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Archive for the ‘enterprise 2.0’ Category

In the same way that the Web has changed the communication habits of millions of people, social computing is evolving to help us work with and in complex adaptive systems. The insights from Snowden and Jackson about ‘foresight’ and complexity, and their relationship with social computing, are fascinating not just for futures planning, but also for re-thinking processes in knowledge intensive organisations like knowledge management, communication and collaboration processes. For instance:

Developing a sensor network: The ability to quickly access authoritative guidance from colleagues, and to regular streams of intelligence regarding clients, competitors, market changes, and so on, is crucial to the development of actionable current awareness. But too often, companies rely on a handful of sources to feed them information, constrain sharing to document and email centric models and squeezed people’s interactions into pre-existing software models and workflows. That leaves the better part of a company’s extensive network of resources untapped and a void of higher level meta-data or collective intelligence derived from people’s diverse activities and contributions to a social computing platform.

If employees, clients and collaborators are able to contribute fragments of information, like tags, bookmarks, comments and links, as they come across or create the information in the course of their daily work not only will this be of benefit at the individual level (e.g. there’s no extra or less effort involved), when that information is aggregated, patterns can be determined which help others to spot trends and focus on hotspots in realtime. That makes for a potent early warning system and truly effective current awareness.

Sharing your way to competitive advantage: To operate in complex networked environments, companies are having to rethink old models based on the control of proprietary information. Snowden articulated it in these terms: “The paradigm has shifted. For whole of last century ownership gave economic power. Now, it is the speed at which you exploit things that matters not ownership. A strategy of openness makes more things available to you. What matters then is your agility and ability to exploit things.”

Over the last few years we have seen some companies become more open and share their learning/information with clients and other organisations. For instance, Innocentive.com enables companies, academic institutions and NFPs to come together in an open innovation marketplace to post challenges, share ideas and devise breakthrough solutions. In the UK, several major international law firms established the Banking Legal Technology portal in 2006 due to pressure from investment banking clients wishing to reduce costs and streamline access to all advice/information from the different firms. Likewise, Legal OnRamp provides another forum for lawyers share information and showcase their expertise, and for in-house counsel to access to precedents of major law firms and the pool their resources with other general counsel.Going forward, we will see companies using increasing volumes of fragmented data (e.g. tweets, blogs, comments, html links and pages) to contribute to social extranets, accessible by clients and competitors alike.

In that way, companies will get to see more and do more for less. By opening up the scanning process, not only will they add to the overall pool from which they can draw, they will also be presented with new narratives and possibilities which would not have been apparent or available in a closed setting. It will then be companies’ ability to interpret and apply the information quickly, innovatively and insightfully that will provide competitive advantage.

Developing new meaning through deliberate ambiguity: This picture presents a classic example of ambiguity. Woman - Young and OldThere’s an old and a young woman in there. Perhaps you see one or both of them. How long did it take you to focus on the different images? Does that mean anything? Is one more persuasive than the other?  Snowden proposed ‘deliberate ambiguity’ as a vehicle for encouraging emergent meaning and contributing to to the effectiveness and richness of a work. Increasing moves toward the use of fragmented materials in our work, like clipping items from feed readers, adding to them notes and tags, linking the clippings to blog posts and engaging people in further online discussions and idea sharing, we are deliberately introducing a higher degree of ambiguity to the system. It is precisely this ambiguity that allows us to interpret and give new meaning to the fragments, which provides new perspectives, ideas and interpretations. This is the source of innovation and difference – not best practice and compliance regimes.

There are also ramifications for traditional information categorisation and classification regimes, the purpose of which was to disambiguate and establish order in the system. Efforts to create order in this way can be counter-productive. If you are looking for something that hasn’t been categorised in the way you expect, then you probably won’t find it (quickly or perhaps at all). You are also less likely to make valuable serendipitous discoveries by stumbling across items that sit outside of traditional categories. As Thomas Gruber (2007) explains in his article “Ontology of Folksonomy: A Mash-up of Apples and Oranges”:

“Tags introduce distributed human intelligence into the system. As others have pointed out, Google’s revolution in search quality began when it incorporated a measure of “popular” acclaim — the hyperlink — as evidence that a page ought to be associated with a query. When the early webmasters were manually creating directories of interesting sites relevant to their interests, they were implicitly “voting with their links.” Today, as the adopters of tagging systems enthusiastically label their bookmarks and photos, they are implicitly voting with their tags. This is, indeed, “radical” in the political sense, and clearly a source of power to exploit.”

