Barrett – Judge Business School

Why IS Practice Essential for Digital Innovation Research

Prof. François-Xavier de Vaujany – Université Paris Dauphine-PSL

The Birth of Digitality: Computing for a World in Crisis in the 40s

Dr Mareike Möhlmann – Warwick Business School

App-based surveillance – Lessons from the algorithmic management of Uber drivers

Prof. Mark Thompson – Exeter University

Public services during COVID:  the curious case of a ‘digital’ council

Dr Edgar Whitley – London School of Economics

Managing digital identities online: Public, private and interoperable?

Prof. Mike Chaisson – The University of British Columbia

TBA

Dr Wendy Günther – INDEX

Wendy will act as rapporteur and provide a summary at the end of the event.

Topics for discussion include

  1. Methodological innovations.
  2. Changes to Privacy and Identity.
  3. Digital infrastructure and the emerging role of the state .
  4. Changes in Information Systems development practices.
  5. Digital nomadism and emerging organisational forms.
  6. Globalised supply chains and outsourcing.
  7. Practices, processes and performances.
  8. Materiality in a dematerialising world.

For administrative Questions please contact f.white@lse.ac.uk

Chiasson, M., Davidson, E., and Winter, J. 2018. “Philosophical Foundations for Informing the Future(S) through Is Research,” European Journal of Information Systems (27:3), pp. 367-379.

Sprint Week – Launch with Jake Knapp

It was fantastic to launch the annual “Sprint Week” I run, with Carsten Sorensen, as part of our MSc in Management, Information Systems and Digital Innovation . During the week our students follow Jake Knapp’s Sprint book (albeit with changes to use more complex modelling tools) to develop a solution for VISA. The week is supported by Roland Berger consultants and various outside speakers.

We were pleased to launch the week with myself interviewing Jake via Skype about his Sprint techniques. In the talk (30minutes) is below.

 

Presentation of our research in Map Camp 2019

Roser Pujadas presented in Map Camp 2019 some of the findings of the research she is conducting with Will Venters and Mark Thompson on Wardley Maps.

Map Camp (map-camp.com/) is a yearly event that brings together a community interested in Wardley Maps, a tool used to support strategic decision-making by helping organizations develop situational awareness. More than 600 people from across the globe attended this year’s Map Camp in Sadler’s Wells Theatre (London). Presentations were recorded and will be available @map_camp.

Roser’s presentation explored the social dimensions of mapping and sensemaking. Instead of thinking about Wardley Maps as a tool, she suggests instead to consider mapping as an active doing, an ongoing process that involves making knowledge explicit through visualisation. Wardley Maps constitute a common language that facilitate communication and collaboration, and can also be used to gain legitimacy. As our research shows, most mappers see the main value of mapping in the process, in the discussions that are generated through mapping and interpreting maps, and not so much in the production of ‘a perfect map’. In fact, as Roser went on to argue, all maps are partial, and reveal some things but obscure others.

Recruiting Again – Research Fellow.

I am looking to recruit someone who can work in the interdisciplinary space between information systems and formal modelling. The aim is to work with a large industrial partner to build and test models (of various kinds) of systems at scale. Ideally we would find someone directly able to do that – but realistically the candidate is likely to have a stronger flavour in one of these areas.

Research Fellow – Programming Principles, Logic and Verification Group, – Ref:1820659

University College London is seeking to appoint a Research Fellow for examining modelling of large enterprise systems and architectures. This fellowship will involve working with industry partners to analyse and model their digital ecosystems. The Information Systems and Innovation group (ISIG) at the London School of Economics is well known for its research in the social, political and economic dimensions of information and communications technology.

The Interface Reasoning for Interacting Systems (IRIS) project, led by Prof. David Pym, uses logical and algebraic methods, as well as management research theory, to understand the compositional structure of systems and their communications, seeking to develop analyses at all scales, from code through distributed systems to organizational structure, generically and uniformly. The role will be jointly managed by David Pym at UCL and Will Venters at LSE’s Department of Management — a world-leading centre for Information Systems research.

