Understanding Networks

Conrad Taylor writes:

The 80th meeting of the Network for Information and Knowledge Exchange (NetIKX) took place on 14 July 2016 on the topic ‘Understanding Networks’ and was addressed by Drew Mackie and David Wilcox, who also took us through some short exercises. The meeting was chaired by Steve Dale, who has worked with Drew and David on a number of projects.

Drew has researched around network analysis. David’s background is as a journalist (Evening Standard) and he has tried to give people a voice within regeneration and urban development issues. They exercise their joined skills typically in projects for community development and social service strengthening.

In my account of the meeting, I do not exactly follow the order in which the points were made. I also offer my own observations. Where those deviate significantly from the narrative, I’ll signal that in indented italics, as here.

The idea of networks
The concept of a network has many possible applications, such as computer networks, but Drew said our focus would be networks in general and how they can be represented visually and thus analysed. Visualisations appeal greatly to Drew, who is by background an architect and illustrator.

There are various ways in which the nature of an organisation or a community can be expressed, e.g. through stories. Network thinking is a more structural approach. In network representation, one typically has some form of blob which represents an entity (such as a person, department, organisation), and lines are drawn between blobs to show that a relationship exists between the entities on either end.

Mindmap diagrams and ‘organograms’ are forms of network diagrams representing hierarchical set-ups, designed to limit the number and kind of connections possible. Others networks are more freeform.

Hierarchical organisation is just one way in which networks can be constrained. Other examples of constrained networks: connections between components in an electronic circuit are anything but random. You cannot travel on the Underground between King’s Cross and Seven Sisters without passing through Finsbury Park. Connections may also be strongly typed: the connectors in a genealogy diagram may indicate ‘was married to’ or ‘was the child of’, and some connections are not possible – you can’t be the mother of your uncle, for example.

‘Anything that can be drawn as a set of nodes and connections is a network,’ said Drew. The nodes could be people – they could be ideas. For the purposes of this workshop, we considered networks where the nodes are people, organisations and institutions: while not being accidental or random, such networks are not particularly constrained.

People who work with networks
Drew identified four kinds of people who may work with networks. These roles are not mutually exclusive and can overlap.

Network Thinkers understand the power of thinking in terms of networks and promote that view, usually applying it to their particular field, such as management or urban design. In economics, he mentioned author Paul Ormerod, who is a visiting professor at the UCL Centre for Decision Making Uncertainty.

Network Thinkers recognise that networks may have been designed for a purpose (‘intentional networks’), or may emerge from a variety of connections and purposes ‘unintentional networks’; the latter have patterns which evolve and change over time.

Network Analysts are probably those most likely to work with formally diagrammed representations of networks. They survey networks to figure out which nodes are more central, which are more on the periphery. For example, someone may not themselves have many links, but they may link key clusters within the overall network and thus play a central role.

For a simple network with up to about 20 nodes it isn’t too difficult to spot these characteristics in a network diagram, but when the diagrams get more complex it is a good idea to use software which not only draws a representation, but can also perform mathematical analyses (as described more below).

Network Builders help networks grow by creating and strengthening connections between other people, not just their own. Often these connections are between people (or organisations) already connected to the ‘builder’, who might also be described as a broker or bridge-builder. In the kind of community building work that David and Drew do, these people are out there in the community and serve a valuable function.

Networkers, Drew defined as people who are trying to build their own network. They may call their contacts ‘a network’, but more properly it is a list of their direct contacts.

Uses of network theory and analysis
Drew mentioned a number of applications for network thinking.

Organisations, partnerships. A prominent use is in management of organisations, e.g. creating networks to optimise the flows of knowledge and information. A more expanded but similar use is to facilitate partnership working between organisations, communities and individuals: this is a major focus of the work which Drew and David do, and Drew promised to give us examples.

Life transitions. Within a project for the Centre for Ageing Better, they are deploying network analysis with a time dimension, showing how a person’s networks of support and friendship and engagement can change as they age. In the example he showed us later, a fictitious aggregated persona had her network connections changed as her husband retired, then died; she compensated for this by joining activity groups in the community, but later her ill health prevented her from attending them. Also changing over time was her relationship to agencies and individuals in the health service.

Space design. As an architect, Drew notes that network theory can be used in urban design, to identify those places that are most central to the structure of and life in a city. Epidemiology uses network theory to understand how infectious diseases spread, and behaviours which have positive or negative health consequences (from jogging to alcoholism).

Military doctrine is defined by NATO as ‘fundamental principles by which military forces guide their actions in support of objectives… authoritative but [requiring] judgment in application.’ Drew said that the US military now talks about ‘fighting networks with networks’. In the US Military Academy at West Point, Virginia there is now a Network Science Center, a multidisciplinary research project for representing and understanding physical, biological and social phenomena through network-analytical approaches (see http://www.usma.edu/nsc/SitePages/About.aspx. Security services, police forces and of course intelligence services also use network analysis.

Some network concepts
Link maxima. There is quite a bit of maths in network theory, but some levels are easy to understand. Consider, for example, the relationship between the number of nodes, and the number of connections possible between them.

My explanation: suppose I have two friends: in network terms we are three nodes (ignoring our other friends for the sake of argument!). I’m friends with Jim, also Anna, but they don’t yet know each other. So Jim has one connection within the network, Anna has one, and I have two. I introduce Jim to Anna; now each of us has two connections, and the maximum number of possible connections between three nodes (three connections) has been reached.

Try drawing a series of simple circle-and-line diagrams, and count the connections possible. With four nodes, each can have up to three connections and the maximum number of connections is six. In a network of six nodes, each can form up to five connections; the total possible number of connections is 15.

There is a general formula; where n = the number of nodes, the maximum number of connections is n times (n minus one), and the total divided by two. With ten nodes, the maximum number of connections is 45. Double the size of the network to 20 nodes, and now 190 links are possible.

Of course, in a real live network, not everyone is connected directly to everyone else; in any case we just wouldn’t have the cognitive ability to maintain so many links. In networks which Drew and David have mapped, the most links any one node directly makes is about 15. But everyone is connected to everyone indirectly through intermediate nodes in the network.

Centrality. Network theory identifies several forms of ‘centrality’, which broadly stated is a measure of which are the most important nodes in a network system. Today, said Drew, we would look at closeness centrality and betweenness centrality.

As I understand it, the most basic kind of centrality measure is ‘degree centrality’, which simply means the number of links each node has. A person with links to 2 others in the network has less degree centrality than someone with 10. But this can be complicated if the links have some directionality. Consider, on Facebook or Twitter someone may have two million incoming links (‘likes’ or ‘follows’) and so is popular, but has few outgoing links and so is not particularly gregarious.

More complex centrality indices use the idea of the ‘length’ of a path between nodes. This is potentially confusing, because the spread of nodes on a network diagram is bound to mean that some connecting lines appear longer than others, but this is not what is meant. Length here is measured as the number of hops it takes to get from one node to another. If A is linked directly to D, and D directly to M, and M directly to Y, and that is the only way to get from A to Y, then the length of the path from A to Y is three hops.

A simple definition of closeness centrality is centrality to the network as a whole. Nodes which have a high closeness score are best placed to spread information across a network, and they also have a good overview of what is happening across the network.

