1. business and industrial

Data Capability Gap Analysis Level 3 to 4
Assessment Block
People and Culture
Gap Description
Information Asset ownership is not taken seriously.
Data Roles have been created but are not being fulfilled.
Sponsorship for data is sporadic and tactically focused.
The value of data is only understood in terms of known
outputs.
Investment is being made in areas not returning value.
Process
Data Activities
Targets for data are set but the why and how isn't clear.
Business processes are undermined when there is a
perceived crisis.
Business change tends to be communicated at a very late
stage.
Issue tracking and resolution does not follow the correct
process.
Data Governance decisions do not always filter into
operational activities.
Data is still collected for unknown purposes and inside other
business units.
Data improvement activity is not prioritised or well
supported.
Data management roles are not trained into - learn on the
job.
Gap Mitigation
Demonstrate the value in a wider data management context. Move
from data to information.
Demonstrate the value of a data management capability in terms of
support for specific business initiatives.
Find a sponsor who can see value of 'data in the round' and agree a
data improvement plan with actionable milestones.
Look for ways data can support existing initiatives or create whole new
services.
Focus on the 'value chain' of data and target resources and investment
there.
Consider all datasets and shift responsibility to information asset
owners. Only set targets you can measure and realistically achieve.
Consider reworking processes, they should be the simplest and fastest
way to resolve issues.
Ensure those responsible for business change understand the value of
engaging early especially around integrity of data models.
Consider reworking processes, they should be the simplest and fastest
way to resolve issues.
Data Governance lead takes responsibility for actionable plans from DG
forums.
Declare a data amnesty! Use data modelling to understand collection
requirements and strive for efficient collection.
Show value of increasing data management capability, so link to other
initiatives and ongoing business change.
Show value of increasing data management capability, so link to other
initiatives and ongoing business change.
Assessment Block
Technology
Gap Description
Data models are not complete and the integrity is regularly
compromised.
Technology solutions have no benefit outside of the IT
Department.
Technology solutions around data quality do not have much
traction.
Tools are disparate without any obvious framework.
Gap Mitigation
Start with conceptual models and engage senior management.
Normalise physical models and create logical models to close the gap.
Probably the wrong solutions! Workshop requirements, create
roadmap, increment functionality - no big bang.
Ensure the value of measurement is understood before automating it.
Work into a wider Roadmap with other tools. Work backwards from
real outputs and deliverables than have value.
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