Resources

Volker is interviewed for the 28th episode of The EXperience Lounge, a weekly podcast dedicated to EX design, the future of work, and digital HR.

List to the full podcast interview here.

In this episode, Laura and Sasha get the inside scoop on FOUNT. You can check out Volker’s previous interview here.

These leaders are redefining the way people look at the HR industry and HR tech. They’re also helping develop and innovate products and start important conversations in the HR tech market.

It’s humbling to see our cofounder and CEO, Volker Jacobs listed among a list of the world’s best HR leaders. We’re so very proud! This list, compiled by the team at recooty, a recruitment software provider, includes a lot of well-known faces such as Kathleen Hogan, Chief People Officer & EVP, Human Resources at Microsoft; Jess Miller-Merrell, Chief Innovation Officer at Workology and People Analytics leader, David Green.

To learn more about these HR influencers, read the full article on LinkedIn.

Companies know they need to be better in tune with what people at work want and need – whether triggered from the demands of COVID-19, hybrid working plans or from the ongoing reality of competing on talent in the experience-based economy. We can venture to say that empathy is on the rise at organizations, and that is a good thing.

Companies know they need to be better in tune with what people at work want and need – whether triggered from the demands of COVID-19, hybrid working plans or from the ongoing reality of competing on talent in the experience-based economy. We can venture to say that empathy is on the rise at organizations, and that is a good thing.

A more empathetic stance, of course, comes with higher expectation for action. Employees feel more heard and expect better experiences from it. In turn, Boards, CEOs, and shareholders expect the organization to deliver on employees’ most important needs as a matter of good business strategy.

This growing consensus from all stakeholders is encouraging. At the same time, it puts leaders that own Employee Experience in the spotlight. They are under high performance expectations and tight timelines for making real impact. Without near-term results, attention and investments risk getting diverted. Worse still, valued talent might seek better experiences elsewhere.

This is a crucial moment where budding EX teams will either ascend into the short list of value-creating functions in their organization or be side-lined for a few years.

The Experience Intelligence Breakthrough

The volume of experiences happening and diversity of people having them at organizations are overwhelmingly large, so how can EX leaders quickly converge on where they are most likely to achieve measurable impact?

Organizations need to build better Experience Intelligence. They need better visibility into the actual experiences people are having with the organization. Better experience intelligence starts with shifting to a new experience-based paradigm to capture data that reflects the complexity of human experiences, allowing a rich and insightful analysis on the back end.

This data framework captures a high-fidelity picture of an individual’s experiences at the point of interaction. Notably, it differs from existing employee listening approaches such as engagement or pulse surveys in that it is specifically designed to capture experience data.

While engagement tools are useful to assess an individual’s degree of commitment to the company, they do not fit the purpose of telling the experience story. Surfacing the specific experience highs, lows, and gaps in the context of an individual’s interactions with the organization is a view that all organizations need but most lack.

At TI People, we have applied our proprietary data framework to collect, organize and analyze over +1M experience data points. This unique dataset offers some noteworthy indicators towards more focused and prioritized EX efforts.

The job matters

First, organizations should recognize that the majority of high impact moments happen throughout everyday work. Specifically, the “I Perform My Job” moment carries the greatest overall influence of all interactions a person has with the organization. The everyday beats infrequent moments, no matter how emotional or personal they may be. It also beats L&D, Performance Management and Mobility moments. Notably, these “Macro” HR moments often attract the most EX management attention despite their relatively lower influence.

Better EX Intelligence, Greater Impact

With that in mind, it is crucial that EX Leaders expand their perspective to encompass both realms of experience to deliver meaningful experience improvement for people and the business. Leaders should continue efforts to understand employees’ experiences of “Corporate Services” like HR, IT and Finance to ensure ease and efficiency throughout. Yet they also need perspective focused specifically on key job segments – as individuals do their everyday work. First-hand, job specific experience data reveals what matters most in day-to-day work and what stands in the way. EX and business leaders can then partner to identify and eliminate obstacles that inhibit performance.

