Santosh Singh on Work Architecture and AI

Work architecture AI transformation fails when organizations treat AI as a budget line item rather than a cultural shift. The enterprises making genuine progress are the ones who build the architectural foundation first, validate it with the business, and only then move into workflow redesign and agent deployment. Santosh Singh, Senior VP of Corporate Functions at DENSO, one of the world's largest automotive technology companies with over 160,000 employees globally, has led exactly that sequence in real time.

This conversation, from Reejig's Work Blueprint series, covers why AI transformation is a trust curve before it is a technology curve, how DENSO achieved over 90% business validation of its work architecture data, why human judgment cannot be engineered out of complex organizations, and what bold-and-responsible actually means as a deployment philosophy.

What they covered:

Why bolt-on AI into existing processes is not a work architecture strategy, and why it fails
How DENSO built work architecture data that the business validated and co-owned, reaching over 90% approval
Why AI transformation is a trust curve, and why organizations that skip it will see adoption fail regardless of how much they spend
How the “Genchi Genbutsu” principle from manufacturing explains why human judgment must be strengthened, not eliminated, in the AI era
Why the governance layer that links workflow redesign back to Work Architecture is the piece most organizations are missing
Why bold-and-responsible is a deployment philosophy, not a communications message

Key takeaway: AI transformation is not a technology curve. It is a trust curve. The organizations that build work architecture the business believes in, co-create the redesign with their people, and govern the impact back to individuals will get adoption. The ones that do not will get resistance regardless of how much they invest.

Bolt-on AI fails. Work architecture first is what works.

The clearest pattern across enterprise AI deployments right now is that organizations which went AI-first, deploying agents into unchanged processes, have come back to the same conclusion: you have to understand the work before you can change it.

DENSO's approach was the opposite of bolt-on. Start with building the architecture. Map the work at task and subtask level. Validate it with the business until the data carries a 90%+ approval rating. Then, and only then, move into workflow reimagination. From Job Architecture to Work Architecture is the prerequisite, not an optional first step.

Every enterprise is deploying AI. Almost none can see the work they're deploying it into. The Work Architecture is the map that makes every subsequent decision, which tasks to automate, which to augment, which to keep human-led, possible to make with confidence.

AI transformation is a trust curve, not a technology curve

The reason most AI programs stall at proof of concept is not technology. It is trust. Employees who do not understand why their work is being redesigned, what the intention is, and how the organization is planning to look after them will not adopt new workflows. Spending does not overcome distrust.

Singh was clear on where DENSO's advantage sits: "the easiest part is to buy software, because it's a line item in the budget. But the difficult part is building trust with employees to make sure that they understand what's the implication."

The practical sequence at DENSO was: co-create the work architecture with the business so they see themselves in the data, make the purpose of redesign explicit, and communicate the individual development investment alongside the workflow change. That sequence is what produces a 90%+ business validation rating. It is also what produces adoption when agents are deployed.

The business must own the data, not just consume it

One of the most critical lessons from DENSO's journey is the difference between work architecture data that HR owns and work architecture data that the business co-owns. When the business has validated the data, edited it, and stamped it as theirs, the entire dynamic of AI transformation changes.

When DENSO's business leaders validated the work architecture at over 90%, the result was not a HR project being pushed uphill. It was shared infrastructure that every function had a stake in. That foundation is what makes it possible to move into workflow redesign, agent deployment, and career pathway activation, because the map is trusted by the people who have to act on it.

Human judgment must be strengthened, not engineered out

The organizations predicting fully agentic enterprises with no human in the loop are not building for complex, regulated, safety-critical industries. The reality for organizations like DENSO, which powers the automotive systems that people's lives depend on, is that human judgment is not a legacy constraint. It is a design requirement.

The implication for work architecture is direct. AI changes which tasks humans perform. It does not change the need for human discernment, judgment, and contextual sensing at the points where those things matter most. The agent + human operating model is not a transitional phase on the way to full automation. For the most complex organizations in the world, it is the destination. AI capability is compounding. Work visibility is not. The organizations that map the two together, clearly and at task level, are the ones that can make that distinction deliberately rather than accidentally.

The governance layer is what most organizations are missing

Most enterprises are focused on the workflow redesign question: which tasks should be redesigned, and how? The harder and more important question is what happens to the Work Architecture when those workflows change. If redesigning a workflow changes 30% of a software engineering role, someone needs to know that, and it needs to trigger an action.

This is the Work Record layer of the Work Context Graph: the enterprise-grade audit trail of every change to work. Without it, workflow redesign accumulates hidden impact that no one has mapped back to the people whose roles are affected. With it, the organization can govern the change in real time, communicating to individuals before they find out through rumor or restructure.

Bold and responsible is a deployment philosophy, not a message

The phrase that Singh returned to throughout the conversation was bold-and-responsible. Not as a communications message, but as a practical description of how DENSO makes AI decisions. Bold means solving the problems that prevent people from contributing their full capability. Responsible means bringing them along as you do it.

The practical test is whether the organization can answer, clearly and honestly, why it is deploying AI, what the expected impact is on each role, and what it is investing in to develop its people toward that future. Organizations that can answer those questions will get trust. Organizations that cannot will get resistance, regardless of how good the technology is.

Executive Checklist: work architecture and responsible AI deployment

Build work architecture before building agents. Map work at task and subtask level across each function. Do not start agent deployment until the business has validated and co-owns that data.
Get to subtask depth. Task-level data signals AI potential. Subtask data is what makes workflow reimagination possible and what gives agents the context they need to operate reliably.
Co-create with the business, not for it. Involve business leaders in the validation and editing of work architecture data. The goal is a 90%+ approval rating before any redesign work begins.
Articulate the purpose of AI deployment before announcing it. Employees who know why the organization is redesigning work, and what it means for their development, are more likely to engage than resist.
Build the governance layer alongside the redesign layer. Every workflow change should trigger an impact read against the Work Architecture so the organization knows in real time which roles are affected and can act before people are surprised.
Strengthen human judgment as a deliberate capability. Identify the judgment and discernment tasks that must remain human-led and design development around them, not just around the tasks agents will handle.
Treat AI transformation as a continuous operating capability, not a project. The workflows will keep changing as agents get stronger. Build the internal muscle to keep redesigning rather than treating each wave as a separate program.

Where CHROs and CIOs must partner

CHRO Focus	CIO Focus	Shared Outcome
Work architecture co-creation with business leaders: building data the business validates and owns	Agent inventory, approved AI stack, and Work Context Graph infrastructure to support deployment	A trusted, business-validated task and subtask map that is the foundation for every AI deployment decision
Trust-curve management: communicating purpose, impact, and people development plans before and during redesign	Governance layer: triggering impact reads back to Work Architecture when workflows change	Real-time visibility of how workflow redesign affects individual roles, before people are impacted
Human judgment capability development: identifying and designing for the tasks that must remain human-led	Agent + human workflow design: ensuring agents and people are orchestrated deliberately at each handoff	An agent + human operating model that strengthens, rather than bypasses, the discernment and judgment the organization depends on

Executive FAQ

Why does work architecture need to come before AI agent deployment? Work Architecture is the task and subtask map of how work actually runs across every role and function. Without it, agent deployment is blind: organizations cannot identify which tasks to automate, which to augment, and which must stay human-led. Bolt-on AI into unchanged processes produces efficiency theater, not redesigned work. The architecture is the prerequisite for every deployment decision that follows.

What does it mean for the business to co-own work architecture data? Co-ownership means the business has validated, edited, and approved the work architecture data rather than simply received it from HR. When business leaders see themselves in the data and have a stake in its accuracy, the architecture stops being a HR project and becomes shared infrastructure. DENSO reached over 90% business approval of its work architecture data before beginning workflow redesign, which is what made subsequent AI deployment decisions credible and actionable.

What is the trust curve in AI transformation and why does it matter? The trust curve describes the relationship between employee trust in the organization's AI intentions and actual adoption of new workflows. Organizations that skip the trust curve, deploying AI without explaining purpose, communicating impact, or investing in people development, find that their people do not change how they work regardless of what agents are deployed. Building trust requires clarity about why AI is being deployed, what it means for individual roles, and what the organization is doing to develop its people toward the future.

What is “Genchi Genbutsu” and why is it relevant to AI transformation? Genchi Genbutsu is a manufacturing principle that translates as going to the place of work to observe, sense, and discern what is happening, using judgment rather than KPI dashboards alone. Singh used it to argue that human judgment, the ability to sense abnormalities and make decisions based on direct observation, is innately human and must be strengthened in the AI era, not engineered out. For complex, safety-critical organizations, this kind of judgment is a design requirement for the agent + human operating model.

What is the governance layer and why do most organizations not have it? The governance layer is the mechanism that links workflow redesign back to Work Architecture in real time, so that when a workflow changes, the organization automatically knows which roles are affected and by how much. Most organizations focus on the redesign question and miss the impact question. Without the governance layer, workflow changes accumulate hidden consequences that surface as restructures or role disruptions rather than planned development interventions. The Work Record layer of the Work Context Graph is what makes that governance possible.

