Automation – unlocking human potential and machine power

What would you give for a workforce of engaged, creative people actually WORKING creatively?
7 June 2023

Automation – shattering the chains of day-job drudgery?

• Automation allows professionals to do professional work.
• Businesses benefit from better agility.
• Automation is the way younger generations expect things to be.

Automation is becoming an increasingly vital, if often unnoticed, part of any successful business in the post-pandemic era. In Part 1 of this article, we sat down with Abhijit Kakhandiki, Chief Product Officer at Redwood Software, a full-stack SaaS automation company, to discover the drivers behind this increased automation across the business world.

Towards the end of Part 1, Abhijit mentioned that automation had the power to allow small teams to meet bigger goals than they would otherwise be able to dream of. While we had him in the chair, we asked him to expand on that.


We’ve said that business teams are now dealing with a colossally increased amount of data, and of data checking, storage, and containerization. How is automation able to help teams – and businesses deal with their enormous day-to-day challenges?

Utopia calling.


Let’s do a thought experiment. Imagine a world where any company is able to automate any process. An IT process, a business process, end to end, no matter how complex that process is, and no matter what the underlying technology stack looks like.


We hear birds twittering in the trees. Come to that, we hear Twitter working effectively with only 20% of its required staff…


In that world, what will happen is that the company’s most valuable resources, which are its people, will focus on the big picture, strategic goals.

Normally, you hire an MBA graduate for over $100,000, and you’re forced by the nature of the work that exists to use them for swivel chair work.

They’re actually just doing monkey work, like getting data from one system to another, when they could be helping you make your business more agile and seeing the trends in the market.

Because what human beings are great at is figuring out what problem to solve, and then bringing in the cross-functional stakeholders to say “There isn’t a repeatable process or a playbook for this. How can we do that better?”

Once you have that figured out, you’ve changed the world from the strategic to the mundane, and you can let automation take care of it.


So the thought experiment is that in the world where automation can be applied to any process, the mundane work is removed, and human beings can get on with the kind of thinking that got us down from the trees in the first place?

The strategic, problem-solving, solution-finding thinking that’s worth employing $100,000sworth of MBA for?


Exactly. Let humans be humans, doing the things that humans do best.

“I don’t want to do this anymore.”


Nice trip into Utopian thinking – but does it work in real life? And does it work now?


We had an interesting case, where we had gone to a company, and the manager who was leading their overall automation efforts was in her twenties. She came up and said “Oh, this automation stopped working.”

And another manager said that before the automation was installed, just six months earlier, they had done a process manually. “Why can’t you just go back to doing it that way, we can fix it up in the morning.”

She said “No, no, no, no, no, I don’t want to do this anymore manually. It was good when the automation was doing it.”

Some people, especially in the younger generation who adapt to automation faster, and may have less patience with manual ways of doing things because they know there’s a smarter, faster way to do them – they don’t want to go back to doing the swivel chair work at all – under any circumstances.

That manager sat till past midnight, fixed that automation, and then felt able to rest easy, knowing that she wouldn’t have to do the manual work that the automation took care of.


That does seem to be a generational thing – especially with younger generations, who in fairness, know there’s an automated way of doing things, and have, more than any previous generation, grown up in an instant world.

They’re not prepared to do work they know is what they consider to be machine work – menial work – when the way the world should function is that there should be an automation to do that work.


The further thought experiment of course is to be the platform that can make that ideal world of automating any process, anywhere, a reality.

Because that’s what process automation does – it frees people from worry, from that dispiriting sense of meniality in their work, it frees up their time, and it frees up their creative energies.

How valuable is the freedom of your professionals to be professionals?

Business booster.


Let humans be humans, and MBAs be MBAs?



And of course, it’s not wholly altruistic, either. Companies with more people being people, rather than cogs in a process, help the business become more agile, respond better to market demands, provide faster customer service, and make the company’s operations much more efficient, so that you can invest more dollars towards growth initiatives.

From our point of view, that makes automation a technology that can truly unleash human potential, and through that, unleash the company’s potential.


Is there not a validity to the fear that the more processes that are automated, the more unlikely it is that human beings are necessary in the chair? That’s a fear as old as the industrial revolution of course – but it was valid then. Would it not be valid now?


Ah, but you can automate processes. You can’t automate human instinct. If somebody has worked for a company for a number of years, they actually have developed great domain expertise. One use case that I commonly refer to is the benefits you can get when you combine AI with automation.

The eye of the human.

Take the loan approval process. Banks and loan companies approve thousands and thousands of loans each year. And typically, the decision is dependent on some 25 to 30 different variables.

If somebody applies for a loan, it’s a case of how much do you earn? How much do you spend? And in the spend category, there is rent, which is going to be a fixed outgoing every month, and then finally, how much do you manage to save?

Loan assessors are just evaluating the viability that you can pay back the loan.

What happens in this case is there are loan assessors that are looking at hundreds and hundreds of these applications every day.

And they’re probably just doing this now as swivel chair work – quantity of processed loans, rather than quality of decisions, you know?

What you can now do is you can use automation to process those transactions, you can have an AI model that actually learns from every transaction, and based on that it’ll actually then start becoming more and more confident and start predicting results – loan agreed, loan denied, loan uncertain, refer to human.

And at first you can even have that AI model just in the background, saying “Hey, I think you’re going to approve this loan,” or “I think you’re going to reject this loan – here’s why.”

And the human assessor could also train it further and say, yes, you’re right or no, you’re wrong – here’s why.

Based on that, it could get to a certain level where the AI could take say 60% of cases, and approve or deny them as the human would have likely done based on those simple criteria.

But the things that the AI is just not confident about would be referred to the human. So humans can actually bring their expertise to bear on those truly gray areas to say, “Oh, I see some discrepancies here – good call.”

So what you get is a streamlined, automation-assisted process for the drudge cases, the obvious cases that really speaking, require no human intelligence to decide, but currently require human scrutiny.

And you free up the human in the system to deal with the cases where human intelligence is necessary.

So that’s the thing – you get examples like that across the business world. Automation and AI can actually empower humans, rather than replacing them.


In Part 3 of this article, we’ll take a deep dive into the different approaches to applying automation, including the potential of full-stack SaaS as a way of enriching the potential of your data layers.