In that way, user participation in the form of social tagging offers a far more powerful means of discovering information and meaning.

Using technology to provide decision support: Although previous generations dreamed of artificial intelligence and people feeding computers information and receiving answers, we now understand that the roles should be reversed, and we are interested in using computer networks to augment human intelligence and make it easier for us to make decisions of our own. This is the key differentiating factor about social computing – it has human agency in it. Whilst computers can present more data, human agency is needed to determine the meaning of the information fragments. That requires us to deliberate model/look at things from different perspectives then present the data back for human-based interpretation and decision making.

To conclude: “the whole point about technology is to provide decision support for human beings not to make decisions” (Dave Snowden).

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In today’s complex and turbulent environment, organisations need ‘foresight’ to be able to respond promptly to various change drivers including technology, sustainability, globalisation and the economy. Essentially ‘foresight’ is a participative approach to creating shared long-term visions to inform short term decision-making processes (see http://www.foresight-network.eu/). During a recent webinar, Dave Snowden (Cognitive Edge) and Mike Jackson (Shaping Tomorrow) outlined how horizon scanning and social computing can help organisations plan for the future, protect themselves against unexpected threats and exploit forthcoming opportunities.

Jackson outlined the following five components of foresight development and managing change:

  • ID and Monitor Change: Identify patterns from the stories, fragments of information and behaviours of many participants in a system or network and decide how those patterns impact business.
  • Critique implications: Inform the impact assessment with a cross-section of information not just intelligence regarding one’s own industry. That means monitoring much more change and developing a better peripheral vision to be able to understand the broader implications for the business.
  • Imagine difference: Establish the risks and alternatives for different scenarios.
  • Envision preferred route forward: Established where you are, then determine where you want to go by scanning plausible, possible and probable ideas and changes for the future.
  • Plan and implement: Identify goals, resources, strategies and stakeholders required to create change and help them cope with the inherently uncertain future.

The participatory, evolutionary and social nature of ‘foresight’ development makes for a snug fit with social computing (i.e the simpler more networked online applications that connect people and allow them to pool their knowledge and interact better with those in their network). More specifically, social computing enables the content and online interactions to constantly shift so as to better reflect the knowledge, ideas, opinions, preferences and even aspirations of all contributors. Not only does this allow us to develop a better radar of what is happening across our network, it also provides us with higher level of collaborative intelligence: a range of opportunities and outputs that could not be created by any number of individuals or small groups working alone.

(Interestingly, these are also features of complex adaptive systems (emergent, highly connected and simple on the micro level; complex and unpredictable on the macro level) which evolve through rapid feedback loops making them highly adaptive to changing conditions.)

Snowden picked up here, talking about complexity theory, the creation of human sensor networks and the need to manage the evolutionary potential of the present as an alternative to traditional scenario planning. Referring to his recent blog Think anew, Act anew: Scenario Planning, Snowden cited a wonderful quote from Seneca:

“The greatest loss of time is delay and expectation, which depend upon the future. We let go the present, which we have in our power, and look forward to that which depends upon chance, and so relinquish a certainty for an uncertainty.”

This quote emphasises that what matters now is managing the present by switching from “fail safe design strategies to safe fail experimentation”. That involves the use of small early interventions in the form of exploratory behaviour, allowing the ones with good results to be amplified and the ones that don’t work to be eliminated.

Snowden went on to outlined the three fundamental consequences of complexity theory, which need to be present to mange a complex system, which he covers in great depth along with a critique of horizon scanning and scenario planning, in his post mentioned above.