What does bold-and-responsible mean as an AI deployment philosophy? Bold means solving the problems that prevent people from contributing their full capability at work, using AI to remove friction, automate low-value tasks, and unlock capacity for higher-value work. Responsible means bringing people along the change journey with clarity, transparency about impact, and genuine investment in their development. Organizations that are bold without being responsible get resistance. Organizations that are responsible without being bold get stagnation. DENSO treats both as equally non-negotiable.

Conclusion

The organizations that will get lasting ROI from AI are not the ones that bought the most AI or moved the fastest. They are the ones that built work architecture the business trusts, co-designed the redesign with their people, governed the impact back to individual roles, and treated trust as the currency that makes adoption possible. That sequence takes longer to set up. It compounds faster than anything built on a skipped foundation.

Book a demo to see how Reejig's Work Operating System helps you build work architecture your business validates, govern workflow redesign in real time, and move from proof of concept to proof of value.

Speakers

Siobhan Savage

CEO & Co-Founder of Reejig

Santosh Singh

Senior VP, Corporate Functions at DENSO

Episode transcript

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Santosh Singh: Hey Siobhan, how are.

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Siobhan Savage: I'm great. So, folks, a little bit about Santos. So, my guest today has spent nearly 25 years helping the world's largest industrial companies transform how they lead, how they grow and develop talent.

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Siobhan Savage: Santos joined Dentsu in 2021 to strengthen the company's collaborative culture and reimagine the future of work across North America.

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Siobhan Savage: Today, as Senior Vice President, he oversees human resources, legal, corporate communications, all while shaping the people, culture, and leadership strategies behind one of the world's leading mobility companies.

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Siobhan Savage: And I think one of the things that, like, fascinates me, so Dentsu as a company is one of the world's largest Japanese automotive technology companies.

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Siobhan Savage: So folks, if you have driven a car, there is a really good chance that Denso has built something inside that car. They are a Japanese company, they've got over 160,000 employees globally. Santosh, thank you so much for giving us your time today.

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Santosh Singh: No, it's my pleasure. Thank you, Siobhan, for inviting me, and an opportunity

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Santosh Singh: With you, you know, where the world is shaping towards the work blueprint. So thank you. I'm excited. My pleasure.

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Siobhan Savage: Pleasure. So folks, the thing that's really awesome about Santosh's career is it's very different. So Santosh, the thing that when we met that I was really into was your background. So why don't you tell folks a little bit about your background and how sort of the whole thing has come around with your career and how did you end up in HR?

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Santosh Singh: Thank you for asking that. You know, I've always been curious about work since I graduated. I'm an engineer by trade.

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Santosh Singh: And I have… Had this mindset that you have to be.

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Santosh Singh: At work, at the place of work to understand how work gets done.

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Santosh Singh: In my early career, I was a design engineer. I developed products, for mining, construction equipment, and I had to be on the production floor for 6 to 7 months, building a machine from nuts and bolts to an entire machine, and that was part of our development program.

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Santosh Singh: That instilled this behavior that it's important to

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Santosh Singh: ensure that you bring your knowledge to work, but you also rely on people's experience on the production floor to get things done. And…

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Santosh Singh: From there, I, you know, I moved across multiple functions, including Six Sigma, Process Excellence.

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Santosh Singh: I had a startup in India.

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Santosh Singh: For a global engineering design center.

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Santosh Singh: And then…

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Santosh Singh: You're coming to your question on HR. I was transforming a business, and somebody tapped me on my shoulder and said, you know, we would like someone who has delivered business outcomes to lead HR.

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Santosh Singh: And, I said yes, as I've done throughout my career. And that led me to, you know, human resources. And that gave me a different perspective about how work gets done is not just by technology or tasks. Yeah. But how, how it gets done is by, with people.

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Santosh Singh: and how we enable people, through this, transformation. So, an engineer transformed to HR professional, and I think, I owe it, to the experiences that I've had over… across continents, Asia, and then, currently in the U.S.

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Siobhan Savage: Do you know the thing that I think is really important about your background is, like, systems thinking?

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Siobhan Savage: Mhmm. So, like, right now, when you think about the role of HR, we're kind of in this position where there's this new kind of expertise that's forming, which is around reinventing of work itself.

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Siobhan Savage: And really, work is programmable now. When you think about work itself down to the task, it's programmable. It's systems thinking. And that's where I've really enjoyed working with you is the way that your brain thinks is very systems first.

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Siobhan Savage: And then you get to it. So I think that's kind of where you are a little bit of a rare breed in the sense that you have both.

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Siobhan Savage: You know, those expertise sets at the same time, which is great.

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Santosh Singh: I owe it to the experience that I've had and I'm happy that it comes naturally because of the experiences that we have had and how we can think about the work first and outcomes first and then how we enable it to people.

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Siobhan Savage: Yeah, and I think one of the things, like, you and I are both kind of seeing across, sort of, our peer group, the CHROs that are, you know, leading, sort of, the most complex transformations, is that everyone is right at the front

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Siobhan Savage: of… they're kind of, like, everyone has, like, a clear destination where they're wanting to go, which is, like, AI-driven, without leaving people behind. The one thing that has been really impressive about your, sort of, leadership style in this is the culture that your company is also bringing to this moment. It's not just about AI first.

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Siobhan Savage: So why don't you talk a little bit about that? Because I think that's been really connected to the values that we have as a company about being really bold, but also being really responsible. Tell us a little bit about that, because I think that's going to be something that I think politically is starting to shift in the industry right now.

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Santosh Singh: Absolutely. And I think that that comes as an advantage for any organization whose culture is grounded on valuing human skills.

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Siobhan Savage: Mmh.

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Santosh Singh: and realizing human potential. And that's what DENSO stands for in terms of ensuring that every associate is a part of the change curve and change journey and is deeply engaged in those opportunities. So that's what has made us 75 years strong and still going.

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Santosh Singh: And, we invest in our human capital. We invest in our people, and, and for any large change, we don't go tool-first. We go, you know, what's the purpose? What's the… what are we trying to solve?

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Santosh Singh: And therefore, I think it's an advantage that we have as an organization where change was not difficult in terms of why we're doing this.

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Santosh Singh: you know, reinvention of work and work architecture. It was more important to Understand that…

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Santosh Singh: humans are always going to be at the center of DENSO.

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Siobhan Savage: Yeah, and I think it's really true, because a lot of the conversations I have with customers right now is where everyone's talking about this, like Agentic first.

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Siobhan Savage: no human in the loop. And I'm like, the most complex organizations in the world are not gonna, like, vibe code a car. They're not gonna vibe code a bank. They're not gonna vibe code medicine. So the reality will be that there will always be human in the loop for the most complex organizations in the world, right? Especially when it comes to safety.

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Siobhan Savage: and regulation, and you fall into that category of, like, that as well. So, human in the loop is not only, like, the right thing to do, but also, like, the chances of, like, us going to fully AI is just…

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Siobhan Savage: I don't think it's real. I think it's a little bit, like.

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Santosh Singh: Yeah, let me take a leaf out of manufacturing as an example, right? In organizations which are lean, manufacturing-focused.

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Santosh Singh: Generally, what you've seen is, there is a principle called genchi genbutsu. What it literally translates to is on-site verification, meaning you go to the floor.

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Santosh Singh: And you use all your senses.

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Santosh Singh: To discern what's going on.

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Santosh Singh: which is

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Santosh Singh: innately human, because it's not about verifying if the KPIs are being met. It's understanding, sensing, and feeling if there are any abnormalities.

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Santosh Singh: In the line.

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Siobhan Savage: Really interesting.

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Santosh Singh: Yes, and I think that's at the core.

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Siobhan Savage: Okay.

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Santosh Singh: Understanding how human in the loop cannot be eliminated, in fact, has to be strengthened.

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Santosh Singh: in the age of AI, because I was reflecting on, like you mentioned about the future of automotives and self-driven cars, you know, there comes a point where if self-driven cars

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Santosh Singh: What do humans do in a fully self-driven car?

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Santosh Singh: What do the, what do they, how do they use their time?

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Santosh Singh: During that moment. So, while it's a comfort, convenience, safety.

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Santosh Singh: Humans are known to apply judgment.

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Santosh Singh: And a few humans probably feel tentative about riding a self-driven car. And I think where does that come from? It comes from the core of the human nature to discern things, to make decisions based on what they observe and what they sense.

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Santosh Singh: So I think we shouldn't lose sight of that.

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Santosh Singh: And human in the loop is always going to be relevant.

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Siobhan Savage: That's really interesting. How did you, what was the word that you described that thing as, that when you feel it, what's that called?

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Santosh Singh: Actually, Gemba means a place of work. genchi genbutsu means going to the place of work. Go see, feel, sense, and act.

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Siobhan Savage: Okay, that's really interesting. I might steal that because I have a, I think I talked to my team. I can just feel the creaks of the floorboard in my company. I don't know how to describe it. I just know it. I can feel certain things that don't feel right. And then I kind of lean in a little bit and I find things aren't going well.

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Santosh Singh: And I think the key aspect is many people have tried to replicate that principle without teaching how to do it. Meaning, you need to teach people that how you go and look at abnormalities, not from a, what's the outcome?

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Siobhan Savage: Mmh.

