Stakeholder Analysis of Open Government Data Initiatives

Many different actors are involved in open government data (OGD) initiatives, and it can be hard to understand the different roles they play.

Stakeholder analysis can help, such as mapping onto a power-interest grid (see example below).  This analyses stakeholders according to their power to impact the development and implementation of open government data, and their level of interest in OGD.  The former measured via a typical sources-of-power checklist: reward, coercive, legitimate, expert, personal, informational, affiliative.  The latter measured via text analysis of stakeholder statements.

Primary stakeholders are “those who have formal, official, or contractual relationships and have a direct and necessary… impact” (Savage et al., 1991:62). Others who affect or are affected by OGD but less formally and directly and essentially, can be categorised as secondary.

Applying this to Chile’s open government data initiative produced the mapping shown in the figure.

 

We can draw two conclusions.  First, that OGD in Chile has been mostly determined from within government. Second, that it has otherwise been shaped rather more by international than national forces.

Three absent stakeholders can be noted:

• The local private sector is not an active part of the ecosystem at present, restricting options to derive economic value from OGD.
• Citizens are not active in discussion or use of open government data, restricting options to derive political value from OGD.
• Multinational firms and investors are not directly involved, but have a tertiary role: they are an audience to whom the presence and progress of OGD is sometimes projected.

In sum, this is an “inwards and upwards” pattern of open government data which is shaping OGD’s trajectory in the country.  Government is the “sun” and other stakeholders merely “planets”, so that perspectives and agendas within government dominate. One agenda is to broadcast signals of democracy to the outside world.

In facing “upwards” to these external stakeholders, what matters most is an appearance of transparency. This can be satisfied by the presence of datasets, some empowerment and accountability rhetoric in pronouncements, and membership of the Open Government Partnership and adherence to its minimum standards. This is not to say that government stakeholders care nothing for delivery of results; simply that the external audience-related incentives are much stronger for appearance than fulfilment.

Stakeholder analysis should therefore be a fundamental tool for open government data researchers and practitioners; helping them to understand the identities, strengths and weaknesses of key OGD actors.

This research is reported in more detail in: Gonzalez-Zapata, F. & Heeks, R. (2015) The multiple meanings of open government data: understanding different stakeholders and their perspectives, Government Information Quarterly, 32(4), 441-452

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The Multiple Meanings of Open Government Data

Many different stakeholders are engaged with open government data (OGD) initiatives, and they understand OGD differently.  In what way?

Recent research from the University of Manchester’s Centre for Development Informatics identifies four different perspectives that derive from OGD’s conceptual foundations (see figure):

• The bureaucratic perspective – associated with ideas of government data – sees OGD as a government policy that uses greater data management efficiency and effectiveness to improve public service delivery.
• The technological perspective – associated with ideas of open data – sees OGD as a technological innovation that improves the functional qualities of government data infrastructure.
• The political perspective – associated with ideas of open government – sees OGD as akin to a fundamental right that will empower citizens and improve transparency and accountability of government to citizens.
• The economic perspective – emergent from the ideas of open government data itself – sees OGD as a means to create additional economic value through new products and services.

This perspectives model was applied – via template analysis of text from reports and interviews – to analyse open government data in Chile, which was one of the second cohort of Open Government Partnership members.

Analysis showed a dominance of bureaucratic and political perspectives. The technological and economic perspectives are present but they are not really incorporated into the mainstream discourse around policy and strategy on OGD in Chile. This reflects the lack of voice for technical experts and private firms within that discourse.

Looking at the two principal perspectives, there is the sense of a mirror image. The bureaucratic perspective is strongest within government and is shared to some degree by international organisations and local activists. The political perspective is strongest outside government via international organisations and local activists and is shared to some degree by government stakeholders.

Within government, the political perspective is used particularly for outwards messages around the values of OGD that are broadcast to international stakeholders.  But the bureaucratic perspective prevails in internal discourse around the administration and implementation of OGD.  With the bureaucratic perspective therefore dominating implementation, it can be argued that the political perspective reflects aspiration but the bureaucratic perspective reflects reality; a reality that has therefore not yet fully delivered on the political or economic potential of OGD.

Using this analytical model as a lens to examine specific OGD contexts will help those involved understand themselves, those they work with, and how best to manage the different identities and values of all OGD stakeholders.  We therefore invite others to repeat this perspectives analysis in other countries.

This research is reported in more detail in: Gonzalez-Zapata, F. & Heeks, R. (2015) The multiple meanings of open government data: understanding different stakeholders and their perspectives, Government Information Quarterly, 32(4), 441-452

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Actor-Network Theory, Technology and Development

What can actor-network theory offer to our understanding of technology and development?

