In a previous paper, we considered how survivorship – and other types of bias – can impact and impede understanding of real world issues economically, politically and within operational business environments. Invisible data – data which is ignored, remains uncollected or poorly interpreted – can have a negative impact on decision making, planning and transformational delivery. Whilst bias in its many forms will remain an inevitable symptom of the human condition, our understanding of it and how it materialises in the decision making process will help us mitigate its most significant impacts.
In this second paper, we delve further into the impact of invisible data, bias and the principle of data maturity across a range of real life human problems. We will consider how, through the different applications of data science and statistical analysis, we can approach problems in different ways, using data to mitigate risks and issues.