Decision making is the forming of a causal argument that a chosen alternative will result a certain future outcome. The quality of a decision is largely dependent on the accuracy and relevance of the information on which it is based – as well as being free from subjective bias in reflecting the true needs. When poor quality or biased evidence is used for decision making, the proposed alternative will risk producing an ineffective or adverse outcome. Standards, such as ISO 9001 on quality management and ISO 16355 on QFD, therefore calls for factual decision information.
Evidence-based decision making is about establishing high level confidence in the causal argument’s prediction of the future outcome. This is achieved by establishing relevant and sufficiently accurate information to support the choice being made. Well-defined processes and well-trained people equipped with effective, cost-efficient data collection and analysis devices will improve the organisations decision making competence.
Good decision evidence further ensures transparency and accountability. When presented with the same evidence, anyone looking at a situation should practically reach the same conclusion. The evidence effectively makes the decision.
Hierarchy of evidence-base
The above diagram, adapted from the DIKW pyramid, ranks different sources of evidence by their assumed quality.
The term ‘primary data’ defines what was collected for the specific purpose of the immediate study. ‘Secondary data’ was collected for some other purpose, but is considered transferable to the new purpose. Primary data tends to be more relevant and thereby improve predictability in the causal argument.
In practice, the evidence will consist of some data, some information, some knowledge and some wisdom, producing a total level of quality. When faced with making a decision, think about where the evidence-base is on the quality scale and think about where it should ideally be, to provide sufficient confidence in the decision. If the main source of evidence cannot establish the full extent of required confidence – say, if only a partial data set is obtainable – then supplement with other sources of evidence. The multiple sources will complement each other and add up to an overall level of quality. When multiple sources of partial evidence agree, then it adds strength to the overall quality of evidence. Similarly, say, if two sets of data are in conflict then it weakens the overall quality of evidence and additional new data may be necessary.
We must of course be pragmatic when determining the sufficiency in the quality of evidence. Moving from unreliable subjective information to reliable objective data in the hierarchy of the evidence-base will improve the predictive powers of the decision, but it will also demand an increased investment in information resources and time. Sufficiency must appropriately balance the opportunities from making a good decision with the risks from making a poor decision, including consideration to any urgency in the immediate situation. Intuition and gut-feel are rarely reliable in reaching the perfect decision; but under certain urgent circumstances their method may be necessary and good enough, to counter an adverse risk associated with a delayed decision. When circumstances force the reliance of less than ideal evidence, then establish monitoring steps to help the earliest possible detection of a poor decision and to enable a timely corrective action.