Digital Social Innovation: Understanding business models across private sector, social enterprise and non-profit organisations

In this post I briefly outlines my plans for a research study of the business models that support and enable digital social innovation, as part of my broader ESRC funded fellowship project. As ever I am seeking to work in open and transparent manner, and I will continue to post updates on my blog as my research develops. I very much welcome feedback on this research outline, so please do get in touch with thoughts, comments and suggestions. Also if you are working on a digital social innovation and would be interested in participating in the research it would be great to hear from you.

Digital Social Innovation

Rapid advances in digital technologies are opening up new possibilities to catalyse social change, or in other words there are rapidly growing opportunities for digital social innovation. At its heart a digital social innovation is the novel application of digital technologies to better address a social need and to empower members of society[1] (The Young Foundation, 2012). Digital social innovations can emerge from any sector of the economy or from civil society, and seek to address major social needs such mitigating climate change, reducing social exclusion, improving education and access to knowledge etc. Examples include Wikileaks, Raspberry Pi and Kickstarter, but in a short research outline it impossible to do justice to breadth of innovative activity currently taking place.  Rather the Nominet Trust’s list of 100 of “The World’s Most Inspiring Social Innovations Using Digital Technology” remains an excellent resource for exploring the current and potential impact of the digital social innovation.

Research scope

In this research study I will explore the business models that underpin and enable the development of digital social innovations; defining a business model as describing how and why an organisation creates, delivers and captures social (and in some cases economic) value. The study will focus on the business models of private sector, social enterprise and non-profit organisations, and explore four interrelated themes as follows.

• Motivations for and mechanisms of social value creation - seeking to understand how organisations: formulate their social and customer value propositions, make the trade-offs (e.g. between social value creation and the financial position of the organisation), respond to competitive and collaborative dynamics, and evaluate and manage their social impact (including any potential downsides of their activities). 
• The system of activities orchestrated by organisations (Zott and Amit, 2010) - seeking to understand: which activities organisations include within their business models (e.g. developing web platforms, developing communities of users ...); how collaborators, customers and co-producers are involved in these activities; and which activities are central to business models for digital social innovation.
• The resources models of organisations – seeking to understand how organisations develop and draw up on financial, social (e.g. networks of contacts), cultural (e.g. skills and knowledge) and symbolic resources (e.g. the social purpose of the organisation) to develop digital social innovations.
• Patterns in business model design – seeking to understand the dominant drives of value creation in digital social innovation, and how business models designs vary with organisational scale and across sectors.

Research outputs

The research programme outlined in this document will deliver three key outputs: (1) two academic journal papers reporting the findings of the research; (2) a report for policy-makers and funders with interests in promoting digital social innovation, presenting evidence on the types of business models that enable digital social innovations to emerge, become sustainable and scale up; (3) a toolkit to support organisations and entrepreneurs engaged digital social innovation to review, design or re-design their business models.

Research approach

The research approach consists of two phases: first, a pilot project, the findings of which will inform the design and execution of a second larger scale phase research activity. The table below provides a high-level view of the timescales for the research. The pilot project will focus on better understanding the business models of organisations engaged in digital social innovation, which in turn will inform the design of the 2^nd phase of research. During the pilot project I will conduct semi-structured interviews with members of organisations engaged in the practice of digitally-mediated social innovation.  

Phase 1: pilot study
Research design for the pilot research project	March 2014
Data collection (approx. 5-10 interviews with members of organisations)	April – May
Data analysis	June
Reporting findings of pilot phase	July
Phase 2: larger-scale study	August 2014 – May 2015

References

THE YOUNG FOUNDATION 2012. Social Innovation Overview: A deliverable of the project: “The theoretical, empirical and policy foundations for building social innovation in Europe” (TEPSIE), European Commission - 7th Framework Programme Brussels.

ZOTT, C. & AMIT, R. 2010. Business Model Design: An Activity System Perspective. Long Range Planning, 43, 216-226.

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[1] This description of the nature of digital social innovation draws upon the work of the TEPSIE project that seeks to establish empirical and theoretical foundations for the study of social innovation.

Defining Digital Social Innovation

Rounding off my working year it seemed a good time reflect on my research to date on Digital Social Innovation. Offering my initial thoughts on a definition for Digital Social Innovation and hopefully complementing the exciting research going on elsewhere in this emerging field – e.g. the work of NESTA and others mapping digital social innovation across Europe. As an academic researcher I find it interesting that the concept of digital social innovation has emerged from practice. Developed and used by organisations such as the European Commission, The Nominet Trust and Google. Some of these organisations use alternative but equivalent terminology for digital social innovation such as ‘technology for good’, ‘social computing’ or ‘social tech’. Whilst from an academic perspective, the concept of digital social innovation has yet to become established within the literature. This of course provides some very intriguing avenues for research which I’ll be exploring over the next couple of years. Not least the addressing the challenges of adequately defining the term Digital Social Innovation. So here is my current by no means definitive sketch of a definition.

