An Intellyx BrainBlog for iGrafx by Jason English
In our previous chapter on automated decisioning, we discussed the importance of bringing together all of the real-time and historical data necessary for a human expert to make better decisions in the moment.
As we shift our gaze from the present to the future, we uncover another critical factor in continuous process optimization: predictive analytics.
At the time of any strategic or tactical decisionpoint, what if we could already predict the most likely best path forward?
With so many variables in play, teams may not be able to accurately observe the success or potential failure of a process in flight—and in the real world, there will often be varying degrees of success or failure rather than a clear binary outcome.
A predictive analytics approach looks at how close we can get to the intended outcome in order to guide our actions.
How will we know when we’re done?
I didn’t get to spend enough time with the legendary optimization guru Ken Sharma in my early supply chain days at i2, but I do remember his signature line upon starting any meeting: “How will we know when we are done?”
Indeed, if there wasn’t a clear intention to accomplish something at the beginning of a meeting, even with all the bluster and strategizing in the world, it’s unlikely that thing would ever happen.
Using predictive analytics, we can start with a timing goal for a desired outcome, and work backwards from there.
Take for instance a mortgage approval process, a complex flow which contains many tasks such as market evaluation, appraisals, risk assessment, fair housing, insurance, and more—with manual forms, checks and approvals conducted by agents on behalf of the lender, buyers and sellers.
There is a best case or ideal timing goal we want to try to meet in order to provide a great customer experience for buyers and sellers, which could be a week, or even a day, if everything flows smoothly.
There is also a worst-case or minimum drop-dead date for process completion, one in which an SLA violation or compliance issue is triggered, or in the case of our home mortgage, the contract period expires and the whole deal becomes null and void.
Being able to accurately predict when a process will be complete is absolutely fundamental to any enterprise and its customers, and it is the primary reason why leaders might intervene to correct or expedite that process.
Read the entire BrainBlog here.