Effective prioritization of EX efforts, and lasting commitment from senior executives to those efforts, demand an experience-centric dataset that reflects the gaps between people’s expectations and their experiences of work. By shifting perspective to a new paradigm, organizations will become increasingly more intelligent about the experiences that matter most to people at work. Better experience intelligence lays the groundwork for more impactful improvement efforts where they matter most.

Today’s most ambitious GBS leaders are redefining their mandate. It’s no longer just about delivering services efficiently – it’s about creating new value across the enterprise.

That shift changes everything:

• How success is defined
• How functions partner across silos
• And especially, what data leaders rely on to steer change

But here’s the problem: the data GBS teams use hasn’t caught up.

Most still depend on lagging, siloed metrics – SLAs, ticket volumes, system usage, post-implementation surveys. These show symptoms, not root causes. They track when things go wrong, but not why.

Worse, every function owns its own slice:
HR tracks policy use. IT tracks uptime. Ops tracks workflows.
But no one owns the full experience.

This fragmented view creates friction – not just for employees, but for transformation itself.

The Real Cost of Bad Data? Lost Trust.

Executives want GBS to act like a value engine. But when leaders can’t explain why tools aren’t adopted, or why processes stall, confidence erodes.

You see it play out:

• New digital tools quietly fail
• Employees revert to manual workarounds
• Transformation timelines stretch, and rework creeps in

And yet, GBS has the scope to solve this. It cuts across IT, HR, Finance, and Ops. It sees the end-to-end work.

What’s missing isn’t ambition – it’s a shared, reliable way to measure what’s broken.

You Can’t Create Value Without Seeing the Friction

Most traditional metrics are echoes. They tell you something happened – but not where or why. Like hearing a car crash but not knowing what caused it.

To truly lead transformation, GBS needs leading indicators: data that shows where work is breaking before it affects KPIs.

That means measuring how employees experience the work:

• Where do they get stuck?
• Which tools or processes cause delays?
• How much time is wasted?
• Where do they give up entirely?

This is what friction data reveals.

What Is Friction Data?

Friction data measures the hidden obstacles that slow employees down – across every touchpoint: tools, policies, approvals, and people.

FOUNT’s structured friction data model captures:

• Work Moments (e.g., submit vendor request, plan leave)
• Touchpoints (e.g., systems, policies, support channels)
• Impact (e.g., time spent, frustration, abandonment)

It shows which work experiences cause the most pain – and how that pain is distributed across tenure, region, role, and business unit.

And because it cuts across functional silos, it gives HR, IT, Ops, and Finance a shared view of what’s broken and how to fix it.

Example: Fixing GBS Without the Rework

One global GBS org rolled out a new procurement workflow. Adoption looked good – until tickets spiked and employees reverted to spreadsheets.

SLAs were met. Usage was logged. But employees were stuck.

Friction data revealed:

• 35% found the approval logic confusing
• 42% didn’t know where to go with questions
• The total time to complete the process averaged 3x longer than expected

None of this showed up in their existing dashboards. But friction data made it visible – and fixable – across functions.

This Is Bigger Than Experience. It’s Value Creation.

Removing friction doesn’t just improve service. It:

• Frees up capacity
• Accelerates adoption
• Reduces rework
• Boosts retention
• Unifies disconnected teams around clear action

That’s what transformation actually looks like.

Why Now

AI, automation, and digital platforms are changing the way employees work. But those investments won’t deliver value if GBS leaders can’t see where they’re failing.

Friction is the leading indicator of whether transformation will stick. And structured friction data is how you see it in time to act.

The Bottom Line

You can’t create new value with old data.
And you can’t lead transformation from inside a silo.

Structured friction data gives GBS leaders the clarity and credibility to act — before adoption stalls, before frustration builds, before rework costs pile up.

