It’s no longer rare to see machine learning (ML) models used to support a variety of business decisions, from whether a financial transaction should be sent to the fraud investigation team, to what discount a distributor should get.

Still, even in organizations that have embraced ML-based systems, it’s common for business problems that could benefit from machine learning to be solved using a less effective (and often more costly) approach. 

As a business analyst, it’s useful to be aware of some signs your business problem might benefit from ML...

Rather than building systems in house, many organizations outsource development to contract development companies. They might outsource the work to take advantage of skills they do not have available in-house, to augment their internal staff, or in an attempt to save money or time. The outsourced development supplier could be located physically nearby, on the other side of the world, or anywhere in between.  The role of a business analyst is even more important on these projects than on a co-located project. If the team members are all in one location, developers can walk down the hall to ask the BA a question or to demonstrate newly developed functionality. This close collaboration can’t happen in the same way with outsourced development. Compared to in-house development, outsourced—and particularly offshore—projects face requirements-related challenges...

A point in time field supports a business need for an information system to know when an event took place (or will take place). Date, Time, and Date/Time field values represent a quantity of time involving a specific unit of measure and precision. Like other quantity values, they can participate in calculations (E.g. subtracting one date from another to determine the number of days in-between).