This blog entry summarises the answer from an open access paper in the journal Development Studies Research: “Technological Change in Developing Countries: Opening the Black Box of Process Using Actor–Network Theory”, and it builds on an earlier entry on ANT and development.

Technology rather dropped from the development agenda during the 1980s and 1990s, but has re-emerged strongly in the 21^st century; not least due to the spectacular diffusion of ICTs.

Yet, to date, conceptualisation of technological change in developing countries has had three problematic gaps:

• It has been de-humanised: organisations are recognised as actors but people – as identifiable individuals with agency – rarely appear in the technology and development literature.
• Technology may be understood as a physical artefact, as a system of elements, as the embodiment of knowledge. But it is not seen as playing any active role: technology is acted-upon but is not itself acting.
• Research has tended to study factors or social structures affecting processes of technological change. But it does not describe those processes in detail: actual practices of change tend to be black-boxed.

In sum, research to date has typically stood outside the technology processes it seeks to investigate; freezing them in time and concealing their main actors.

As luck would have it, these are just the kind of lacunae that actor-network theory was intended to address.  Yet application of ANT to cases of technological change in developing countries has been rare; and within development studies literature, almost non-existent.  So new ANT-based case studies of technology and development are required to assess what insights actor-network theory can offer.

One such case study – applying Callon’s “moments of translation” to a digital information system in the Sri Lankan public sector – is presented in the Development Studies Research paper (which should be accessed for full details).  It finds that an initial network supporting technological change fell apart in mid-project, and had to be reconstructed around a new technology design and a new vision for future change.

Three challenges emerged in applying ANT:

• Methodological: admission of subjectivity in framing an ANT-based case, and problems of thinning out detail to fit a journal-length account.
• Analytical: that ANT can provide a rich description of how things happen, but stutters in seeking to analyse why.
• Instrumental: the difficulty of extracting practical guidance from ANT other than rather “Machiavellian” prescriptions.

On the other hand, the case analysis shows that ANT can open the black box of technological change processes and offer new insights:

• Networks: explaining the networks of relations that both support and oppose technological change, and also the detailed process by which they come to be formed, dissolved, etc.
• Technology: exposing the active role that technology plays in international development – shaping, enabling, co-operating, resisting, etc.
• Human practices: providing a detailed account of the role played by individuals and groups in technological change; particularly the way in which lead actors modify the perceived interests and even identities of others involved.

ANT therefore shows us not just that human interests, identities and relations change in a technology-and-development project; it also explains in what way they change, how it is that those changes come about, and how they relate to the project’s trajectory.

The case analysis shows that ANT will not help answer questions about the impact of context on technological process, or about the developmental impact (in the traditional sense) of technology. However, it may help to answer questions such as:

• How do we explain the trajectory of a technology and development project?
• How does a particular innovation in a developing country diffuse, scale up or sink without trace?
• What role does technology play in processes of technological change?
• How does power manifest itself in such processes? How are apparently relatively powerless actors sometimes able to influence the direction of technological change? How are apparently relatively powerful actors sometimes not able to get their way on a technology project?

As the technology used in development becomes more complex, more interconnected, more intertwined into the lives and livelihoods of developing communities, and changing at an ever-faster pace; then ANT will likely become more relevant and more useful as a conceptual frame.

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A Better e-Government Maturity Model

e-Government develops over time.  Researchers want to track this; practitioners want to benchmark where they are in relation to others.  The result has been the development of e-government maturity models.  But there are difficulties with the most popular models, and here I propose an alternative.

There are many e-government maturity models: Fath-Allah et al (2014)[1] provide a helpful overview that identifies and then analyses 25 different models.  By far the best-known is Layne & Lee’s (2001)[2] four-stage model (see below): not just the most highly-cited model but the most highly-cited of all e-government papers.

This foundational model has been revised (e.g. Andersen & Henriksen 2006[3]) and revisited (e.g. Lee 2010[4]).  Drawing on this past literature but also additional insights, three key challenges to the Layne & Lee model can be identified:

1. US-centricity. All models are a product of their context. Layne and Lee’s model derives solely from e-government experience in the US.  As a result – even 15 years after its development – the model focuses mainly on higher levels than actually achieved by most governments worldwide; at least judged on the basis of the UN e-Government Survey (e.g. UNDESA 2014[5]).

To address this, it will be useful for a revised maturity model to disaggregate two pre-transactional stages; one related to one-way publication of government information; one related to two-way interactive capabilities of e-government.

2. Beyond Integration. All models are a product of their time. At the time Layne and Lee were writing, it was perfectly reasonable to identify integration – joining up e-government services vertically across levels of government, and horizontally between sectors of government – as the pinnacle of e-government’s achievement: the completion of all of a citizen transaction online.  Subsequently, however, e-government has moved beyond this.  Maturity model designs that move beyond integration are therefore the focus for a number of the revisions charted by Fath-Allah et al.