That’s how GBS regains the trust of leadership – and earns a new, strategic role in shaping the future of work.

Ready to get to the core of the problems at your organization so you can be the one who identifies solutions? Let’s talk.

With thanks to Stephanie Denino for sparking this line of thinking in her recent LinkedIn post

Traditionally, GBS has been optimized for one primary goal: reducing costs through efficiency. The KPIs have reflected this focus – cycle time, accuracy, cost per FTE.

But those metrics no longer tell the whole story. Expectations have changed. GBS leaders are now tasked with driving transformation, improving adoption, and delivering more value – with no additional resources. The current data isn’t enough.

‍

The New GBS Imperative: Experience as a Strategic Lever

According to industry research:

• 35% of GBS leaders plan to prioritize internal customer experience within three years, recognizing that outdated efficiency-only models fail to address hidden costs like low adoption and rework (Deloitte).
• 44% now view customer centricity as a top strategic priority, according to SSON, with leaders emphasizing trust-building and user-centric design to drive long-term value.

This shift reflects a critical realization: efficiency and experience are interdependent.

“When employees struggle with fragmented tools or unclear processes, costs rise – even if SLAs are met.”

The Myth: Better Experience Means Higher Costs

There’s a common misconception that improving experience comes at the expense of efficiency. In reality, the opposite is often true:

“Efficiency isn’t the opposite of care. Often, it is the care.” – Stephanie Denino , Managing Director TI People

“The false choice between efficiency and experience is what holds so many GBS teams back! If it’s hard to use, it’s expensive to run” – Isabella Kosch , Transformation Consultant, ex-Head of GBS Service Management at Swarovski

Poor experience drives cost – through escalations, delays, abandonment, and low productivity. According to Gartner , poor employee experience contributes to higher turnover, more errors, and lower overall output.

What Poor Experience Looks Like

Imagine a new digital process aimed at reducing FTEs and increasing self-service. On paper, everything checks out – UAT passed, change management completed, SLAs met.

But employee frustration persists:

“I couldn’t find the answer.”

“I didn’t understand the steps.”

“I didn’t know where to go.”

As a result, support volume unintentionally rises, rework increases, and ROI stagnates. Why? Because the process was technically sound, but the experience was broken.

Why Traditional Metrics Fall Short

Most GBS teams rely on lagging indicators:

✔️ SLA breaches

✔️ Ticket volumes

✔️ Post-implementation NPS

✔️ System usage

These signals tell you what went wrong after the damage is done – but not why or where employees are getting stuck.

A met SLA for HR inquiry resolution doesn’t explain why 40% of employees abandon self-service portals. High system usage metrics might mask frustration with clunky interfaces that waste 2–3 hours per employee weekly.

And since IT, HR, and Operations often own different parts, the full experience remains uncoordinated.

The New Approach: Friction Data

Forward-thinking teams are now adopting friction data – a new measurement layer that reveals:

• Where work is breaking down
• How much time is being wasted
• Which tools or touchpoints cause frustration
• How to resolve issues proactively, before costs escalate

This structured data (like what FOUNT provides) allows GBS leaders to identify root causes of:

• Rework
• Abandonment
• Poor tool adoption
• Low productivity

It offers a shared view across silos- creating a roadmap for continuous improvement.

A Case in Point

At one global pharmaceutical company, friction data revealed a breakdown in the performance management process. The insights led to a redesign that:

• Saved over 30,000 hours
• Avoided $3.49M in costs
• Increased employee satisfaction by 22%

The Power of Reducing Friction

When friction is reduced:

• Employees need less support
• Tools are adopted more reliably
• Processes run closer to their intended design

You’re not overspending because you care too much about experience. You’re overspending because friction hampers adoption and inflates support costs.

To transform GBS from a cost center into a strategic value driver, you need more than dashboards and CSAT scores. You need visibility into how work actually feels – and where it’s breaking down – so you can actively improve it.

