Problem

Information management systems have evolved organically

As is the case in many organizations that have been around for more than a couple of years, information management often evolves organically and is often not focused on value creation.

Improved by these Interventions

Rapidly create and test a new data model

Once new value opportunities have been identified, test a new approach rapidly using real data.

Technologies used

Information Architecture (IA)

Domain-Driven Design (DDD)

Review data models for improvement opportunities

Discovery exercises to ascertain whether improvements can be made to data models and information architecture.

Inhibits these Capabilities

Maintain a low cost of incremental innovation

To be competitive, and to have the ability to pivot rapidly, it is essential to keep the cost of innovation low.

Ability to pivot rapidly

Leads to these Problems

Legacy support costs are growing

Agile deliveries create new tech legacy

The need to significantly rework data services for each project

Technical Debt (Tech Debt)

Seen in these Maturity Models

Digital Media Metadata Maturity Model

Stage 1: Basic Metadata - Maturity Stage

Assets have simple, unstructured "Tags" used to power free-text search and can aggregate/group the assets. This level offers no information for machines or humans beyond free-text search and basic collections.