Process First, AI Second: Michael Schank on Building the Foundation for Digital Transformation

In the rapidly evolving landscape of artificial intelligence and digital transformation, organisations often rush to implement the latest technologies without fully understanding their own operations. We recently had the pleasure of hosting Michael Schank, a digital transformation and operational excellence consultant with over 25 years of experience, on the Project Flux podcast. His insights into why transformations fail—and how to ensure they succeed—offer a refreshing perspective that puts process understanding at the heart of technological change.

Michael's Journey: From Technologist to Transformation Expert

Michael's path to becoming a transformation expert began in the technical trenches. "I started as a technologist and I was a Java C++ programmer, solution architect, et cetera," he shared, reflecting on his 13 years at Accenture. But it was during his subsequent decade at EY that his perspective fundamentally shifted.

"One of the first projects was a large bank in the US said, hey, create a capability model," Michael recalled. This six-week project involved interviewing business stakeholders to map out what the bank actually did. "It was just an epiphany moment for me because coming as a technologist, had no idea, literally no idea what the business did other than I was a banking customer."

This revelation—seeing an entire organisation's operations laid out on a single page—transformed Michael's approach to consulting. "I dedicated myself to really serving clients from that perspective," he explained. Over the years, he served clients across various capacities, from strategy definition to IT architecture, risk and compliance, and transformation programme management.

Throughout this work, Michael observed patterns in why transformations fail. The oft-cited statistic that 70% of transformations fail resonated with his experience, but he identified a fundamental root cause: "The complexity of these organisations. They have very complex people, process, technology, regulatory environments, and no one has a full understanding of everything."

This insight led him to develop the Process Inventory Framework, a comprehensive approach to documenting and understanding what organisations actually do—before attempting to transform them.

The Alignment Challenge

At the heart of successful transformation lies alignment, which Michael breaks down into two critical dimensions:

"There's vertical alignment. So everyone from the CEO, all the senior leadership down to individual contributors that are writing requirements or operating a process, building code, making sure that everyone's aligned and they're working towards the strategic direction of the organisation."

Equally important is horizontal alignment: "Within an organisation, there's a lot of peer teams of different practitioner types. So you have the business and technology and risk and data and you name it, you could go on and on. Making sure that those teams can collaborate effectively to advance the goals of the strategy."

The second essential element is systems thinking—understanding that organisations comprise many different components that must work together. "Systems thinking is really about understanding how all those parts connect and how they individually drive performance," Michael explained.

When asked whether he was surprised by what he found when documenting processes at large organisations, Michael's response was telling: "One of the first things I always tell myself is never be surprised when I walk into a big organisation because they're just dominated by bureaucracy and confusion."

He shared a striking example of how organisations can create unnecessary complexity: "I was at one organisation and a lot of teams are stood up based on knee-jerk reaction. So this particular case, there was a problem with statements where they were showing wrong numbers to customers. Obviously a big deal. So they stood up a statements team to govern it, quote unquote. But when I really dug into what they do, they didn't really have a role other than just to be watchers of watchers who watch the watchers."

This layering of oversight without clear purpose exemplifies how organisations evolve over time without intentionality, creating inefficiencies that digital transformation must address.

The Process Inventory Framework Explained

Michael's Process Inventory Framework goes beyond conventional process management, which typically focuses on understanding upstream and downstream processes. "I define it a little bit differently than conventional process management thinks of it," he noted.

His approach emphasises two additional aspects: "One is having a comprehensive understanding of every process because there'll be gaps and there'll be bureaucratic processes that slow things down. So really understanding the full landscape."

The second critical component is data alignment: "Our organisations have a lot of operational data that's locked in various silos, siloed repositories that are unconnected that have different indexing structures." Connecting this data to processes provides the context needed for effective transformation.

Michael illustrated the framework's application with an example from an insurance company being spun off from a larger global insurer: "We spent a few weeks and just defined what their business areas are aligned to the organisational hierarchy. So we followed who managed what and laid out at just two or three levels, not very deep, of what they did."