Sources:

• https://www.linkedin.com/posts/stephaniedenino_betterwork-ex-gbs-activity-7336382847592652802-A9IJ?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAawMR8Bi7QFEzpwn_7YqdGYqwd5znLfG2o
• Chief Executive: Expanding GBS Adoption Through Increased Focus On Customer Experience
• SSON: Creating a Customer-Centric GBS: Focused Goals, Feedback & Vision
• Harvard Business School Online: Customer Experience Management Strategies for Brand Loyalty
• Psico-Smart: What are the hidden costs of neglecting employee experience management?

Register for the Upcoming Webinar, organized by SSON Beyond AI Hype: How to De-Risk Your GBS Transformation with Friction Data

‍

Everyone is talking about it. Your competitors are doing it. Your board is asking about it. AI is everywhere – and your organization needs it. That’s a lot of pressure. And it’s little wonder that 60 percent of leaders worry their organization lacks a plan and vision to implement AI.

That’s why part of the stress you’re feeling when it comes to AI is likely based on confusion. In this fast-moving, high-stakes environment, how can you possibly keep up with the latest and greatest AI developments? And how can you be sure which AI tool will work for your organization?

Here’s the good news: you don’t really have to. Finding the right tool isn’t the most important part of an AI investment. It’s finding business problems that AI can solve. In this post, we’ll show you how getting to the bottom of that question will make your AI journey far less overwhelming – and far more successful.

Choose the Right AI Starting Point

Keeping up with the constant flow of new AI tools is a stressful, full-time job. It’s also something that most leaders don’t have time for. And even if you manage to stay on top of the latest developments, picking an AI tool and hoping it will increase productivity in your organization is like backing into your investment.

Why? Because AI is a user-driven digital transformation, meaning a traditional top-down approach won’t work. In other words, you can’t just roll out a new AI tool and expect employees to do their work better or faster. If the tool doesn’t solve a specific problem for them, employees won’t adopt it and your investment will fail.

Instead, start from a business problem. Find a process in your organization that isn’t working and determine how AI can help. This way you’ll be trying to solve an actual problem, rather than just finding a way to use AI. In doing so, you’ll be much more likely to win both employee adoption and positive ROI.

Define the User Experience to Understand How AI Can Help 

The place to look for those problems is within your employees’ day-to-day work. Again, employees will only adopt an AI tool if they can clearly see how it helps reduce their day-to-day pain points. Without knowing these work friction areas, you’ll never know where AI can make a difference.

For example, one recent client embarked on a major enterprise services transformation to try and reduce operational costs and enhance the employee experience. To do so, the company invested in a number of innovative technologies, including AI chatbots. But the AI was focused only on a high-level outcome – it wasn’t aimed at a defined employee problem.

Processes that seemed straightforward on paper were far more complex in real life, and gaps in resources or misaligned systems left employees to solve problems on their own. As a result, employees grew increasingly frustrated and adoption rates for the new tool were low. That meant the AI experiment wasn’t having its hoped-for impact on operational costs.   

Use Work Friction Data to Evaluate AI Tools

The purpose of AI is to increase productivity by smoothing out problem areas, removing obstacles, and accelerating work. That’s why every AI investment should start with an understanding of where work friction exists in your organization. Detailed work friction analysis gets to the heart of employee pain points to show you exactly where an AI tool might be most effective. 

In the example above, work friction data helped show exactly where employees were running into issues. These areas included problems related to using the HR chatbot to request parental leave and dissatisfaction with internal career mobility, which the platform was supposed to improve.

With this more detailed information in hand, the company was able to adjust its AI deployment to specifically address these problem areas. As a result, users saw the value of the retooled AI and adopted it, and a streamlined workflow led to $2.3 million in annual operational savings.

To Get AI Right, Start With a Business Problem

The pace of AI can be overwhelming. Trying to keep up with every new development is impossible. It’s also not how you’re going to find an AI tool that works for your organization.

