From good advice to lasting change

Using research to understand problems and test change

Good advice becomes useful when people can act on it. Autopoietic ecology (AE) asks what they need to do that: time, skills, resources, workable decisions and ways to learn from what happens.

EdgeLab is the research and development partner for Cambridge Global Knowledge Nexus (CGKN). The partnership connects research with consultancy and training. Together, we ask: will a proposed change help people do their work, learn and respond to new problems?

These questions can be explored in businesses, public services, healthcare, charities, education, cultural organisations and community settings. The inquiry is shaped by each organisation’s purpose, scale, responsibilities and resources.

See AE in practice for organisations for worked examples of decision-making, hidden workload and meaningful participation, with possible interventions and evidence to examine.

Start where the work happens

A strategy can be agreed while budgets continue to reward the old priorities. A new digital service can appear efficient while staff absorb growing amounts of checking and repair. A consultation can reveal a problem while leaving those affected unable to influence the next decision.

We follow how the work actually happens: who does it, what they depend on, who can decide and how a problem reaches someone able to respond. That helps identify a change worth testing.

What AE brings into view

AE follows how people’s activities create and change the arrangements they rely on. Two questions guide the inquiry: what makes the work possible today, and what is doing it changing for tomorrow?

Meeting a target may build capability, leave it unchanged or exhaust the people and resources on which it depends. Continuity can also preserve an unfair or harmful practice. An AE approach therefore asks what should continue, what should change or end, whose purposes count, and who has the authority to act.

This brings understanding, decisions, workload and resources into the same inquiry. It complements professional knowledge, other organisational research and established ways of evaluating change.

Four ways to advance consultancy

1. Find out why the problem keeps returning

When a difficulty keeps returning, trace what recreates it. A backlog might arise from limited capacity, conflicting priorities, duplicated approvals or a measure that rewards closing cases prematurely. Following actual decisions and handovers can help distinguish these explanations.

Practical contribution: a shared account of the problem, its dependencies and the decisions that could change it, supported by evidence from the people doing and experiencing the work.

2. Find the work and costs that are easy to miss

An improvement in one team can create extra work elsewhere. Staff may repair errors informally; customers may navigate new obstacles; maintenance may be deferred. AE encourages consultants to follow these consequences across the boundaries of a project and examine whether those carrying the burden can influence its design.

Practical contribution: a fuller assessment of value, including rework, workload, service quality and the resources needed to sustain an improvement.

3. Help concerns reach someone who can act

A concern changes as it moves from a conversation into a survey result, a dashboard and a management decision. Meaning mediation helps examine what is retained, lost or reinterpreted along the way. Consultants can then ask whether the resulting account reaches someone with the authority and resources to respond.

Practical contribution: clearer routes from evidence and participation to decisions, with responsibility for reviewing consequences and making revisions.

4. Make AI use open to checking and correction

AI adoption changes how information is produced, interpreted and acted upon. An AE approach follows the whole sequence: how an output is checked, when it becomes an authoritative record, who can challenge it, and whether a person can stop or revise the resulting action.

Practical contribution: pilots that examine task performance alongside the quality of human judgement, the effort required for verification and the effectiveness of intervention.

An example: testing the real value of AI

Illustrative scenario.

An organisation introduces AI to draft responses to enquiries. Drafting becomes faster. Staff then spend more time checking uncertain answers, correcting records and handling complaints. A measure focused on drafting speed captures only part of the change.

An inquiry using AE would follow an enquiry from arrival to resolution. It would examine where time is saved, where work accumulates, how an uncertain answer becomes an approved response, and who can revise the workflow when problems recur.

That inquiry could lead to a narrower use case, clearer review responsibilities, better escalation or a decision to discontinue an unsuitable application. A pilot could compare total handling time, correction rates, unresolved cases, staff workload and service quality against the previous process. The decision to expand would depend on the combined evidence.

A practical route from inquiry to action

1. Define the change that matters. Agree the problem, the people affected and the outcomes worth pursuing. Establish a baseline and identify whose experience is missing.
2. Follow the work. Use interviews, observation, documents and operational data, as appropriate, to examine decisions, dependencies, handovers and repair.
3. Test a focused intervention. Specify what will change, who can authorise it, the resources required and the evidence that would justify continuing, revising or stopping.
4. Build the capacity to keep learning. Give people workable review arrangements, access to evidence and authority to respond after the consultancy engagement ends.

Depending on the scope, an engagement could produce a diagnostic account, a map of critical dependencies, a pilot design, an evaluation plan and agreed responsibilities for change. The consultant’s own assumptions and measures should also be open to challenge: they help shape what becomes visible and whose account is taken seriously.

Research that stays in conversation with practice

EdgeLab contributes conceptual development, research design, exploratory prototypes and critical evaluation. CGKN provides a setting for consultancy, training and organisational application. Questions arising in practice can, in turn, sharpen the research.

AE is a developing framework, and its value in a particular engagement must be demonstrated through evidence. Our research programme and AE Engine and AEAI work explain the ideas and development behind this approach.

Bring us a problem that keeps returning

You may be introducing AI, improving a service, supporting learning or helping people influence decisions. Start with a concrete difficulty and the change you want people to experience.

The aim is a stronger capacity to make progress—and to recognise when a different course is needed.

Discuss a consultancy challenge with CGKN · Explore the EdgeLab–CGKN partnership · Contact EdgeLab about research