One example now visible is government undertaking a transaction proactively; e.g. proactively reissuing a passport when the old one nears renewal or an auto license with payment set up via an automatic direct debit mandate.  Or, governments now customise processes so that services are individualised; e.g. providing personalised information matched to the known needs of the individual citizen.  Or, governments may even eliminate a process, no longer requiring anyone to do it; e.g. government proactively issuing a birth certificate from hospital records so the citizen no longer needs to register a birth.

These types of further development need to be incorporated into any revised maturity model.

3. Disaggregated Dimensions. All models are a product of their mindset. Not just the Layne and Lee model but also its suggested  variants have a single-path perspective on e-government maturity.  At first glance this can be hard to notice since the Layne & Lee model plus some variants is illustrated within a two-dimensional space.  But that space is not used: these models are functionally-equivalent to a one-dimensional ladder model.

As a result, there is no differentiation between the “front-office” nature of the interface / interaction, and the “back-office” nature of the underlying process.  Yet these can progress at different rates.  Some e-government applications are quite transactionally complex but not integrated with other services.  Other e-government applications – such as a number of government portals – are simple in interactional terms but integrate across all of government.

A revised maturity model should take this into account, and provide a truly two-dimensional space within which e-government can mature.

The Manchester e-Government Maturity Model

The Manchester e-Government Maturity Model seeks to incorporate the responses to these three challenges:

1. It reflects current global realities of e-government by having separate categories for “Informing” (one-way publication of information) and “Interacting” (two-way communication between government and users).
2. The extent of change in underlying government processes includes the Layne and Lee components via categories of “Digitisation” (simple automation of existing processes) and “Improvement” (bringing processes together via horizontal or vertical integration). But it then moves beyond these to more fundamental process change via categories of “Redesign” (such as proactive or customised transactions) and “Transformation” (complete reworking of processes such as their elimination or reversing from government- to citizen-led).
3. Delinking front-office interaction from back-office process change.

The figure below shows the model, including some examples at various different points in the maturity space; with growing maturity understood to be movement from bottom to top, and left to right.

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[1] Fath-Allah, A., Cheikhi, L., Al-Qutaish, R.E. & Idri, A. (2014) e-Government maturity models: a comparative study, International Journal of Software Engineering & Applications, 5(3), 71-91 http://airccse.org/journal/ijsea/papers/5314ijsea06.pdf

[2] Layne, K. & Lee, J. (2001) Developing fully functional e-government: a four stage model, Government Information Quarterly, 18(2), 122-136

[3] Andersen, K.V. & Henriksen, H.Z. (2006) e-Government maturity models: extension of the Layne and Lee model, Government Information Quarterly, 23(2), 236-248

[4] Lee, J. (2010) 10 year retrospect on stage models of e-government: a qualitative meta-synthesis, Government Information Quarterly, 27(3), 220-230

[5] UNDESA (2014) United Nations e-Government Survey 2014, UN Department of Economic and Social Affairs, New York, NY http://unpan3.un.org/egovkb/Portals/egovkb/Documents/un/2014-Survey/E-Gov_Complete_Survey-2014.pdf

The Curse of Hyper-Transparency

Openness and transparency are good things and the more we have of them the better.  Right?  Wrong.

In contexts of too little openness – “hypo-transparency” – ICTs can help bring greater transparency, with positive developmental effects.  But in contexts of relative openness, ICTs are ushering in a hyper-transparency that will destroy public institutions.  As summarised in the figure below, I therefore propose an inverse-U relation between e-transparency and various measures of political development, such as trust in public institutions.

As an experiment, try the following.  View your beloved from a very far distance.  They are a tiny speck, and you feel nothing for them.  Now move closer to view them from a few feet away.  Likely you will see much to admire and feel a warm glow (if not, it may be time for an upgrade).  Now get up really, really close and examine them in minute detail – take a look up their nose, in their ears, inside their . . . well, you get the idea.  That glow’s probably not quite so warm now, is it?

Something similar happens with ICTs and transparency.  Applied in corrupt, opaque, self-serving environments, ICTs have been shown to reduce corruption and improve the efficiency and equity of practice.  But applied further in democratic environments where a reasonable degree of e-transparency and openness already exists, ICTs can make things worse rather than better.

Through greater e-transparency, ICTs help us know ever-more about the behaviour (decisions and actions) of those within public institutions.  The majority of that behaviour will be appropriate.  But humans are flawed, so they will always make mistakes, act selfishly, and do bad things.  Absent other effects, the greater the transparency, the greater the absolute amount of such inappropriate behaviour that will be revealed, and the less citizens will value and trust public institutions.

