Digital Engagement - Making it Work

Digital Engagement, Gov 2.0 whatever moniker you want to use is on the up and up now. President Obama’s successful use of social networking and other social media tools during the campaign followed by the change.gov and new recovery.gov sites has brought the issue front and centre for many governments. In Australia both the PM and the Opposition Leader are on twitter and the Opposition Leader recently launched a blog for conversing with Australians. The UK government is hiring a Director of Digital Engagement and has a various initiatives like the Number 10 e-petition system.

For all the enthusiasm, Andy Oram wrote a very good post yesterday about the questions about government participation. For Governments and citizens looking at digital engagement, these questions have to be answered. Without answering these questions, initiatives will fail.

Is digital engagement worth it? It is as implemented well it has the following benefits:

• Reduction in cost of compliance for business which leads to lower prices reducing cost of living,
• Supports the flourishing of new businesses,
• Lower cost to running the government, and
• Improve perception of the value of government services.

While these benefits may not seem like much they produce a positive feedback loop that increases the overall value to society.

So the question isn’t so much whether we should do it but rather how do we do use digital engagement tools effectively?

Just get out of my Way

Digital Engagement isn’t simply about holding a conversation. The context matters. For example, if I am looking for the address of a service centre I don’t want to enter into a conversation. However, if there is a new bill on the table in parliament then I will want to join the conversation.

The minute digital engagement gets in the users way or adds no value to what they are doing at the time is when you get push back.

The context is king for digital engagement.

Policy and bills before parliament are a perfect example of where digital engagement can work extremely well. In this case the bills would be available online. It is to borrow a phrase, a social object. To bring engagement to policy and bills would be in the form of comment system like Disqus or Intense Debate. In essence each policy or bill becomes its own blog post.

Build a little, test a little

Rome wasn’t built in a day, but often initiatives such as digital engagement try to build Rome in a day. Instead, digital engagement should use Werner Von Braun’s engineering approach: build a little, test a little. The idea here is to build prototypes that are quickly deployed, which are then iterated based on user feedback. Trying to build an all encompassing solution simply chews up time especially when the users will start using the system in ways no designer could have foreseen. The evolution of Twitter is a great case study for how users take a system and begin using it in ways the designers and builders never expected.



Winning the Sceptics

Winning over the sceptics is likely to be the hardest part of any digital engagement initiative. Sceptics will question the value of digital engagement. They will also worry about how it changes their workload and job. Even for some whether it will mean losing their job. Others will ask whether the government will keep the conversation two-way. Addressing these real and legitimate concerns has to be the primary responsibility for those in charge of any digital engagement initiative.

The build a little, test a little approach neatly provides a way of demonstrating the value of digital engagement without extensive investment in time and money. Perhaps more importantly, it provides those involved with concrete and tangible feel for how their work will change.

The on-going involvement from both sides of the conversation will be the hardest to tackle. The key here is to be realistic. Fred Wilson continually points out how the community around his blog is built from his active involvement. For digital engagement to work, the public service and Government will have to participate in providing answers to comments and questions. Will Ministers and senior public servants want to do this? Some will and some won’t. The answer is to have “Untouchables”, “Community Managers” or “Community Advocates” who can effectively engage in the conversation.

Work/Life Balance

Drawing a line between work conversation and personal conversation is fraught but important for any digital engagement to succeed. Some organisations take the ridiculous view of everything being professional. It doesn’t work that way and is an imposition on people because organisations don’t want to address the issue at stake but instead repress it.

Mistakes will be made, gaffes will happen and the “wrong” thing said. Creating a policy that doesn’t address that is madness and will drive people (particularly Government and public servents) away from participation. Instead the policy needs to recognise when someone is a representative of the public service and government and when they are private citizens.

Showcasing Engagement

Without showcasing the prototypes across the Government and Public service web presence, all of the above will be wasted. Case in point, the OPSI “Unlock Service (beta)” is buried in the jungle of government portal pages. I only found it by accident. Given the importance of open government and digital engagement, this service needs to be showcased on the Direct.gov portal at the very least. Without making the prototypes, tools and developments that come out from a digital engagement initiative its very likely they will fail. In this President Obama’s Change.gov, Whitehouse.gov and recovery.gov are good examples of surfacing the tools.


Digital Engagement initiatives will change Government. How much change and how effectively they realise the benefits of Digital Engagement, depends on execution.

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• change.gov Becomes whitehouse.gov (radar.oreilly.com)

Intersection of the web and tangible objects (manufacturing-as-a-service)

MIT's Technology Review have an interesting article examining the rise of web services that allow users to design and make objects via the web. These services have the potential to disrupt traditional manufacturing. While at an early stage its useful to consider what disruption these services could lead to.