Suppose you have 26 nodes in a network labelled A to Z and you want to calculate the closeness centrality of node M, add up the number of hops it takes to get from M to A, from M to B, from M to C and so on. The sum of all those lengths for M, divided by the total number of nodes, has been called its index of ‘farness’, and its index of ‘closeness’ is simply the inverse of this.

Betweenness centrality notes that some individual nodes are central to different bits of the network: this is common in networks made up of people. We can identify clusters of nodes that hang together, versus clusters weakly linked to the others. You might do this to identify who to lobby, to whom to feed information, to have the most effect on the network. Nodes with high betweenness centrality act as important bridges within the network, but may also be potential single points of failure.

Betweenness centrality is more difficult to compute. Repeating the above example, we would ask how often does node M act as a ‘stepping stone’ on the path between any two other nodes? This concept was introduced by Linton Freeman in 1977 to help identify, in human networks, who in a network has the most influence or control on communication between other people.

Eigenvector centrality measures how well connected a node is to other well-connected nodes, and such nodes generally play a leadership role within the network.

As I understand it, this is a kind of ‘metameasure’ based on already computed centrality indices for the nodes. Connecting to a node with a high closeness or betweenness centrality (a well connected and influential node) counts for more than connecting to one with a low score. You raise your eigenvector centrality score by connecting to as many well-connected people as you can.

Network density. There are various definitions of this metric. Drew thinks the most useful one is, the average number of connections per node within the network. This works for any network size.

Our imagined ‘A to Z’ network has a theoretical maximum of 325 connections, and if they were all active, each node would have 25 links and we could call that situation ‘100% density’. But polling the network, we may find that A actually has 5 connections, B has 7, C has 3, D has 11 and so on.

Clusters and communities. Network analysis software can identify clusters of nodes which tend to hang together. This is not because they share a common characteristic, but because of the place they occupy in the network. The software can then auto-colour those nodes in groups to help you to notice them. Usually these network clusters turn out to have a basis in the nature of real functional links within the community.

One method for detecting hierarchical sets of communities and sub-communities in large networks was developed at the Catholic University of Louvain in Belgium and is called the Louvain Method. It’s available as C++ or Matlab code and is used in social network analysis tools such as NetworkX and Gephi. (See a pretty thorough if dense explanation on Quora at https://www.quora.com/Is-there-a-simple-explanation-of-the-Louvain-Method-of-community-detection

Another approach to cluster detection is able to notice clusters that overlap, and that it would seem is what the Kumu web-based network analysis tool uses.

Types and uses of networks
David now took over the meeting. As a journalist he had noticed how in a community affected by some proposed urban development project, a ‘helicopter view’ might reveal disconnected initiatives across the community; how to join them up, how to overcome the silo mentalities which crystallise around different professions and cliques? Thus he became interested in network thinking.

David showed us a couple of diagrammatic slides originated by Harold Jarche. One, labelled ‘the network learning model’, creates a space between two axes. The vertical axis indicates ‘diversity’ and ranges from ‘structured and hierarchical’ at the bottom to ‘informal and networked’ at the top. The other axis has ‘goal-oriented and collaborative’ at the left and ‘opportunity-driven and cooperative’ at the right. Ranged up the diagram from bottom-left to top-right are three slightly overlapped balloons representing three levels of networks for sharing and learning:

  • Work Teams (structured, goal oriented): based inside a formal organisational structure, sharing complex knowledge, driven by deadlines, strong social ties, co-creating learning.
  • Communities of Practice (half-way along both axes): spanning shared concerns across organisations, a trusted space to test ideas, people don’t know each other personally, but integrating work and learning.
  • Social Networks (informally co-operative, opportunity-driven): high diversity of ideas and opinions such that you might find stuff you hadn’t considered in your task group; weak social ties.

Visualisation and analysis software
I have already mentioned the use of specialised software to help represent networks and to analyse them. After the exercise and a break, Drew returned to this topic. Most network analysis software, he said, has an analytical and heavily mathematical flavour: examples are UciNet and Gephi. But recently, easier-to-use software has appeared and he described three that he and David have used.

  • yEd is a free , open-source diagramming package for Linux, Mac and Windows. I have used this myself, but for drawing a particular kind of non-social network diagram: Entity-Relationship Diagrams (ERD) used in database design. According to Drew, yEd also has some ability to analyse network maps.
  • Kumu is their current favourite and main recommendation. It is a web-based system, and you can sign up for a basic free account at kumu.io. You can draw network diagrams with Kumu or it will make them from data and do the analysis; it can also hold stacks of attribute information attached to the nodes and the connections, which enables clever searches and filters on the diagram. Drew and David have been combining network analysis with Asset-Based Community Development methodology (of which, more later), and being able to annotate the notes with what assets they bring to the table has been very useful.
  • Polinode. Drew described this as ‘a very slick program’, also web-based, and business oriented. It has a built-in survey mechanism which is useful for collecting information about people in your business network and automatically populating the network diagram accordingly.

Example network maps

Readers may want to look at the PDF file of the slides to see the examples described here. The slides can be found online by clicking here unless you are reading this off paper, in which case the URL is: https://docs.google.com/presentation/d/1peVwMMIMvlzsfz9AWgA5rtVm_JNMzCyl3 7HUxJTYr0o/edit?ts=5784d539#slide=id.g115d229400_2_10

The first example was created through a survey conducted for the Irish Crafts Council, polling designers and makers, suppliers, retailers and agencies in Ballyhoura, South Tipperary, Wexford, Kilkenny and West Cork. It presents as quite a dense diagram with over 400 nodes and an overlapping mesh of connection lines which in places all run into each other so it is hard to distinguish them. The software discovered three major clusters, based on the link patterns. Interestingly, the clusters were based strongly on geographical proximity – it wasn’t the case that jewellers would network with other like craftspeople across the region, for example, but across the crafts, people networked locally and helped each other out.

The study also revealed that economic development agencies had lots of connections; in West Cork in particular, the agency played a leading role in the network. Meanwhile, though the Wexford and Kilkenny cluster showed a very dense pattern of connections, they were mostly connections within cliques of craft workers, and as such were not very influential across the area.

A second example was for a regeneration partnership programme for Berwick upon Tweed; in this diagram, all 50 or so nodes were organisations. Seven, highlighted on the diagram by the software, were major ‘hubs’ with multiple linkages, with the Borough Council as the most central, playing a ‘brokering’ role between the more strategic organisations at the top of the diagram, and the tightly focused local organisations at the bottom.

Within this project, they then compared the network graph with the results of a survey in which each organisation within the network was asked to rate their perception of (a) the skills held by the other organisations, across five categories and (b) resources those organisations also had to offer, across the same five categories. Dramatically, the Borough Council which the network analysis had identified as being ‘most central’ scores spectacularly the worst on both counts! This leads to interesting discussions. So do you pump money and training and resources into the Council as the centre of that network, or bypass them with a new project? (What actually happened was that all Borough Councils in Northumberland were disbanded.)

Kumu again, in detail
Drew was keen to point out that whereas in the past different software tools would have been needed to work on the different phases of the Berwick upon Tweed project, they were able to do it all simultaneously in Kumu. If anyone is interesting in pursuing this, after this session, he suggests that we get a free Kumu account. That will give each of us a Kumu ‘name’, and he suggested he could put up a Kumu site where we could discuss this stuff and experiment.