Any effects of transparency in reducing the amount of behaviour that is inappropriate are mitigated both internally and externally.  Internally, transparency pushes institutions to spend increasing time on non-value-adding defensive activities.  These include trying to second-guess and avoid what might cause offence or other negative public reaction; excessive caution in behaviour to avoid risk or failure; and inefficiencies in protecting necessary confidential interactions – the “safe space for genuine deliberation” – from external gaze.  Yet, “without the exchange of confidences, it is not possible for people to have real confidence in their colleagues and in the organisations that employ them”[1].

Externally, ever-greater flows of e-transparency data undermine public institutions because of . . .

• Cognitive deficits: the greater the flow of data, the lower the absolute availability of knowledge and motivation among the public to properly interpret that data, leading to a dominance of simplistic interpretations, many of which are negative because of . . .
• Cognitive bias: the negativity bias that causes humans to attend more to bad than good news, to remember bad more than good news, and to form negative stereotypes more quickly which are more resistant to disconfirmation. And the tendency, for example when searching online, to attend to extreme rather than average data.  Extreme and negative interpretations of data on public institutions become more prevalent because of . . .
• Political incentives: attention and profile online accrue to those who posit more extreme views, and there are plenty of commentators who have political or economic incentives to criticise current public institutions and who – within already-relatively-open contexts – are able to do so. They have an ability to shape the narrative in part because citizens give up their own interpretation due to cognitive deficits.  And thus we have a self-reinforcing spiral.

The impact of this can be seen, for example, in the decline of trust in public institutions in democracies during the Internet era.  Dating this from the turn of the century, some illustrations:

• A decline in trust in the European Union from 40% to 30%.
• A decline in Americans’ confidence in Congress from 27% to 7%.
• A halving of Americans’ confidence in news media.

Of course e-transparency is not the only factor behind trust, but a review of some key literature finds little evidence that transparency builds trust.  Instead, “in a number of cases, the evidence points in another direction: that is, transparency may ultimately decrease trust”.

This has a number of negative knock-on consequences if lack of trust leads to calls for greater transparency which leads to a further erosion of trust.  With only a minority – sometimes a small minority – of citizens trusting institutions, those institutions are weakened in their ability to defend the public realm and public interests.  And we see a shift in power from public to private institutions, and from centrist to more extreme political views and parties.

Is this an argument against e-transparency?  It is not.  But it is an argument that:

1. We are guided by the inverse-U curve to give highest priority to using ICTs to open up the most-powerful, least-transparent institutions. That means authoritarian regimes and transnational corporations.  Oh, and FIFA.  Don’t applaud Edward Snowden until he exposes the workings of the 3PLA, or Julian Assange until he leaks the tax avoidance plans of global IT firms.  If you want a transparency hero, pick Herve Falciani.
2. We place greater emphasis on accountability than transparency. Transparency, in Furedi’s words, fosters “a political culture of voyeurism”.  Accountability – at least when properly designed – fosters reasoned, considered checks and balances against abuse of power.
3. We accept there are limits to openness, and that we want transparency but not hyper-transparency: “A democratic society should understand that it is important to uphold the right to the private exchange of views and that not everything officials do ought to be visible to all”[2].

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[1] Furedi, F. (2011) Let’s stop kowtowing to the cult of transparency, Spiked, 5 Oct http://www.spiked-online.com/newsite/article/11140

[2] Furedi ibid.

Steering e-Government Projects from Failure to Success

How do you turn a relatively unsuccessful e-government (or ICT4D) project into a relatively successful one?

There’s not a lot of guidance on this question.  Lists of success and failure factors are generic rather than specific to any one project, and need to be analysed before the project starts.  Evaluation methodologies focus more on impact than implementation, and generally apply only after the project has ended.

What is needed is a “mid-implementation toolkit”: something that will both analyse where you’ve got to in the project, and recommend an improvement action plan for the future.  Researchers working alongside an Ethiopian e-government project have recently published the results of testing just such a toolkit.

Using the “design-reality gap” framework, the researchers gathered data from four different stakeholder groups involved with the e-government project, which had introduced a land management information system into one of Ethiopia’s city administrations.  The system was only partly operational and was not yet fully integrated into city administration procedures: it could therefore be described as a partial failure.

The design-reality gap framework helps measure any differences that exist between the project’s initial design expectations and current implementation realities.  It does this along seven dimensions (see figure below).