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Santosh Singh: You should sense it based on what you're observing.

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Santosh Singh: And what does your judgment tell you? And then that skill is kind of innately human, and I believe the future generations have to be probably educated on those aspects more than… and, of course, the fundamentals of physics.

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Santosh Singh: Are necessary so that we don't lose,

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Santosh Singh: our next generation to, you know, automation and AI without understanding the concept of why we do what we do.

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Siobhan Savage: It's one of the things…

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Siobhan Savage: So I use, like, quite a lot of AI, as you can imagine. And one of the things that's gonna be really interesting is that

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Siobhan Savage: AI can be so arrogant and say something of like it's a true expert. And if you don't have expertise and challenge it, it will sound like so real that it's true that if you don't have that feeling, that taste, that judgment.

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Siobhan Savage: you're gonna be shipping stuff that isn't true, because it sounds so believable. Like, I've even got to the point where Claude and I are fighting a lot now, because Claude says things so, like.

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Siobhan Savage: Clear. And and I'm like, no. No. You're wrong because I know the answer because I'm checking all the work. And it's like, it's not saying I'm wrong, but it's like, well, you you I I only did it like this. So it's arguing back a little bit with me around like that. Now imagine the amount of people that are gonna be using AI that don't have expertise or, like, that feeling, that judgment.

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Siobhan Savage: are shipping rubbish because they think that it look it sounds so believable. So I think expertise is gonna be really important for us to figure out what is real, what is not real, because AI has the incredible power of, like, gaslighting us.

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Siobhan Savage: So it sounds like really real.

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Siobhan Savage: And that's where I think the human AI component is — we're not talking about startups. We're talking about the most complex orgs in the world who power all of the things that we all either interact with, use, banks, cars, all of those medicines, et cetera. I think that's going to be really important.

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Siobhan Savage: That's the tricky part, where it's like…

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Siobhan Savage: the way that you've been thinking about it is not AI for the sake of AI, it's like, where will we use AI, and then what does that mean in terms of our people, and the impact, and how do we amplify our people, so that we're… which is, like, a really great way to think about structuring the design process of where you go.

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Santosh Singh: Absolutely and I think you hit the nail on the head. Discernment is a skill. What you get as a response, it's important to discern it and I think most complex organizations are taking a holistic view like we are working on looking at our work and how work gets done.

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Santosh Singh: And… organizations that have not been successful in deployments and have been AI-first.

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Santosh Singh: have quickly understood that bolt-on AI in antiquated processes is not the solution. It's an opportunity for all organizations to redefine how they think about work.

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Siobhan Savage: Mmh.

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Santosh Singh: And that means the easiest part is to buy a software. Yeah. Because it's a line item in the budget. But the difficult part is building trust with employees to make sure that they understand what's the implication.

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Santosh Singh: And how we develop them towards the future, like the skills of discernment, judgment, or upskilling them towards a stronger skills that only humans are expected to lead.

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Santosh Singh: And that creates a sense of trust where they are able to participate in work reinvention. So I think that's the part that's most important and we are trying to work our way through.

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Santosh Singh: such a methodology.

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Siobhan Savage: do you know what's really funny? Like, I'm going a little bit off-script here in topic, but I was at this CIO private lunch maybe 2 weeks ago, and CIOs from top organizations that we all know and, you know, we know the names of the companies, right? And I don't know how I ended up at this table, but I'm at this table. And…

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Siobhan Savage: One of the CIOs was saying that basically.

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Siobhan Savage: AI, our young people love it. They're going to be the best adopters.

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Siobhan Savage: There was this whole like, oh, AI is gonna take all our jobs and like, it's gonna be great. And like, our people love it. And I was like, I was sitting quiet. And as you, you know, that's pretty unusual for me to sit like when I've got, like, I was sitting there and I was like, hold on a second. Like, are you guys all really sitting around this table saying that like our young people, just 'cause they're young, are gonna automatically adopt ai? So then I was like, when it came right, like we're doing this like kind of talking thing, circle thing.

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Siobhan Savage: thing, it was a hosted thing. I was like, are you guys, like, on social media? Does anyone pay attention to what's going on in the real world? Because the employees of your companies

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Siobhan Savage: Do not trust AI. They do not trust the leadership around AI. They are booing people in the graduations. This generation is actually… I read somewhere they're more against AI than they've seen an against in a political form before, which tells you there is this complete…

00:14:11.086 --> 00:14:33.896

Siobhan Savage: distrust and not want to adopt. And I think the way that your company and the way your leadership is driving bold and responsible is meaning that your people are much more likely to actually adopt. So, I think there was like this, like, I was like, hold on a second. You guys are like completely in your ivory tower right now and not listen to your people. Because I can tell you right now, your people, you're going to spend millions of dollars on technology.

00:14:33.896 --> 00:14:54.955

Siobhan Savage: You're going to buy all of these AI tools, and then you're going to ask for the ROI. And by the way, your people are going to have to use the AI for you to get the value. Because remember, your companies don't allow full agent end to end, which means getting your people wanting to adopt this new way of working is going to be the most critical thing of our journey. And you are all thinking that they love it. OK.

00:14:54.956 --> 00:15:02.296

Siobhan Savage: Okay, this is going to be a really interesting 18 months to watch, like, the panic in the system come down the chain, right?

00:15:02.296 --> 00:15:07.965

Santosh Singh: Yeah. And I think to your point, it's about the vision and purpose of deployment of AI.

00:15:08.086 --> 00:15:14.955

Santosh Singh: You know, I think when you, when you talk about, we all have watched the graduation ceremonies and people walking out.

00:15:15.226 --> 00:15:17.365

Siobhan Savage: Well, apparently we did, but they didn't.

00:15:17.366 --> 00:15:28.085

Santosh Singh: But the point is, you know, what are they trying to signal and who are they walking out on? They're walking out on people who actually have claimed that AI can solve efficiency.

00:15:28.086 --> 00:15:28.486

Siobhan Savage: Yes.

00:15:28.486 --> 00:15:40.325

Santosh Singh: replace humans. So that's the that's the message for organizations to think about that the purpose should be very clear and it depends on the purpose of your organization and ethos of your organization.

00:15:40.436 --> 00:15:50.005

Santosh Singh: where we are augmenting our humans, or making humans, enabling humans through AI, and enabling humans to make better decisions

00:15:50.176 --> 00:15:52.166

Santosh Singh: with use of AI, but not

00:15:52.346 --> 00:15:59.495

Santosh Singh: augmenting them, not replacing humans. And I think, Shivan, you're on to something.

00:15:59.686 --> 00:16:02.706

Santosh Singh: The future of education might have to change.

00:16:03.056 --> 00:16:06.325

Santosh Singh: Because, you know what, I, I've been thinking about.

00:16:06.526 --> 00:16:19.946

Santosh Singh: Of course, we need… we need people who know the fundamentals, and we do… we do need a deep science, experience if you are discerning something, but about judgment and human skills.

00:16:20.286 --> 00:16:27.116

Santosh Singh: are going to be absolutely critical. I was reading a report, I think it was by Gartner, that the human

00:16:27.506 --> 00:16:31.886

Santosh Singh: A span of attention has reduced to the span of attention of a goldfish.

00:16:32.226 --> 00:16:33.246

Santosh Singh: With…

00:16:33.246 --> 00:16:34.295

Siobhan Savage: The social media.

00:16:34.366 --> 00:16:38.735

Santosh Singh: Yes, it's like 7, 7 seconds or 9 seconds.

00:16:39.056 --> 00:16:44.776

Santosh Singh: So… We have headwinds, so we may have to make sure that our education system

00:16:44.966 --> 00:16:50.825

Santosh Singh: reimagines how we build skills of staying still, observing.

00:16:51.086 --> 00:16:54.536

Santosh Singh: Forming judgments and ensuring that, you know, you.

00:16:54.696 --> 00:17:12.626

Santosh Singh: proof test, or that judgment against the reality. And I think those skills are going to be very critical, be it AI or be it any solution in the future. When you drive efficiency, you cannot take human out of that process. In fact, you need to ensure that the humans keep pace with that evolution.

00:17:13.296 --> 00:17:25.096

Siobhan Savage: I think the other thing that folks also don't factor in, which kind of I've been thinking about a lot, is, like, when you look at manufacturing, we're not just talking about AI. We're also talking about robotics too. Mhmm.

00:17:25.096 --> 00:17:35.926

Siobhan Savage: Right? And if you look at, like, in China and all these other countries where they have, like, light-side factories, we're not just talking about AI, we're also talking about robotics, which means that

00:17:35.926 --> 00:17:47.625

Siobhan Savage: I believe in that kind of like domain education and high, and, and I wouldn't, I actually think the learning space, I'm pretty, I feel the way that we talk about learning is so old school. Yeah.

00:17:47.626 --> 00:17:56.456

Siobhan Savage: Actually, what we need to do is make sure that people understand, like, what the impacts will be to our jobs, what jobs will still be important.

