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Benchmarking e-government in web 2.0

Random thoughts on policy for technology and on tech for policy

Is freer circulation of #data likely to lead to winner-takes-all markets?

If we free up more data, and enable data to circulate more, should we expect the emergence of new oligopolies such as Google? Is there a rich-getting-richer effect on data, and is it more likely to happen the more freely data circulates? Or is this concentration effect more likely to happen in a context where data does NOT circulate freely?

The analogy comes from a 2003 Clay Shirky comment on blogging, where he suggests that greater freedom leads to power law distributions:

In systems where many people are free to choose between many options, a small subset of the whole will get a disproportionate amount of traffic (or attention, or income), even if no members of the system actively work towards such an outcome.

 

There’s a thin line between groupthinking and scientific consensus

So, the evaluation report of IMF is out, and says all sorts of negative things about how the financial crisis in the Euro area was handled; basically that the stability of the Euro area was more justified by group thinking than by economic evidence.

This is a nice complement to the Chilcot report on the Iraqi war, recently published in the UK. They certainly shows the importance of policy evaluation. Taken together, both reports appear as a serious hit at “Blair-style” left wing parties, which are both pro-austerity and pro-american.

I haven’t read the report yet but I am fascinated by this accusation of group thinking as opposed to evidence. In fact, Kuhn shows well how, even in hard sciences, group thinking is an integral part of the scientific process. The evidence about the centrality of the sun was available long before Copernicus. The “paradigm shifts” are not simply caused by the evidence accumulated, but by a cultural shift of the scientific community.

So is the accusation legitimate? What is the line between group thinking and scientific consensus, especially in soft sciences? And where does the Washington consensus stand in this continuum?

Do we need better property rights on #data to enable greater sharing and reuse?

Raw data are not covered by IPR, while curated database are.

It is not clear who owns the raw data, across different sectors of the economy. As a farmer, data gathered by tractors are managed by the tractor provider, but who owns them? As a bank, data on ATMs technical functioning are managed by the ATM machine builder. As a consumer, data on my banking transaction are managed by the bank. And so on…

But property rights are the basis of capitalism. If you don’t establish ownership, you can’t buy and sell stuff.

So if it’s not clear who owns the data, then they will be not shared or sold or reused. Unless of course they are totally open data.

Interestingly, a similar problem is happening in science. One of the main barrier for scientists to share data is that there is no established format for data citation (as opposite to publication citation) and no practical application of it, so they will not gain but only loose by sharing data.

Who owns my farm’s #data? #bigdata #agrofood

Big data is changing agriculture, moving towards the so-called “precision agriculture”.
Almost all new agricultural machinery is equipped with sensors that monitor the field. Drones are taking photos of the field to map their growth.
Traditional technology producers, such as John Deere, are equipping tractors with sensors and offering cloud based analytics to farmers based on these data.
New agri-tech startups are gathering data and providing data services for precision agriculture.

Moreover, as we wrote before, Business Insider reiterates that in agriculture.

the real potential is what happens when the data from thousands of tractors on thousands of farms is collected, aggregated, and analysed in real time.

But who owns these data? Who can share them and analyse them?  Typically these data are gathered by sensors in the equipment and managed directly by the ATPs. Monsanto’s equipment generates about seven gigabytes of data per acre.

It is not clear to what extent farms own these data, and to what extent ATPs and other third parties can access and reuse the data. Contracts are difficult to interpret and understand by the farmers.

My impression is that there are players with competing interests: farms who want to use these data to increase productivity; ATPs who can manage and merge datasets from many farmers to improve their services and expand their business; and third parties such as startups which could use data held by ATPs to develop new services.

In the US, there is a Agriculture Data Coalition which aims at putting farmers in control of the data; there is even a transparency evaluator that helps farmers assess whether their contracts put them in control of the data. There is also an interesting global agriculture open data initiative.

Some questions emerge:

  • Who owns the data today? who controls access?
  • Should these data be controlled by the farmers, just as the MIDATA initiative has done for banking data?
  • Are farmers equipped with skills and market power to understand the contracts and negotiate with ATPs?
  • Are ATPs likely to use these data to expand into new segments of the value chain such as farming and data analytics?