Digital Social Innovations are new solutions that meet a social need, more effectively than existing solutions, and are enabled by digital technologies. Simultaneously, DSIs enhance society’s capacity to act - leading to new or improved capabilities and relationships and better use of assets and resources – and transform existing socio-technical structures - by digitally mediating relationships and embedding digital artefacts.

This statement integrates aspects of established definitions for Social Innovation (The Young Foundation 2012) – emerging from the ground-breaking work of the TEPSIE project - and Digital Innovation (Yoo, Lyytinen et al. 2010). At this point it is worth briefly grounding this rather abstract discussion, by exploring the key components of the definition using Streetbank as an illustrative example.  

“Streetbank is a (web)site that helps you share and borrow things from your neighbours (e.g. drills, ladders, skills …). Streetbank is meant for everyone. It is not for private benefit - for individuals to make a profit or professionals to sell their services. It is for the common good.” - http://www.streetbank.com/faq

• A new solution that meets a social need: Streetbank is a new solution to the social need of developing social cohesion within neighbourhoods and communities. By enabling neighbours to share resources and get to know each other Streetbank seeks to make communities nicer places to live. In a neighbourhood where people borrow and share with their friends and family, and neighbours interact predominately face-to-face through ad hoc meetings, then use of Streetbank would be novel (i.e. a new solution).
• More effectively than existing solutions: in a neighbourhood where there is limited social cohesion Streetbank is likely to be more effective than relying on ad hoc face-to-face interactions alone (i.e. the existing solution).
• Enabled by digital technologies: the Streetbank website enables neighbours to share things, and view other the offers of people living with a 1 miles radius. Without the website it is challenging to see how the Streetbank concept could operate effectively.
• Enhance society’s capacity to act: the use of Streetbank with a neighbourhood leads an improved capability to share things, to new relationships forming between neighbours and to the things shared by neighbours being used more frequently (i.e. a better use of resources).
• Transforming existing socio-technical structures: the use of Streetbank changes the nature of the neighbour relationship. With the scope of the relationship being expanded to include someone identified and initially contacted via the Streetbank website (i.e. a digitally mediated relationship). So the Streetbank website (i.e. a digital artefact) itself becomes embedded within the socio-technical structure of the neighbourhood.

One of the challenges I have faced in forging a definition for Digital Social Innovation is that the terms Social Innovation and Digital Innovation both remain relatively hotly contested. With some pretty fundamental questions remaining open for debate and further research such as: is digital innovation a distinct form of innovation? What is the relationship between social innovation and technology or business driven innovation? At the moment though, I have taken a pragmatic decision to somewhat set aside the implications of such fundamental questions. Working instead to identify the core characteristics a Digital Social Innovation, alongside the characteristics one might frequently expect to observe. My initial thinking on these two sets of characteristics is shown in the diagrams below. Again here I draw on the work of the TEPSIE project (The Young Foundation 2012) and Yoo et al. (2010), adding insight from the literature on innovation in complex socio-technical systems (Geels 2005).

In concluding this blog it feels apt to consider my future research plans, via a little personal detour. On Sunday during a pre-Christmas family visit I was posed a tricky question (by my girlfriend’s father) – what are your big plans for 2014? I have to admit to struggling to summon an articulate response to this off the cuff, but after a little reflection research-wise (at least) I feel a vision is starting to come together. So now three months in to my 2 year ERSC Fellowship, I feel I have an exciting programme of research on Digital Social Innovation to pursue throughout 2014 (and beyond). This research will draws on and further develops the definition proposed above, and seek to address some tricky research questions including: What are the narratives, within the Social Innovation literature, on the relationship between the Social Innovation and Digital technologies? What examples exploring the relationship between digital technologies and social innovation exist? How to the digital and social aspects of Digital Social Innovation evolved together over time?

References

Geels, F. W. (2005). "The dynamics of transitions in socio-technical systems: a multi-level analysis of the transition pathway from horse-drawn carriages to automobiles (1860–1930)." Technology Analysis & Strategic Management 17(4): 445-476.

               

The Young Foundation (2012). Social Innovation Overview: A deliverable of the project: “The theoretical, empirical and policy foundations for building social innovation in Europe” (TEPSIE), European Commission – 7th Framework Programme, Brussels: European Commission, DG Research: 1-43.

               

Yoo, Y., et al. (2010). The Next Wave of Digital Innovation: Opportunities and Challenges: A Report on the Research Workshop 'Digital Challenges in Innovation Research.

               

Barriers to Open Government Data

Earlier in the year, as part of my on-going research on open data, I ran a survey exploring the barriers to open government data. More specifically, I was seeking to understand how the open data community perceived potential barriers to realizing value from open government data. The initial idea for research formed when reflecting upon my experiences working in ICT and innovation in the UK public sector - around the time (2009-11) that the open data agenda was starting to gain traction and profile in the UK. I felt the topic of barriers (although may be not as ‘glamorous’ as other areas of open data) was and remains an import area to explore. First, to better articulate the challenges faced by the open data community - as the initial wave of enthusiasm for open data is met by the practicalities of realizing its promise. Secondly, better articulation of the barriers will hopefully enable holistic, socio-technical approaches to overcoming these barriers to emerge. In this blog I present some of initial results of the survey, in a form that is hopefully useful to the open data community, and provide some personal thoughts on the implications of these results. First though, a little detail on the survey itself in order to place the rest of the blog in context.