There are various ways of getting network data into Kumu. You can draw directly to the screen; Drew likes drawing so he appreciates this. Or, you can type commands into a screen terminal. Comma-separated database files (.csv) can also be uploaded. Kumu can ingest spreadsheet files from Google Sheets, and these in turn can be fed from Google Forms, Google’s form-interface web-based input software. Drew also noted that Kumu is planning to introduce its own integrated survey module soon.

Kumu, as already explained, lets you add extra data to nodes, add node attributes, and tag nodes, which makes search and filtering more powerful. Drew also believes that the developers are very responsive and they listen to how people want it to develop.

More examples, fictitious and applied
Drew showed a network map for ‘Slipham’ – a fictitious community which they use for testing ideas and policies. It is populated by the kinds of local people, organisations and services which would be typical for most communities: there’s the General Hospital and a group GP practice, a branch of Age UK, a number of local councillors, a Somali Association, the Rotary Club, the Police, several sports clubs, etc… and a number of individuals who provide bridging functions through their multiple engagements.

The ‘centrality’ measures for the nodes are emphasised on the map by having the more central, better connected nodes displayed as a proportionately larger circle. The circles are coloured – automatically by the software, on the basis of attribute data that has

been entered for each node. Nodes around education are coloured yellow, red signifies health and social care, and blue is socio-political. (How Kumu displays nodes and links can be customised by bits of Cascading Style Sheet coding, as used in Web site design.)

Drew switched to the Slipham map in Kumu itself, online, and demonstrated how each node can have attributes stored ‘within’ it. He also showed some of the ways that a map can be probed, for example by clicking on one node and having the map display only those other nodes directly linked to it as working contacts – or perhaps within two ‘hops’ rather than one. Selecting two nodes at opposite sides of the map, he got Kumu to show the immediate links of each, helping to identify a couple of nodes shared between them, which could be used as conduits for contact or liaison.

Drew demonstrated a network map produced for NHS Education Scotland (NES). The connector lines on here were interesting in three ways. Firstly, they displayed as curved rather than straight; they displayed with three grades of thickness; and they also seemed to indicate directionality, as each line had an arrowhead at just one end.

The purpose of this investigation was to identify sources and flows of information. The thickness of the line indicates the ‘volume’ of flow (an attribute which you can control by adding a value to the data behind the connection), and although Drew did not explain this, the arrowheads clearly indicate the direction of information flow.

Drew used this diagram to warn of an effect in mapping in real life, which is that one often works for a single client within the network (in this case, the NES), who readily provide their own links, and those initially dominate the map. If you want a more thorough picture, you will have to make contact with the organisations they have identified, and survey them to try to ascertain their links too. It may take a few iterations of this process to get the wider picture.

A second exercise (or game)
We had already had a simple discussion exercise about networks in our table groups. Drew now offered something more playful. He used Kumu to present an abstract network map where the nodes were identified by numeral only. Displayed next to this map on the left was a listing of the ‘top ten’ nodes ranked by betweenness centrality. Each table was to ‘adopt’ one node and then try to promote it up the centrality score table, either by adding a link, or deleting one. (The ‘adopted’ node did not have to be a terminus for the link added or deleted.) Based on table choices, Drew input the changes into the Kumu map and re-displayed the rankings. We did this a couple of times.

The game was competitive and fun, and less confusing than it might have been, because three tables adopted the same node, and two another. The biggest effects came from making or breaking links between nodes which were already well connected. This was a good exercise in learning how to ‘read’ a network diagram.

Collecting information for mapping
After the exercise and a coffee break, Drew gave us guidance about how to prepare for network mapping by gathering information. Where a community is dispersed or hard to collect together, you might prepare an online survey; they’d used Google Form, but Survey Monkey also works. The data may have to be fed in via Excel or Google Sheets, and as Comma Separated Values (.csv). London Voluntary Service Council is currently doing a network mapping exercise using online forms.

If you are holding an event where participants are present, you could get people to input data straight into Kumu, or create a drawn-up paper sheet or questionnaire. Drew showed a model: an Organisational Mapping Sheet they had prepared to collect data for a project on tobacco reduction. Each organisation notes their name at the top of the sheet, and adds some ‘interest keywords’ – I guess this is used to sift the nodes into categories, and so would work best with a predetermined tag vocabulary.

The sample illustrated then had a number of small repeated tables, the first of which was for ‘your organisation’. One box asked ‘Sharing?’ – if you think your organisation is good at sharing, you tick it; if not, you leave it blank.

The sample form then listed five rows of activity: Online communications, Technical, Management, Financial and Community, and next to each of this was a box for ‘Skills’ and another for ‘Resources’. If you have technical skills, you tick that box, and if you have financial resources, you tick that. Otherwise, you leave them blank.

The sample sheet shown had seven other mini-tables identical to the first, except that rather than being about ‘your organisation’ this was for your private opinion about the sharing abilities, skills and resources about the other organisations with which yours was most in contact. There was a note to assure people that ‘individual contributions will be confidential and unattributable’.

This is just one example. Depending on the theme and the nature of the community, the skill and resources sets may be different. Instead of a tick or the absence of one, you could calibrate the data with a numerical score, for example a plus or minus figure, or a number between 1 and 5, or a number of ticks. A calibrated assessment seems to have been used in the Berwick upon Tweed case study described earlier.

Other supplementary means for collecting data could be face to face or telephone interviews. If you are ‘iterating’ the investigation by contacting other organisations named in the linking, telephone interviews make a lot of sense unless you have an online form resource and can invite the second-round participants to fill that out too.

Not that difficult!
Drew showed one example of a fairly complex network map encompassing about 70 organisations, which had been created by the manager of the a Children’s Centre in Croydon to indicate those involved in some way in Croydon’s ‘Best Start’ programme, for children under 5 in families at risk in some way. Following a workshop, she went home, created a Kumu account and without previous experience of network mapping created the network map in two hours.

Another advantage of developing a network map in an online environment like Kumu is that Drew was able, as it were, to ‘look over her shoulder’ and help her remotely to develop her network map further.

One problem with a network map created thus by an individual is that, although she thinks those links exist, she doesn’t know for sure, and the links are unqualified in other ways. A maxim in the network mapping community is ‘the node knows’ – best not to speculate but ask people and organisations in a prospective network what their connections really are.

Time-base networks: the CFAB example
Networks can have a time dimension, and Kumu can cope with these too. An example might be a flow-chart, or a process-mapping chart.

Family Maps. As mentioned briefly above, a recent project which Drew and David have tackled is for the Centre for Ageing Better (CFAB), which wanted to investigate how technology can be used to assist people in later life. They started by developing six ‘personas’. A persona is a fictitious person who embodies a set of characteristics typically found together, so can represent a sector of the population in a simulation game such as one that CFAB ran with 50 people at one of their conferences.

These personas were based on research conducted by the polling company IpsosMORI, who have a database of population characteristics from polling, plus focus groups. IpsosMORI had already concluded that three factors dominate in securing well being in later life: financial security, health, and social connections.