  • Need for distributed cognition. The crux of this is decentralisation and mass participation. The idea that the few can decide for the many, whether it be drawing up scenarios, selecting technology, imposing structures or the like, is inherently unstable. Instead, we need to start to use large numbers of people to feed decision making processes with current information and diverse perspectives.
  • Fragments are key. Material that is used must be finely granulated. A big problem with traditional scenario planning is that it produces ‘chunked’ reports. The human brain has evolved to handle fragmented data patterns – pictures, comments, captions, labels, etc. One of the reasons social computing is so successful is that it presents information in multiple inter-threaded fragments, so that the brain can ‘conceptually blend’ those and link those fragments to determine how to move forward. Documents don’t tune in to the evolutionary nature of humans. Fragmented information has evolutionary advantage.
  • Overcome disintermediation. People making decisions about the future have to have direct contact with raw intelligence. They can’t afford to have middle management or processes mediating, summarising or grouping information. The information must come from trusted sources and permit interaction with those sources (so the information can be validated).

In Part II of this post I will look at some of the implications of this participative evolutionary approach for traditional current awareness and information creation and categorisation processes.

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To what extent does your company facilitate social networking between employees split by geographical or organisational distance, or with (existing or potential) clients and business partners?  What’s the value of this social capital to the company (i.e. the connections within and between social networks as well as connections among individuals).  How does it change the nature of opportunities and constraints each person faces, and the flow-on effects to the team and company as a whole?

IBM recently published its research surrounding Beehive (an experimental internal platform designed to blur the boundaries of work and home, professional and personal, and business and fun).  The report provides empirical evidence of the power of nurturing social capital in the enterprise. IBM Social Networking Research.pdf

The researchers studied issues associated with adoption, usage, motivations, and impact of social networking in the workplace, and they found that:

[E]ven with limited use of Beehive, over a relatively short amount of time, there are associations between types of usage and … different types of social capital. When someone is using Beehive for meeting new contacts, they report a greater interest in making these types of contacts at the company in general.

When someone is using Beehive for keeping up with known colleagues, both in their workgroup and in their extended network of loose ties, they report having closer ties with their immediate network (bonding social capital), a higher sense of citizenship (willingness to help the greater good of the company), and greater access to both new people and expertise within the company [(bridging social capital)].

And finally, the more intensely someone uses Beehive (meaning more frequent visits and stronger associations with the community on the site) the higher they report their social capital is, across all measures. They have closer bonds to their network, they have a greater willingness to contribute to the company, they have a greater interest in connecting globally, have greater access to new people, and a greater ability to access expertise.”

As IBM has illustrated with its customised Beehive-development, supporting social networking in the organisation means more than simply bring in-house functionality from (public) social networking tools.

Instead, social networking functionality should be integrated not only with existing information systems, but also with the particular needs of the organisation to enable people to grow informal networks which exist alongside formal structures, and fully exploit the wealth of information and expertise circulating in and around the organisation.  The latter is very difficult for public social networking sites to deliver.

As with any change initiative, building the right adoption models are equally important as building the right architectural/technical models.  Adoption models raise important issues around the situation of social tools, control of people’s (private) information/discussions, and building on existing networking behaviours, to ensure that levels of information flow and control match needs, cultures and expectations.

Here are a few thoughts in that regard:

  • Well ‘situated’ social tools: This is a concept that we’ve talked alot about (e.g. here, here and here) as it helps in lowering the barrier to adoption.  By ensuring the networking platform is well integrated with key existing information systems and social tools, as people contribute and work with information, trails are automatically created, which when aggregated in profile/personal pages, automatically reflect people’s social network and information connections.  The information is constantly refreshed and kept current without extra effort on the part of the individual user.  People can readily identify who’s working with who on what, or who is connected with who and may be able to make an introduction or support a proposal/project idea.
  • Technology and communication preferences: To maximise involvement, tools need to be made available which reflect people’s preferences for technology and communication style.  As we are seeing from the public domain, there should be a greater emphasis on presence sharing, status updates and other ad hoc style exchanges during people’s work, which can be rapidly embellished and/or responded to by others.  These quick fire exchanges can then form a feed of information in the same way that friendfeed streams information.
  • Professional and personal ‘identities’:  For some people, the line between professional and private lives is increasingly opaque.  But we can’t assume that professional and personal identities will merge comfortably.  As Doug Cornelius points out, as colleagues and clients become friends, we may want to share information with them that we don’t want to share with others.  In the same way that some people use Facebook to keep in touch with their freinds and LinkedIn for their business contacts, people should have the ability to manage ‘professional’ or ‘public’ and ‘private’ profiles in a way which suits their desired level of openness or privacy.
  • Intelligent social networks:  To be even more useful, the networking systems needs to give us a little bit of extra information – like a pat on the back for having participated.  For instance we should see not only ‘who is connected with who’, but also the proximity of people’s connections based on shared attributes, such as tags, groups, communities, and signals based on RSS from social news-reading and interactions (e.g. visits to or comments on posts).  So if we give a little we get alot.

