Effective Use of Data

The effective utilization of data is key to continual process improvement. Data is able to provide information on the current status or level of performance at an organization, key process or department and work unit level. Data can provide a critical contribution to the diagnosis of problems or issues, and to the validation of theories on cause and effect relationships. Without using good data correctly, we are often only guessing at solutions or alleging the existence or extent of improvement.

In order to aid the achievement of the above goals, data must be appropriate and meaningful. Both how data are selected and the methods used to assure data reliability and integrity are significant issues to be addressed and fully integrated during improvement planning and implementation. Additionally, variation is present in all data. Consequently, the analytical methodologies employed to interpret data must address the impact of variation to be considered truly effective. This too must be addressed during improvement planning and implementation.

Indicators/ measures, the numerical information that quantifies input, output, and the performance dimensions of processes, services and products must be in evidence to facilitate learning and improved process outcomes. Comparative or benchmark data can also be significant in the context of improvement. These data may provide key information on performance relative to competitors, other service providers and to best practices. Comparative data and information may also be used to set stretch targets for improvement. The potential sources of these data and information are numerous; they can be gleaned from key competitor groups, from organizations/institutions of a similar nature and/or from other industries entirely.

A review of the documentation from the assigned process improvement effort should demonstrate the effective use of good data throughout. The panel of judges must validate the activities and methodologies. When it is unclear that appropriate and meaningful data were collected, analyzed and effectively used during the improvement effort, clarification must be sought during presentations to the panel of judges. The following steps and methods comprise the award criteria for the effective use of data.

Data Collection Methodology will employ the following steps:

Data is selected based upon its relevance to the improvement initiative and the theories of causal relationships to the identified problem or issue. Data analysis techniques must employ stratification, where appropriate for the type, scope and complexity of the improvement effort, to extract the information content from the data. These techniques must also account for the variation in the data.

• Data must be systematically utilized to quantify the critical cause and effect relationships important to the improvement initiative;
• Data must be systematically utilized to quantify key performance levels and outcomes, goals, objectives, strategies and tasks;
• Where appropriate, comparative or benchmark data for the important factors relating to the improvement initiative must be in evidence.

Scoring Guidelines:

Improvement initiatives scored in the 50% to 60% range will demonstrate effective, systematic approaches to the use of data. The methodology for collecting data will demonstrate adherence to the overall purposes of the criteria through adherence to the data collection process illustrated in the flow chart above. Additionally, the approach will engage analytical techniques that stratify the data and account for the variation in the data. These approaches to utilizing data will quantify key causal relationships and performance levels and outcomes etc. Some use of comparative and/or benchmark data for important factors to the improvement initiative will be in evidence. Higher scores will result from increased integration and refinement as a result of improved analysis based upon experience and cycles of improvement.