A better approach is to use work friction data to uncover your employees’ needs and pain points. Then you can base your AI investment on finding a tool that will solve those problems. That’s how to move from problem → AI solution → positive ROI.

We can help you succeed with AI by not trying to keep up with AI. Book a demo to see how.

REGISTER

LIVE Webinar | July 9th | 10 AM EDT

Today, ambitious GBS leaders are expanding the way they define transformative business value. Whilst their goals are growing, the data they use to de-risk their transformation hasn’t changed much.

This webinar will spotlight how GBS leaders are fixing a bigger problem: the way they measure work.

Process Mining, SLAs, and ticketing systems only tell what happens after something goes wrong. They don’t show how to prevent problems before they start.

In this session, you’ll hear real stories from leading GBS teams using a new kind of data – called friction data – to find and fix what slows workers down and leads them to reject new digital and AI-powered GBS tools.

In this session, you’ll hear how GBS teams are using friction data to:

✔ Accelerate AI and digital tool adoption
✔ Bridge silos and unify service delivery
✔ Free up to 2 hours of productive time per worker, per day

What You’ll Learn:

• Why friction data is a leading indicator for successful digital and AI adoption
• How to apply a proven framework to proactively measure day-to-day friction
• How a unified friction data model creates better GBS experiences across HR, Finance, Procurement, and IT

Speakers

Christophe Martel
CEO and Co-Founder, FOUNT Global

Christophe Martel is the co-founder and CEO of FOUNT, a SaaS platform that helps companies identify and remove work friction. He has 30 years of experience helping organizations improve the way their people work. He was formerly Chief Human Resources Officer at talent management and employee experience consulting firm CEB, which sold to Gartner for $2.7 billion in 2017.

Stephanie Denino
Director of Applied EX practice, TI People

Stephanie Denino is the Director of Applied EX practice at TI People – an employee experience consultancy (EX). Stephanie works with leaders who are eager to shape and apply the practices that will allow them to systemically improve experiences for and with their people.

Lucy Hughes
Senior Vice President, Head Global HR Operations and Shared Services, PepsiCo

Lucy Hughes is a strategic HR executive at PepsiCo with deep expertise in HR services, systems, and global shared services. She brings extensive experience in talent management, organizational development, and transformation, consistently leading complex, outcome-driven projects. Known for driving sustainable performance and large-scale change, Lucy excels in identifying key challenges and delivering impactful, results-focused solutions.

REGISTER

Enterprise AI spend is expected to increase 75% in 2026, per new a16z research. At the same time, enterprise leaders are resistant to outcome-based pricing models because of a “lack of clear, measurable outcomes” tied to the tech.

In other words: enterprises are spending more on AI but still don’t know how to make it deliver ROI.

That’s because nearly every AI deployment – and industry analysis, for that matter – ignores the problem of friction.

What is friction? It’s any person, process, or technology that prevents people from doing their work.

And it’s a huge reason why AI projects don’t deliver as promised in the business case. That’s because AI is a bottom-up technology: it depends on individual users implementing an AI tool day after day in task after task.

But if a tool isn’t easy to use, they won’t use it. And there goes your investment.

Friction is more pervasive than most enterprise leaders realize:

• 87% of employees report friction from trapped resources
• 50% report overwhelmed teams as the cause
• 48% are stymied by rigid processes

Bottom line: if you’re investing in AI without also measuring friction, you likely won’t see the ROI promised by the business case. Not sure how to measure friction? Read on.

🎙️ Now live: SSON podcast with Christophe Martel, CEO of FOUNT Global – on why transformation stalls when friction goes unmeasured, and how leaders can change that. 🔗 https://www.ssonetwork.com/intelligent-automation/podcasts/friction-data-blocking-ai-transformation

FOUNT in Action: How to Weed Out Friction in the Enterprise

Use case 1: Gamma Financial drives AI chatbot adoption, slashes $5.4 million per year in friction

Gamma Financial, a large financial services organization, introduced an AI chatbot to help its IT team code more efficiently. A few months after rollout, however, overall productivity for the team hadn’t budged.

