2023 Knowledge Mapping - Hexi approach

• The whole point of Hexi is reuse and trans-initiative integration rather than multiple siloed initiative within a utopian paradigm

Discovery Phase

• Two parallel activities
  • Gather decisions (to set the meaningful context) and also to ask the ASHEN question
  • Discover matters of concern to senior and primarily middle management in a larger organization
    • Could be the whole of the organization if needed

Collection methods include:

• Anecdote circles (physical or virtual)
  • Gather anecdotal material about actual projects and activities that happened in the past
• Future Backwards
  • Fictional stories of what might have happened or might happen in the future
  • Fiction is as good, and often a better disclosure technique than seeking facts
• MassSense which is a SenseMaker® application that can present material to stimulate multiple respondents or simply ask them for ideas
  • Prompt is a map of key processes
  • Used that map as a signifier in SenseMaker® to support material entered and interpreted by each respondent
• Genba, a SenseMaker® application allowing journal based capture of decisions, observations, ideas etc.
  • Use one-time or as part of a continuous process
  • It is both a journal and a tool for journalists so people can interview other people abut decisions
    • Technique works well with senior management and high status professions who will respond to an apprentice but less so to a consultant and don’t think they have time to maintain a journal

• Once gathering is complete we move into decision extraction and identification of various aspects for each decision cluster:
  • Information received (and that we would have like to receive)
  • How the decision is communicated (and how that communication might have been improved)
• Decision clusters are then given a name and placed onto a brainstorming area (physical or virtual)
• Sequence and connect decisions
  • Information out from one decision will be information in to another and so on
  • If a decision doesn’t connect to another decision or a start end point then we have missed something and we need hunt it down
  • Outcome will be a very messily coherent map
• As we identify the decision clusters we also ask the ASHEN typology question
  • Gather the results of that on another work area, randomizing them in initial placement

• In parallel to the above, find out from managers or those with funding what are the current strategic and operational issues that are keeping them awake at night
  • Ideally they too will use the Genba system or respond to the MassSense survey
  • Otherwise you may need to go and interview them

• We finish this phase with a decision map, a mass of ASHEN elements and a list of things that matter to whoever is the effective sponsor – might be middle management, leadership or the wider workforce or even external stakeholders
• One of the nice things about software methods for discovery is that they not only scale, but they also allow us to capture of a lot of the elements for decision mapping

Sense-making Phase

Stream one: reality check on process (vertical on hexi map)

• Compare the decision map (work-as-done) with the process map (work-as-imagined or planned) for the organization
  • If they don’t have that then sit down with Executives and get them to describe how they think the process works, draw it up and get their endorsement
• If the differences are so great that meaningful comparison is impossible
  • Abandon the how we think it is more or less
  • Look at how we can stabilize and consolidate current reality to create something with more transparency and scalability
• In the extreme case where it seems people do not follow process, treat as a learning opportunity
  • It may be due to passive aggressive resistance to change which will need a mix of enforcement and understanding
  • It may be helpful to introduce Cynefin to describe why people are not following process
    • Do they feel close to the Clear/Chaotic boundary?
    • Are they confused (Aporetic domain)?
    • Do conditions enable uncertainty or unpredictability to emerge {Liminal domain between Complex/Complicated)?
  • Making sense of the situation may mean
    • agreeing in the middle
    • a set of amendments
    • exception-based decisions (distributed decision making in which combinations of roles have the authority to change any formal process and even break it, subject to transparency)
• All of the above results in a series of action items
• Items are randomized onto a work space for later use

Stream two: creating the dependency grid (horizontal on hexi map)