Adoption issues aside, another sticking point for getting top-down buy-in for a social networking project in the company is the difficulty of measuring the value that social capital.  This was one of the caveats the IBM research team highlighted in their report, i.e. the results are indicative of a relationship between use and the measures they used, but are not causal.  As Bill Ives rightly points out, the next steps for us will be to see how we can illustrate the relationship with improved performance and bottom line results.  Your thoughts on this as always are welcome!

Thanks to Bill Ives for reporting the IBM research.

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Think for a minute about how you used to book your holidays, buy your music, find an address or select insurance – 10 or even 5 years ago?  Do you even bother to search for things these days or do you just rely on the recommendations from your network via Facebook, Twitter, Zemanta or even Amazon?

These prolific and radical changes are not limited to social and consumer interactions on the internet.  They also impact the nature, shape and conduct of business both internally and externally.

Companies are increasingly working in networks, whether they be loosely coupled or tightly integrated because of technology and the globalisation that technology has brought with it.  Those networks are essentially virtual entities, and this trend will accelerate over the coming years.  To be in or join a network, people need insight and connections, as well as appropriate processes capable of supporting various business needs across the virtual entity.  That signals fundamental shifts in the way people do business and the underlying business models.

This was one of the issues Leo Apotheker (co-CEO and a member of the Executive Board of SAP AG) and Andrew McAfee discussed during an interview with Charlie Rose earlier this week.

It echoes the message from Pisano & Verganti in their article Which Kind of Collaboration is Right for You? (Harvard Business Review December 2008):

In an era when great ideas can sprout from any corner of the world and IT has dramatically reduced the cost of accessing them, it’s now conventional wisdom that virtually no company should innovate on its own. … [But] greater choice has made the perennial management challenge of selecting the best options much more difficult. … [How] open or closed should your firm’s network of collaborators be? And who should decide which problems the network will tackle and which solutions will be adopted?

Those opportunities and challenges are equally applicable within organisations, with changes affecting the way people are now able to work together and the nature and style of management. Everything happens and needs to happen so much faster just so businesses can stay in the same (market) position and not loose ground to competitors.  But whilst the technology is there to expedite work processes and help people work better and smarter, often barriers in the form of cultural, organisational and behavioural changes are stifling.

As McAfee points out, it’s in this ever-changing technology context that management is being pressed more than ever to rethink the boundary between (i) control -> dictating how things will be executed and by who and (ii) autonomy -> allowing people to organise themselves and seeing what emerges. Frederic Baud explores similar themes in his interesting post Will Enterprise 2.0 ever enter big organisations? More particularly, he considers whether an organisation viewing itself as an internal market where resources can freely recombine to pursue emerging projects can greatly augment the output by loosing control of the nature of that output.  The ensuing discussion is also worth a read!

In any case, the ‘control’ model prevails in many orgaisations, where decision-making processes are closed or simply pay lip-service to employee involvement, the few decide for the many based on their view of what people want, and networking of information and expertise occurs in very localised instances.

