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From Reality to a governed business

DD

Hi All

I’ve taken some time to go through Phil’s document - From Reality to a Governed Business properly. This is my take on it.

@PhilipM
First off - I think it’s a really strong piece of thinking. The way you’ve laid out the progression from discovery, through modelling and visualisation, into analysis, simulation and governance is clear and coherent. It does a good job of moving the conversation away from tools and towards capability, which is exactly where it needs to be.

The diagram in particular brings it together well - it’s easy to see how the different elements fit and how something like x42, Integreli and BIG can sit within that flow.

What struck me, looking at it alongside the conversations we’ve been having, is that this feels like a very solid description of the capability and end state. Where I think we could strengthen it further is in how an organisation actually gets there in practice.

A few thoughts that might be useful to build on what you’ve already got. I think you have already thought about these things, but here is my take:

The first is around what triggers this in the real world. The steps outline a practical route from complexity to organisational intelligence - but why would we take them? Most organisations won’t start from a desire to “model themselves as a system” (maybe a CIO might?) - they’ll start from a problem they can’t resolve - and perhaps from one angle unless a coalition forms. What is happening today that creates the need for this approach? I think we might need to help raise perception of this need.

Related to that, is the idea of priorities and roadmap. The document is strong on structure, with a lot of ‘do’ in it - but a little lighter on the stepping stones to get there. Being a generic document - I would not expect specifics but reference needs to be made to a journey of steps. The idea of capability maturity, and adaption / adoption through business areas?

Thinking about how this maps onto a BIG lifecycle:
https://big-cic.org.uk/wp-content/uploads/2025/04/BIG-CIC-Services-Taxonomy.pptx
First Steps - this is the step I think isn’t included?
Discovery - Steps 0 and 1. Includes roadmap (Current to Target Operating Model, with stepping stones) and busienss case
Build (Core Enablers) - this is a service to the roadmap at the back end of Discovery. Creating a sequence of capability
Adopt (Culture Change) - this is helping the business leverage the capability in Build into the new operating model
Sustainment - supporting operation, overseeing product releases into the environment, on boarding additional areas etc.

None of that detracts from what you’ve put together - if anything it feels like the natural next layer. What you’ve got is a really solid foundation for how to understand and model the organisation. The opportunity is to connect that more explicitly to how organisations decide, prioritise and act.

Happy to talk this through if useful - I think there’s a strong combined story here.

Best,
David
@EliO @TonyS @ChrisB

simon

DD From Reality to a Governed Business

@PhilipM is this the pdf you were trying to upload?
I’d be interested to look too.

@dd at a guess we can make a ppt an embedded display in a post

I’m going to experiment…
Haven’t cracked it yet…

https://logicalmodel-my.sharepoint.com/:p:/g/personal/simon_logicalmodel_onmicrosoft_com/IQDaZm--f0eYQ7_3q96MRKSRAV6z_zGrfYhO4V9ZgEn-qKA?e=TQqzHO

TonyS

Hi all,

The business should already have a clear TOM i.e.
we need to change X, Y and Z (systems, process, structure, suppliers, etc.)

The question then becomes:
what is the impact of those changes on how the business actually operates?
That’s where x42/BIG comes in with a focus on OPS and procurement, as they cut across most transformations.
For any proposed change, we can assess:
• does this impact operations currently in flight or planned?
• does it affect existing or new supplier contracts?
• does it affect customer commitments?
• does it impact workforce obligations or capacity?

In other words:
how do these changes propagate through real obligations, constraints, and dependencies?
The output is a business impact assessment, not a TOM:
• what breaks
• where pressure builds
• what is at risk
• and what needs to change to make the TOM viable
So:
• TOM defines the intent (X, Y, Z)
• x42/BIG evaluates the viability and consequences of that intent
Which then allows the TOM to be refined based on how the business actually behaves.

Tony

simon

Hi @TonyS
I’ve long had a model with a four‑column picture of Simple, Complicated, Complex and Chaotic themes within leadership, management and supervision.

Most of what we’re wrestling with in real organisations isn’t neatly in one column or at one level.
It’s a moving mix of all four at once and heavily skewed by incentives and individuals navigating the system for personal gain and risk(threat) avoidance.

I’m really interested in how x42 is intended to navigate this terrain.

When supervision, management and leadership are simultaneously dealing with deterministic cause–effect in some areas, probabilistic and partially‑known factors in others, and genuinely unpredictable or chaotic elements at the edges, most notably the future how does x42/BIG help them work with those variation rather than seeming to provide (hallucinate) answers ?

More concretely: how does the x42 model represent and support decisions across all four columns in a way that gives leaders genuinely useful visibility and challenge, without creating an impression of certainty or control that is stronger than is actually safe in practice? How does it port managers and supervisors engaged in keeping the lights on and the doors open today while transitioning towards tomorrow?