00:17:56.456 --> 00:18:11.805

Siobhan Savage: what do I need to be able to know and learn to be able to complete that work? And, like, that's where, like, you know, your first phase of, like, reskilling and pivoting education comes. But there's this one thing that I'm, like, most obsessed with right now, and we've shifted into the product,

00:18:11.806 --> 00:18:31.126

Siobhan Savage: And I'll show you it the next time we catch up. So if you imagine that I go and I reinvent, so I've told you all of your work, I give you a GPS that says where to go, most people stop at that from a product perspective and go, oh, that's great. That's just insight, that just tells you where to go. Then, as you know, we take the workflow, we break it down into all of the subtasks.

00:18:31.126 --> 00:18:44.496

Siobhan Savage: and we capture the last mile of context, so the handoffs, like, all the critical stuff, and we recommend, whether you're using Copilot or whatever your agent of choice is, we're then recommending, like, what agents? All of that going really good.

00:18:44.496 --> 00:18:54.335

Siobhan Savage: where I see this big drop, and, like, a cliff, is most customers that I've seen, and the narrative that's come from everyone was, like, everyone has to do prompt training.

00:18:54.436 --> 00:19:13.195

Siobhan Savage: And everyone's view is that that now means that they've got AI literacy, and suddenly they're going to be able to do that. The problem is that whenever you roll out this new way of working — and I talk about this example, which I've seen, which was we redesign the invoice and how we pay the invoice. We've got 100 people that do this. They've only been given prompt training.

00:19:13.216 --> 00:19:29.986

Siobhan Savage: And suddenly we're expecting people to actually know how to pay the invoice in a new way, and they all fall off a cliff. And by the way, it's not the employee's fault, it's because no one has actually shown the employee actually how to be successful and how to pay the invoice in the new way. So what's really interesting is there's this, like.

00:19:29.986 --> 00:19:46.295

Siobhan Savage: And I don't, I hate the whole, like, in the flow of work, like, in the flow of learning. It's, it's actually, like, just on time learning. It's the ability for you to give folks the skilling to teach them how to complete the thing ahead of them. And when you can, like, rapidly, like, teach people that fast.

00:19:46.356 --> 00:19:56.485

Siobhan Savage: You're kind of like it's more like ambient constant like in in in practical use of completion of task and showing them high. That's where I think there there is.

00:19:57.036 --> 00:20:15.415

Siobhan Savage: big change coming, because as you know, when you bring in an agent, you take away tasks, but you're introducing new tasks that you haven't done before, which means you need to be able to teach. So, like, that's… and we talk about this, like, stealth management thing, you know, we've been talking about stealth change management and that whole, how do we do that? That's kind of where I think

00:20:15.666 --> 00:20:22.096

Siobhan Savage: I don't know whether you call it learning, but it's definitely enablement for the employee to be able to work in a new way.

00:20:22.376 --> 00:20:35.436

Santosh Singh: Yeah, I think, you know, you're spot on. I think it's gone beyond learning. It's enablement, but in the past, like your example of automation and robotics, in the past, automation or robotics

00:20:35.516 --> 00:20:51.405

Santosh Singh: you know, has automated tasks that were clearly… boundaries were drawn. When someone saw a robotic arm, they could tell that, well, this is to take care of the complex roles, and so that I am safe as a human. But with… with the…

00:20:51.526 --> 00:20:58.855

Santosh Singh: Redesign and redeployment of workflows, it's not just about automation of task anymore, it's about

00:20:59.156 --> 00:21:17.186

Santosh Singh: automation of work in a way that there is a triage of not only automation for a certain purpose, but also discernment and judgment to a certain extent. And I think the line has to be drawn ahead of this redesign as to how do we reimagine the work.

00:21:17.306 --> 00:21:23.106

Santosh Singh: And where are humans going to lead? Where are humans going to rely on AI?

00:21:23.286 --> 00:21:29.816

Santosh Singh: where it's, it's possible for AI to do tasks better, but humans are still supervising it.

00:21:29.996 --> 00:21:39.225

Santosh Singh: and where is it that we'll have humans and AI co-create things. If that's clarified, and we bring our people along.

00:21:39.536 --> 00:21:46.756

Santosh Singh: And as I said earlier, it's judgment comes from experience and many organizations are not investing.

00:21:46.866 --> 00:21:50.796

Santosh Singh: In that experience, and probably this is why early career talent is not

00:21:51.096 --> 00:21:54.885

Santosh Singh: the graduation ceremonies example that you gave.

00:21:54.886 --> 00:21:55.386

Siobhan Savage: the boo.

00:21:55.386 --> 00:22:10.656

Santosh Singh: They're seeking real life experiences and it's actually a positive sign that they're actually seeking to belong to a workforce that actually welcomes them versus says that even before you join, we're going to teach you prompt.

00:22:10.756 --> 00:22:20.226

Santosh Singh: And, by the way, why we're teaching you prompt is because we just want you to do mechanical work without thinking about why you're doing what you're doing. So, it goes back to a full circle on

00:22:20.946 --> 00:22:30.115

Santosh Singh: Our role is going to be very important for us to be able to enable people to understand the purpose of why we are redesigning the work.

00:22:30.236 --> 00:22:44.945

Santosh Singh: Towards what end? And what role do they play? And do they have the skills to play that role? And how are we going to invest in their development? So they build the skills so that in a world that has AI enablement.

00:22:45.286 --> 00:22:49.055

Santosh Singh: Humans become more autonomous to do things that they really should be doing.

00:22:49.056 --> 00:22:55.655

Siobhan Savage: Mhmm. I do think there's gonna be a poli I can feel the feeling of, like, a political shift in the market.

00:22:55.656 --> 00:23:20.326

Siobhan Savage: where the AI frontier firms are pulling back a little bit from their aggressive language of, like, everyone's jobs going. Like, you see Sam Altman and the Anthropic folks, like, their whole narrative was everyone won't have a job, and now they're getting ready for IPO. They're now pulling back a little bit on that, and they're basically like, oh, we kind of were a bit, like, too dramatic. And I think that's because they're realizing that

00:23:20.396 --> 00:23:27.245

Siobhan Savage: you know, most people are stepping back and they're getting the booze, and I think they've been too,

00:23:27.746 --> 00:23:44.675

Siobhan Savage: I don't know, in their bid to, like, sell a tool, they're actually cannibalizing their ability to even sell more, because they're terrifying people. And if people don't adopt their tools, like, you can buy a tool, as you know, and if no one adopts it, that becomes shelfware and eventually churns.

00:23:44.676 --> 00:23:59.835

Siobhan Savage: Right? At what point does a company continue to pay hundreds of millions of dollars for AI without seeing the ROI of the AI itself? And look at the amount of, like, kind of terrifying articles right now where, like, you see

00:23:59.916 --> 00:24:08.355

Siobhan Savage: the stories of, like, CFOs now saying that they're spending more money on tokens than the people they let go in the first place. I mean…

00:24:08.366 --> 00:24:21.505

Siobhan Savage: if all of that isn't, like, a really clear message to leaders to kind of, like, regroup, because what I've seen sort of happening… sort of, one in market, there's, like, the shift now where they're starting to be more positive.

00:24:21.576 --> 00:24:26.306

Siobhan Savage: And I think it's because, one, they're IPO-ing, but two, they're realizing that

00:24:26.306 --> 00:24:48.876

Siobhan Savage: The CEOs of these companies are gonna be held to account. And by the way, if you're redesigning work in a complicated organization, remember your humans are still gonna be needed in the loop of work. Therefore, if they don't adopt it and they kick back at you, you are going to go backwards in productivity, and you will not make money because you need those people. So I think there's this, like, recognition right now that, hold on a second. We need to tone it down a minute.

00:24:49.126 --> 00:25:00.235

Siobhan Savage: And then I think the other part that's really interesting, Santosh, as well, is, like, if we are buying AI and we're spending more on the tokens than the people that we had in the first place.

00:25:01.146 --> 00:25:18.296

Siobhan Savage: Doesn't this whole thing kind of defeat the whole point of what everyone was, you know what I'm saying? Like, it's kind of like, that's a big thing. And then the third thing, I think there's a leadership thing right now where CEOs and leaders have went out and said, everyone build these like token boards.

00:25:18.296 --> 00:25:41.175

Siobhan Savage: where you get a leadership of who's spending the most tokens. That is just nonsense. You're driving people to go and build technology with no outcome, no goal, no clear requirement of why it needs to the business, and it's costing you so much money, so it doesn't make any sense. So, I think this is why the employees are getting the shits, to be honest, because they're actually seeing all of this play out in front of them.

00:25:41.406 --> 00:25:42.136

Siobhan Savage: Yeah, okay.

00:25:42.136 --> 00:25:46.115

Santosh Singh: And I think if you think about larger organizations.

00:25:46.496 --> 00:25:49.236

Santosh Singh: That seems to be a bias.

00:25:49.566 --> 00:25:55.956

Santosh Singh: In some and I'm speaking on from my observation and my personal capacity is.

00:25:58.086 --> 00:26:05.115

Santosh Singh: Short-term gains or flash in the pan approach versus what do organizations really stand for?

00:26:05.586 --> 00:26:07.036

Santosh Singh: And…

00:26:08.066 --> 00:26:16.925

Santosh Singh: Humans in the future, if they are not developed in a certain way, they cannot, you know, even confirm the abnormalities, as I mentioned in the first.