The PPLV group at UCL conducts world-leading research in logical and algebraic methods and their applications to program and systems modelling and verification.

While based at UCL, the role will involve working at the LSE for around two days per week where you will have a desk.

The post is funded for 12 months in the first instance with a possible extension up to 36 months.

Ideally you will have a technical/engineering background with experience in business modelling,  business analysis, programming, and formal methods, and an understanding of qualitative and quantitative research techniques. An understanding of information systems and management research would be highly desirable, as would experience of action research or design science.

Good communication skills are essential.

Applicants must hold, or be about to receive, a PhD in information systems, logic, theoretical computer science, or a closely related area. An interest in systems modelling verification, together with underlying logical and mathematical theory, is essential. Advanced programming skills and knowledge of, or some interest in, distributed systems and/or information and systems security are highly desirable.

Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at research assistant Grade 6B (salary £30,922 – £32,607 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.

Further details and how to apply:

https://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5041404&ownertype=fair&jcode=1820659&vt_template=965&adminview=1

 

 

Professor of Information, Logic, and Security Head of Programming Principles, Logic, and Verification University College London

 

Turing Fellow, The Alan Turing Institute, London

 

d.pym@ucl.ac.uk

www.cs.ucl.ac.uk/people/D.Pym.html

www.cs.ucl.ac.uk/staff/D.Pym/

 

Assistant: Julia Savage, j.savage@ucl.ac.uk, +44 (0)20 7679 0327

 

Control-Generativity Paradox – Visiting student Michael Blaschke is working with me for the next year.

For the next year Michael Blaschke, is visiting me at the LSE. He is a final year PhD student from University of St Gallen (HSG) and the SAP Innovation Center St.Gallen. His research mainly focuses on digital platforms and value co-creation.

The following  paper-summary written by Michael gives an idea of his research. 

Abstract

The platform economy represents the most profound global macroeconomic change since the industrial revolution. Digital platforms afford organizations to synergistically co-create value in digital third-party ecosystems. Considering these ecosystems’ specificities, digital platforms require a delicate balance of two conflicting ends: control and generativity. While pure control makes adaptation difficult, pure generativity suffers the costs of experimentation without gaining associated benefits. In turn, embracing the complementary benefits of simultaneous control and generativity is challenging given its inherent contradictions. Beyond summarizing the control-generativity paradox of digital platforms, this blog post makes four alternative modes of balancing control and generativity available to platform managers. The publication can be found here.

The Control-Generativity Paradox

Key Takeaways

What? Digital platforms—digital core technologies upon which third parties add peripheral derivatives—afford organizations to co-create value in networked business ecosystems.

So What? While platform owners aim for stabilization to exploit their third-party ecosystem (control), third parties aim for autonomy to explore unanticipated avenues of innovation (generativity).

Now What? Platform owners draw upon at least four modes of balancing control and generativity in digital platforms—contextual, structural, temporal, and domainal balance.

Managerial and scholarly interest in digital platforms is mounting. Some of the most valued companies—including Alibaba, Amazon, and Alphabet—embrace the platform logic with surprisingly short histories. At the same time, many long-lived companies are considering how they can adopt the platform logic to improve performance. Prominent digital platform exemplars are social media platforms (e.g., Facebook and LinkedIn), mobile operating system platforms (e.g., Android and iOS), payment platforms (e.g., PayPal and Apple Pay), and peer-to-peer platforms (e.g., Uber and Airbnb).

Digital platforms are characterized by synergistic value co-creation in digital third-party ecosystems. These ecosystem make digital platforms subject to a delicate tension between (1) maintaining control and, at the same time, (2) stimulating—not directly managing—generativity through dynamically recombining third-party resources (Blaschke and Brosius 2018). While control captures mechanisms that encourage desirable outputs or behaviors by third parties (Tiwana et al. 2010), generativity describes a technology’s overall capacity to produce unprompted change driven by large, varied and uncoordinated audiences (Zittrain 2006).