This disruption potential comes from two different causes. The first is the rise of micro-businesses around manufactured products (I am excluding already existing craft companies which simply use the web to sell their products). One example company would allow users to find and order fittings such as taps and facets that are no longer being made by the original manufacturer. The company creates and ships the taps and facets on demand to the user. Think printing-on-demand but for products.

Manufacturing based web services open the long tail of manufactured products. Suddenly, manufactured products never really stop being made just like books now never really go out of print with print-on-demand services from Amazon et al.

The other cause of the disruption is the way these web services change the economics of manufacturing and how this ties into increasing conciousness of energy/carbon cost of manufactured products. Why buy simple products like plates, pots, pans etc. that are made in China and shipped half-way around the world when you can purchase the same products at roughly the same price that is shipped from someone down the road?

Carbon concerns will change the economics of manufacturing by making smaller factories closer to large markets more economical than large centeralised factories. Web services based around manufacturing will further erode the economics of large scale factories by removing the need for companies to purchase or rent expensive manufacturing machines. These companies are the first of manufacturing-as-a-service.

Manufacturing-as-a-service removes the equipment and capital barrier to entry for new product companies. These companies can focus on product design and building the community around the product and leave the operation of the manufacturing hardware to manufacturing-as-a-service guys.

There will be a range of responses to manufacturing-as-a-service. Some manufacturers and factories will ignore it only to be over taken by the tide. Others will embrace it and will aim to become the Amazon Web Services of manufacturing-as-a-service. What the response will be is largely going to be determined by the DNA of the company.

Manufacturing-as-a-Service, Web Applications, Trends

Wither Social Networks, Arise Communities

A community is an assemblage of people around a common interest. What Hugh MacLeod calls a social object. Social Networks, like Facebook, are glorified contact books. And as Facebook is finding out, people get stroppy when you get between them and their contact books.

A community, on the other hand, behaves differently. The members of a community are there because of the shared interest or bond, the social object. Consider the rise of communities around particular diseases as highlighted in this week’s NewScientist (vol 198, issue 2656). These communities are generating a wealth of data about these diseases that would otherwise be expensive or impossible to obtain. Communities tend to generate data around the particular shared interest beyond simply demographics that you get in a Social Network.

The data is hugely important. As Tim O’Reilly is fond of saying, “data inside” is the new “Intel Inside” (between time point 2.15 to 3:20 in the presentation). The value of web companies is entirely determined by the data they can aggregate and turn into new knowledge. Communities generate large amounts of data by harnessing the network effect. As each member adds more data around the shared interest this creates a positive feedback loop encouraging more people to add more data and so on in a virtuous cycle. A good example of this principle in action is the company Wesabe (also discussed by Tim O’Reilly in his keynote at 2008 Web2.0 Expo).

Social Networks don’t have this positive feedback loop that generates great swathes of data. While they do have network effects this is merely increasing the size social network by members rather than adding large amounts of data. We are even seeing indications now of limits to how far network effects work in maintaining growth of membership. The amount of data in social networks is relatively limited and most of this information is limited to who knows who and simple demographic data.

Social advertising is the “next big thing” in advertising. However, achieving this on a social network has not been easy. An outcome that is not surprising. The effectiveness of advertising comes down to two things: attention and intent. Attention being what is the person doing at the moment. Intent being why are they doing what they are doing at this time. The more closely you can determine the attention and intent of the user the better the advertising can be made to be of interest to the user.

Social Networks do not offer great data to determine attention and intent. Just because you are a 46 year-old climate researcher, does that determine why you are looking for a holiday? An advertiser could assume you are looking for a holiday for yourself but there is no evidence for this. Nor can a social network really say whether you are looking for holiday in the first place. There is little data to indicate attention and intent. Communities on the other hand do offer good data for determining attention and intent. Consider the climate researcher. He joins a community around travel and holidays and asks the question of the community “what is a good holiday as a birthday present for my 16 year old daughter?” Now we know attention (searching for a holiday) and intent (as a present for his 16 year old daughter). Having this data allows the advertiser to very accurately target with information about holidays suitable for a 16-year old girl.

People like being part of a community. We are tribal at heart. A social network is a mathematical abstraction that merely indicates a connection. The tribe will always win over the maths. Communities will win over social networks.

Tags: Tim O'Reilly, Social Networks, Hugh Macleod, Social Object, Community, Data Inside, Attention and Intent, Facebook, Wesabe

Google App Engine is final leg of the strategy to disrupt social networks

With the announcement of Google App Engine and the resulting symphony (or cacophony) of conversation a lot has been said about cloud computing and Amazon's Web Services. For all the conversation not much has looked at the Facebook angel in detail.

Google App Engine strikes me less as a competitor to Amazon Web Services and more as the finial piece in the puzzle for creating a web-spanning social network. Google App Engine provides a place for applications to be built and hosted external to any social network. Coupled with Google's APIs for a users social network (the contact API), an identity mechanism (Google Accounts) and the OpenSocial APIs, everything that can be done in Facebook or any other social network can now be done by any application without having to be internal to any social network.