In strategy sessions, they defined strategic imperatives around whether each area should be "best in class" or "best in cost"—a distinction that drove investment decisions. "Best in class being these are customer facing and we really want to deliver a good experience versus best in cost. We just have to be good enough. Like you're back office finance or whatnot."

This clarity enabled the company to make priority decisions and define their transformation roadmap. "It helped them define their transformation roadmap, make priority decisions around what programmes they want to start first," Michael explained. "And it was one of the smoothest transformations I've been a part of."

AI and Process Inventory: A Perfect Match

As organisations increasingly look to embed AI into their operations, understanding processes becomes even more critical. Michael referenced a Deloitte State of the AI report where leaders expressed a desire to see "AI deeply embedded in their processes and functions." His response was unequivocal: "You can't do that unless you know what your processes are."

This connection between process understanding and AI implementation leads to the concept of digital twins—virtual models of real-world environments. Whilst already established in manufacturing as a $183 billion industry growing at 40% annually, Michael sees untapped potential in information-based businesses.

"It's really about creating a virtual model of your real world environment and then educating AI on what your business does so that you could feed it data around any operational signal," he explained. These signals could include defects, issues, customer complaints, or process mining data.

The challenge for information-based businesses is creating this model without the physically tangible elements of a factory floor. "How do you construct a model of the environment? Well, you need a common semantic structure. And the best one to do that is what does my business do? By inventorying every single process."

Looking ahead, Michael envisions AI agents operating in multi-agent environments to transform how organisations plan and execute change: "Let's say I'm doing a transformation programme, I could not only educate AI on what my business does, but estimating models, et cetera. So now I could say, here's the transformation programme that I wanna do."

In this scenario, one agent could analyse the repository of processes and operational intelligence to understand impacts, whilst another creates a detailed work plan with resource requirements and dependency analysis. Eventually, this could extend to automated risk assessments, code creation, testing, and deployment—but only with the proper context of what the business does.

The Shadow Systems Problem

A significant challenge in many organisations is the proliferation of shadow IT and shadow processes—unofficial systems and workflows that emerge when official channels don't meet needs. Michael sees this as a fundamental trust issue: "I think the fundamental issue is they can't trust technology to get them what they need on the right timing."

This stems from a disconnect between technology teams and business operations: "Enterprise architecture and technology teams as a whole just don't really have an understanding of what the business does. So they create their strategy. They do governance on what technology is being implemented, but without that understanding of what the business does."

Without this understanding, technology teams can't have productive discussions about future needs or priorities, leading to situations where business units circumvent standards out of necessity: "It really becomes pressing where the business says, I need this and I don't care about your standards, just implement something."

When asked if documenting processes might risk over-engineering, Michael disagreed: "My first and foremost, I think it's just about documenting what already exists." He also challenged the perceived trade-off between detailed understanding and innovation, noting that innovation can be enhanced when people understand the full context of their work.

"There's now democratic innovation where you look at your people in your company and you say, everyone has some level of expertise in what they do," he explained. By giving people both autonomy to test new ideas and accountability for what they own, organisations can drive innovation—but only if people understand the broader context of their work.

"People don't understand the upstream processes, the downstream, all the impacts. So they really can't drive change or generate new ideas. But if you give them this repository of information, now they could do that."

Culture Change: The Missing Piece

Technology deployment without adoption represents a significant missed opportunity—a reality James Garner highlighted regarding Copilot implementations: "When you actually ask them how many people are using it, it's tiny percentage."

Michael identified the likely root cause: "They're probably lacking the why. So why are they deploying Copilot and what behaviours do they want to see from their people?" Without clear expectations, education, and training, even the best technology investments fail to deliver value.

This extends to AI strategies more broadly, where transparency is essential: "There's a lot of companies that have come across that state certain strategic imperatives, but people on the ground aren't connected with it. So I was talking to one friend, they're like, my CEO says we're going to be cloud first. He's like, I have no idea what that means to me."