I’m also curious how x42 thinks about the guidance to the organisation at all levels: Ashby’s requisite variety advise that our governance machinery must possess n + 1 dimensions of control, n is the number of variables to be controlled with in the variety of the environment, while Herbert Simon’s Bounded Rationality reminds us that individual and collective decision‑makers can only process so much info in so much time (which never stops advancing And the future is a combination that includes our historic actions and how others respond to them).

How does x42/BIG design its models, views and decision flows so that they increase the organisation’s effective variety without overwhelming bounded human rationality?

How do you judge when the granularity or confidence implied by the model is tailing off (or contains catastrophic cliff edges - Thin red downward arrow below) for the reality it is being used in?
See

Finally
I’m also wondering where x42 is intending to sit in the existing tool landscape?
Is x42 using, extending or effectively replacing gluing together or sitting above notations such as Issue‑Based Information System notation (Questions/Issues, Ideas/Options, and Arguments/Pros/Cons from Horst Rittel, GQIM from sei/cmu, BSC + OKRs etc) and or classes of tools such as graph databases (e.g. Neo4j‑class property graphs), enterprise knowledge‑graph platforms (e.g. Stardog‑/eccenca‑class semantic stores), graph‑visualisation frameworks (e.g. Linkurious‑/KeyLines‑style dependency explorers), and modelling/architecture tools (e.g. ArchiMate‑/SysML‑style model repositories)? Or is it envisaged more as a specialised capability that orchestrates and overlays these kinds of components rather than substituting for them?

Ciao
Simon

simon

Yep.
Mostly I agree with everything you said and I said that above.
Here

simon It’s a moving mix of all four at once and heavily skewed by incentives and individuals navigating the system for personal gain and risk(threat) avoidance.
And
simon And the future is a combination that includes our historic actions and how others respond to them).

Everything is interpreted by individuals through the lens of what makes sense to them given their culture, experiences, aspirations, and that none of that is the same even for one person across all times And that’s before you take into account group think which has no relationship to rationality.

ChrisB people try and move complex things into the complicated (or simple) realm by essentially ignoring ‘things that could go wrong’ by d

Yep that’s the red arrow that drops off the cliff edge in the hand drawn graphic above.

Chomsky describes it as “Deletion, Distortion and Generalisation” 😄

And Yep; culture eats strategy for breakfast although Druker never said it it is still true. All ‘Machiavellian level’ change has to start with a ‘guiding coalition’ that deals with the culture.

I think there’s a post on here somewhere that expresses the data information knowledge wisdom hierarchy. Information is data plus context and context is transient and personal (That appears to be part of what your expressive in the post above.)

I’ve always thought the aspirational statement in the BoK about a “single source of truth” was all of misguided, impossible and missing a competitive advantage (because it doesn’t exist in the real world). For example trump is a very real phenomena with impact globally and no truths or adherence to governments anywhere. The only response which the rest of us have not yet managed to get traction with is an irrational one. Can we point to anything in BIG that would guide us here? I don’t think so, so we’ve a good model for the simple colum in my table above and with effort it will be made to operate in the complicated but I don’t think we know how to transition it into the other columns and that is where the world actually operates for everything but operational, replicatable simplicity.

I don’t think that means we should stop or think it’s hopeless But it does require more iterations!

Ciao
Simon

ChrisB

Hi Simon,
You are quite right that much of what we must make decisions about is actually in the complex realm, although some may be chaotic and some may be simple or just complicated. However, my experience is that people try and move complex things into the complicated (or simple) realm by essentially ignoring ‘things that could go wrong’ by descoping the system. Effectively - we make assumptions about things we can’t control or predict, or prefer not to look at too closely, and a big part of strategy implementation (and governance) is, as you know well from your BSC work, testing assumptions early and often. We need to add sensemaking to that to cater for the complex systems where linear cause-effect paradigms do not hold. And in many (maybe most) these attempts to descope complexity mean ignoring culture (human behaviour) as this is something that can make the simplest systems fail quickly and easily.

I am working on my own response to this thread, and I hope it helps answer your questions here, or at least expands the ability of a BIG system to cater for relationships (including human ones) that are not dependencies, or constraints, such as can be extracted from documents, and that allows as to monitor and improve culture, visualise and sense the relationships, and assure what we see in the BIG governance model.

It is not just a question of collecting data, it is also about understanding the environment that data will be observed in e.g. how do the stakeholders feel about it, do they see it the same way, do they want to implement the decision? This culture is as much a part of governance as knowing what constraints live in my contracts.

Data about this environment is an important part of data needed to make a good decision, it provides context, and much of this data can only be captured meaningfully at the time of the decision. It does not help to know how someone felt about something an hour or day or a month before the decision, if they have changed their mind 5 minutes before the decision. A lot of this data is dynamic and involves humans communicating in real time.

BIG data and information has to cater for all of this, and it is going to look different to different people at different times.

BIG needs to make sure that the data supporting the BIG governance model provides three things in relation to each decision: context, decision information and details, and the record of the decision made by the accountable person.
In addition, for good governance, we need information/feedback on whether our governance is working and where it isn’t. i.e. governance performance data. This performance necessarily covers culture, decision-making and decision implementation.



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