Yet when we look around for examples of successful businesses to emulate, who do we look to?  Google?  Proctor & Gamble? Toyota?  Hubbards? Headshift 😉 ? There are plenty more.  And what do they tell us?  Well, to quote Eric Schmidt – Google CEO (The Mckinsey Quarterly November 2008):

There’s a lot of evidence that groups make better decisions than individuals. Especially when the groups are selected to be among the smartest and most interesting people. The wisdom of crowds argument is that you can operate a company by consensus, which is, indeed, how Google operates.  …

One of the things that we’ve tried very hard to avoid at Google is the sort of divisional structure and the business unit structure that prevents collaboration across units. It’s difficult. So, I understand why people want to build business units, and have their presidents. But by doing that you cut down the informal ties that, in an open culture, drive so much collaboration. If people in the organization understand the values of the company, they should be able to self organize to work on the most interesting problems. And if they haven’t, or are not able to do that, you haven’t talked to them about what’s important. You haven’t built a shared value culture.

For me, those views are examples of organisational learning theory in practice.  I’ve described the themes within that theory before, and for present purposes would just like to reiterate a couple of those themes:

  1. Learning requires challenging existing mindsets that form the basis of (possibly out-of-date) behaviour.
  2. Managers should encourage the generation and spreading of new ideas and practices about purpose, values and vision.
  3. That vision requires the maximum number of people to contribute to and share a picture of the where the organisation is going, and how personal and business goals coincide.
  4. Feedback is central to this system as it is critical to learning and adaptation.

Those ideas have been around alot longer than much of the technology that has caused such radical change to the way things are done in the public domain.  That same technology is steadily entering and disrupting the way things are and can be done in organisations.  But for that technology to be of real value, progress needs to occur simultaneously in respect of each of those ‘organisational learning’ elements.  And if you’re reading this thinking that this type of change doesn’t apply to your business or your industry sector, best you start with #1 on that list.

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Consider for a moment where you turn when you’re looking for a document, a reference or information about who’s working on what and with which clients. Commonly people will ask their colleagues or send out an email to their team or people in their wider network. People will use their networks when ever and where ever they can to supplement their face-to-face interactions, and to get information that’s tailored to what they need when they need it. It is precisely these drivers that have led to the exponential rise of online social networks and the evolution of social technologies.

However, instead of supporting the social networks through which information and knowledge circulate, many of the large, centralised, top-down implementations in firms have focused on enforcing information and management processes. It’s no wonder that many of these specialist applications are underused – with their different interfaces and rules for user interactions that require people to spend time figuring out how to use them, compiling information to be approved for inclusion, and then trying to find the information once it has made it into the system. They are not user-friendly, and they don’t reflect the workings of a network where people turn to people to get what they need.

Aside from these technology issues, a shift is needed away from traditional ideas associated with knowledge ‘management’. People use technology because they provide an individual benefit, like getting their work done more efficiently or building their expertise in an area that will help them win clients or get promoted. It’s time to get rid of the notion that people must capture and share information to make the firm more profitable. Instead we should be thinking about the behaviour shift and support that is needed to help make individuals more productive and sharing a by-product of doing not an end in itself.

Social software can play a useful role in streamlining the interaction and communication necessary to support existing ways of working. It can for instance help tackle the burgeoning email and information overload problems suffered by so many legal professionals, and help them quickly and easily find what they need when they need it.

It requires simple changes to the way people work like using a wiki to prepare pitches instead of sending out emails to a limited group of contributors. That change can provide the immediate benefits of reducing email traffic and keeping all the information in one place for assimilation, review and future reference. It also provides the flow on benefits of providing greater transparency (subject to any confidentiality restrictions) to those who would have been otherwise excluded from the pitch preparation process and adding to the collective intelligence of the firm. Likewise feed readers and social bookmarking are excellent personal KM tools. Not only do those tools provide direct benefits to individuals by putting current relevant information at their finger-tips, they also provide a collective benefit. On the one hand, people can find out about others’ interests or expertise in different fields, and on the other, when the information is aggregated, patterns can be determined which help others to spot trends and focus on hot spots in real-time.

This is one of the most important lessons of the Web 2.0 world for the enterprise social computing world, and hints at an important improvement that online social networking can bring to bear on the firm – a significant increase in participation based on the fact that the tools support individual needs. These shifts will shape the possibility of new, flatter and less costly ways of working in the future.

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