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Data Capability Gap Analysis Level 1 to 2
Assessment Block
People and Culture
Gap Description
No accountability for data assets.
Data not seen as valuable or important.
Process
No processes to create repeatable activities for common
outputs.
Lack of capability, skills and motivation in staff working with
data.
No processes to create repeatable activities for common
outputs.
No documentation on how activities should be carried out.
No business process for creating outputs linked to data
activities.
No forward planning on change.
Issues are not every followed up.
Data Activities
Data activities are not obviously output driven.
Data may not be secure or legally compliant.
Data is being collected for no obvious reason.
Data extract and manipulation is a very high percentage of
our daily operations.
Gap Mitigation
Record where the assets could/should be owned and create a list of
main datasets in use.
Start to develop a 'data landscape' of all known datasets, links and
outputs.
Start to develop a list of commonly used processes and which outputs
(if known) they work towards.
Record skills/staff shortages around what isn't getting done.
Record activities that appear to be repeated and support
common/frequent outputs.
Record how activities are carried out most frequently and create
documentation where possible.
Begin to map activities that are carried out very often to outputs known
to be important.
Record number of changes, notification and output to use to show
value of a change process.
Record all issues in a format that can be used later to show value of a
formal process.
Record activities that appear to be repeated and support
common/frequent outputs.
Record known issues (and ones you are worried about) in a log and find
responsible risk officer to share with.
Record lists of collections and their purpose (if known) as part of
populating a data landscape.
Record where data is being extracted and re-loaded as part of
populating a data landscape.
Assessment Block
Gap Description
Data is all over the place both in IT and business units.
Technology
Technology is hindering daily operations.
Many point solutions are in place for ETL and analysis.
No specific data management technology is in place.
Gap Mitigation
Record where data is found, stored, used and deleted. Populate data
landscape.
See if there are any short term fixes. If not use manual workarounds at
this level.
Record these as part of data landscape for work at more mature levels.
There is little point introducing it until an understanding of what DQ etc
is required.
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