One of the most important assets that a business has at its disposal is its data. It is important that the data a business uses is not only high in quality but governed properly. However, it is also important that the data being used contain certain characteristics.
Arguably the most important characteristic that data has to have is completeness. This could be considered to be the biggest factor that can affect data quality. Data completeness is a term that refers to potential gaps that data may have from what was expected.
If any pertinent information is left out in data, this could be considered less value and incomplete. In order to ensure that data is always complete, businesses should enforce policies that state data cannot be submitted unless all of the expected information is present. With paper, this can be exponentially difficult because human error can interfere greatly. Therefore, paperless data collection has become more popular, as it features mandatory fields.
Of course, another factor that can affect data quality is the accuracy of the data being used. This refers to whether or not the data being used is correct and is an accurate representation of the information required.
As opposed to completeness, data accuracy can prove to be a more difficult aspect of data to maintain. Usually, data inaccuracies are a product of poor training. In order to minimize human error that is bound to happen, extra measures may be necessary. For example, GPS location and time stamp for recorded events or picture capture are certain interventions that can be implemented. That way, inaccuracies can be spotted and corrected in a timely manner.
Next to accuracy and completeness comes the consistency of the data being used. Data consistency refers to whether or not the data being used is in alignment with expected versions of the data that comes in. On the surface, this seems similar to the completeness of the data, but there are also different aspects to be considered. Completeness encompasses whether or not there is pertinent information missing. Consistency is there to ensure similarity in the content.
Many companies today utilize mobile data collection apps, and this can help out immensely. This is because drop down menus are utilized to give the operator a predetermined assortment of options to choose from. This can ensure that data not only remains consistent but allows for complete search results and accurate event recordings.
The timeliness of the data works together with all of the other aspects of good data. This refers to when it can be expected that the data will be received. Oftentimes, businesses will not align reality with expectations. This can directly lead to data being used ineffectively and alter the thought process of making important business decisions driven by data.
A general rule of thumb to ensure consistent timeliness of the data is to use real-time data so that personnel can collect similar data that they would on paper. This can eliminate potential time lags from when the data is completed and when it is received by the branch making the big decisions