Where large gaps are found, these highlight the key and specific problem areas for the project.  In this particular e-government initiative, significant design-reality gaps were identified in relation to:

• Management systems and structures (a failure to set up an ICT department and to hire permanent IT staff).
• Staffing and skills (hiring only five of the required nine IT staff, and undershooting the necessary qualifications and experience).
• Project objectives and values (allowing some culture of corruption to remain among lower-level administrators).
• Information systems (absence of one core system module and of digitised documents).

These gaps demonstrated that the e-government system had not yet institutionalised within the city government.  The gap analysis was therefore used as the basis for a discussion with senior managers.  From the analysis and discussion emerged two things.

First, identification of small gaps that had lain behind the partial success of the system – the commitment of project champions, process re-design being conducted prior to introduction of new technology, and stability in the information that was digitised onto the e-government system.

Second, identification of an action plan that would close the main extant gaps between design and reality: creating the proposed new ICT department, hiring additional IT staff, and setting up permanent positions with clearly defined salary scales and promotional criteria. These, in turn, would provide the basis for implementing the missing module, and scanning the missing legal documentation.

Not all the gaps can readily be closed: it will take a much longer process of cultural change before the last vestiges of corruption can be eliminated.  Nonetheless, design-reality gap analysis did prove itself to be a valuable mid-implementation tool.  It is helping steer this e-government project from partial failure to greater success.  And the authors recommend its use by e-government managers as they implement their projects: it has helped to focus management attention on key e-government project issues; it digs beyond just technical issues to address underlying human and organisational factors; and it offers a systematic and credible basis for project reporting and analysis.

Feel free to comment with your own experiences of design-reality gaps, or other mid-implementation techniques for e-government project analysis and improvement.

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e-Government Benefits And Costs: Why e-Gov Raises Not Lowers Your Taxes

Often, IT companies sell e-government to politicians, and politicians sell e-government to citizens on the promise that it will save money.  These claims regularly appear as “news” items, especially in IT- or government-related media.  This has in part encouraged the huge expenditure on e-government: a ballpark figure would be US$3 trillion during the first decade of the 2000s[1].

So here’s my question: “If e-government is so great at cutting costs, how come my taxes haven’t gone down?”

Of course, taxes depend on far more variables than just e-government.  But the simple answer to the question is “. . . because e-government does not save money, it costs money”.  That seems likely the case in the global North where e-government seeks to cut costs by replacing expensive humans with cheap technology.  It is most definitely going to be the case in the global South where the technology is more expensive and the humans are much cheaper.

Despite the obvious importance of the topic, good quality cost:benefit calculations are rare but can be found.  Six years of e-government in UK local government saw £3.90 billion of investment release just £0.97 billion of savings[2].  The aggregate cost:benefit ratio of e-government projects in Australia was 1.64:1[3].

Rarer still is good quality work from developing countries.[4]  However, a recently-published study of e-government in Bhutan by Mayumi Miyata provides a model for systematic and comprehensive evaluation of e-government costs and benefits. The case study focuses on the Road Safety and Transport Authority of Bhutan, which issues driving licences and vehicle registration documents.  This was traditionally a paper-based process, and often slow; particularly for driving licences which had to be sent by post from regional offices to the head office in Thimphu.  In the mid-2000s, an Internet-enabled database system was installed so the main information associated with these processes could be passed instantly between offices.  (This was therefore an “e-administration” application for use by government staff rather than an “e-services” application for use by citizens.)

Data for Miyata’s research was gathered both before and after the introduction of this e-government system including detailed observation and timing of work processes, a breakdown of departmental accounts, and a survey of citizens.  The “after” component was undertaken in 2007; two years after implementation of the system, allowing plenty of bedding-in time.

Activity-based costing showed that the direct labour cost for issuing licences and registrations fell 24% following introduction of e-government; from US$15,080 to US$11,530 per year[5].  For example, the direct cost of issuing one driving licence fell from US$1.57 to US$1.17.  This was achieved largely through a significant redesign and decentralisation of internal decision-making and workflow.

However, introduction of e-government brought additional costs – hardware, software, internet connectivity and the cost of IT staff – totalling US$11,080 per year (set-up costs being amortised over 10 years).  The only indirect saving was in reduced postal cost (US$720).  Thus, overall costs were US$15,800 per year before e-government; US$22,610 after e-government.  A rise of 43%.

We need to recognise some specific features of this case that make it typical of a least developed country:

• the particularly low labour costs and high IT costs;
• the relatively low volumes of transactions across which costs can be spread (the case is more akin to a local than national government in size);
• the use of e-administration rather than a web-based self-service system which, while still requiring human back-office intervention, would automate some processes.

Miyata’s research thus provides a model that should be replicated for a broader set of examples.

