For #futurefridays let’s talk about RPA (Robotic Process Automation) and what will happen to it in 2020.
With all the rage about AI (Artificial Intelligence) and the Future of Work, people have been saying that RPA seems to have taken a back seat from all the action.
So back to what will happen to RPA, in the recent past, people have been so afraid about RPA and that people would lose jobs because of it.
That was only for RPA. What more for AI? I guess people are, and were, just afraid of what they don’t know.
But now that people have become accustomed to having a “Digital Workforce” or software robots working alongside them, people’s thoughts have changed from fearing about job security, to scrutinizing where RPA falls short!
In my opinion, that’s a good thing, because we can now start doing innovations!
Here are some of the things I’ve heard people say about RPA lately:
It’s becoming a band aid solution
It can only do so much
With AI coming in, let’s just set our sights on that
With that, I’d like to talk about each of those bullet points in detail.
I will share my thoughts based on my own experience, as well as where I think RPA will be going to next.
I would say that this information is GOLD, and I’d recommend every leader to have this as a checklist where you will ensure that each and every one of these “employee needs” get addressed at certain intervals.
Based on a study performed by Gallup, there are 12 Needs that Employees Require to find True Engagement and Perform at Their Best:
For #wisdomwendesdays I’ve been asked by someone trying to learn Data Science what the difference is between Variance and Standard Deviation in terms of purpose.
For #transformationtuesdays I’m sharing how AI is Transforming the way you can determine if you will encounter any health issues in the near future – specifically Heart Attacks.
So if you have a problem that requires root-cause-analysis before you find the appropriate solution, then Lean Six Sigma’s DMAIC approach is what you need.
You can’t just implement some sort of software automation or that snazzy new technological tool just for the sake of it.
To put it bluntly, Automations and such Technologies are part of the Solutions. But to uncover the root causes of the problems that require these solutions, that’s where you would need Lean Six Sigma.
So if anything, Lean Six Sigma is actually becoming a foundational skill that continuous process improvement and innovation experts of today must master.
You know when there’s a skill that you haven’t practiced for some time and you feel rusty so you want some sort of refresher to enable you to get a hang of it again?
Well I was in that exact situation a few years ago, specific to Logistic Regression, when I had to create a predictive model to address one of the business pain points I was working on.
Thankfully, I found this tutorial by Brandon that was even better than when I first learned all about Logistic Regression.
And I’d like to share it with you so that you can benefit from it as well.
It’s #transformationtuesdays and today we’ll talk about a Use Case of Lean Six Sigma being implemented successfully in the Technology industry.
Usually, Tech firms would default to the Agile approach and talk about how they can make further improvements during their Scrum rituals.
And non-Technology companies take best practices from Tech firms implementing Agile and Scrum, to see how they can work in a non-Technology setting.
But here you’ll see the opposite happening.
Lean Six Sigma, a methodology widely used in non-Technology settings, being implemented in the Software and Technology industry.
Today I’ll be showing you the entire Lean Six Sigma Green Belt Project Storyboard by Eduardo Torres, where he was able to reduce Software Bug Fix Lead Time from 25 to 15 days.
This not only improved Customer Perception in a good way, this has also increased Team Member Morale as they were able to free up some of their capacity for them to work on features, moving them in the right direction to become Best in Class.