Aim of this topic
To provide guidance to Tasmanian Government agencies on performing and undertaking effective data collection.
Before collecting any data, it is good practice to identify and define the reasons why you want the data, and what you are hoping to achieve as a result.
Using a tool such as the ABS Data Quality Framework can assist you to clearly define your data needs and give you the best chance of achieving your desired outcomes.
When describing a data need, it is useful to create a list of questions beneath each of the seven dimensions contained in the Data Quality Framework (Institutional Environment, Relevance, Timeliness, Accuracy, Coherence, Interpretability, and Accessibility). This will help to ensure that aspects of data quality are considered when defining a data need. The questions can be used to help assess potential data sources for fitness for purpose for required objectives.
The following resources can provide information to assist in defining a need for data.
Data can be sourced directly or indirectly. Direct data (or primary data) is essentially new data which has been collected for a specific study. Direct data can be collected through a variety of approaches including:
By contrast, indirect data sources (or secondary purpose data) is existing data that was collected for a purpose other than what you intend to use it for.
Administrative or service data are common examples of indirect data sources. This type of data is collected primarily for administrative purposes as part of the day-to-day operations and processes of an organisation but it is often used for other purposes, such as informing research into service delivery policies. Hospital admissions, records of births, deaths and marriages, school enrolments, and even financial transactions, are all types of administrative or service data.
The following resources provide information on the importance of identifying what type of data to source.
There are a number of factors which can impact the choice of collection method. These include:
Each collection method also has pros and cons e.g. surveys can reach a large number of respondents and can generate standardised, quantifiable, empirical data. However, surveys are prone to error and can be subject to misinterpretation by respondents. It is important to choose the correct collection method to achieve the most effective and highest quality data.
The following resources will assist you in choosing an appropriate collection method.
When undertaking a data collection, things often do not go according to plan; uncertainties can eventuate at any stage and can take different forms.
Examples include loss of data from a computer malfunction, or loss of skilled staff during the collection process. Such events can impact the collection process itself or even the continuity of a project.
While it may not be entirely possibly to remove or avoid all risks, it is important to identify potential risks and develop a plan to understand, manage, mitigate and attempt to eliminate risks if they eventuate. Developing a risk management strategy is an effective approach and tool to manage risks in a data collection.
The following resource will help you to develop a risk management strategy.
In some instances, where there is neither the resources nor expertise in statistical sampling or sample survey design, you may choose to engage a consultant to conduct a survey on your behalf. If this is the chosen path then a brief and contract will be required to be prepared. The aim of the brief and contract is to clearly state the aims, objectives and requirements of the sample survey. This includes the background, objectives, population, timing and budget.
The following resources provide information around what to consider when engaging a consultant to undertake a sample survey.
There are many advantages of using existing indirect data sources (such as administrative and service data) as opposed to undertaking a direct data collection. However, there are common issues with acquiring and using indirect data sources including:
As such, when acquiring and using indirect data sources, it is essential to assess the data quality, the fitness for purpose and identify if there are any gaps.
The following resources provide information on assessing data quality, including assessing the fitness for purpose of potential administrative data sources.
Note: the guidance and information on data collection and statistical sampling in this Toolkit should be applied with caution as this topic does require a degree of expertise. If you believe that you and/or your area are not equipped with these skills it may be worth considering seeking advice from a consultant or engaging a consultant to undertake the data collection process.