00:26:17.116 --> 00:26:26.566

Santosh Singh: place. So that is, you know, while short term, it might seem like a large capacity unlock and an efficiency gain.

00:26:26.986 --> 00:26:40.355

Santosh Singh: Towards what end is unclear and in the future I want to draw a parallel to organizations having business continuity plans or emergency response plan.

00:26:40.506 --> 00:26:44.735

Santosh Singh: Well, what happens if electricity shuts down? What if there's a natural calamity?

00:26:44.926 --> 00:26:48.666

Santosh Singh: I think we may need to have a similar approach.

00:26:48.666 --> 00:26:49.146

Siobhan Savage: Mmm.

00:26:49.146 --> 00:26:55.736

Santosh Singh: With organizations trying to do a mock drill to say, imagine a world five years from now.

00:26:56.136 --> 00:27:04.136

Santosh Singh: Going at the pace that we are going, without… if we don't have structured thinking on how we redesign work, and bringing humans along with us.

00:27:05.196 --> 00:27:10.895

Santosh Singh: Imagine your workforce, Then, and then try to do a business continuity plan.

00:27:10.896 --> 00:27:11.546

Siobhan Savage: Yep.

00:27:11.546 --> 00:27:13.095

Santosh Singh: If AI shuts down.

00:27:13.096 --> 00:27:13.996

Siobhan Savage: That's a really.

00:27:13.996 --> 00:27:19.136

Santosh Singh: Yeah, how many… how many humans would have the ability to discern and problem-solve.

00:27:19.136 --> 00:27:19.766

Siobhan Savage: Okay.

00:27:19.766 --> 00:27:27.395

Santosh Singh: And therefore, it's better positioned to bring them along and ensure that the fundamental skills of

00:27:27.465 --> 00:27:44.336

Santosh Singh: discernments and process discipline is understood deeply, and AI helps us, but I've heard that there are certain organizations that are doing, like, a Friday where let's test out without AI and see what happens, but I don't think it's that kind of a test. It needs to be a continuous cycle.

00:27:44.445 --> 00:27:58.096

Santosh Singh: where it's an integral part of what you called enablement. Yeah. You know, or giving people experiences, rotating them across multiple functions faster, so they have the judgment skills developed sooner to see the upstream and downstream impact.

00:27:58.296 --> 00:28:02.235

Santosh Singh: of their processes to their clients or stakeholders.

00:28:02.856 --> 00:28:26.665

Siobhan Savage: You've just freaked me out a little bit because I'm thinking because I'm the chairman of my board, and I'm like, maybe I should be thinking about this for my company because, like, you know, I'm building a billion dollar company with a hundred people right now, and we're halfway there. And the way that we're able to work is because we are so AI amplified, but I've never even thought about the world where what if it didn't exist and the risk register like, every board needs to have a risk register. Right?

00:28:26.726 --> 00:28:35.376

Siobhan Savage: And that is like a true risk. So thank you. You're good. Not giving me nightmares. It's like, okay.

00:28:35.376 --> 00:28:36.075

Santosh Singh: Or probably earlier.

00:28:36.076 --> 00:28:41.446

Siobhan Savage: Well, you look after the legal department as well in your company.

00:28:41.446 --> 00:28:43.835

Santosh Singh: Thank you for that. I think it helps.

00:28:43.946 --> 00:28:45.255

Santosh Singh: I've been thinking about…

00:28:45.256 --> 00:29:02.375

Siobhan Savage: OK. This is great. So if we think about — we're all clear on the unknowns of the unknowns of what AI is going to do. I think the thing that you have done really well is you've been through so many different types of transformations.

00:29:02.376 --> 00:29:12.015

Siobhan Savage: In other organizations where you've built real physical products, not just software, you've been redesigning work itself, even pre-AI.

00:29:12.366 --> 00:29:23.666

Siobhan Savage: one of the things I want everyone to get out of this is the steps that folks need to take. Like, most people haven't got to the point that you've got to, right? So I think, like, imagine you were starting from scratch.

00:29:23.866 --> 00:29:33.415

Siobhan Savage: And we call you up, and we're like, okay, how do I do it? What is the most important steps that I need to go through to actually do it? Talk us through a little bit of that.

00:29:33.846 --> 00:29:41.215

Santosh Singh: Yeah, I lean on my past experience in Six Sigma, right? I've been thinking about it as I was thinking about having this conversation with you.

00:29:41.356 --> 00:29:47.945

Santosh Singh: If you think of any process, process improvement has been around for a long time.

00:29:48.116 --> 00:29:56.116

Santosh Singh: Especially in large manufacturing industrial companies. Any process, including transactional processes, can be simplified or improved.

00:29:56.276 --> 00:29:59.355

Santosh Singh: But the difference was, you define

00:29:59.586 --> 00:30:02.146

Santosh Singh: There's a business case, you define the problem.

00:30:02.726 --> 00:30:12.365

Santosh Singh: What… the sponsor defines the problem by saying, here's a real problem that we have. Our… as an example, our sales has remained flat, irrespective of our revenues going up.

00:30:12.806 --> 00:30:24.845

Santosh Singh: there seems to be some underlying issue, which I'm not sure of what it is. Let's put a team together, six months project, you know, in Six Sigma, they would call it a define, measure, analyze, improve, and control process.

00:30:25.066 --> 00:30:30.266

Santosh Singh: DMACC, so you define the problem, put a team together, they go out and measure.

00:30:30.526 --> 00:30:34.586

Santosh Singh: And understand if… and validate if the problem is real.

00:30:34.816 --> 00:30:53.066

Santosh Singh: and then they analyze with root cause analysis, and then they address the root cause with improvements. Now, here's where improvements can be manifolds. Improvements can be, you're reorganizing the process, simplifying the process, using tools, which can be digital solutions, or now AI,

00:30:53.276 --> 00:30:56.005

Santosh Singh: And then the key part was control.

00:30:56.206 --> 00:31:04.186

Santosh Singh: Once you establish the process, you need to put it in a governing structure. You have governance where a process owner

00:31:04.426 --> 00:31:11.996

Santosh Singh: Monitors the process after the team hands that process over to them, and ensures that the process doesn't reverse back to the old ways.

00:31:12.276 --> 00:31:15.896

Santosh Singh: Or because humans have a tendency to practice work a certain way.

00:31:16.186 --> 00:31:24.886

Santosh Singh: but also continues to take ownership of continuous improvement. Yeah. So, why I share this framework is, I think it's relevant in work redesign.

00:31:25.106 --> 00:31:34.676

Santosh Singh: Now, even more than before, because what we are talking about is a team of people coming together, bringing their experiences from the process to solve issues.

00:31:34.756 --> 00:31:53.785

Santosh Singh: Versus now, for organizations like ours, we are thinking the same as I explained, you know, think about the work first, think about the issue, think about why. And I think this framework would be an important one for people to remember. The improvement or the augmentation is a tool.

00:31:54.046 --> 00:31:59.076

Santosh Singh: But the solution is actually a brainchild of a collective collaborative team.

00:31:59.226 --> 00:32:06.066

Santosh Singh: And I think we need to form probably smaller teams like that, build trust, understand the end game.

00:32:06.296 --> 00:32:11.476

Santosh Singh: And then probably use AI as an augmented tool that enables people.

00:32:11.796 --> 00:32:27.145

Siobhan Savage: Yeah, the thing, so you… you're in our… what we would describe as Pioneers Club, which is, like, our early… our early customers, and you got it when we… when I met you, it was in Gartner, right? Like, it was in Orlando, I think, when we met you. And…

00:32:27.946 --> 00:32:30.696

Siobhan Savage: We were, like, so early in the task.

00:32:31.116 --> 00:32:43.955

Siobhan Savage: conversation, like, task, subtask for me was, like, my background is workforce optimization, right? So, I don't have an engineering background, but I think about squeezing, and, like, the… I think about work as a programmable sense, and that you can, like.

00:32:43.996 --> 00:33:01.485

Siobhan Savage: break it up and reprogram. And what was really interesting was you instantly got task-subtask as the critical core unit of work to under… for any reinvention, that was, like, critical for you. So, talk a little bit about

00:33:01.616 --> 00:33:15.435

Siobhan Savage: Sort of what you've learned, like the stuff that we've been doing around tasks, like quality of tasks, like so that folks understand that before they run towards reinvention, they have to have like a visibility of the work that's actually happening in the company, right?

00:33:15.886 --> 00:33:27.906

Santosh Singh: Yeah I want to tell everyone that you know the one thing that stuck with me when I met you first time is when you mentioned not only work ontology you said tasks have tasks and you said work has tasks, people have skills.

00:33:27.906 --> 00:33:28.636

Siobhan Savage: Mmhm.

00:33:28.636 --> 00:33:37.525

Santosh Singh: And I think that connection is very important to make. There are many solutions out there where people have talked about skills-based career.

00:33:37.816 --> 00:33:46.595

Santosh Singh: But without a connection to the work. And I think this connection was very important, and I was glad that, you know, your organization was making that connection.

00:33:46.846 --> 00:33:51.546

Santosh Singh: And the way we've gone about it is we have, we are working on defining our work.

