The importance that data quality plays in the improvement of public sector performance has been highlighted through the recent publication of the UK`s Varney report.
The investigation, conducted by Sir David Varney, presented the disjointed way that public services are delivered to citizens due to poor data quality control. He likened government departments to islands, with citizens having to join them up in order to meet their needs.
The report went on to make a number of key recommendations, including increased standardisation in data capture and use of better co-ordinated business delivery and process redesign arising from the use of shared data.
The findings of the report resonate with SA`s own public sector data quality problems.
The South African public sector is facing the same data quality problems as the UK, but they are exacerbated by the fact that the local public sector information systems and related processes are still in a state of transition.
Many of the old public sector systems are being migrated to modern business application systems and hardware and software platforms, which is a good thing, but the focus is on the function rather than the data quality, which should be the pivotal driver.
Too common in South African government departments are independent silos of business divisions, each having their own application systems and standards. This usually spells data chaos, where the order of the day is overlapping information requirements and business procedures and the same business entities being represented differently on different applications.
In any single application system, one would find bad data quality often because of a lack or disuse of data standards.
A typical example is the switching off of validation checks on data capture screens to improve system performance. Rigid business applications with differing data standards are also contributing factors to the chaos.
It is thus not surprising that departments such as Stats SA and other institutions have different versions of the truth when reporting to the ministry or when doing performance management because of weak data linkage and poor conformance to the same standards.
Too common in South African government departments are independent silos of business divisions, each having their own application systems and standards.
Mervyn Mooi is a director at Knowledge Integration Dynamics.
If public sector services are to be efficient, where citizens can capture their personal details, for example, data standardisation and data quality enforcement are key. In order for this to happen, the South African public sector has to recognise the value simple analysis of the data brings to the fore and take action.
The sector can begin to take action to improve data quality by implementing the following steps:
* Establish a formal data management function consisting of data architects and business and systems analysts who understand the public sector`s business strategy.
* The data management team must identify, based on computer applications and systems, all the data items necessary to operate or turn the business. They must also identify manual and external data needed for operational and management purposes.
* They need to assess the business processes and procedures to confirm data usage.
* They must determine and agree on a standard data naming and storage convention between the different systems, including mappings and rules.
* The data management team must agree all business rules for the data and agree default values for missing data.
* They should formulate data transformation and correction rules for all key data items.
* Once completed, they must document and publicise the data quality standards and rules.
* They need to apply these rules and standards into the operational applications and business intelligence systems. But data quality doesn`t end with a successful project. It`s an ongoing process sustained as an operations process as part of the data management function.
By the South African public sector implementing these steps, it will gain from numerous data quality benefits, including having access to trusted information; a single viewing of an entity; enhanced ICC and business understanding; and application systems integration achieved via common data standards, as opposed to special interface code.
Ultimately, for data quality to be efficient in the public sector, it has to include data conformance across different application systems and proofs of concept with funding to help the sector achieve the required improvements.
* Mervyn Mooi is a director at Knowledge Integration Dynamics.
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