Based on IpsosMORI cluster work, the CFAB project created ‘Mary’, whose tagline was ‘Can Do and Connected’. The character was represented by a cartoon portrait by Drew, in which she says ‘I want to remain independent as long as possible!’ Five sentences explain that she is 73, owns her home outright, but feels she has to watch her spending. She recently lost her husband, but stays positive with support from friends and family, and engages in local activities. She has long-term health issues, but hopes things will improve and stays optimistic. She uses an old mobile phone for calls and texts, but her attitude indicates she would explore technology further if she thought it would help…

Mary lives in ‘Slipham’ (of course) and has connections with various agencies there such as the General Hospital, a community nurse and a bowling club, plus several individuals who are friends, children and grandchildren, etc.

For this project (perhaps through the gaming process?) they also developed time-based maps which showed how Mary’s network might evolve over time: she compensated for the loss of her husband by joining community social activities such as ‘PowerAgers’ (a walking group), but later had to give them up due to advancing ill health, which also changed her needs and her network of support from health and social care agencies. For the network mapping in Kumu, this evolution of her network was coded by tagging each node in it for inclusion in various year bands. You can then advance year by year (in this case, in five-year steps) to see how the persona’s network develops.

The purpose of the exercise was to explore how support services might be better co­ordinated to help people as they get older – and the role which technology might play in that. This was allied to investigation of how vulnerable people are to social isolation.

Drew spoke of the phenomenon of ‘social ageing’ – how our social connections change as a result of ageing. A related concept is ‘network risk’, which spots which kinds of contact network are vulnerable to sudden collapse. They tend to be the ones dependent on physical activity – but could also be impacted by poor public transport provision, or financial hardship, meaning that you can no longer afford to participate in activities.

Multi-level maps. Drew showed how for the CFAB exercise they created a custom version of ‘Slipham’. So long as the node entities reside in the same Kumu project, their links and other attributes will be inherited by other maps created within the project. Drew pointed out that a couple of the nodes on Mary’s personal map are also on the wider Slipham map – others, which might be relevant to Mary’s future happiness and well-being (such as Age UK Slipshire and the University of the Third Age), were not.

Linking to Asset Based Community Development projects

Drew’s final slide showed a very complex network map developed around several projects in Croydon, on which he and David are currently working.

I was interested to note that in the Croydon work, the network mapping is part of a larger programme using ABCD methodology – Asset Based Community Development. My awareness of ABCD has come from another community development practitioner, Ron Donaldson – who spoke at the NetIKX#78 event – and who uses ABCD in some of his own work.

Asset Based Community Development is an approach to developing activities and services within communities which focuses not so much on community needs as on the skills, resources and capabilities of individuals and groupings and organisations within a community. The approach was developed in the 1990 by John L McKnight and John P Kretzmann at the Institute for Policy Research at Northwestern University in Illinois, USA. The website of the ABCD Institute which they founded, anchored within the university’s Center for Civic Engagement, is at http://www.abcdinstitute.org/

For example, we may find out that the Methodist Church has a meeting hall, the school has a grassy area suitable for a neighbourhood fair, Darren is a whiz at Web sites, Ant is a cartoonist, Charmaine and Sue make Jamaican patties, Nguyen is a videographer and videomaker with his own kit, three of the gents from Men In Sheds would like to teach basic woodwork, Sarah has a pillar drill and lathe and can weld, Pushpinder creates theatrical costumes, three Green Party activists want to encourage materials recycling, Jordan can drive a minibus… If these assets can be put together in inventive ways, the community can start to help itself rather than waiting on help from on high.

A key tool in ABCD is the Capacity Inventory which gathers data about who has or can do what, and also finds out how they are connected to projects in the community. To me it has now become obvious that rather than a static card index or other capacity inventory database, an interactive network map with data behind it such as Drew had shown us using Kumu fits beautifully with Asset Based Community Development.

Audience feedback
Many people likes the example of ‘Mary’. Steve Dale said that it is not uncommon for our networks to shrink as we get older. Rob Rosset wondered if that is something we accept, or struggle against. Steve felt that maybe the ageing brain is not as able to cope with lots of connections, but thinking about people he knew years ago, such as in his Navy career – well, their paths have diverged from his anyway, and he would rather stay close to a smaller circle of family and friends who mean a lot to him.

Someone else affected by the story of ‘Mary’ thought exclusion and isolation are the other side of networking. She added that many people are not confident and outgoing networkers, so as well as thinking about how to strengthen our networks by building the links between those who link readily, we should also think about those who stand on the sidelines only for lack of encouragement.

Conrad reflected on the game we had played. Some people with try to strengthen their local dominance in a network, whereas if they were less egotistical and were prepared to connect on an equal basis with people at the heart of other clusters, more could be achieved. Drew commented that a network map can identify someone who occupies a strong network position – but that doesn’t guarantee the right constructive attitude!

David Wilcox reported that a concern of the London Voluntary Service Council is that in the current austerity climate, voluntary action is being crippled as the agencies and associations which used to serve as hubs are taken out. How can the existing groups become better at using network thinking and technology? But those organisations rarely have those skills and capabilities.

David has begun thinking it would be good to develop a range of personas which might represent Londoners – as a starting point for examining what kinds of connections they tend to have, and what they might benefit from in the future – either on their own, or assisted by ‘Network Builders’. Because it looks as if increasingly we are going to have to create social infrastructure from the bottom up. He’d be interested to know if anybody else would be interested in that, to get a project going.

Clare Parry thought that people may share a neighbourhood, but the communities don’t connect – the example she offered was of traveller communities not connecting to settled ones (different ethnic and cultural communities would be another case in point). David said that this was a feature of the ABCD work in Croydon which has been going for about four years. They have volunteer ‘community connectors’ and Drew has been using network mapping to help them identify useful points of inter-community connection.

Finally, Martin expressed concerns about the ability of network maps to misrepresent situations if the data input is wrong or insufficient. Drew said that network maps can give you insights – but if you really want to know what’s going on, you have to investigate that in the field.

This was an interesting and well-attended NetIKX meeting. It’s nice when we have use of the Upper Mews Room at the British Dental Association – it accommodates 50 comfortably around tables and is well lit, very suitable for the round-table syndicate groups which are a hallmark of NetIKX meetings. (To learn more about NetIKX, see http://www.netikx.org.)

As one of the early slides said, there are various ways of getting a picture of how things and people are organised, such as through stories. Network analysis is a more structural and structured method. But I think more people are comfortable with stories and I suspect some of my NetIKX colleagues felt they had waded beyond their depth when we tackled network theory! This may be why the story of ‘Mary’ resonated so well – however fictitious, there was a story in there. The stories around other projects such as the Berwick upon Tweed one also helped bring these to life for me.

I was intrigued enough by betweenness metrics and other abstract aspects of network theory to do more reading around them, if only to help explain them. I hope my expanded explanations of how these things work with reference to my fictitious abstract ‘A to Z’ network are (a) helpful and (b) not misleading!

Obviously there are subtleties of social network analysis and visualisation which we didn’t cover (and which could have led to rapid cognitive overload has it been attempted). For example: the directionality of links; the strength of links; how if at all to weight the value of a particular node’s contribution to the network. I look forward to playing with Kumu to discover more and I have signed up, as suggested by Drew.

On the CFAB example and social ageing —The story of Mary made me think too. Many people of my age (early 60s) and even decades older find that the Internet and social media, even Facebook plus digital photography, help us keep in contact with friends dispersed across the globe, people whom we meet face to face but rarely, and even make new friends by being introduced online to friends of friends. Quite cost effectively, and even if we are housebound.

