For governments, groups and alliances

One essence, many entities

What each entity is responsible for, how it is implemented, where they overlap and what a change will affect, with every fact backed by its evidence.

The problem

More entities than any one architect can hold in their head

Duplicated investment

The same outcome gets funded in two or three places, because nobody could see it was the same outcome.

Fragile change

A change in one entity travels along dependencies into others that were not in the room.

Unaccountable decisions

Decisions are taken whose reasons were never recorded against the evidence.

What it is

One place to understand every entity you manage

A government is a federation of departments, authorities and funds. A corporate group is a set of subsidiaries and divisions. Each documents itself in its own vocabulary, so two entities doing the same job look different, and group-level questions go unanswered.

Red Bear: Enterprise Ontology Management gives a federated group one place to discover, capture, check and maintain the ontology and architecture of every entity it manages, partners with or measures itself against. Which entities issue licences, and with how many systems? Which vendor is in all of them? What does this change affect?

How it works

Five pillars, useful alone and better together

Knowledge and evidence

Every fact is an assertion with evidence and a confidence level. Conflicts are raised, never dropped.

Understanding the enterprise

Managed, partner and baseline entities, with questionnaires, workshops and read-only connectors.

Analysis

Overlap by function with the duplicated spend behind it, impact analysis, maturity, and a completeness score per entity.

Decisions and recommendations

Patterns proposed with their reasons and trade-offs, and questions answered with citations or refused.

Roadmap and governance

Transition timelines that respect dependencies, consolidation candidates, and an audit of every read and refusal.

What makes it different

One essence, many entities

Compared by what they do

A unit of work is defined once and used by any number of entities without being copied, so overlap is found by function, not by name.

No merged model

Every cross-entity view is computed from the facts. No entity's truth is overwritten by another's.

Provenance, then authority, then a person

AI extraction starts as inferred. Only a named person can confirm a fact, accept a recommendation or approve a change.

Two reviewers on intake

Questionnaires and documents need two reviewers, and the system administrator runs the tenant without seeing its content.

How you adopt it

A first quarter of establishment

  1. Connect (weeks 1 to 2)

    Tenant, roles and read-only connectors, with your own standards loaded as the highest authority.

  2. Discover (weeks 2 to 4)

    Entities registered, giving an honest statement of how much is known about each.

  3. Understand (month 2)

    Questionnaires, submissions and workshops, with AI extractions reviewed by two people.

  4. Compare (months 2 to 3)

    The shared essence is modelled capability by capability, producing the first overlap and duplicated-spend reports.

  5. Govern (month 3 onward)

    Cross-entity review, with changes classified and routed, and decisions recorded with their impact.

See it working

A real screen from the working prototype

Shown with synthetic data for fictional organisations.

Red Bear: Enterprise Ontology Management: how well the group understands one entity, and what would improve it
Red Bear: Enterprise Ontology Management: how well the group understands one entity, and what would improve it

Read further

11 documents on this product

No form, no email address. The link downloads the PDF.

Running more entities than anyone can hold in their head?

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