00:33:51.636 --> 00:34:08.056

Santosh Singh: And we're doing it very diligently with our leadership team, meaning the people who are actually the practitioners of work. We are doing a pilot run with a couple of functions. But when we have a task, subtask level, decisions made and tasks validated.

00:34:08.086 --> 00:34:15.066

Santosh Singh: you know, as Regic came as a partner to us in helping us through the process in some of the functions we have seen

00:34:15.256 --> 00:34:29.405

Santosh Singh: the work output aligned 90% of the time to what people actually did, and… and so there's… it was a journey, but it was a change journey for us as well, and I think our change management

00:34:29.676 --> 00:34:39.496

Santosh Singh: is effective when we bring our leaders along and they validate that this is the effort that it takes to do this task and this is really what our associates do.

00:34:39.856 --> 00:34:43.085

Santosh Singh: And that's the first step. Our future vision is that

00:34:43.376 --> 00:34:49.875

Santosh Singh: We also have a language of skills that's coming out of this, and how do we prepare, enable this

00:34:50.386 --> 00:34:53.466

Santosh Singh: Task, subtask, language into a job profile.

00:34:53.806 --> 00:34:57.146

Santosh Singh: And activate carrier for our employees.

00:34:57.386 --> 00:35:04.486

Santosh Singh: To enable them to understand that, you know, today this is the human skills they have, these are the technical skills they are… they have.

00:35:04.746 --> 00:35:13.426

Santosh Singh: And where are we going? So we're working on adding a strategic workforce planning element, where we define

00:35:13.546 --> 00:35:18.246

Santosh Singh: Our 5-year outline, we define our 5-year vision for where we want to go.

00:35:18.356 --> 00:35:19.286

Santosh Singh: And then…

00:35:19.616 --> 00:35:28.045

Santosh Singh: This input plus, you know, the delta would tell us where do we need to augment, where do we need to upskill and reskill our employees, and that's our first priority.

00:35:28.046 --> 00:35:34.945

Siobhan Savage: Yeah, I think for folks as well, just listening, I'm gonna, like, click in a little bit to what Santosh is saying, because, like.

00:35:35.736 --> 00:35:53.795

Siobhan Savage: task is really important, subtask is the most important. And the reason that subtask… like, if you wanted to go and get tasks of a job description, just go put it into ChatGPT or Claude, and you can get that, and that's, like… and you get an AI percentage on that based on who knows whatever model it's pumping out.

00:35:53.796 --> 00:36:05.036

Siobhan Savage: But if you truly want to understand the work that happens in your company and understand, like, how work flows within your company, there's kinda, like, three different levels. There is the task.

00:36:05.036 --> 00:36:06.745

Siobhan Savage: There is the subtask.

00:36:06.746 --> 00:36:29.726

Siobhan Savage: And then there is like the handoffs, the connection points. The way I describe it is like work context. That's the third level when you really get to reinvention. So if you're only sitting at a high level task, that's just insight. It doesn't enable you to take action. So you went through task, subtask, that give you action. Now you're in like actual, or that give you intelligence, sorry. Now you're moving into like actual action and reinvention.

00:36:29.726 --> 00:36:51.756

Siobhan Savage: Which is where you break it down, re-engineer it, think about where AI comes in, what tasks are being removed, what tasks are being added in. So that's the phase one of getting to there. The other thing I would say that we have noticed to become really critical — and Santosh, you and I will see this play out the deeper we get into reinvention.

00:36:51.756 --> 00:36:52.316

Santosh Singh: Cool.

00:36:52.896 --> 00:36:59.575

Siobhan Savage: If you go to the business and you give them task data without the subtask data, they just dismiss it as a HR project.

00:37:00.166 --> 00:37:19.425

Siobhan Savage: And the reason that they will dismiss it is because the business has to see themselves in this work. And if they don't believe the thing that you were really strict with us on is like, you want to validate all of this with the business, because if they don't believe it and see themselves in that work, they will never take any of that intelligence or feedback or strategy off you if the critical foundation.

00:37:19.426 --> 00:37:42.186

Siobhan Savage: isn't right and that they haven't, like, bought into that. And I think that was kind of where you were really early in that, like, journey of, like, like, critical step is build an infrastructure and an architecture that the business, like, has that foundation, and then everything will come after we have that. So I think that's where you did really well. It was painful, I think, for everybody in the sense of, like, you were early in that thinking, but.

00:37:42.626 --> 00:37:57.575

Siobhan Savage: now you have, like, over 90% approval rating from the business in your tasks, which is, you know, like, I don't think many other situations you can actually, like, put a stamp on that and say that, which means when you go into meetings, you're not trying to push a HR project.

00:37:57.586 --> 00:38:05.016

Siobhan Savage: You're actually… You've co-built with the business infrastructure and an architecture to wire their house.

00:38:05.016 --> 00:38:19.096

Siobhan Savage: So now you can start to think about how you move the furniture around. You know what I mean? That's the difference between — and the one lesson that I learned from my first career building — Rejig was very focused on skill when we first started.

00:38:19.096 --> 00:38:32.656

Siobhan Savage: And it always felt like I was dragging people over the hill, that it was a HR thing that the business didn't care about. And my career before was, like, weird because I was HR, but I wasn't. I was a workforce optimization person who sat in the business.

00:38:33.166 --> 00:38:34.286

Siobhan Savage: And…

00:38:34.286 --> 00:38:59.276

Siobhan Savage: When I was stuck doing the skills work in our first version, it always just felt like a HR project and that the business kind of felt like it was a vitamin versus a painkiller. Whereas this is like a business problem. Like work is basically how we all make money. Like it's how your business does its thing, right? So I think that was like a big learning from Santosh and watching him, like kind of the leadership here was get visibility to the work, to the depth that the business believes in.

00:38:59.276 --> 00:39:00.656

Siobhan Savage: and trust it.

00:39:00.886 --> 00:39:11.415

Siobhan Savage: Make sure that they have a say in, like, co-creation of that and editing, and then have those validation results so that you have… it's kind of like when you get your ISO certification.

00:39:11.416 --> 00:39:22.556

Siobhan Savage: You know, like we know I have this percentage of like review and validation, which means that like you are never selling that to the business. That's the business is saying that's our data. Like, so I think that was a really big, lesson.

00:39:22.846 --> 00:39:39.006

Santosh Singh: Yeah, and I've had, you know, the fortune of having good peers, right? They're very collaborative. And once you have the proof point, and we co-create a solution, the one thing I'll add, Shivan, is that we have to make sure to reimagine work

00:39:39.276 --> 00:39:41.376

Santosh Singh: Because we're doing by function.

00:39:41.806 --> 00:39:53.646

Santosh Singh: This is not task and subtask level automation. So we are pausing to think, wanted to think about, you know, not just workflow optimization, but because each of the functions work with each other.

00:39:53.826 --> 00:39:54.146

Siobhan Savage: Yep.

00:39:54.146 --> 00:40:01.595

Santosh Singh: And so we want to do this exercise for all other functions. We are doing it for other functions this year and beyond.

00:40:01.876 --> 00:40:14.666

Santosh Singh: and then see how work gets done, orchestrated across the organization. And I think that's where we will probably do a deeper dive in working with the business to understand that how can we reimagine the work, rather than

00:40:14.766 --> 00:40:23.215

Santosh Singh: automate tasks in our current state processes because we have an opportunity and insight now to

00:40:23.366 --> 00:40:39.996

Santosh Singh: redefine, drive efficiency, unlock capacity to invest in our human capital, and reskill them for a brighter future. So I think that's the… that's what we are focused on. So this year, it'll be more about taking the language for those functions that have completed the work.

00:40:40.336 --> 00:40:48.665

Santosh Singh: and activate career pathways. So, that's our primary work that, you know, it's a foundational aspect of HR's work design.

00:40:48.836 --> 00:40:51.346

Santosh Singh: And activating people's career.

00:40:51.566 --> 00:41:08.326

Siobhan Savage: Mhmm. It's really interesting because I just signed off on our quarter next quarter drop product drop. So exactly what you just said. So right now, we take the work, we reinvent the workflow, we go to subtask, we match the agent, we give them the agent blueprints to go and build. We track.

00:41:08.346 --> 00:41:24.705

Siobhan Savage: The changes, what we're seeing is customers now are getting more adventurous. So they don't just wanna do that level, they wanna look at horizontal, so processes and work streams. So like, let's say, onboarding or I think things that sit across multiple streams of the business.

00:41:24.706 --> 00:41:41.146

Siobhan Savage: Then you've got your, like, vertical, which is your, like, task workflow that sits within, like, paying an invoice. It sits within a division and it's kind of boxed off. That's kind of playing out. And then the third thing I'm seeing is now customers are going, okay, in both of those scenarios.

00:41:41.146 --> 00:41:55.776

Siobhan Savage: give me a version that can show me what I'm allowed to do with the agents that I've got, with the compliance and everything that we know about your company, and then they want a completely rejigged version. What, like, think about, like, day zero, if you were to completely sketch up how work runs.

00:41:55.816 --> 00:42:09.146

Siobhan Savage: So we've now got that releasing in our next product drop, which I'm, I, I'll, I'll, I'll send to you after like the, the figmas of it, but you'll see like this is like, this is where it's coming. And that comes from a level of maturity in the customer base. Yes.