Writing and reading – perhaps falling out of fashion? – can network us with others in great depth. Frequent emails are important to my mother and me. Text can link us to ideas across time as well as space, for example by reading books – or accounts like this of interesting meetings we may have missed…

In Mary’s story of ageing, illness decreased her access to wider networks, but that is not the only factor. There are many activities I cannot join for lack of funds. I cannot begin to express how grateful I am to have a 60+ Oystercard and therefore free travel across London!



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Storytelling For Problem Solving & Better Decision Making

Conrad Taylor writes:

On 22 March 2016, Ron Donaldson came to speak on the topic ‘Storytelling for Problem Solving and Better Decision Making’. This attracted nearly forty people, a larger than usual NetIKX attendance.

The focus of Ron’s work is helping organisations and groups of people to solve problems and improve understanding. He is eclectic in the workshop exercise methods he uses, drawing on Cognitive Edge methods, Participatory Narrative Inquiry (https://narrafirma.com/home/participatory-narrative-inquiry/) methods, and also the ‘TRIZ’ methods (www.triz.co.uk) and models for inventive problem-solving developed in the Soviet Union by Genrich Altshuler.

Ron describes himself as a ‘knowledge ecologist’. He has a degree in Ecology and Geology and a professional interest in ecological thinking and nature conservation, having worked for 21 years at English Nature, first on systems analysis and process modelling, then on knowledge management.

In around 1998, a workshop was run at English Nature by Dave Snowden, later the founder and Chief Scientific Officer of Cognitive Edge, but then a director in the IBM Institute for Knowledge Management. Snowden was then developing a framework for understanding complexity in organisational situations and a set of working methods for engaging people in problem solving. Exposure to these ideas and methods turned Ron’s interest towards the power of storytelling and knowledge management. Ten years later this interest pulled him away from English Nature into self-employment.

Ron explained that he has difficulty with the term ‘knowledge management’ – does ‘knowledge’ mean everything an organisation knows? Is it what’s left after you have pigeonholed some stuff as data and some as information? If knowledge is the stuff that is in people’s heads, as many would say, can it be managed? This is part of what turned him towards describing himself as a ‘knowledge ecologist’ instead: because one can at least aspire to manage the conditions/environment and community practices within which people know and learn things, and share what they know. Also, because ecology de-emphasises the individual and focuses on systems and interaction, it tends to subvert ‘business as usual’ in search of better and more communitarian ways of doing things: dampening ‘ego’ and amplifying ‘eco’.

Since 2008 Ron has been working freelance. In the last three years this has taken him into a series of local engagements, which he used to illustrate to the meeting the power of storytelling in solving problems and making better informed decisions. He had chosen examples from work around environmental issues, work with public services, and work with health.

Ron then went on to explain his various methods, including storytelling, small-group discussion (with half of each group moving on after a fixed time – rather like David Gurteen’s Knowledge Cafés) and techniques such as ‘Future Backwards’, which Ron later used as an exercise for the NetIKX group (see below).

Ron emphasised that he felt that he simply guides the process, facilitating without directly engaging with the subject matter. In fact, Ron has made this something of a guiding principle for himself: not to engage much with the content, simply make sure that people are participating, create the starting conditions, context and activities to support that, and reduce the opportunity for individuals to take over the conversation.

In a project that involved getting data shared between different local firefighting forces (even the hoses of one force would not couple with those of another), Ron suggested that they organise a workshop and invite people from all the local forces plus anyone connected with data and information externally, whether they collected it, processed it or used it. In this case the very fact that people were talking led to positive developments, both in practice and in the development of a ‘Knowledge Network’ across the fire services. Here Ron used an exercise called the Anecdote Circle, which has its origins with Shawn Callahan and colleagues in the Anecdote consultancy (http://www.anecdote.com/) in Australia. The Anecdote consultancy’s own guide to how to run an anecdote circle is at http://www.anecdote.com/pdfs/papers/Ultimate_Guide_to_ACs_v1.0.pdf. However, Ron went on to describe how he implements this approach.

Ron then gave another example. Steve Dale has been working with a project called the Better Policing Collaborative, which unites five universities and five police forces in a search for priorities in innovation in policing, which should lead to lower crime rates and a safer community. Steve and Ron worked together to facilitate a workshop at Birmingham University, getting police to tell their stories. Again, this was an application of Ron’s approach to the Anecdote Circles method.

One of the stories told concerned a man who had been arrested for shoplifting, somewhere in the West Midlands. It was his fourth offence, and this time he was going to be prosecuted. What social services knew (but the police didn’t) was that all the people in this person’s household had poor health. The Housing Association (HA – and they alone) knew that all the houses in that area were suffering badly from damp. What the hospital knew (but not the HA, nor the social service, nor the police) was that they were beginning to be inundated with admissions for major breathing difficulties and asthma. These connections had come to light only as the result of informal conversations between members of these groups, when they happened to be together at a conference. The way the story ended was that money was found from a health budget to pay the housing association to sort out the problems of damp; and it is hoped that as health improves, so will financial well-being, with a concomitant improvement in the crime statistics.

What Ron took away from that was that although the purpose of the exercise was to share stories between police, the story cast light on the advantages to society if stories could be shared between different agencies and departments.

Finally, Ron discussed some training courses run for a group of West Midlands nursing staff with responsibility for knowledge management.

One of the major health problems in Coventry, contributing to the pressure on services, is Chronic Obstructive Pulmonary Disorder (COPD), including emphysema and chronic bronchitis. Ron suggested that they should invite anyone engaging with COPD in the Coventry area to join a meeting using storytelling workshop methods. There has now been a series of such workshops, involving NHS staff, the various lung charities, staff from Coventry University, a chaplain who was involved with terminally ill sufferers at the hospital, and people suffering from COPD, including two women patients who had met in the hospital waiting room and were now supporting each other, as ‘buddies’, by sharing what they know.

Ron described what happens as the result of sharing stories as ‘mapping the narrative landscape’ for the subject you are dealing with. So, the participants at the workshop were asked to come up with ideas, and then cluster around the ideas that appealed to them the most.

What these COPD-focused workshops identified was that, as well as the various hospital-based and home visit services, it would also help to organise social events that people with COPD could attend and be made aware of knowledge available from the experts, who would also be there. So the meetings have been happening, on Monday afternoons in Coventry – people talking together, and playing Bingo, as well as talking to the specialists and the charities on a general or one-to-one basis.

Ron followed this observation with some stories about how COPD patients have been benefitting from the drop-in sessions, and how much they valued them.

The Coventry COPD drop-in project, known as RIPPLE (standing for ‘Respiratory Innovation Promoting a Positive Life’), has now been picked up by the innovation fund NESTA and mentioned in their recent report ‘At the Heart of Health – Realising the value of people and communities’. They cite RIPPLE as a great example of Asset-Based Community Development (ABCD), which is an approach that encourages people to discover their own assets and abilities and build what they want on that basis, rather than relying on the provision of services.

There is more at Ron’s Web site about the RIPPLE project (including a video) and NESTA’s reaction to it, here: https://rondon.wordpress.com/

Now the West Midlands has got the go-ahead to fund another six similar RIPPLE-based community projects, as well as the pilot for a similar initiative around diabetes.

