On Monday, I talked about node and edge thinking. As an edge thinker, I look for data points indicating how the connections between nodes change. This is an excellent opportunity to explain parts of my process.
Why is this important? A valuable part of decision support is scenario planning. Companies that can map out non-obvious potential scenarios and assign a likelihood to each have an advantage over competitors who won't see them coming. As the likelihood increases, it makes sense to position the business to take advantage of opportunities and mitigate risks.
We are seeing an increasing divide between companies that can execute well in uncertainty and those that cannot. Reliable data and model-driven decision support systems make this possible. How do these systems start?
That's the process I am describing and why edge thinkers are a critical piece of the data science process. Using experts and prior knowledge, we can assemble a new ontology. Assumptions are detailed for validation. This process applies to more than decision support systems, but that use case provides a good example, especially now.