Return Assessment
- · A focused first indication of where data, analytics and AI value may be getting stuck.
- · Used as an entry instrument, not as the full programme.
Discover Gravity
Build a shared, evidence-based view of where information, decisions and value are getting stuck.
A senior diagnostic engagement that gives leaders a common language for the friction they experience — and a prioritised view of where intervention is most likely to move the organisation. The Return Assessment is one possible entry instrument inside Discover Gravity, not the whole programme.
Incoming transmissionnow · live
Your Organisation
gravity · undiagnosed
…the friction is present. Its shape is not yet visible.
transmission · discoversignal · trusted
When this programme is relevant
You will recognise the situation.
- — Leaders agree that movement is too slow but disagree about why.
- — Data, analytics and AI investments exist but value remains difficult to demonstrate.
- — Different teams describe the same problem in incompatible language.
- — Ownership is fragmented and priorities compete without a shared evidence base.
- — Dashboards and initiatives multiply without changing decisions.
- — A transformation is active but no common baseline exists.
- — A public or regulated organisation needs a structured current-state view.
- — AI ambition exists but automation readiness is unclear.
Questions the programme answers
The questions worth asking.
- ?Where does information lose meaning or trust?
- ?Which decisions create the most delay — or the most value?
- ?Where does ownership become unclear?
- ?Which processes and decision flows create unnecessary friction?
- ?Where are data, analytics and AI investments producing movement, and where are they not?
- ?Where is the Return Gap largest?
- ?Which flows are most suitable for intervention first?
- ?What is the current DAL profile? What is the current ARL view?
- ?Which evidence already exists — and what is missing?
Working logic
An adaptive, structured way of working.
Phases describe the logic, not a fixed calendar. Every engagement adapts to the organisation.
01
Frame
- · Define the organisational question.
- · Agree the decision domains or value flows in scope.
- · Identify relevant stakeholders and sponsorship.
- · Establish what observable movement would mean.
02
Observe
- · Inspect information flows, decision flows and ownership.
- · Inspect process dependencies.
- · Review existing data, analytics and AI initiatives.
- · Review existing evidence and measurement.
03
Measure
- · Return Assessment where a first indication is useful.
- · DAL baseline in the priority decision domains.
- · ARL view for the flows considered for automation.
- · Return on Data view, Information Performance indicators and Decision Value where relevant.
04
Interpret
- · Identify friction patterns.
- · Distinguish symptoms from causes.
- · Identify Return Gaps and high-value intervention points.
- · Identify constraints and dependencies.
05
Prioritise
- · Create a prioritised movement roadmap.
- · Define initial intervention hypotheses.
- · Establish ownership.
- · Create the initial Evidence Pack.
Modules and pathways
One programme. Many possible applications.
Not every module applies to every engagement. They are composed to fit the question.
Return Gap Map
- · A view of the difference between current investment, intended value and demonstrated movement.
Decision-Domain Scan
- · A structured view of important decision flows, ownership and latency.
DAL Baseline
- · An initial view of where decisions lose time before becoming action or observable outcome.
ARL View
- · An initial assessment of whether selected flows are ready for safe and effective automation.
Information Performance Scan
- · A review of whether information is available, understood, trusted, timely and actionable.
Data & AI Readiness View
- · A practical view of the organisational, semantic, information and control conditions required for data and AI initiatives to produce movement.
Proof Baseline
- · The initial evidence structure against which later intervention can be reviewed.
Tangible outputs
What you leave with.
Depending on the engagement, outputs may include the following.
Shared understanding
- Shared problem statement
- Current-state movement map
- Friction map
- Ownership view
Measurement
- Return Gap
- Decision-domain map
- DAL baseline
- ARL view
- Information Performance findings
- Initial measurement set
Direction
- Prioritised intervention areas
- Dependency map
- Prioritised roadmap
- Executive decision brief
- Initial Evidence Pack
What changes
Intended movement — observable, not guaranteed.
- — Leadership gains a shared language for the problem.
- — Competing initiatives can be prioritised against movement and value.
- — Symptoms and causes become easier to distinguish.
- — Ownership becomes more visible.
- — The organisation identifies where intervention is most likely to matter.
- — Future transformation work starts from a common baseline.
- — Evidence is established before major change begins.
Evidence
Grounded in the Proof Model.
Discover Gravity establishes the baseline from which later movement can be demonstrated. It is the first entry into the Proof Model.
Reference measures
- · Return Assessment
- · DAL baseline
- · ARL view
- · Return on Data
- · Decision Value
- · Initial Evidence Pack
Framework foundations
The concepts this programme applies.
The Framework explains the concepts. The programme applies them — it does not redefine them.
Who is involved
Cross-functional by nature.
No single executive can resolve organisational gravity alone. Typical roles involved include:
- · Executive sponsors
- · Data and analytics leaders
- · AI leaders
- · Information and process owners
- · Transformation leaders
- · Public-sector directors where relevant
More on how we engage: About · Working with us
Starting point