The company worked with FOUNT to identify friction sources for the team and discovered that the documentation underpinning the codebase was subpar. This meant the AI chatbot, trained on that dataset, was not as helpful as it could be – which meant the junior developers who could have most benefitted from AI assistance weren’t using the bot.

With a clear sense of the main source of friction, Gamma was able to update documentation, improve chatbot adoption, and ultimately slash $5.4 million per year of wasted IT team hours.

Use case 2: A CPG giant tweaks its AI-powered ordering system to cut product waste

A CPG giant launched an AI-powered ordering system to streamline relationships with vendors. But early on, vendors were frustrated: they started getting too much of some products and too little of others. Product was expiring and they were missing out on potential sales.

Tensions were rising among valued vendor partners, so the company decided to look for friction.

They discovered that the AI system didn’t account for certain demand nuances, like when a product was popular due to temporary circumstances but wouldn’t be in the future. The solution: update the AI system to include more parameters so it could accurately reflect vendors’ needs.

The updated system reduced product waste while also ensuring vendors had what they needed in stores.

Use Case 3: Global enterprise accelerates Agile transformation

A global enterprise was shifting from Waterfall to Agile product development. As part of the change, it introduced a new Product Owner (PO) role and competency framework across five business units. Some POs were hired externally; others transitioned internally – bringing diverse backgrounds and interpretations of the role.

To support the transition and ensure teams could work effectively, the company partnered with FOUNT to identify sources of friction impacting the PO role.

FOUNT’s analysis surfaced two key blockers:

• Leadership Misalignment – Business, Technical, and Product leaders lacked alignment on priorities, complicating decision-making for POs.
• Role Clarity Gaps – Expectations for the PO role varied across units, and POs were often stretched thin or pulled into responsibilities outside their remit.

By addressing these friction points, the company implemented targeted improvements, resulting in a 26% improvement in Feature Time to Release, signaling a smoother transition to Agile and better alignment across teams.

Most Recent Blog Posts:

Breaking the False Tradeoff in GBS: Efficiency vs. Experience

Too many GBS teams are stuck in a false tradeoff: efficiency vs. experience. But modern leaders are measuring friction and using experience data to drive productivity, reduce costs, and transform service quality. This piece explores an emerging framework for GBS leaders.

🤔Dig into this emerging line of thinking

What We Are Reading:

Recalculating the Costs and Benefits of Gen AI

In this HBR article, associate professor of organizational behavior Mark Mortensen suggests considering not just the potential benefits of generative AI (increased speed and productivity, for example) but also its costs (e.g., decreased learning or skill development). It’s a thoughtful argument for how organizations can be more deliberate about where to use gen AI – and where to invest in developing human talent.

🤖Get the full story

New from Deloitte: 69% of Tech Leaders Expect Hiring to Increase Thanks to Gen AI

Deloitte’s latest Tech Exec Survey found that, contrary to buzzy media headlines, most IT executives expect to expand hiring because of generative AI. The catch: the workforce may not have the skills these execs are seeking (but 58% of IT leaders have investment plans to build those skills). The full report includes insights on pivoting to being an AI-first organization.

👩💻Get the full story

Upcoming webinar (Last Reminder to Register!):

Join Christophe Martel, CEO of FOUNT Global, Inc. , Lucy Hughes, VP Head Global HR Operations and Shared Services of PepsiCo, and Stephanie Denino, Manang Director of TI People , as they spotlight how GBS leaders are fixing a bigger problem: the way work gets measured. Lucy will share real stories of how friction data is helping… Register here!

New Event Alert!