Notably, control and generativity are not incompatible or mutually exclusive goals. Successful digital platforms meet both ends as pure control makes adaptation difficult and pure generativity suffers the costs of experimentation without gaining associated benefits. As balancing has in fact become the innate mindset of digital platform management, we ask: How do digital platforms balance simultaneous control and generativity?

Balancing Control and Generativity

Based on our research, we extracted a set of four modes of balancing control and generativity in digital platforms, namely contextual, organizational, temporal, and domanial balance. This set of modes is drawn based on the premise that digital platforms seek both (1) for stabilization to exploit the given ecosystem of third-party actors (through control) and (2) for dynamism to explore new avenues of resource integration in adapting to third-party actors’ external stimuli (through generativity). Next, we summarize these modes of balancing control and generativity in digital platforms.

 

 

Contextual balance denotes a situation-dependent combination of concurrent control and generativity. It is a form of contextual buffering, whereby the platform owner maintains control and generativity activities (1) situation-dependent for each platform partner individually and (2) simultaneously at any given organizational level. For instance, Microsoft (Windows) employs contextually configures control and generativity within the contexts of either exchanging, adding, or synergistically integrating third-party resources.

Structural balance refers to different types of partners that are subject to either control or generativity. It is a form of spatial buffering, whereby the platform owner maintains control and generativity (1) simultaneously on the platform ecosystem level, but (2) are situated within distinct organizational units for distinct partner types (e.g., new and existing partners), respectively. For instance, SAP (SAP Cloud Platform) runs one unit to negotiate and onboard new partners (control), while a different unit explores novel software with already existing partners (generativity).

Temporal balance denotes sequential shifts over time from control to generativity, and vice versa. It is a form of temporal buffering, whereby control and generativity (1) coexist for the same given platform partner but (2) at different points in time, so that the platform owner switches sequentially between control and generativity for each platform partner. To illustrate, Alibaba Group (Alibaba.com) predominantly maintained generativity to become a two-sided platform (1994-2004), relied on control to mitigate the threat of platform envelopment (2005-2006), and fostered generativity again to pursue a digital ecosystem strategy (2007-present).

Domainal balance denotes control in one domain with simultaneous generativity in another domain. It is a form of domanial buffering, whereby any given platform partner is subject to both control and generativity (1) organizational domains while (2) the platform owner balances these domain-dependent control and generativity activities globally across domains. For instance, Microsoft (LinkedIn) differentiates a platform’s core, interfaces, and complements as key architectural domains, each of which require different control-generativity configurations.

Recommendations

  1. Thriving platforms simultaneously seek (1) for stabilization to exploit the given digital ecosystem (through control) and (2) for dynamism to explore innovation in adapting to third parties’ external stimuli (through generativity).
  2. Thriving platforms balance control and generativity through a platform-specific adoption and adaption of the four proposed balancing modes.
  3. Effective platform mangers identify novel modes and mechanisms to achieve the targeted control-generativity balance.

About the paper

References

Blaschke, M., and Brosius, M. 2018. “Digital Platforms: Balancing Control and Generativity,” in: 39th International Conference on Information Systems (ICIS2018). San Francisco, US.

Tiwana, A., Konsynski, B., and Bush, A. A. 2010. “Platform Evolution: Coevolution of Platform Architecture, Governance, and Environmental Dynamics,” Information Systems Research (21:4), pp. 675-687.

Zittrain, J. L. 2006. “The Generative Internet,” Harvard Law Review (119:7), pp. 1974-2040.

 

Fully funded PhD studentships in Interfaces / Boundary Resources / Digital Ecosystems / Cloud Computing.

I am part of my large research grant with UCL, QMUL and Imperial (https://binaryblurring.com/2017/12/04/win-of-6-million-to-research-digital-interfacing/  )  titled “Interfaces Reasoning for Interacting Systems.