It is an innovative way of dealing with the issues of social networks by explicitly turning the web into a giant social network without walls.

Of course this will mean the very act of surfing could see you have a sheep tossed at you!

Tags: Google, Facebook, Google App Engine, Amazon,Amazon Web Services, Social Network, OpenSocial

Web2 Finance, Mobiles and Two Factor Authentication

A friend has just had problems with fraud and it got me thinking about two factor authentication and how web2 finance sites such as Mint.com and Wesabe can play a role in making online fraud harder.

The Web2 Financial sites could Email and sms the individual whenever a payment or transaction is done to confirm the transaction before it is committed. Essentially the mobile phone (or email) becomes the second factor of authentication. No need to carry around a separate dongle or bit of hardware in order to make a transaction.

Implementation of this would require the companies to partner with the banks or online payment processors to get the realtime-ness need for the second means of authentication to be effective.

Banks and the payment processors could also do this as well and probably should. I would like to be able to receive an SMS to authorise ATM transactions or when paying by card at a shop prior to being the money being handed over. Not the ultimate solution to card cloning and pin card issues but it would certainly put a crimp in that type of fraud.

Web2 financial services have an advantage over the banks, credit cards and payment processors for the following reasons:

• Online banking sites suck - badly
• People often have many bank accounts, credit cards and setting them all up is likely to miss something. As the financial sites already aggregate this information they can act as single point for passing transactions through to authenticate
• Many online payment processors are merchant focused and never have a relationship with user so can't really send an SMS or email
• The financial sites are focused on the user while banks, credit cards and payment processors lack this focus
  

In the end the more services that offer this type of two factor authentication the better for reducing fraud. It isn't going to make it go away (phone and wallet stolen etc) but it can be reduced without having to roll out great numbers of bits of hardware.

Tags: Mint.com, Wesabe, Two Factor Authentication, Mobile, Fraud, Online Payments, Web2

When Humans are Removed

Ars Technica has an interesting report on a recent music industry conference. What struck me as interesting was an exec of a music label on a panel justifying their existence of labels by the work of "finding" music. To quote:

"anyone who has spent an hour or a day listening to demos understands the labels' place in the food chain"

The iLike CEO pointed out that this is no longer the case. That a label only need to look for musicians with 50,000 friends on MySpace.

What is interesting is how MySpace, iLike et al have turned finding new music from a costly human based activity to a software program. I'm not sure many people in the industry (whether the labels or companies like iLike) realise what is happening. The best analog is what Google did with advertising as Chris Anderson pointed out in his recent article in Wired:

"When Google turned advertising into a software application, a classic services business formerly based on human economics (things get more expensive each year) switched to software economics (things get cheaper)"

Did Google realise what would happen by turning advertising in a software application? Probably not. Just as Google unleashed value that was otherwise tied up as costs, so to will a software application(s) for finding new music unleash value otherwise tied up as costs. Music is going to shift back from being a package product to being an experience.

Tags: freenomics, Google, disruption, economics, iLike, chris+anderson, music

Web Next & Data Ecosystems

Web Next is not some quantum leap in reality but rather the culmination of several long term trends. Web 1.0 was the translation of real world services (e.g. Amazon) onto the Internet and Web 2.0 is Darwinian evolution of UI and social media tools and technologies. Web Next is exploiting of information to achieve new products and services with no direct analog in the real world. Some will call this Web 3.0 but I prefer the simpler moniker Web Next.

Web Next is about the creation of value not through the control of information but via the creation of synergies and knowledge through combining information and functionality. There already exists the primitive examples in the Web2 world, those such as the map-based mash-ups. Essentially value is derived via the showing a spatial relationship between data. However, these mash-ups are relatively primitive. They rely on a users existing knowledge of the spatial area in question. I personally have no appreciation of the real layout of New York City having never been there. Consequently, the value I gain from viewing or using a mash-up consisting of crime statistics plotted on a map of NYC is less than someone who has visited which will be less than a resident of NYC.

The synergy of information and functionality is created through Data Ecosystems.

Data Ecosystems

A Data Ecosystem is two or more different data sets that when combined with complementary functionality produce multiplicative effect in usefulness. Or put another way, a Data Ecosystem contains more than one source of data (a data set) (e.g. temperatures and rainfall) that can be combined, analysed and processed with the overall Data Ecosystem being more valuable than data or functionality on its own. Importantly, having more than one data set is not sufficient on its own. Rather you need various tools and functions that allow the user to act on the data. An example will help to clarify.

