Zero-Gravity.ai

Reduce Gravity

Change the organisational conditions that prevent information, decisions and action from moving effectively.

The primary intervention programme. Reduce Gravity works on the operating conditions — ownership, information, semantic meaning, process, governance, architecture and readiness — that determine whether data, analytics and AI actually change decisions and action.

When this programme is relevant

You will recognise the situation.

  • — The causes of friction are sufficiently understood.
  • — A transformation is active but movement is fragmented.
  • — Data and analytics teams produce outputs without influencing decisions.
  • — Process ownership is unclear; governance is duplicated or disconnected.
  • — Information definitions conflict across systems and teams.
  • — Technology architecture and organisational reality have drifted apart.
  • — AI initiatives lack operational readiness.
  • — Public-sector or regulated organisations need stronger IPM.
  • — A strategic roadmap exists but coordinated action does not.

Questions the programme answers

The questions worth asking.

  • ?Which organisational conditions must change?
  • ?Where should ownership sit — and which decision rights require clarification?
  • ?How should information and process management connect?
  • ?What semantic structures are required to make data, analytics and AI usable?
  • ?Which governance protects value, and which creates unnecessary friction?
  • ?How should data, analytics and AI connect to operational decisions?
  • ?What must be true before selected flows can be automated?
  • ?How should architecture support the intended operating model?
  • ?How will the intervention be measured?
  • ?Which capabilities must be created or strengthened?

Working logic

An adaptive, structured way of working.

Phases describe the logic, not a fixed calendar. Every engagement adapts to the organisation.

  1. 01

    Focus

    • · Confirm the priority decision or value domains.
    • · Confirm the baseline.
    • · Agree intended movement.
    • · Clarify ownership and sponsorship.

  2. 02

    Design

    • · Redesign information and decision flows.
    • · Clarify ownership and decision rights.
    • · Define semantic requirements.
    • · Define process, governance, architecture and capability changes.

  3. 03

    Mobilise

    • · Translate design into workstreams and roles.
    • · Establish dependencies and decision cadence.
    • · Establish measures and an Evidence Pack.

  4. 04

    Implement

    • · Guide or lead execution.
    • · Resolve cross-functional friction.
    • · Connect data, process, governance and AI work.
    • · Make decisions visible.

  5. 05

    Demonstrate

    • · Compare movement with baseline.
    • · Review DAL, ARL, ROD and relevant measures.
    • · Update the Evidence Pack and adapt the intervention.

Modules and pathways

One programme. Many possible applications.

Not every module applies to every engagement. They are composed to fit the question.

Decision & Analytics Acceleration

  • · Connect insight to operational decisions.
  • · Reduce decision-to-action latency.
  • · Clarify decision ownership.
  • · Make the influence of analytics on decisions visible.

Information Performance

  • · Improve the ability of information to perform in decisions, processes and action.
  • · Address availability, understanding, trust, timing and usability.
  • · Connect information quality to organisational use.

Semantic Layer

  • · Establish shared business meaning across people, systems, analytics and AI.
  • · Define entities, metrics, relationships and decision context.
  • · Enable consistent interpretation and controlled automation.

Data & AI Readiness

  • · Establish the organisational, semantic, information, governance and control conditions required for data and AI investments to produce movement.
  • · Connect AI readiness to ARL.
  • · Distinguish experimentation from operational readiness.

Information & Process Management Enablement

  • · Connect information, processes, decisions, ownership and improvement.
  • · Establish capability ownership.
  • · Create governance and operating structures suited to complex and regulated organisations.

Data and Organisational Operating Model

  • · Clarify roles, ownership and decision rights.
  • · Connect product, process, data and technology responsibilities.
  • · Align governance with delivery and value.

Architecture for Movement

  • · Align semantic, data, analytics, AI and process architecture with organisational decision flows.
  • · Ensure technology choices support the intended operating model.

Governance and Decision Design

  • · Distinguish useful governance from unnecessary friction.
  • · Clarify forums, ownership and escalation.
  • · Reduce meeting theatre and establish decision principles and evidence.

Public Sector and IPM

  • · Apply Reduce Gravity in complex public-sector and regulated environments.
  • · Address fragmented information ownership, legal and regulatory constraints, public accountability and process complexity.
  • · Support NIS2-related dependencies, data classification, semantic alignment, IPM capability and evidence and auditability.

Tangible outputs

What you leave with.

Depending on the engagement, outputs may include the following.

Operating clarity

  • Operating model
  • Capability ownership
  • Decision-rights model
  • Governance design
  • Role and responsibility model
  • Dependency map

Information and process

  • Information-flow design
  • Process and decision-flow design
  • Semantic model
  • Information Performance measures
  • IPM roadmap

Data, analytics and AI

  • Data & AI Readiness roadmap
  • ARL view
  • Semantic requirements
  • Analytics-to-action design
  • Automation pathway
  • Architecture principles

Mobilisation

  • Workstream structure
  • Prioritised roadmap
  • Implementation plan
  • Decision cadence
  • Programme governance
  • Risk and dependency structure

Evidence

  • Intervention baseline
  • Measurement framework
  • Evidence Pack
  • Movement review

What changes

Intended movement — observable, not guaranteed.

  • — Decisions have clearer ownership.
  • — Information reaches the right decision at the right time.
  • — Duplicate governance is reduced.
  • — Programmes operate from shared priorities.
  • — Semantic ambiguity decreases.
  • — Data and AI work connects more directly to operational action.
  • — Automation readiness becomes explicit.
  • — Processes and information ownership become connected.
  • — Intervention outcomes become measurable.

Evidence

Grounded in the Proof Model.

Reduce Gravity uses the Proof Model to connect intervention to observable movement. Evidence is a working instrument during the engagement — not a retrospective report at the end.

Explore the Proof Model →

Reference measures

  • · Baseline
  • · Intervention hypothesis
  • · DAL, ARL, ROD
  • · Information Performance
  • · Decision Value
  • · Evidence Pack
  • · Learning

Framework foundations

The concepts this programme applies.

The Framework explains the concepts. The programme applies them — it does not redefine them.

01

Organisational Gravity

The invisible drag between what an organisation knows and what it actually does.

02

Decision-to-Action Latency

The time between knowing enough to move and actually moving.

Also applied

Automation ReadinessReturn on DataInformation PerformanceSemantic LayerInformation & Process ManagementThe Proof Model

Who is involved

Cross-functional by nature.

No single executive can resolve organisational gravity alone. Typical roles involved include:

  • · Executive sponsors
  • · Programme leaders
  • · Data, analytics and AI leaders
  • · Information and process owners
  • · Capability owners
  • · Technology and architecture leaders
  • · Governance, risk, security and privacy roles
  • · Operational and product leaders
  • · Public-sector directors where relevant

More on how we engage: About · Working with us

Starting point

Begin with a conversation.

Book a conversation →Start with Discover Gravity →
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