Volker Jacobs, co-founder of FOUNT Global, Inc. , will be presenting key findings from the research “AI-POWERED HR – How to Evolve the HR Operating Model for the AI Era” (Read about Research here) at an upcoming Executive Networks Webinar on July 10th. The webinar will explore how AI is transforming HR operating models and what steps organizations can take to stay ahead.

Join Volker at the webinar: Register here!

Here are the links to the sources mentioned:

1. a16z Research
2. Forrester
3. Deloitte
4. HBR – Recalculating the Costs and Benefits of Gen AI
5. Deloitte Tech Executive Survey

‍

‍

Guest Post by Isabella Kosch, freelance business consultant, ex-Head of GBS Service Management at SWAROVSKI, regular contributor to SSON.

Not all friction makes noise. Some of it hides in plain sight, camouflaged as efficiency.

After two decades in transformation, I’ve learned this: you can meet every target and still frustrate the people you’re supposed to serve. If you’re not asking how it feels for the user, you’re not managing flow. You’re managing optics.

Your GBS might be on time, under budget, and hitting every SLA. But if people are confused, waiting, or bypassing your systems, it’s not working.

Here are three signs your GBS is silently slowing everyone down:

1. Your help portal is built for the GBS team. Not for the user.

The portal is technically complete. Every form has been uploaded. Every process has a defined SLA. The chatbot knows its lines.

But users still bounce. They give up and ask around. Or worse, they go back to email.

Why? Because it reflects how you think about services, not how users search, ask, or decide.

One client showed me their immaculate portal. But the data told another story: users were abandoning forms midway, returning to email, or phoning their old local contacts.

When knowledge bases are structured by GBS ownership instead of user intent, employees end up bouncing from link to link.

Want to fix it? Start mapping what users are actually trying to do. Not what you’re trying to offer.

Forget the service catalog. Focus on user missions. What are the top three things people need? Build around that.

A portal that makes sense to you isn’t the same as one that works for them.

2. You standardized everything and now no one trusts it

Standardization is good. Until it isn’t.

When local teams feel unseen, they create their own fixes. Shadow trackers. Parallel approvals. Unofficial escalation paths.

I’ve seen this movie. A global onboarding workflow looks fine on paper. But in one region, people still organize their own welcome meetings. In another, HR adds three extra layers of compliance. In a third, managers stop using the tool entirely.

The resistance isn’t loud. But it’s there. And it costs more than you think.

In trying to protect scalability, you lose relevance.

In trying to enforce structure, you erode trust.

If local teams feel like your processes don’t see them, they’ll resist. Not loudly, but subtly. Delays. Pushbacks. Shadow fixes.

Instead of defending your global blueprint, ask where flexibility would actually increase trust.

Standard doesn’t mean identical. It means stable enough to flex where it matters.

3. Your dashboard says green. But your users are red.

There’s always a dashboard. And it’s always green.

But here’s what you’re not tracking:

• How often users follow up because they’re unsure
• How much time they waste re-explaining their issue
• How many quietly avoid your systems for important tasks

This is what I call the “false green.” It’s what happens when KPIs tell one story, but lived experience tells another.

I’ve seen this play out in payroll, IT, procurement – you name it. The process works. But trust is broken. And once that happens, it doesn’t matter how fast or cheap you are.

If your GBS isn’t trusted, it won’t be used. And if it’s not used, it can’t deliver value.

You don’t need to throw away your dashboards. You need to supplement them with qualitative feedback and frontline diagnostics. Friction often hides in escalation loops, repeated follow-ups, or in the silent choice to “just fix it ourselves.” Friction often lives in the gaps between your swimlanes.

If you want flow, focus less on control and more on credibility.

Fix what’s quietly broken. Rethink what “standard” really means. And design for how people actually behave, not how your process chart says they should.

Because process doesn’t equal progress. And operations don’t equal experience.

Prioritize experience.

Is your GBS trusted – or tolerated?