The challenge of AI adoption is compounded by legitimate concerns about data quality and security. "I don't think we're at the point where we could trust the data that comes out of it," Michael noted, referencing cases where lawyers have cited non-existent court cases generated by AI.

His advice echoes what we at Project Flux call the "bookending approach"—human judgement at the beginning and end, with AI handling the middle: "You need to look at it as an assistant. And you wouldn't, even if you hired an assistant, a human assistant, you wouldn't necessarily trust everything they say... But you ultimately, you're accountable for what you put in an email, the decisions you make, and you still have to retain that ownership."

Practical Applications for Different Organisations

The Process Inventory Framework can be applied differently depending on organisational size and maturity. For large enterprises with multiple business lines across global operations, Michael recommends starting small: "You don't have to implement this for an entire organisation... you could take one individual business unit, document all the processes, align all the data, create AI for that, and then show how the advanced analytics that you would receive from it really helps your business."

This approach creates a compelling case study that can drive adoption elsewhere: "Once you get that, now you could expand to other areas because other businesses will want that insight."

For startups and SMEs, the framework offers different benefits. Whilst early-stage companies may focus primarily on growth rather than efficiency, there comes a point where understanding processes becomes crucial: "When you get to a point where efficiency really matters and capturing all this and understanding how you're using your resources... if you're starting to develop bureaucracy or overlaps to make sure that you address that with a full understanding."

Regardless of organisation size, success ultimately comes down to business performance: "If it's cost and efficiency, I need to understand where the resources are in terms of people, pounds, et cetera, so that I could align and prove, look, I'm providing transparency that's allowing you to be more efficient with money. If it's customer success, then am I getting better metrics from my customer surveys or am I getting better engagement or repeat business?"

The Future of AI and Work

When asked about the future of AI and its impact on work, Michael was both optimistic and measured: "I think it's going to have a huge impact. So I've been sceptical a lot of technology advances like RPA, process mining, have some level of scepticism. I'm not sceptical about AI. I think it's really going to be revolutionary."

However, he rejected fatalistic views about job displacement: "I'm not fatalist though that it's going to take all our jobs and we're going to be slaves to it. I mean, if you've seen The Matrix, we're not going to end up in pods where they tap into our energy sources, et cetera. I think we're going to have to find an equilibrium with it."

This equilibrium involves leveraging AI to advance businesses and lives whilst ensuring it doesn't become "the sole means of production where it's creating products and services that we can't use because we're poor."

A critical factor in this future will be data quality: "AI to be effective has to have good data. And a lot of these large organisations just don't have good data." Organisations need not only to deploy AI but also to develop strategies for managing incomplete or conflicting data.

Conclusion: Starting Your Process-First Journey

Michael Schank's insights offer a compelling case for putting process understanding at the foundation of digital transformation. By documenting what organisations actually do—not just what they think they do—leaders can make more informed decisions about technology investments, identify inefficiencies, and create the context needed for successful AI implementation.

The Process Inventory Framework provides a structured approach to this understanding, connecting the dots between strategy, operations, and technology in a way that enables both alignment and innovation. As AI continues to evolve, this foundation will become even more critical for organisations seeking to leverage its full potential.

For those looking to start their own process-first journey, Michael's advice is clear: begin by understanding what your business does, create a comprehensive inventory of processes, align your data, and only then consider how AI and other technologies can enhance performance. This approach may require more upfront investment than jumping straight to technology implementation, but it dramatically increases the likelihood of transformation success.

As Michael put it, "If you as a leader are defining a transformation strategy and you have clarity on how everything connects and getting alignment with people, that will get you to success in these large efforts."

Want to stay updated on the latest in digital transformation and AI? Subscribe to the Project Flux newsletter for weekly insights, tools, and expert perspectives. You can also connect with Michael Schank on LinkedIn and explore his book "Digital Transformation Success" on Amazon or visit processinventory.com for more resources.