As part of this we have four fully funded PhD studentships available –  http://www.cs.ucl.ac.uk/prospective_students/phd_programme/funded_scholarships/

While the advertisement focuses on computer science issues, the final bullet point “Tools for modelling and reasoning about organizational architecture” directly relates to Information Systems and Digital Innovation areas. Essentially if you would like to undertake a funded PhD focused on the managerial, social and organisational impact of Digital Interfacing (e.g. Digital ecosystems, Cloud Computing, Platforms, Boundary Resources, APIs,) please apply! While the advert insists on computer science or mathematics degrees – for those seeking to work with me a strong Information Systems Masters, or First-Class Degree in a related discipline would be sufficient.

[Note the PhD may need to be based at UCL while supervised by myself with Prof. David Pym as joint supervisor. The starting stipend will be approximately £17,000, with an approximate annual uplift of 3%. ].

It is possible that the studentship would be supported by AWS (Amazon) and involve working with AWS (Amazon), BT or Facebook among others .

Please apply ASAP as we are looking to recruit very very soon! Applications need only be a couple of pages long. 

Best wishes,

Will.

 

Five days of trials, tech and teamwork: welcome to Sprint Week

Innovation can transform the world. So how can it be encouraged and nurtured? Sofia Klapp, studying my course in “Innovating Organizational Information Technology” for her MSc Management of Information Systems and Digital Innovation (MISDI), reveals how our Sprint Week concept challenged her and her fellow classmates to generate, develop and pitch genuinely groundbreaking ideas. 

It was Monday morning, and 18 multidisciplinary teams were assembled at their desks. It was the beginning of the Sprint Week. We all had our materials ready (post-its, tape, markers, cardboards, and one big whiteboard) and plenty of healthy snacks to keep our energy levels high. Visa, one of the world’s leading payment brands, were explaining their global innovation challenges. From this moment until Friday afternoon, we would have to work in an “agile manner” to create an  innovative digital solution to win this innovation competition.

The Sprint Week: A learning-by-doing process framed as an innovation race

Will Venters and Carsten Sorensen, scholars on the “Innovating Organizational Information Technology” course, came up with a better use for the reading week for the MISDI Programme at LSE. Instead of just teaching about digital innovation and agile theory, why not use this week of no classes to immerse the students in a hands-on learning experience? They called it “The Sprint Week”, and this is the second year they´ve run this 5-day bootcamp.

As if making Sprint Week 50 % of our course assessment wasn’t enough, to add some extra adrenaline the teachers framed it as an innovation competition. Two key partners (Visa and Roland Berger) were invited to make things even more exiting. Both would be judges and choose the best projects for the grand final on Friday. Visa shared its strategic digital challenges to inspire our innovation ideas. Trending topics like mobility, digital identity, and a cashless society, served as fuel to ignite our imaginations. At the same time, Roland Berger, a strategic consulting firm and design sprint expert, was there to support our hands-on learning process.

The Sprint Week Methodology: The MISDI approach to developing digital innovations

But how did it all work? Sprint Week addresses digital innovation development by combining the best of two approaches: Design Sprint Methodology (a five-day work process for answering business questions through design, prototyping, and testing digital ideas with customers created by Google Ventures) and Soft Systems Methodology (a socio-technical approach broadly used to understand, design and intervene in information systems and digital innovation). While the first approach encouraged us to work in an agile manner as a multidisciplinary team, the second allowed us to understand the digital challenges from a systemic perspective considering their social and human implications.

The Sprint Week Experience Challenges: It’s not about intellectual capacity, but about the right mind-set and team-work skills.

Initially, these methodologies seemed simple. But as we moved forward we realised that putting them into practice wouldn’t be easy. For me, the biggest challenges we faced weren’t intellectual, but mostly related to how we managed uncertainty and how we interacted and communicated as a team. Whether we felt lost or on track depended on how well we managed our teamwork, triggering a roller coaster of emotions in our team throughout the week.