00:42:09.146 --> 00:42:22.955

Siobhan Savage: Where people are starting to now get a little bit of game tape, and they're like, okay, rather than just subtask level, let me take out the whole thing, and think about redesign. And that goes back to your point about the Six Sigma, like, how you think about that whole process.

00:42:23.146 --> 00:42:38.315

Santosh Singh: Exactly. Yeah, it's not workflow by verticals, but as you mentioned, the entire value chain. It used to be called in manufacturing value stream mapping. You know, you used to map value streams and say, where are the delays? Where are the bottlenecks?

00:42:38.316 --> 00:42:38.726

Siobhan Savage: Yes.

00:42:38.726 --> 00:42:45.145

Santosh Singh: And this is exactly that. It just so happens that the tool that we might end up using is an AI tool.

00:42:45.146 --> 00:42:45.486

Siobhan Savage: Yep.

00:42:45.486 --> 00:42:54.785

Santosh Singh: But it's a value stream mapping at scale but for a large complex organization this has to be done across all functions to realize the benefit.

00:42:55.026 --> 00:43:05.686

Siobhan Savage: I'm thinking of calling it work streams only because processes feel so like 1980s. Yeah. And RPA. So I'm thinking like, I think work streams and then workflows.

00:43:05.686 --> 00:43:06.046

Santosh Singh: Yes.

00:43:06.046 --> 00:43:19.836

Siobhan Savage: Or kind of like how I'm structuring it, but like, yeah, keen, keen to see what you think when I release it out to you. I think one of the, the other things that, you know, you are by far standout passionate about is like, okay.

00:43:19.976 --> 00:43:28.985

Siobhan Savage: I'm doing that, but I also want the governance and the trigger of the data. So, back to the point, folks. So, you go and you reinvent Workstream or Workflow.

00:43:29.456 --> 00:43:54.316

Siobhan Savage: You take away tasks, you remove work, you introduce new work that you haven't done before. So you see all that work that Santosh was doing at the start where he built the wiring of the company and built the architecture. That's going to be constantly changing. So there's the governance layer now where you kind of do both things on the one data framework, which means that as he's going out and he's reinventing his work, that it triggers back to the architecture that says, oh, by the way, we've

00:43:54.316 --> 00:43:58.686

Siobhan Savage: Now I impacted 30% of the software engineer roles or sales roles.

00:43:58.696 --> 00:44:02.625

Siobhan Savage: which means that you and I have the information to act on.

00:44:02.706 --> 00:44:12.815

Siobhan Savage: preventing any impact to that individual role. So the way you're structuring it is like, okay, I've done this whole, like, reimagine. Talk me a little bit, Nya, about, okay, we go wide and reinvent.

00:44:12.816 --> 00:44:22.835

Siobhan Savage: Talk to me about then, like, how you're thinking about how that links to career and what you're gonna do in terms of, like, the design for the sort of being responsible, looking after your folks.

00:44:22.836 --> 00:44:31.056

Santosh Singh: Yeah, and this is not new to us, and we call it power shift, meaning we always have believed that, you know, our associates

00:44:31.146 --> 00:44:46.646

Santosh Singh: need to be developing towards the future of where we are going, and we are a large Tier 1 supplier, so we have to take cues from our customers. So, as the industry evolves, you know.

00:44:47.226 --> 00:45:01.126

Santosh Singh: vehicles are becoming more software-defined vehicles in the future. So, capabilities also evolve. So, we are, you know, we look at our inventory mapping of our skills, we look at, you know, starting with engineering as an example.

00:45:01.316 --> 00:45:08.416

Santosh Singh: We then invest in our people's growth, and there is an individual development plan that we put in place.

00:45:08.866 --> 00:45:13.595

Santosh Singh: And with this information that we're getting from our work architecture.

00:45:13.776 --> 00:45:19.816

Santosh Singh: This augments that and makes it more real, because now we know these are the skills expected.

00:45:20.086 --> 00:45:27.875

Santosh Singh: And if we are able to extrapolate and reimagine in our workforce plan that what will the future of work look like?

00:45:28.216 --> 00:45:31.146

Santosh Singh: Then, that enables us to be more proactive.

00:45:31.386 --> 00:45:36.116

Santosh Singh: And… and… Share that with our employees, and make sure that they

00:45:36.256 --> 00:45:40.325

Santosh Singh: Understand the why behind why they're being developed.

00:45:40.526 --> 00:45:52.195

Santosh Singh: And I think that piece is very important to build trust. As I said before, this is not a technology curve. This is a trust curve. And once you establish the trust and you know where we are going.

00:45:52.526 --> 00:45:55.965

Santosh Singh: Absolute clarity towards our future purpose and vision.

00:45:56.216 --> 00:46:02.495

Santosh Singh: And we also want to make sure that our employees understand that as to the investments we make in them.

00:46:02.706 --> 00:46:05.636

Santosh Singh: are… Pertinent to the future.

00:46:05.636 --> 00:46:08.396

Siobhan Savage: Hmm. Do you think that, like.

00:46:08.706 --> 00:46:17.816

Siobhan Savage: and I don't know the answer to this, and I don't know what to do. Do you think, because I've got all the task data, and I can tell you the impact to the task, and I can tell you, like.

00:46:17.886 --> 00:46:29.826

Siobhan Savage: What to do next? Do you think I should expose that task data to the employee? Like, do you think there's a world, or would that freak everybody out? Like, like, what do you think is the, the best thought? What do you think I should do?

00:46:29.826 --> 00:46:35.556

Santosh Singh: Yeah, I think I think it depends on if employees have been brought in.

00:46:35.896 --> 00:46:38.576

Santosh Singh: To… in the problem-solving journey or not.

00:46:38.856 --> 00:46:39.246

Siobhan Savage: Mmm.

00:46:39.246 --> 00:46:48.616

Santosh Singh: So if the work has been defined or the business case has been defined to say we would like to redefine the work for this purpose.

00:46:48.756 --> 00:46:57.085

Santosh Singh: Which is, enabling humans for a stronger future. And when the trust is built, yes, I think then

00:46:57.296 --> 00:47:02.096

Santosh Singh: Employees should know the insights so that they can make even better, stronger decisions.

00:47:02.316 --> 00:47:08.835

Santosh Singh: decisions and actually contribute. Everybody brings a fresh perspective and contribute to newer ideas.

00:47:08.836 --> 00:47:13.596

Siobhan Savage: Yeah, yeah. 'cause I like the, the thing that I kind of struggle with, like just.

00:47:14.166 --> 00:47:27.065

Siobhan Savage: morally, or, I don't know, like… like, I don't want to be building a company that's gonna be taking people out of jobs, right? Like, that's not, like… I absolutely want to be bold and responsible at the same time, and I always think about, like.

00:47:27.096 --> 00:47:48.815

Siobhan Savage: What, what's my role to play? And I sit on, as you know, the biggest, largest source of data in the world, specifically in this for each industry. So it's like, do I make that publicly available for folks so that they can come and like see themselves or does the company do that? Like what, whose responsibility is it? You know, like, is it like, that's the part where I'm kind of trying to figure out.

00:47:48.816 --> 00:48:00.546

Siobhan Savage: Like, what's my rule? What's the company's rule? Like, is it the company's rule when they impact people to make sure that they're being re-skilled, or is it the employee's rule? Like, that's… I think it's actually a jewel rule.

00:48:00.546 --> 00:48:02.846

Siobhan Savage: Is my personal opinion?

00:48:03.756 --> 00:48:14.925

Santosh Singh: I think initially because every company has its own drive and intention so probably if for organizations that are more responsible.

00:48:15.266 --> 00:48:21.446

Santosh Singh: It's an organization's role, because they have a methodical approach to how to bring employees along.

00:48:21.446 --> 00:48:21.926

Siobhan Savage: Mmm.

00:48:21.926 --> 00:48:41.386

Santosh Singh: And so I think starting with it should be an organization's role to define the purpose is the right way to start it. And I would like to say, you know, bold and responsible is a good phrase. Bold in solving issues and problems that hinder associates or employees.

00:48:41.486 --> 00:48:43.186

Santosh Singh: To bring their full potential.

00:48:43.186 --> 00:48:44.016

Siobhan Savage: Mmhm.

00:48:44.266 --> 00:49:00.405

Santosh Singh: and being responsible in bringing them along. The change journey is what I would like to expand so that people know bold doesn't mean optimization bold. Bold means that optimization to a cause which takes away from our humans to realize their full potential.

00:49:00.856 --> 00:49:06.735

Siobhan Savage: Yeah, I like that. I do, I do think, I think that's, that's really important. And given you've done like.

00:49:06.736 --> 00:49:22.026

Siobhan Savage: You know, your career has been transformations, large scale, you know, like, what are the things when you look around the market or your peer group or other companies that you think folks are just not understanding or they're getting wrong? Like, what are the things, like, the watch outs for people?

