by Uday Kumar, Chief Digital Officer
February 11, 2022
When building transaction fraud and credit underwriting decision engines and #ml models at my previous job, I came across a new concept called “Alternative Data Sources” or ADS. #alternativedata draws from non-traditional data sources so that when you apply #analytics to the data, they yield additional insights that complement the information you receive from traditional sources.
Here is more context on the business drivers fueling the ADS movement from my first-hand experience:
Organizations can unlock massive business value with the help of ADS but it I learned the hard way that there are a ton of challenges getting there. Here are some of them:
The possibilities and sources of data are growing at an exponential rate — from consumer online activity (e.g., social, reviews, search) to geospatial (e.g., footfall) to industry-specific data (e.g., trade flows and shipping).
For business process owners, the BIGGEST CHALLENGE will be the speed of data ingestion. One best practice I would give leaders is to define smaller steps and projects that can be executed immediately and iterated continuously. When done right, this can be a org-wide enabler — adding value not just to operations and research functions but also to demand planning, logistics, and customer support teams.
I am reliving these lessons and best practices as my team at Akira Technologies attempts to build a POC to improve the forecasting of the next forest fire and the optimal mobilization of resources (man, machine) for a timely and effective response.