Before the tea break, Ron briefed the meeting about the form of ‘Participatory Narrative Inquiry’ exercise that those attending were about to do, to gain some experience in table groups of a type of exercise evolved by the Cognitive Edge network, called ‘Future Backwards’. This is the same exercise that the fire service groups had undertaken. NetIKX members (and those who attended the meeting) can find out more about this in the fuller report on the NetIKX members’ website (www.netikx.org)

Ron brought the exercise to an end with about fifteen minutes to go, so that he could add some further information. He described how, in collaboration with Cynthia Kurtz, he has set up PNI2, the Participatory Narrative Inquiry Institute, as a membership organisation for people who use these methods (http://pni2.org).

Ron ended the afternoon by explaining more about the way he applies the various exercises and how he decides which technique to use in which circumstances. He emphasised, however, the importance of talking. Churchill’s comment that ‘To jaw-jaw is always better than to war-war’ seems to apply just as well to less dramatic situations than war!

Ron added that he always welcomes further conversations around these topics and would be grateful for referrals to any communities that might benefit from a similar approach, or gatherings wanting to hear some heart-warming stories. His contact details are:

Ron Donaldson, freelance knowledge ecologist

email:     ezrond@gmail.com
mobile:   07833 454211
twitter:   @rondon
website: https://rondon.wordpress.com/

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Storytelling For Problem Solving & Better Decision Making – Tuesday 22 March 2016

A story is a recounting of events based on emotional experience from a perspective.

We use stories to:

  • build maps of the world we experience so we can make decisions about how to act;
  • make decisions about what to believe in, what we see and hear;
  • transfer knowledge and information;
  • playfully simulate possible outcomes before we commit to a course of  action;
  • condense experience into packages that re-expand in the minds of listeners.

Stories engage our attention, influence our beliefs or actions, and provide a “partial suspension of the rules of the real” that helps us safely explore the future. Participatory Narrative Inquiry (PNI) is an approach in which groups of people participate in gathering and working with raw stories of personal experience in order to make sense of complex situations for better decision making.

In his presentation at the next NetIKX meeting, Ron Donaldson, who is an expert practitioner in the art and science of storytelling techniques, will facilitate a highly interactive and engaging workshop demonstrating the use of PNI in exploring a topical issue relevant to knowledge and information sharing. Delegates will get new insights into the topic we explore as well as practical experience in how to apply storytelling techniques to issues and problems they face in their own organisations.


Ron Donaldson is a knowledge ecologist and facilitator, experienced in applying Participatory Narrative Inquiry (PNI), Cognitive Edge ideas around complex systems and TRIZ the Russian Inventive Problem Solving methods.

Taking an ecological perspective means that you focus at the community level and catalyse the flow of meaning, knowledge and realisation of insights within a narrative landscape.The sharing of knowledge in an organisation is much more analogous to an ecology that needs to be nurtured than a precisely defined machine that can be managed. Ron is particularly fond of the idea that Ecology has at times been called the ‘subversive science’, since it subverts our egocentric insistence on separateness, and with it, our inclination to ride roughshod over the rest of the natural world.

Ron Donaldson’s website is https://rondon.wordpress.com/ and his Twitter account: https://twitter.com/rondon. To find out more about PNI see https://narrafirma.com/home/participatory-narrative-inquiry/.

Intended Learning Objectives

  • To understand how to create the starting conditions for new relationships and collaboration
  • To understand how to remove constraints and disrupt linear thinking, to allow an anticipatory awareness of the present to emerge
  • To know how to seed, trigger and encourage creative thinking and to experience storytelling as a way to share knowledge and ideas

Please register at http://www.netikx.org/content/storytelling-problem-solving-better-decision-making-tuesday-22-march-2016.

Although the normal rate for non-members is £30, there will be discounts available for returning members and others. For further information, please send an email to web[at]netikx.org.

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Human Capital – The Last Differentiator: Conrad Taylor writes

The speaker at this meeting was Rooven Pakkiri, who describes himself as helping business managers in organisations to use social media tools to further ‘Social Knowledge Management’.

RoovenPakkiriWhen he was working for the National Westminster Bank in the late nineties, Rooven attended a training session introducing the Internet, which for him was a transformative experience. He concluded that, as this technology would ‘level the playing field’ between large and small organisations, the main differentiator between successful organisations and those less so, was how they made use of ‘human capital’.

For me this begs a few questions. For a start, what is human capital? I think that Rooven specifically equated it with knowledge and, to be more specific, with ‘intellectual knowledge’. This is probably truer in some business contexts than in others – and, of course, it’s an opinion well tailored to appeal to Knowledge Management types. However, there are fields of collective human endeavour where plenty of other human attributes contribute a great deal to the success of organisations – for example, empathy and kindness, loyalty, patience, attention, bravery, honesty and imagination.

It also seems clear that there are many kinds of organisation where the key to success is a very material form of capital, where, for example, you need money to invest in building plant, access to cheap electricity and perhaps political leverage, as well as hiring people with the requisite knowledge and skills.

Rooven asked us to recall when we first used Google. (Actually, I thought further back, to the ‘fast’ aggregated search facility on GeoNet, to Gopher and, when the Web came along, to Altavista and OpenText.) The reason we are able to find out so much online, he said, is because it is in human nature to want to share information.

He also set up a dichotomy between broadcast television and ‘the Internet’ (I think he meant the non-social-media side of the Web) on the one hand, and the likes of Facebook, Twitter and Instagram on the other. The first set he characterised as ‘broadcast media’, and rather old hat, and the latter group as made up of user-generated content.

I’m less inclined to see these as opposed; rather, each form has its strengths and weaknesses and we combine them in ways that work best for us. Many tweets and Facebook postings contain short-form URL links to blog posts, YouTube videos, online articles and other more considered forms of exposition.

There was some discussion about the degree to which people are prepared to share their knowledge, especially if their relative monopoly of it confers status and power. Rooven talked about some organisational practices, and technology deployments, which could be used to encourage people to share knowledge within their organisation, for example ‘reverse mentoring’, where a junior person shadows a more senior and more knowledgeable employee and writes blog posts representing the senior’s knowledge and insights.

There is an issue here about what kind of organisational culture encourages people to part with knowledge, the possession of which may well make them more secure in their position and less disposable. It reminded me of one of David Gurteen’s knowledge cafés at which someone from the HR department of a consultancy enthused about their knowledge sharing culture, while in discussions after, people from PWC said you’d be mad to give any advantage to your ‘colleagues’, who were always scrambling to climb over you to the top of the heap.

Then Rooven cited Deloitte as saying that, these days, employees have to be treated more like customers than subordinates. Again, I think that can only be true in certain organisations and work-roles. I see no evidence that the modern shop-worker, bus-driver, nurse, teacher or fast-food restaurant worker is treated with this sort of consideration.

Rooven’s next foray into knowledge transfer looked at the enhanced opportunities for self-directed learning which the Web gives us access to, for example videos on YouTube, TED talks and participation in online groups. I think Rooven’s view is largely that any sufficiently self-motivated person can, by dint of tracking down online training materials and doing a lot of study, succeed in learning anything. He spoke approvingly of Malcolm Gladwell’s assertion that 10,000 hours of study and practice can turn anyone into an expert. (This is from Gladwell’s book Outliers, which Steve Pinker has described as made up of ‘cherry-picked anecdotes, post-hoc sophistry and false dichotomies’; I certainly think that autodidacticism doesn’t suit everyone and that interpersonal knowledge transfer still has its place.)