On the other hand, Miyata’s work misses out three additional reasons why e-government globally fails to deliver cost savings:

• the relatively high rate of e-gov project failure, the costs of which must be included in any overall cost:benefit accounting[6];
• the learning curve – often of some years – that must be traversed before e-government applications can be used efficiently and effectively[7];
• the need for government e-services to be run in parallel with existing face-to-face, phone and postal service channels in order to bridge the digital divide and avoid excluding large sections of the population from access to government services; public e-services thus being a supplement to, not substitute for, other channels[8].

Does this mean e-government is a waste of money, and we should ask for our US$3 trillion back?  No.  What it means is that e-government is not going to save money for government and help bring taxes down.  The benefits of e-government lie elsewhere.  Again, Miyata’s paper is a good illustration:

• External savings: the lead time from application to receipt was reduced by minutes, weeks, even months for outlying offices.  Wait times in offices may also have come down.  Other studies report shorter waits and fewer journeys.  Saving of journeys can be monetised, and saving of citizen time might be (it depends how that saving is spent).  The key cost savings of e-government may thus be external not internal: for service users not administrators.
• Internal control and accountability: e-government provided managers with greater oversight of work processes and staff.
• Service quality and equity: citizens reported the quality of service and the fairness of treatment improved after introduction of e-government.

Other research shows further qualitative and external benefits delivered by e-government including: greater transparency of public services; greater accountability of public servants and politicians; reduced corruption; lower costs for business; greater attraction of foreign investment[9].  Please comment to add your own examples of evidence.

So e-government may not bring your taxes down, but – if properly designed and implemented – it will bring a positive economic and social return on investment.

 

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[1] Heeks, R.B. (2006) Managing and Implementing eGovernment, Sage, London http://books.google.com/books?id=hRzAnMulatUC&dq; WITSA (2008) Digital Planet 2008, World IT Services Association, Kuala Lumpur, Malaysia; see: http://www.witsa.org/KL08/DigitalPlanet2008_ReportTables.pdf

[2] Kable (2005) Implementing Electronic Government 4, Kable, London

[3] Foley, P. & Ghani, S. (2007) The Business Case for e-Government, paper prepared for High-Level Seminar on Measuring and Evaluating E-Government, Dubai, 12-13 March http://www.oecd.org/dataoecd/44/42/38404094.pdf

[4] There is a good study of e-government projects in India but it was unable to capture cost data, so focuses only on benefits.

[5] These are costs for issuing just over 31,000 documents.  Note this excludes the cost of materials for licences/registrations, which was the same before and after e-government.

[6] Heeks, R.B. (2006) Managing and Implementing eGovernment, Sage, London http://books.google.com/books?id=hRzAnMulatUC&dq; Gauld, R. & Goldfinch, S. (2006) Dangerous Enthusiasms: E-Government, Computer Failure and Information System Development, University of Otago Press, Dunedin, New Zealand

[7] Poostchi, M. (2003) Implementing E-government, MBA dissertation, Carleton University, Ottawa, ON

[8] Helbig, N., Gil-Garcia, J.R. & Ferro, E. (2009) Understanding the complexity of electronic government, Government Information Quarterly, 26(1), 89-97

[9] Accenture (2004) eGovernment Leadership: High Performance, Maximum Value, Accenture, Dublin; Bhatnagar, S. & Singh, N. (2010) Assessing the impact of e-government: a study of projects in India, Information Technologies and International Development, 6(2), 109-127 http://itidjournal.org/itid/article/viewFile/523/231

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The First e-Government Research Paper

Who wrote the first research paper about e-government?

I’m going to nominate W. Howard Gammon writing in Public Administration Review in 1954.  Please comment with earlier nominations, but otherwise, W. Howard Gammon becomes the godfather of e-government research.

Of course Gammon’s review article: “The Automatic Handling of Office Paper Work” doesn’t mention e-government: according to Heeks & Bailur’s “Analyzing e-Government Research”, “The term ‘electronic government’ seems to have first come to prominence when used in the 1993 U.S. National Performance Review, whereas ‘e-government’ seems to have first come to prominence in 1997.”

However, Gammon is writing about the use of ICTs in the public sector: which is a common definition of e-government.  Hence, his is an article about e-government, even though computing was just in its infancy with, as he notes, some technical literature available but very little written for a management audience and nothing – until his review article – for a public management audience.