• The various ASHEN elements need to be clustered into Knowledge Objects
  • Ask people with experience of the domain to cluster all the ASHEN elements into groups of things that cab be managed as a coherent whole
    • Remember that ASHEN is a typology so your lists should not say that this is an artefact or a skill, but just say what the question revealed
  • Knowledge Objects are then placed on the vertical axis of a grid in no particular order but they are tagged based on an assessment of the vulnerability to loss against impact.
    • High vulnerability/Low impact = no issue
    • High vulnerability/High impact = a priority
• Things that keep people aware at night then form the horizontal axis and impact is the main tag
• We then distribute the grid and get people to score dependencies
  • Use a 0-5 scale or simplify it to high dependency only
  • This can be a spreadsheet distributed to thousands and then the mean scores are used to indicate high dependency (gradated yellow on the picture)
  • In a workshop it can be done with simply voting, discussion in parallel with comparison and so on
• Now look at the picture and cross our eyes
  • It’s a long standing technique to disrupt perception and sense new patterns
• What we then see are two patterns:
  • Horizontal (one knowledge object impacts multiple issues)
  • Vertical (one issue requires more effective management of multiple knowledge objects)
• Each of those patterns is a project and they have different characteristics
  • Vertical are more difficult to execute but generally have a single owner
  • Horizontal are easier to execute but ownership and definition of success are more difficult
• We then look for other patterns
  • An issue with no dependencies may mean that we need to acquire knowledge we don’t have
  • A knowledge object with no dependencies may be surplus to requirements or may be a neglected opportunity
  • Single or limited dependencies require more attention and they are rarer than you would think.
• So we have another portfolio of projects but we also have a built-in prioritization
  • Each micro-project is tangible and linked to a clear need
  • No platitudes, no idealism just plain pragmatism
  • Some projects may contradict others
    • We won’t know who was right until we engage

• As a general note , the approach scales
  • In Bank of Thailand we had multiple spreadsheets and the overall dependency for thousands of rows by thousands of columns
  • In a two day session with the British Treasury (that ended up with the Permanent Secretary staying for the whole process as he was fascinated) we had a single matrix projected onto a screen
  • Granularity scales as you can assemble from the same source material at people’s capacity to act: a key principles of anthro-complexity.

Action phase

• Cluster the projects and then map them onto Cynefin and they will either fall into a domain, or in the liminal areas between domains
• In some cases they may (per the aporetic turn in the EU Field Guide) be in the centre and require further division
• Clustering into Cynefin will result in
  • Ordered projects which just need to be executed,
  • Complex projects which require parallel safe-to-fail experiments
  • Domain transition projects that require constraint modification
  • Hexi forms are available to provide structure as scaffolding helps
• Technology decisions
  • Look at common practices
    • If data capture is needed from employees then the deployment of SenseMaker® Genba might service multiple projects
    • We might need a set of Communities of Practice
    • We might need search technology
  • The point is we don’t start with technology solutions as those come last
• Create monitors per project cluster or project assembly
  • Outcome based or vector based
  • Rhythm of their use may be different along with the consequences of success or failure
  • At this level we would expect significant levels of failure in the short term to increase learning and thus resilience
    • In comparison, a top-down knowledge programme is far too vulnerable to failure

• Finally what we are really trying to achieve here is to create a continuous scanning and response process in which the maps change in near real time rather than being a once off technique
  
• Knowledge is dynamic
  • it changes with context and humans, with their capacity for abduction, are really good at handling uncertainty with the right scaffolding
  • We just don’t build systems which utilise that capacity as we attempt to eliminate rather than navigate complexity

• Adding in Estuarine Mapping can be done as part and parcel of the same exercise and may be a good way to find things that should be keeping people awake at night
  • The end point is another portfolio of projects
• Granularity, the ability to fail and the enablement of emergence – the heart of complexity

Everything together

Colour coding:

• Green are optional methods/tool that can be used standalone or in combination
• Blue (dark and light) represents formal Cynefin methods, the light blue are optional extras
• Yellow represents micro projects
• Red represents workshop of consultancy processes
• The black dot with a C indicates combination or connection
• Double white arrows indicate interaction
• Single arrows represent interaction between processes or method, they are not show where it is obvious