What does it take to make knowledge transfer an ongoing phenomenon in an organisation? Rooven’s business is based on working with HR departments to get collaboration and knowledge sharing going, using network software platforms such as Yammer, Jive and Connections. Here I would have liked more use cases, though I guess Rooven is hampered by issues of confidentiality.

There is, however, some literature to draw on here, such as Julian Orr’s study of Xerox photocopier and printer repair technicians, and Etienne Wenger’s case study of staff at a medical insurance firm, which informs his book Communities of Practice. But this can fall flat, as seems to have been the fate of the Local Government Association’s Knowledge Hub.

Rooven suggested that people who act as ‘connectors’ between people and networks are amongst the most valuable people in companies. This is virtually identical to Wenger’s thoughts on the role such people play – he calls them ‘brokers’.

Towards the end of his talk, Rooven mentioned a computer game where the player has to put together a winning football team by choosing the best mix of players with different talents. He asked, what if companies similarly assessed the human capital attributes of their employees (and potential recruits) and put together ‘teams’ fitted to solve the important problems of the day? Here at least Rooven appeared to acknowledge that intellectual knowledge is only one of a number of desirable aspects of human capital.

I was less impressed by his suggestion that the business world should move towards a general ‘labour on demand’ model, shopping around in a skills marketplace and using short-term contracts to get jobs done. Doubtless that is the logic of capitalism, but it is a poor recipe for human security and development.

Rooven spoke for longer than is usual at a NetIKX meeting and, after the tea break, he offered to continue with a demonstration of some of the software platforms he uses, but we opted to stick with the NetIKX tradition of syndicate groups, of which there were three, each discussing a separate question.

I was in a group that discussed whether business is moving increasingly from the domain of the Complicated to that of the Complex. That is, is the world of business akin to the engine of a Ferrari, which a competent mechanic can disassemble, fix and reassemble? Or is it like the Brazilian rainforest, a complex ecology of interplaying organisms and factors, where not only is it impossible to know everything about the system, but you can’t even know what factors you don’t know about? (The ‘unknown unknowns.’)

Rooven said this was from an article in the Harvard Business Review: ‘A Leader’s Framework for Decision Making’ by Dave Snowden and Mary Boone. It appeared in November 2007 and you can find it here: https://hbr.org/2007/11/a-leaders-framework-for-decision-making. The article presents Snowden’s ‘Cynefin Framework’, in which a situation requiring decisions to be made is analysed as belonging to one of four possible Domains: Snowden labelled these as Simple (later changed to Obvious), Complicated, Complex and Chaotic. Rooven’s question focused on the middle two domains.

Although the basic either/or question was hardly worth discussing, we pushed the topic further. Organisations have a dynamic life in which some aspects are complicated, but rules have emerged to regulate them. Sometimes the organisation finds itself struggling with complexity where the dynamics are hard to figure out, but that’s not cause for despair. Snowden’s recommended response is to probe the situation by devising experiments that are ‘safe to fail’, and see which of these interventions move the situation in a desirable direction.

So, we had quite a lively syndicate session, even if the connection between the question we’d been posed and the topic of Human Capital was very loose.

I’d like to extend this topic towards other human attributes, and towards know-how and tacit knowledge, not just what organisations think they can squeeze out of employee’s brains.

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Human Capital – The Last Differentiator: Lissi Corfield writes


At our seminar on 19th January,  Rooven Pakkiri spoke about – “Human Capital – The Last Differentiator”. If you want to hear a recording of the talk, then you need to join NetIKX (www.netikx.org/). For another view on the meeting, see Conrad Taylor’s comments in the next post.

Human capital 1 croppedDoes our knowledge management work fit the model of Kew Gardens or Richmond Park?  Rooven Pakkiri picked his metaphors well!  This one provided two excellent images to highlight the different scenarios knowledge management might face in their places of work.  His slides were a powerful part of a very coherent look into the future of organisational knowledge management.  Feedback from those attending the seminar made clear that this had been a very enjoyable as well as valuable session.

Let’s start with some ideas that are already familiar to us all.

Knowledge Retention

How can an organisation tap the knowledge of experts so that it does not leave when they do.  He suggested ‘reverse mentoring’ where you pair a bright young employee with your elder expert, to blog about their ideas.  This is a bit more dynamic than than the rather sterile and late in the day ‘exit interview’.

Or how do we flesh out increasing training provision while enabling the organisation to become a learning organisation.  Rooven advocates the power of self directed learning, where the trainee can proactively use web resources to meet their needs at a pace and time to suit themselves.  Youtube and Ted talks were his favoured choices, but of course, this could be mixed with the ever increasing array of MOOC’s and other resources available on-line…

And the familiar issue of culture – do we as humans ‘like sharing’ or do we naturally withhold our knowledge to emphasise our own power.  I really appreciated his perspective on this, focusing on the sharing that goes on with social media to suggest that we have a strong instinct to share with our social groups.  If this does not happen at work, perhaps we should investigate the barriers to sharing that the workplace presents.  Where companies only reward individual performance in isolation from the wider team work, humans are likely to curb their sharing nature to play the system.  Changing the system then might be more appropriate than trying to dabble with ‘culture change’.

Human capital 3 croppedChallenges in the workplace

Rooven then moved into less familiar territory for knowledge managers.

How do we ‘manage’ information and knowledge flows between people when digital is changing so fast? Once BYOD (bring your own devices) flummoxed IT departments who wanted to control all the parts of the IT system.  Where do we stand when people have even more autonomy and BYOA takes over (bring your own applications)?  How will we, as information professionals cope with no control over any of the digital systems that staff are using within one office?  The advantages for staff themselves are very apparent though; as they work with the applications they enjoy using, rather than those enforced by the organisation.  But working out how to integrate the resulting communication and sharing links looks like chaos.  Will we cope?

Human capital 2 cropped

We considered the fate of numerous well-known brands that have been knocked out by digital change. One prime example was Blockbuster, a firm whose business model rose and fell within our own lifetime.  Netflix was their nemesis.  Rooven asked us to face these ‘Black Swans’, changes that can come out of the blue and disrupt business patterns entirely.  Again, it is easy to see the advantages – if you love opera and theatre and now can watch the best productions live streamed to your local cinema.  But we all have to be aware that ‘out of the blue’ amazing changes may affect our own patch of the world of work.

One more example that I found fascinating was the growth of gamification.  I had seen this as about rather crude reward systems based on kids’ games.  But Rooven introduced us to a key aspect of FIFA, the football game that has been popular for a few years now.  The key was not prizes and rewards, but the skill of building a cohesive team that would play together.  Clearly not a team of top stars – even someone who has no interest in football could see that this would be a team overloaded with prima donnas!  The football game player is encouraged to consider the way teams work and meld a team that will bring out the best in everyone.  Now that is a skill that clearly has resonance in our working lives.  So will people willing to take the roles of ‘lynchpin’ and facilitator become more vital than subject experts once so much knowledge can be accessed across the web.

