Algorithms sometimes will involve a genealogy, or matrix. This could be a group of people related in some way or a group of transactions related in some way. For example, affiliates who refer each other to represent a business as sales representatives are all part of a genealogy. In sales commission plans there are often rules about who gets compensated at different levels of the genealogy.
One of our clients had 5,500 people within one genealogy who had to be transferred to a different one that would have a set of new commission rules. However, the current relationships had to be preserved because they would dictate how the relationships in the new matrix would be. As you can imagine this could get pretty complicated!
Thankfully our team was able to employ the power of algorithms yet again to help solve our client’s tricky situation. We figured out the cascading rules to the original matrix that would transfer and translate all of the people into the new matrix through a computer program.
The key that we discovered was that there was a concept of “parent and child rules”. This meant there were specific top level rules that would always have to be applied before the bottom level rules could be applied.
Once we figured out which rules had to be applied first and which variables we had to associate with each data point we were able to create a program that would flawlessly transfer and translate all 5,500 people to the new genealogy.
This was an incredible amount of data we were working with, but the algorithms represented amazing time-saving power.
Our team completed this project in four days. If the client had hired people to manually enter the data it easily would have taken at least four weeks.