In some ways things were very different then.  Even by around 1990, there were more than 1 million computers in use across the US federal government.  Back in 1954, there were roughly forty computers installed in total, half “large-scale” such as the UNIVAC I (weight 13 tonnes, c.2,000 operations per second, memory <1kb; cost c.US$10m in today’s terms) and half punch-card-based “baby computers” such as the IBM-604 (c.100 cards per minute, program of up to 40 steps, monthly rental cost c.US$5,000 in today’s terms plus a shift team of 2-10 supervisors and operators).  Most were in the Department of Defense with a few in the Atomic Energy Commission, Census Bureau and Bureau of Standards.  There was a pilot application to automate selection of optimum procurement bids, and plans to apply computers for use in air traffic control, taxation and weather forecasting.  These applications were part of a broader expenditure (in 1952) of more than US$1.5billion (c.US$12billlion in today’s terms) on “adding, accounting and other business machines” within US public and private sectors combined; by 2008, total spending on ICTs in the US was roughly US$1.2trillion annually – a one hundred-fold increase in spending on ICTs.

However, the more striking thing that echoes across the decades is not how different but how similar the issues in the 1950s were to those we still face today.  The following examples illustrate:

a) Skill Set: E-Gov Needs Systems Skills More Than Technical Skills: “…it is not necessary to know how to make, or even to repair, these machines in order to make use of them.  For the public administrator … the emphasis needs to be placed on how and when to use these new devices” (p63).  Just so, for those learning today about e-government, understanding technical aspects is of relatively limited importance; much more important is to understand the application of the technology.  Put another way, e-government must be approached from an information systems not an information technology perspective: “it is a systems job which depends more on knowledge of what must be done, and why, than on knowledge of what makes electronic computers tick.” (p73).

b) Skill Set: E-Gov Needs Hybrids: a socio-technical approach is required that combines understanding of the ‘business’ of government with knowledge about the application of technology.  Such a combination could be undertaken within a team: a “joint effort between the business managers and the engineers, so that engineers may learn enough about the businessman’s problem to translate the requirements of the job into machine procedure and so that management staff may learn enough about the capabilities and limitations of electronic machines to allow management staff to visualize how the new devices can be applied and how the … organization must be changed to take full advantage of the capabilities of the new equipment.” (p67)  Such a combination might also be effected within a single person to create a socio-technical “hybrid” individual.  But in that case, it will be far easier to hybridise a mainstream manager than an IT person: “As the Metropolitan Life Insurance Company found in its study, it is far easier to teach company management specialists what they need to know about the possibilities and limitations of electronic data processing than it is to teach electronic engineers about the internal operating problems of the life insurance business.” (p73).  The exact same findings were reported in the 21^st Century for e-government in Chapter 12 of Heeks’ book “Implementing and Managing eGovernment”.

c) Implementation: E-Gov Needs Re-Engineering Not Just Automation: More than thirty-five years before Hammer’s exhortations to stop “paving the cowpaths” and stop “automating the mess”, Gammon had already identified the limited gains to be made from automation, and the need to start improvements by re-engineering the business processes of govenrment: “One quick generalization may be made: the introduction of an electronic information processing system is not like buying a new adding machine which can be plugged in as part of an existing established clerical routine. It would be foolish and wasteful to make the large investment required to install electronic methods without first conducting a careful study which begins with considering the basic objective of the operation” (p73) … “The effective application of electronic methods in a given organization requires a rethinking of its organization and procedures. When electronic methods are applied, many of the intermediate reports and steps in the transmission of information become unnecessary and should be eliminated.” (p72)

d) Implementation: E-Gov Needs Top Management Support: “Rapid progress can be made during such an investigation only if the management representatives are high enough in the organization to make the broad decisions regarding the methods of operation” (p67).  In the same way, more recently, top management support is still identified as a key necessity in successful e-government projects and its absence as a key cause of e-government project failure.

e) Implementation: Politics Matters in E-Gov: “there are organizational, procedural, economic, and social problems which must be resolved before automatic operation of … an office can be realized.” (p63).  Some of these problems relate to internal politics given the danger that ICTs in government will cause “the disturbance of established bureaucratic empires” (p72), thus making political factors an important cause of e-government failure.  This further explains why top management support is needed in implementation of e-government: “It also requires a broad point of view which looks to the good of the organization as a whole without being too much concerned about the effects of changes in methods on particular vested interests in the agency.” (p73).

f) Impact: E-Gov Affects Clerical Not Professional and Managerial Jobs: for lower-level clerical jobs, ICT brought the threat of “lowered prestige, relative decrease in real income, threat of unemployment, and routinization of many office skills” (p66).  That has come to pass: around 25% of federal white-collar employees were in clerical/typing work in 1952.  By the mid-2000s that had fallen to roughly 7%, largely as a result of new technology[1].  Meanwhile, skilled professionals would either be upskilled: “our accountants will then be free to do the more important job of analyzing and interpreting financial reports for management.” (p66) or unaffected: “there is no real possibility that the executive or the top administrator will become obsolete as the result of foreseeable advances in the use of electronic equipment.” (p73).  And there were already signs that shortages of ICT professionals would slow the rate of e-government: “the shortage of qualified experts to design, build, program, and service these electronic data processing systems will keep this possible revolution from taking place rapidly.” (p67).  More than fifty years later, Heeks (2006:101) still writes “The dearth of competencies is a major brake on the spread of e-government”.