During January and February 2013 survey participants were invited to review barriers to the supply and use of open government data, alongside crosscutting barriers spanning both the supply and demand sides. The barriers presented had been identified through analysis of policy documents and the academic literature, combined with observation of open government data events in the UK. The presentation below show the diversity of barriers considered including both social (e.g. the lack of a coherent vision for funding open data initiatives) and technical factors (e.g. ICT interoperability issues). 233 people participated in the survey from across the international open data community bringing perspectives from the public, private, academic and non-profit sectors. The majority of participants were involved in open government data in the Europe or North America, and fewer participants came from Africa, Asia and South America. Given that the open government data community is rapidly evolving and it is challenging to define its boundaries, at this stage I make no claims as to whether the participants are a representative sample of the wider community or not.

Some preliminary survey results

The survey participants tended to agree that the statements presented in the survey were (in his or her experience or opinion) barriers to realising value from open government data. This tendency, as shown in the graphs in the presentation below, at least to me is not too surprising for a couple of reasons. First, the open data agenda calls for large-scale social and technical change across multiple organisations with potentially competing interests (so it should be relatively easy to identify barriers). Secondly, the barriers presented in the survey are underpinned (to a greater or lesser degree) by evidence (so one might hope that participants would tend to agree with the current evidence). I now pick out three findings of interest from more detailed analysis of the survey results.

The open government data community seems focussed on supply side barriers, and is more sceptical about demand side barriers

The emphasis survey participants placed on barriers to the supply of open government data, seems to some extent to mirror the data-push perspective that underpins the open data agenda (i.e. make the data available and users will come). The prominence of supply side concerns is also clear within the survey results. With the strongest consensuses forming (i.e. where 75% or more of participants agreed the barrier existed) around five barriers on the supply side.

• Government organisations tend to have risk adverse cultures and so presume that access to data should be restricted.
• Individuals and groups within government organisations treat open data as an extra activity, rather than part of day-to-day activities.
• Government organisations lack a coherent vision for funding open data and promoting open data use.
• Government organisations face challenges establishing effective processes to engage with the diverse community of potential open data users.
• Open data requires change across multiple large organisations, and faces indifference and resistance from members of these organisations.

Conversely, the barriers that were viewed most sceptically (i.e. where 40% or more of participants disagreed and believed the barrier did not exist) all related to the demand for open government data.

• In Government organisations delivering open data the IT (Information Technology) costs are high.
• There is little demand from potential users across the private, public and civil society sectors for open data.
• The open data made available by government organisations is low value.

There are contentious issues around some politicised aspects of the open government data agenda

Opinion was more often divided where barriers related to the more politicised aspects of the open government data agenda. These contentious barriers (where 25% or more of participants agreed and 25% or more disagreed) relate to issues including public sector actors ‘profiting’ from the sale of data, restricted access to the digital infrastructure and conflicting public and private sector objectives.

• Government organisations will lose financial income by opening up data, as they currently generate revenue from some data
• Potential civil society open data users lack access to the digital infrastructure, financial resources and educational resources needed to make use of the data
• Private sector users focus on exploiting financial value from open data at the expense of exploiting social and environmental value

There are some differences in the perceptions of barriers to open government data across sectors

By comparing the survey responses from participants from the across public, private and non-profit sectors some interesting differences in perspective can be identified. Such differences highlight the potential for cross-sectoral learning and collaboration to better understand and address barriers to open government data. Two of the barriers where (statistically) significantly different perspectives were evident were:

• Government organisations face challenges balancing privacy concerns with the public interest when opening up data. Those working in the public sector where more likely to perceive challenges balancing privacy with the public interest than their private sector counterparts.
• There is little demand from potential users across the private, public and civil society sectors for open data. Those working in the public sector where more likely to perceive lack of demand as an issue than those working in the not for profit sector.

What to do about the barriers?

Although this research discussed above is still at an early stage, I conclude by offering two personal reflections on the potential implications of the results. First, the variety, complexity and number of barriers perceived by the open government community suggests the need for the action across the supply and demand sides. Such action should be informed by an understanding of the whole government data system including its social and technical facets. For example, the alignment of the open government data agenda with organisational goals, cultures and processes, need to be considered alongside technological and data concerns. Secondly, open data is an innovation in its own right and is in the early stages of development. This provides important context to the current emphasis on supply-side barriers, which indeed must be overcome to enable further exploration of the potential demand for open data. That said, for open data to make the transition from its current niche to creating a sustained mainstream impact, consideration of the demand side barriers is likely to become more prominent. It is this transition to mainstream impact that I plan to explore in research following on from the barriers survey.

If you are interested in further details please contact Chris Martin at c.a.martin@leeds.ac.uk or @chrismartin81.  I would particularly welcome thoughts and ideas on potential collaborations on a white paper on barriers to open government data and future work on pathways for open data.