00:49:24.366 --> 00:49:25.316

Santosh Singh: I think…

00:49:25.706 --> 00:49:36.056

Santosh Singh: one, and I'm… I'm just sharing it based on… I think many of my peers and many are doing what's right for their organization, but I feel the… the…

00:49:37.996 --> 00:49:41.856

Santosh Singh: What what the risk I see or the.

00:49:42.576 --> 00:49:46.606

Santosh Singh: Concern is treating this as.

00:49:47.306 --> 00:49:49.016

Santosh Singh: A tool.

00:49:49.156 --> 00:49:54.855

Santosh Singh: Purchase as a budgetary item, Versus a cultural change.

00:49:55.686 --> 00:49:59.476

Santosh Singh: Is the largest risk. Again, prioritizing short term.

00:49:59.966 --> 00:50:02.066

Santosh Singh: For the long term.

00:50:02.066 --> 00:50:02.726

Siobhan Savage: I agree.

00:50:02.726 --> 00:50:07.046

Santosh Singh: Is a risk. I, I feel if they clarify the long-term.

00:50:07.526 --> 00:50:11.885

Santosh Singh: Purpose, and probably pressure tested the business continuity plan that we talked about.

00:50:12.336 --> 00:50:18.745

Santosh Singh: Probably they will… they would have a better clarity on why they want to implement what they want to implement.

00:50:19.236 --> 00:50:23.285

Santosh Singh: Of course, there's efficiency to be gained, but towards what end?

00:50:23.286 --> 00:50:23.956

Siobhan Savage: Yep.

00:50:23.956 --> 00:50:27.185

Santosh Singh: And I think defining that might take a longer time.

00:50:27.336 --> 00:50:33.836

Santosh Singh: within the organization but for our for us it was easier because our purpose was very clear.

00:50:34.056 --> 00:50:48.236

Santosh Singh: And alignment was there from that point of view. It was more about how do we get there. So I think that's something that people should watch out for, that it's a… it's a… it's a… how you build trust is by being authentic about

00:50:48.606 --> 00:50:52.146

Santosh Singh: Why you want to deploy such a solution?

00:50:52.416 --> 00:51:00.506

Siobhan Savage: Yeah. And it's so true what you're saying. Like if you look at everybody, I don't know, it's kind of crazy because in the market you've got this like

00:51:00.646 --> 00:51:17.815

Siobhan Savage: I think there's this, like, boardroom conversation that's happening right now, where everyone's looking at these examples, which aren't really true, and that's setting the expectation that they need to be going faster, and it's aggressive. But I think, like, people are treating this like it's like a… like a short-term…

00:51:17.816 --> 00:51:25.376

Siobhan Savage: tool project versus, like, a long-term destination. And, like, I think,

00:51:25.476 --> 00:51:43.045

Siobhan Savage: even if you look at companies that are, like, standing up these multi-multi-million dollar transformation programs, where they're going after, like, certain things, that's a bridge, it's not a destination, right? Like, it's… it's… and I think the thing that I think that you have learned, and I have learned, and, like.

00:51:43.056 --> 00:51:54.935

Siobhan Savage: Customers we're starting to see are seeing the same thing. This is a destination and you need to have the capability in your business to build this forever. It's not a one-time thing and it's not a tool purchase.

00:51:55.156 --> 00:52:13.346

Siobhan Savage: It's an evolution of how you work, and it's going to keep happening forever, so you need to have leaders like you on board, who are thinking about the bigger picture of the destination, and wiring up the company on that journey. Because I look at all of these programs that are happening right now, and I'm like.

00:52:13.346 --> 00:52:31.615

Siobhan Savage: you can tell that most of these are gonna feel… you can just tell, like, I can sit around the side of a project, and I'm like, - that's not gonna work. Because there's so many things that tell me, like, what did you call that word where you just can feel it? Like, I'm going into these companies like, - like, I can see that that's gonna break, that's gonna break, that's gonna break.

00:52:31.616 --> 00:52:31.936

Santosh Singh: Big.

00:52:31.936 --> 00:52:43.985

Siobhan Savage: But I think, I think your point is like true. It's the, it's the true bigger picture. It's a cultural shift. It's a completely new muscle for the company.

00:52:44.416 --> 00:52:50.685

Siobhan Savage: And the one thing that I'm kind of obsessed with right now… so you know when you're, like, on your phone, you get, like, the iP

00:52:50.686 --> 00:53:07.876

Siobhan Savage: Right? Like, and, like, I… when you get an upgrade, and you just know that, like, things are changing in your phone, like, I believe it'll get to the point in our companies where it becomes, like, an Apple iPhone upgrade. That work… how you pay that invoice will change every 6 months, or maybe sooner, because the tool gets stronger.

00:53:07.876 --> 00:53:15.885

Siobhan Savage: So it's how do you build the culture also in your business that they're accepting that and that they are able to, like, adjust to the constant evolution of work.

00:53:15.936 --> 00:53:26.495

Siobhan Savage: I think that's a really important, like, stealth change management component that we've talked about, because I think that culture, the enablement, the stealth change management.

00:53:26.696 --> 00:53:38.876

Siobhan Savage: the treating your people with, like, transparency and, you know, like, like, whether you're telling them that they're impacted. The part that you made that I keep thinking about just in my, in my head while, while we're, we're going through this is like.

00:53:38.876 --> 00:53:47.165

Siobhan Savage: Your point is that the company is responsible at this point of like knowing the impact. You are right because the company does know where they're going.

00:53:47.166 --> 00:53:59.376

Siobhan Savage: Mhmm. They know they know where they're going. They know I have the data that can tell them the if they do that, then this. Therefore, that means that they're gonna know the impact back into their workforce. So I think, like, your point on that is really strong as well.

00:53:59.736 --> 00:54:09.166

Santosh Singh: Yeah, and that comes with the responsibility as a partner, right, for you to make sure that, you know, you let organizations decide it, and over a period of time, when it becomes,

00:54:09.426 --> 00:54:13.815

Santosh Singh: A way of doing work architecture and redesign in a few years.

00:54:14.166 --> 00:54:24.495

Santosh Singh: Probably that's when, you know, everybody thinks it's logical, and everybody should have access to what they do, but everybody's purpose and intentions are very different at this point of time.

00:54:24.846 --> 00:54:36.405

Santosh Singh: And I want to reiterate that, you know, it's more about how do we prepare. The largest risk is for most organizations to think about is how you prepare the future generation.

00:54:36.406 --> 00:54:37.026

Siobhan Savage: the…

00:54:37.026 --> 00:54:45.555

Santosh Singh: for the judgment and discernment. If you don't have that built into your work architecture, and if you don't have that built into your workforce plan.

00:54:46.666 --> 00:54:54.385

Santosh Singh: And I think that's a continuous flow of talent and pipeline and enabling them by building the core human skills.

00:54:54.576 --> 00:55:13.815

Santosh Singh: And that doesn't come, that comes only when you are on the floor or you're walking or you're processing something. Maybe a clue is that we may have to do that at a higher pace and scale that resonates with the expectations of the early career generation.

00:55:14.386 --> 00:55:33.436

Siobhan Savage: I love this. I mean, already I could package this up to be a book to teach everybody. But the core themes that I think that I'm taking away from this, and I hope folks are taking away from, one, build your architecture. So start first with building your architecture. Understand your work down to task, subtask level.

00:55:33.716 --> 00:55:51.316

Siobhan Savage: to bring your business on the journey of them making them feel like it's their data, so they get to, like, rubber stamp it, and make sure that they feel that they trust that data, and that's the critical infrastructure for both reinvention of work and also reinvention of career. Yes. Because that same data set has to feed those two motions.

00:55:51.396 --> 00:56:03.356

Siobhan Savage: Think about work streams, which is like long processes and redesigning that as well as like workflows, which are like isolated in, in a, in a, in a vertical manner into your areas of work.

00:56:04.316 --> 00:56:16.996

Siobhan Savage: Looking after your people. So understanding if I do this, what will be the impact on my people and have an open culture where we talk about it in our companies around, like, we are putting in plans to make sure that we're not leaving you behind, which I love.

00:56:17.096 --> 00:56:31.696

Siobhan Savage: And then go walk the… go walk your factory, get in amongst it, keep feeling it out, and making sure that there's that judgment built into your culture, so that folks, like, know

00:56:31.696 --> 00:56:52.726

Siobhan Savage: that there's, like, actual, like, ability to see if this is nonsense or not, like, and actually be able to pick up that. And finally, Siobhan needs to go and do a risk assessment of why I'm building my company to make sure that, like, I think about that worst case scenario. Santos, this was awesome. Like, thank you for, one, your leadership in the space.

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Siobhan Savage: I love getting to work with you, I love getting to jam with you on our product, you've been really early on the pioneering journey with us.

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Siobhan Savage: Everyone, you can find, Santosh online on LinkedIn. You can follow him and see what he's up to. Hopefully we get to have more of these conversations. For folks as well, like, we have, given there's so much learning that's coming in this space, I've built this kind of, like.

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Siobhan Savage: out-of-the-box course, just so folks can actually start learning. So you can find it here. We can also send it to you after this as well. Santosh, thank you so much. Thank you, everyone, for listening. Take care, folks.

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Santosh Singh: Thank you. Thank you, Sherw Take care.

Santosh Singh on Work Architecture and AI