g) Impact: E-Gov Impact Assessment Fails to Account for Total Cost of Ownership: there have always been ambitious claims for ICT in government e.g. that it “can make substantial savings and render better service” (p63).  But on the savings side, e-government impact calculations often focus just on cost savings (e.g. of labour) but fail to include the costs of ICT.  When the latter are taken into account, overall gains can disappear.  Gammon’s paper is suggestive of this: he reports a case where preparation time for monthly reports fell from forty person-days to six/eight hours.  Given clerical costs (in 1954 prices) of around US$200 per month, that would represent savings of about US$400 per month.  Yet according to P.B. Hansen in “Classic Operating Systems” the IBM Card Programmed Calculator on which this saving was achieved cost US$1,800 per month in rental to which would have to be added the costs of calculator operations staff.  Government’s tendency for lavish spending on ICTs was also already in evidence with reference to a Navy-organised symposium on “moderately-priced” computers; that criterion being defined as those costing (in today’s terms) less than US$1million.

Gammon’s paper is as much a review of then-current ideas about computing, drawn largely from the private sector, for a public sector audience as it is about computing in the public sector.  However, this focus means it still stands eligible for recognition as the first e-government journal article.

How, overall, should we read it?  I invite you to choose from its reflecting:

– “La plus ça change, la plus c’est la même chose”

– The failure of e-government practitioners to take note of key lessons known right from the start of IT in the public sector, given the continuing absence in e-government projects of many of the skill and implementation factors identified all those years ago.

– The failure of e-government researchers to find much new to say: you can see these same issues still in the conclusions of many of today’s e-gov journal articles.

Click here to link to a blog entry on the first application of e-government in a developing country.

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[1] Though total US federal employment in 2009 – just under 2.1 million – was almost exactly what it was in 1952; albeit with a near-halving in DoD numbers.

Understanding ICT4D Adoption via Institutional Dualism

Sometimes with ICT4D projects, you build it and they don’t come.  Why is that?  Why do potential users resist, object, reject?

One explanation comes from the concept of “institutional dualism”.

First developed to explain how Japan reacted to the import of Western ideas and technologies in the 19^th century, this can also be used to understand any innovation – including ICT4D initiatives – in which there is some separation between designers and intended adopters.

Each of those two groups sits within its own institutional network: a complex of institutional elements (e.g. norms, rules, beliefs, values) and organisations and actions.  Left to its own devices, any institutional network will tend to “self-reproduce”.  For example, its cultural values will encourage particular actions, and those actions will in turn reinforce the network’s cultural values.

But innovations like an ICT4D application will bring two different institutional networks – those of the application designers, and those of the application adopters – into contact.  We can call this institutional dualism because of the two institutional networks that come into play (see figure).

A strong example of institutional dualism would occur if a team from a European university designed an ICT4D application and then introduced it into a rural location in Africa.  The European designers’ behaviour is enabled by a set of Western organisations and shaped by a set of Western institutional forces, some of which will be inscribed into the ICT4D application.  During implementation this network is drawn into contact with the very different network of rural Africa, with different organisational structures, behaviours, and institutional forces.

Many ICT4D projects will be a bit less starkly drawn than this, but will still involve institutional dualism because designers and adopters almost always come from different places and different spaces.

What then happens?  There are four possible outcomes from a situation of institutional dualism:

• Domination: one of the institutional networks prevails over the other in the ICT4D project.  If the designers dominate, the project could fail due to its mismatch to the broader local context.  If the adopters prevail, that requires a complete re-design of the project to have occurred.
• Contest: neither of the institutional networks prevails, but there is ongoing competition between them.  The ICT4D project may stagger on, but always in difficulty as it is pulled in two different directions.
• Parallel-Running: a separation is arranged with some aspects of the project guided by the designers’ institutional network, some by the adopters’.  This is only possible where the ICT4D project has a broad flexibility and scope.
• Hybridisation: the ICT4D project becomes the site within which the two institutional networks blend, forming a mixture of institutional values and hence a set of hybrid actions within the organisational structure of the project itself.

Of these four, only hybridisation and some types of domination are likely to lead to a sustainable ICT4D project.  We have seen this in practice with a large-scale ICT4D case study of institutional dualism from the Brazilian public sector.  Although giving some outward signs of hybridisation, beneath the surface this remained a story of ongoing contest and parallel-running even some years after its first implementation.  It was still contingent, and it demonstrates the great difficulty ICT4D projects have in institutionalising themselves when operating in environments of strong institutional dualism.