In other words, is the market efficient?

Should companies share more their #data?

big data sharing

A minority of EU companies use big data: only 6,3% according to our IDC/Open Evidence report on the data market.

According to BCG, companies tend to use their data internally, without sharing them with third parties:

The majority of organizations we surveyed prefer to have control over the development of new products and services. They frequently contract with third parties to help speed development, but full-fledged partnerships or alliances are still a relatively uncommon arrangement.

But according to experts, companies should learn to share their data.

the Data Economy refers to much more than any one enterprise or organization making better use of data. Discreet use cases and applications of Big Data must be part of a larger whole. In the Data Economy, entire industries will operate and markets function all through the intelligent use and sharing of data.

This does not mean necessarily sharing data openly, but normally through APIs. However, the OECD goes further into this, and suggest exploring a “data commons”.

Non-discriminatory access regimes, including data commons or open access regimes, should be explored, as a means to support the production of public and social goods without requiring governments or businesses to pick winners (either users or applications).

So my question is: do we have evidence that companies should learn to share more their data? What are we missing out because of this lack of sharing?

Barriers to scaling-up across Europe: real life stories

Cross-posted from Linkedin

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One of our recent policy focus is on startups and scaleups, and in particular on what should be done at EU level to support them. This is also the main topic of the online consultation on the Startup Initiative, open until the 31st July.

One of the issues the EU faces is that there are relatively few high-growth innovative firms, and that they are reluctant to expand across borders. The fact is, as of today only 23 % of new and young SMEs (up to seven years old) export within the EU. Why is that?

I have been talking with entrepreneurs, gathering experiences of barriers to scaling up across border in the EU. One reason that came up is the different practices in the EU countries when it comes to payments.

Here are their stories told anonymously.

Italian SME “Societá”, a reseller of professional products, aimed to cut costs by bypassing intermediaries and buying directly from German suppliers. Unfortunately, this proved impossible because German suppliers want to be paid upfront, while the Italian SMEs receive payments from their client with a delay. Additionally, the banking system is designed around these local practices,  so they are unwilling to cover upfront costs.

Spanish SME “Empresa,” after much effort, finally succeeded to get a contract with a public body in Italy. Everything went well until the payment was due: the payment was made one and a half year late, which for an SME this is huge. Traditional contingency plans don’t work. Banks don’t provide factoring for invoices with foreign governments. Legal requirements about timely payments are much more difficult to enforce across countries, and lawyers discouraged “Empresa” to submit formal payment request as they would have little impact unless it went to court, which “Empresa” is not willing to do.

In other words, in some countries such as Italy, it is normal to be paid late, and the whole payment practices is that everyone in the value chain is paid late. But then foreign suppliers are wary of making business there, because their value chain relies on prompt payments. This is a major barrier to cross border expansion, even more because it often comes as a total surprise.

Here are some official data about payments by government. Italy stands out.

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I am sure there are many others: what are your real life stories?

 

Would Andreotti worry about Facebook?

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Facebook has a double role when it comes to existing policy: as a driver of change or of conservation.

On the one hand, Facebook is the primary vehicle for very populist ideas. It sometimes looks like a repository of the worst human feelings: garbage tends to spread virally. In this sense, it can be seen as a help to the established power in keeping people busy with the illusion of participation, by letting them rant freely about flat earth and therefore acting as a safety valve to prevent actual changes.

On the other, Facebook offer an alternative platform to mass media, allowing outsiders to have a voice and augment their reach. It is a formidable tool to bypass the filtering of the media conglomerates, and to let ideas circulate more freely. Indeed, one question is the very definition of populism. According to some, Universal Minimum Income is a populist idea; according to others it is a revolutionary idea.

 

In other words: would Andreotti (the Italian politician in power for over 50 years, the ideal-type of the establishment) be worried or comforted by Facebook?

But there is a third option. That Facebook acts as a learning platform for people to discover public engagement over time. That it acts as a force of conservation initially, but as a force for change in the medium term.

