Data Capability Gap Analysis Level 1 to 2
Transcription
Data Capability Gap Analysis Level 1 to 2
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. Page 2 of 2