Take an individual piece of data, say a series of temperatures measurements. On its own you can't do much with those temperature measurements but combined with rainfall measures, annual growth rates and a map, those temperature measurements suddenly have a lot of value. Now a farmer can research and plan when to plant his crops or adjust his crop forecasts based on historical growth rates versus temperature and rainfall. To be able to make the forecast of crop tonnage the farmer needs a series of tools that allow him to find correlation factors and extrapolate the growth trends based on rainfall and temperatures. Without those functions having the data is not particularly useful. There is no use in having gobs and gobs of data if there is poor functionality in the Data Ecosystem.

Data Ecosystems highlight a very interesting point about data. One that I find is continually ignored or not understood by most data companies (including web companies). Data on its own has little intrinsic value. Data only has value with what you can do with it and what you can do with it is determined by what other data you have along with the functionality you can apply to the data.

Like a biological ecosystem, a data ecosystem must mesh together. A Data Ecosystem needs to be internally consistent. If a Data Ecosystem is not consistent then it will not generate value for the user. There is no point in trying to create a Data Ecosystem that has rainfall patterns from Australia and crime statistics in New York City. Designers of Data Ecosystems must not design the systems so they become inconsistent. Consistency is crucial. But given human nature I fully expect consistency will be ignored.

"And there's the sign, Ridcully," said the Dean. "You have read it, I assume. You know? The sign which says 'Do not, under any circumstances, open this door'?"
"Of course I've read it," said Ridcully. "Why d'yer think I want it opened?"
"Er...why?" said the Lecturer in Recent Runes.
"To see why they wanted it shut, of course."
-Terry Pratchett, Hogfather

At this point I expect some readers will be thinking that Data Ecosystems is simply the Semantic Web. Data Ecosystems is not the Semantic Web. Semantic Web technologies will be a part of Data Ecosystems, but Semantic Web is neither a precondition for nor sufficient on its own in order to build Data Ecosystems. Semantic Web helps by automating building the relationships between bits of information. In the temperature example above Semantic Web would have provide information such as the lat/long of the measurements, how it was measured, the accuracy of the measurement, the date and times of the measurement etc. This would then allow a computer to match the data automatically with rainfall data from the same location and time and plot together on a map. Semantic Web makes building Data Ecosystems easier and like objects in programming will allow Data Ecosystem platforms to increase the ease the deployment of Data Ecosystems.

Data Ecosystems can also be built of other Data Ecosystems. The output of several Data Ecosystems can be used as the sources for another Data Ecosystem and so on. Each step creating more value by allowing an individual to achieve more. Data Ecosystems will in effect create an L-space

Why are Data Ecosystems Important?

Data Ecosystems are important for one very, very crucial reason. Data Ecosystems allow people to achieve things effectively. Unlike Web 1.0 which was essentially removing transaction costs from existing real-world processes, Data Ecosystems unlock the potential for new services that are impossible in the real world.

Consider a Data Ecosystem based travel service. Such a service will allow you to research a holiday; book all transport, accommodation and activities; create a comprehensive itinerary of the holiday, send alerts at key points along the trip; calculate how much money you'll spend on the holiday; help you automatically tag video, audio and photos from the holiday and create holiday memorabilia from the items you have uploaded. All through a single Data Ecosystem.

And there are hundreds, thousands, millions of probable Data Ecosystems that have no analog in today's web.

How Things are Already Changing

To close out I want to consider something that has been banging its way around the blog-sphere and offline world: the fate of journalism. Without re-hashing the debate you can read Bill Keller's speech with Jeff Jarvis's responses here and here as background.

If everyone is a citizen journalist, then what is the point of professional journalist? A seemingly valid question but one that has the implicit assumption that both are or will be doing the same process. From the perspective of Data Ecosystems the job of a professional journalist becomes very different from a citizen journalist. The citizen journalist is a source of data. They will most likely only provide a very narrow bit of data on any particular story. Put another way, the citizen journalist becomes a source like the news wires.

The professional journalist moves on from being the source of the story to gathering all the disparate bits of information about a story and then assembling into a consistent and cohesive context around the core story. Professional journalists go form being the gate keepers to information to value builders by creating context to stories. The role of a newspaper/media company is to provide or create a Data Ecosystem within which the professional journalist can assemble, create and publish the context to stories. Within Data Ecosystems, professional journalists, news agencies and citizen journalists will co-exist and combine to produce a more valuable service than either would on their own or exists today.

The media world is already going through pain as it is forced to adjust to the realities of an information economy. Data Ecosystems provide a means to effectively adapt to the information economy. But Data Ecosystems are not limited to media. Data Ecosystems will exist right across the information world. In fact they will reach into material world as L-space is linked into materials at the molecular level. This is the true revolution of Data Ecosystems, they facilitate the merger of L-space and Real Space.

Tags: Web Next, Data Ecosystems, Web 3.0, Web Services, Semantic Web, Web 2.0, L-Space