In fact, I found the same question many years ago when researching the history of philanthropy in the 19th century: one the one hand, it acted as a safety valve for the bourgeoisie and women to be active in public issues without troubling the establishment, on the other, it acted as a stepping stool towards democratic participation.

Innovators and government programs: a tale of two circles

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Government programs seldom involve top innovators. Typically, a very minor percentage of innovators benefit from government funding. Typically, the funding reaches instead more established players, which know how to play the “funding game”: the so-called usual suspects.

This is a common finding in the evaluation of most government funding programmes. For instance, our recent study on the FP7 impact on industry finds that only 5% of the fast-growing innovative SMEs participates in the programme – consistently with previous studies.

This is certainly a problem. We all want public money to go to the best projects, to the disruptive innovators, to the next Google, rather than to the incumbents or to the “industry” of professional project-writers that has emerged around public funding.

The cause seem to lie in a combination of administrative barriers to entry (complex procedures) with the lack of a strategic alignment between the priorities of government and of innovators.

Indeed, the capacity to involve the top innovators could become a success criterion for public policy. For instance, the European Research Council is widely respected, because of its ability to involve the top scientists in Europe. It is able to reward excellence. My understanding is that this is the aim of the forthcoming European Innovation Council: to do for innovation what the ERC has done for research.

In fact, the performance of different policies could be described through different Venn diagrams. Here is a sketch of the impression I have of two different instruments, the ERC and the Structural Funds (at least how they are used in Southern Italy based on my experience in evaluating Kublai).

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But in fact, the involvement of top innovators has never been formally defined as a success criteria or a KPI of public policy.

We know that KPI in public policy are particularly dangerous because they induce government to focus on getting the right numbers and play the metrics game, rather than addressing the real problems. We can easily imagine governments focussing on getting some high profile “unicorn” involved in their programs purely for communication reasons.

But the problem is more complex than that. We do not know if government programs should involve the top innovators in the first place. In the same study we note that according to some scholars, “the involvement of this “elite” could lead to a risk of reduced additionality by attracting firms that would have invested in innovation even in the absence of public support”.

Arguably, the appropriate KPI should be the percentage of unicorns/gazelles/scaleups involved that received public funding BEFORE they became successful.

But this is just a guess, as we don’t have much evidence behind it. After all, Google or Facebook didn’t get any government funding. We know that Defence funding and public procurement (e.g. DARPA) funds top innovators and generates disruptive innovation, but that’s a very specific context.

It could also be that government funding works best when it helps the moderate innovators that create a wider environment conducive for unicorns to emerge. Or perhaps, as a colleague pointed out to me, we should consider research funding just as we consider the Common Agricultural Policy, as a kind of subsidy that pays beneficiaries not for what they actually produce (innovations), but to maintain the environment (research activity).

What do you think?

 

How useful is the wisdom of the crowd in #opengov?

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One of the questions that I often ask myself is to what extent Open Government is a goal in itself, or a mean to actually improve the quality of government.

In our study on Open Government Services, we are starting to see pattern emerge from the case studies. One of the ideas that sprang to mind is represented in this sketch, that we will further discuss at our forthcoming workshop.

Basically, when it comes to Open Government, the more sophisticated the input expected from citizens, the more rare it is to receive useful contributions.

Citizens input is useful when it comes to reporting factual issues such as holes in their street; it’s useful (maybe a bit less) also for qualitative input on service co-design, such as how to improve hospitals. But when it comes to abstract policy issues, the majority of contributions are not really useful.

This is also why local eParticipation is more effective: because local politics is mostly about delivering services to citizens, while national politics is about more abstract issues such as regulation. Of course, this overlooks the intangible and long term benefits of open policy making, for instance in terms of increasing citizens’ trust in government. Moreover, we should note that even if the average is not very useful, there can still be some very useful contribution that make the open policy initiative worthy.

Another observation is that the more sophisticated the expected input, the less effective are online methods. Complex issues need face to face discussions, with iterative dialogue that helps mutual understanding between government and citizens. For reporting holes, online methods work well enough.

What do you think?

 

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