Unknown Knowns and Known Unknowns

If we have looked at the unknown knowns and the known unknowns, the only place to finish was in the unknown unknowns!  The really scary stuff – or is it the really exciting place to be?  We talked about where knowledge and information professionals and librarians may be developing in the future.  As we know, the key knowledge resources are primarily in people’s heads, but with digital changes, are we now moving to a world where multi-faceted relationships brush aside organisational hierarchies?  Where knowledge management does not become easier or any less important, as it has to be ready to move with the unknown opportunities that will emerge.  We may be tending our internal glories, as Rooven modelled in his image of Kew Garden.  Or will we be looking at open systems, more on Richmond Park lines?  His talk left our heads reeling in a most stimulating way.  The images did look enticing (see http://www.slideshare.net/Rooven/icon-uk-2015)!

Questions for the delegates

Here are the three questions that Rooven set us to discuss in the seminar sessions:

  1. Did the group agree with Robin Dunbar’s assertion that humans can associate with a maximum of 150 people?
  2. Google allows us to know how to find something, rather than actually knowing anything – what are the implications for KM and Human Capital?
  3. Is it true that business is moving increasingly from the domain of the Complicated, to the domain of the Complex?

Questions for you

Three questions for members (and others) reading about this seminar:

  1. What changes to your work have unexpected digital revolutions caused?
  2. What ideas do you want to contribute relating to Rooven’s three seminar questions?
  3. Are there ideas here that you would like followed up in a future seminar?

We would be interested in your feedback.

Some relevant Tweets from Rooven

(See https://twitter.com/RoovenP – @RoovenP)

Power of social interaction…

3 Nov 2015: “More knowledge is created in social interaction than can ever be found in a database.” @grantgross http://www.cmswire.com/information-management/knowledge-management-grapples-with-agility-complexity/ … via @CMSWire

Self directed learning…

12 Nov 2015: Self directed learning – The L&D world is splitting in two http://www.c4lpt.co.uk/blog/2015/11/12/the-ld-world-is-splitting-in-two/ … via @C4LPT

A culture challenge!  

18 Dec 2015: imagine HR tagging indivduals and their content for 1 month – calculate the impact in terms of inclusiveness, culture shift and credibility

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Human Capital – The Last Differentiator – Tuesday 19 January 2016

How do you keep your skills relevant in an ever changing environment?

Can Social Knowledge Management provide answers?

As we adapt to new workplace challenges (or opportunities) at a time when organisations are looking to increase productivity and make savings through automating routine work, we need to think about the ’human differentiator‘ – in essence, ensuring that we are all still employable!

In this interactive presentation at the next NetIKX meeting, Social KM expert Rooven Pakkiri, will discuss how we can transform the way we engage in our work, with radical strategies based on ‘Social Learning’, ‘Talent Insights’ and ‘Decision Sourcing’.

As we move forward, a key differentiator of successful organisations will be whether and how they are able to leverage in a consistent way the talent and knowledge of their workforces so as to meet their objectives. Companies that are bound by tradition and hierarchy will struggle to compete.

This session will enable us to consider how we fit within this changing environment and how we can continue to learn new skills and remain relevant.


Rooven Pakkiri works with clients to deliver sustained adoption strategies for collaboration platforms such as Yammer, Jive and Connections. His focus is on engagement (often through HR) with the business managers in an organisation. Together they design, develop and deploy a highly customised Social KM road map that revolves around the use of the social tool set in order to solve client-specific business/organisation problems or to address current opportunities. Everything Rooven does is led by business/organisation requirements and user adoption and not by the features and functions of the chosen collaboration technology.

A veteran of the dot.com era, Rooven is a digital evangelist who focuses on the way technology changes organisational communication and collaboration. He is an author and regular speaker on the subject of Social Knowledge Management and how it is transforming the corporate rule book. Rooven is also the co-founder of a regular thought leadership event in London at which independent thinkers discuss issues of user adoption and cultural transformation.

As a Social KM consultant, Rooven is responsible for developing client-specific adoption strategies and immersion programs. As part of this process Rooven employs a number of techniques such as  scenario modelling, content seeding, champion identification and community development.

Intended Learning Objectives

  • To be aware of how we fit within the changing organisational environment
  • To learn how to keep our skills relevant in this ever-changing environment
  • To understand how Social Knowledge management can provide answers


The British Dental Association, 64 Wimpole Street, London W1G 8YS (The nearest London Underground Station is Bond Street)

Registration is at 2.00 pm and the meeting will run from 2.30 pm to 5.00 pm, with a glass of wine and light refreshments to follow until 6.00 pm.

Seminar Costs

If you are a NetIKX Member or join NetIKX when you register, there is no charge.

Non-members are welcome to attend.

Please register at http://www.netikx.org/content/human-capital-last-differentiator-tuesday-19-january-2016.

Athough the normal rate for non-members is £50, there will be discounts available for returning members and others. For further information, please send an email to web[at]netikx.org.

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Offshoring/Outsourcing Information Services

Offshoring or Outsourcing your Information function – either, neither or both?  Whatever your situation the issues raised by this question are complex and fascinating.

Globalisation and the impact of the internet has changed so many aspects of our lives.  In this seminar on 19 November 2015, NetIKX members and guests looked at one important change that is now possible – relocating your information services team to far off places, or even outsourcing your information altogether to another organisation.

We had two lead speakers – Chrissy Street, now Head of Central Information Resources at Clifford Chance, and Karen Tulett, who is currently a Director at Morgan Stanley. In two presentations that revealed their long and impressive experience as information service leaders, they opened our eyes to the wide range of possibilities that is now available, and the pros and cons of different approaches.

The complexity of the situation was shown by the evolutionary paths taken by the companies as they look to get better research outputs for their money. At times, using employees with lower labour costs in different locations of the same company has proved good economic sense, but at other times, they have used the strategy of getting a separate provider to take on their information service needs.  Our speakers had experience of managing both types of change and Karen had even worked on the other side as a manager of an outsource providing company.

Outsourcing and offshoring were not simple alternatives to keeping work in the home office.  The companies concerned have both used an evolutionary approach. By using a ‘mix and match’ approach, they have been able to widen the range of options to suit their circumstances.  There were serious economies to be made from the best choices.

Much of the work has been focused in India, where a well-educated workforce is available to reduce costs. However, the companies have also continued to have a team in the UK.  Motivating staff was not a serious issue as in many ways, the new arrangement can be positive for all concerned.  Local staff continue to work on the higher value, more challenging work, while offshoring workers enjoy the opportunities offered by the routine work, as can be seen by the fact that some people have stayed with the company for over nine years.

Standards can be maintained by careful controls. If language is an issue as the workers are second-language English speakers, careful controls can be set up to monitor any problems. One important recommendation was to have a very robust quality control process. In addition, it is advisable to use a checklist to assess the suitability of a work task for offshoring and to ensure that there are no copyright compliance issues when information services tasks are taken offshore.

Further advantages were outlined.  Karen’s unit offers services almost 24/7 through a combination of onshore and offshore. Morgan Stanley has set up quick turnaround research unit this year, which shows that change keeps on happening!

At the end of the presentations, seminar groups discussed key issues raised.  These included the problems of setting standards for outsourcing or offshoring and the use of SLAs (service level agreements) and KPIs (key performance indicators), together with their advantages and disadvantages.  The group concerned considered that these could be straightjackets but also were necessary for distance controls.

Looking at changes facing information services, we move on to the next meeting to consider social knowledge management – how we keep ourselves employable while technology cuts a swathe through traditional ways of delivering services.

The meeting finished with a bubbly celebration for all attendees.  It was a powerful and joyful end to NetIKX’s three-year programme.


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