Managing the uncertainty that every innovation process entails can be very hard. We humans seem to have a control seeking mind-set that also looks for right answers. Yet working in an agile manner is not a linear step-by-step process. The agile mind-set is about learning and discovering the answers as you go, navigating in a disciplined way the messiness of the innovation process. If you are a control freak, you will suffer a lot. A good strategy was to keep trusting the methodology, accepting uncertainty as a normal feeling during the process while being open to be suppressive by the outcomes of applying it.

All the teams were highly diverse in their backgrounds and personalities. My team mates were from Indonesia, China, and the UK, whereas I´m from Chile; and their backgrounds ranged from IT-engineering, linguistic, international business, innovation and psychology. The methodology encouraged us to interact and discuss in an active and collaborative way. But it also meant dealing with disagreements among team members. We all speak English but our cultural differences and accents meant we had to focus extra hard. Getting to know each other before the Sprint Week and negotiating working styles was very important. We also ran open-heart sessions after each day gave feedback about what we liked and what we could improve for the next day.

What did I get out of all of this? From connecting theory and practice to being inspired by my classmates

As a MISDI student with previous work experience in innovation and agile development, I did not expect to learn as much as I did. The Sprint Week has definitely been the highlight of the MISDI programme so far.

Getting the opportunity to work on a real-life case challenge for a global company, with the input from industry experts, helped to link the theory I´d learned on the course with real world challenges.  And the ideas and discussions it generated between team members from different backgrounds, life-experiences and nations were amazing. Honestly, I feel that in one week it made me a better team player!

Moreover, seeing the teams´ project presentations on Friday was inspiring (all of them, not just the finalists). All the initiatives were so diverse and creative.  They greatly exceeded my expectations: from a data monetization platform that allows individuals to gain control of and get value from their digital data, to a futuristic payment chip inserted in consumer’s hand linked to an integrated app. Even some of the social projects surprised me; there was a donations platform that streamlines the funding of NGOs for increased transparency and another that provides digital sovereign identity and financial inclusion to the unbanked population.

This hands-on experience helped us gain a practical understanding of breakthrough methodologies while developing the multidisciplinary team skills needed to craft digital innovations. But most importantly, this week reminded me that at LSE your classmates are one of the main sources of learning and inspiration.

ABOUT THE AUTHOR

Sofia Klapp is from Chile and holds a BA in Organisational Psychology, plus diplomas in Business Management and Innovation & Entrepreneurship. Her experience in leading customer experience evaluations in technology projects in a global IT consultancy enabled her to understand the strategic complexities that digital transformation brings, encouraging her to pursue her MSc Management of Information Systems and Digital Innovation (MISDI) at LSE.

Lecturing for Cambridge Executive Education

It was great to be back in Cambridge last week lecturing with Dr Mark Thompson on Digital Innovation and Transformation @ Judge Business School Executive Education Programmes.

20181115_095722My contribution was a deep dive into the digital infrastructures which are transforming our digital economy. I talked about Cloud Computing as transformational in enabling Data and Algorithms to have agency in changing business environments.

Central to this transformation is Artificial Intelligence (AI) which I argued to be a means of industrialising data-analytics at scale. Through AI and cloud computing, organisations can share data across their organisational boundaries in order to derive new business benefit.

For example an FMCG company might harness AI to automatically integrate data from wholesalers, distributes and retailers with complex production data, external statistics on consumer behaviour, logistics movement or meteorology. Through this integration an AI algorithm may better forecast demand fluctuations and thus reduce costs than a closed data-process.

Achieving this though requires effective, secure and agreed interfacing between companies for large data-sets and complex pooled data processes. This digital interfacing is the focus of my current research efforts: https://interfacereasoning.com/  

(Banner image (CC) from Rept0n1x : Used with thanks).