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The employee experience (EX), it’s a hot topic in today’s business world, but what exactly is it? And how do companies go about improving it?

On this episode of Paychex PULSE, an HR Podcast, CEO and Founder of FOUNT, Christophe Martel, talks about just that. Hear what he told host Rob Parsons about the definition of employee experience vs. employee experiences, how to take a more personalized approach, designing work for the needs of your staff, and much, much more.

Topics

00:19 – Introduction to Christophe Martel

00:48 – What does employee experiences (EX) mean?

04:01 – The Big, Bad State of EX research report

07:05 – How to get a more personalized approach

07:59 – Humancentricity capability

09:42 – The importance of dispersal

12:39 – The ability to measure experiences

14:10 – Designing work for the needs of the employee

16:24 – Experience as a philosophy

18:39 – Transparency of opportunity

19:48 – Upping your game to fit your employees

20:54 – Diversity and inclusion is in the eyes of employees

22:31 – Wrap up

Listen to the podcast or read the full transcript below.

Transcript_PULSE_S4E8Download

Commitment to employee experience is growing. With commitment comes expectation, and EX Leaders find themselves in a crucial performance window.

Commitment to employee experience is growing. In our recent Human Experience of Work study, 90% of employee experience Leaders indicate increased organizational intent around understanding and improving people’s experiences of work. CEO and board attention; defined employee experience roles and responsibilities; and budget allocation have been on the rise.

With commitment comes expectation, and employee experience Leaders find themselves in a crucial performance window. Employees expect consistent activity that delivers improved experience quality.

Executive stakeholders need to see quantified impact against their specific business or functional objectives. CEOs and Boards want evidence of progress quickly as proof that investments are yielding. Moreover, the world of work continues to shift and experience leaders must keep pace.

Working with the business 

One critical element to maintaining momentum in EX is to what extent EX Leaders can fully engage and work with the business. Leaders with EX responsibility will more convincingly engage business stakeholders in EX when they can point to precise improvement opportunities – with evidence. Also, talk about ROI cannot be a generic conversation. It needs to be aligned to business leaders’ specific objectives and value conveyed through their business KPIs.

Yet only 24% of organizations surveyed report having the requisite qualitative and quantitative experience data in place to inform experience decision-making with business partners. Many studies, for example, have explored the ROI of internal customer experience and its link to external customer experience and resulting revenue growth, but the ROI exploration often stops there. 90% of organizations believe calculating the ROI of internal customer experience and its linkage to outcomes for their organization is essential, but they have not yet reached this stage.

Meeting executives where they are

Purposeful dialogue starts with meeting executives “where they are” by showing EX’s relevance to their business objectives. It should be defined by value delivered to people and business in the form of observable, measurable outcomes. The ‘Business Value tree’ pictured, for example, shows how one customer facing organization visualized how experience drives business results. They used this approach to support more effective conversations specifically with senior customer facing leaders.

Essential inputs

It is important to note that one ‘business value story’ does not fit the needs of all leaders, nor fully conveys the potential scope of impact. As with employees, appropriate context is essential to understand needs. For example, a functional executive serving internal customers such as a CIO will work with a partially different set of KPIs from a customer-facing leader referenced above, such as UX, internal customer satisfaction, or cost.

In addition, without access to the right (first-hand, interaction level) data, people’s experience expectations of the business will not be fully understood at scale. EX teams need new, experience-centric data inputs to pinpoint opportunities for meaningful experience improvement that are truly relevant to people and business outcomes.

Through our Experience Intelligence solutions, we continue to support EX Leaders and their teams on the activities and capabilities required to drive EX impact — and connect it back to business objectives. We invite you to join in our latest research efforts by participating in our short survey.

Our latest research aims to identify the activities and capabilities EX teams need to better demonstrate business impact.

This survey will result in a robust understanding of how well EX teams demonstrate business impact today, so that you can compare your team’s approach to leading examples around the world. It will also provide a set of clear recommendations and guidance for demonstrating business impact to business leaders, in order to gain long-term engagement and investment.

Participate in the research and be among the first to view the findings and access detailed recommendations for demonstrating business value to business leaders, in order to gain long-term engagement and investment.

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The Challenge

Gamma Financial, a Fortune 500 financial services company with 1,000 developers, faced the following challenges in its digital transformation:

• Low Adoption of GenAI Tools: While AI chatbots and code assistants were implemented to optimize workflows, adoption rates were uneven and lower than expected.
• Friction in Daily Tasks: Developers struggled with two key areas:
  1. Finding Answers About the Codebase: Developers spent 4+ hours weekly searching for accurate information, hindered by an outdated Developer Portal and underutilized AI Chatbot.
  2. Reviewing Pull Requests: This process was time-intensive, with junior developers heavily relying on senior team members.
• Proving ROI: Leadership needed clear data on the ROI of GenAI tools to justify their continued investment.

The Solution

Gamma Financial partnered with FOUNT to pinpoint and address the sources of work friction. The solution involved:

1. Targeted Surveys: FOUNT deployed micro-surveys among 450 developers to measure satisfaction, effort, and time spent on key tasks involving GenAI tools.
2. Dashboard Analysis: FOUNT’s comprehensive dashboard identified the most critical friction points, such as challenges with the AI Chatbot and Developer Portal.
3. Actionable Improvements: Key steps included:
   • Automating code documentation updates to improve the Developer Portal and AI Chatbot usability.
   • Encouraging the use of AI Code Assistants for static code analysis to streamline pull request reviews.

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The Results

Gamma Financial’s targeted approach delivered the following outcomes:

• $5.4M in Annual Savings: Developers saved an average of 3 hours per week, translating to 120,000 hours annually across 1,000 developers.
• Improved Tool Satisfaction:
  • Developer Portal: Satisfaction scores increased from 33% to 60%.
  • AI Chatbot: Satisfaction scores rose from 42% to 65%.
• Enhanced Workflow Satisfaction:
  • Finding answers about the codebase: Satisfaction improved from 55% to 72%.
  • Reviewing pull requests: Satisfaction increased from 63% to 71%.

These improvements not only saved costs but also empowered developers to maximize the potential of GenAI tools, strengthening Gamma’s digital transformation initiatives.

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The Challenge

A national retail logistics group faced an alarming 110% attrition rate among first-year employees, particularly affecting 800 order selectors critical to warehouse operations. This led to:

• Increased waste and error rates.
• Higher overtime and onboarding costs.
• Lost revenue and capacity exceeding $5 million annually.

Despite efforts such as pay raises, enhanced benefits, and better training, traditional solutions failed to address the root causes of employee dissatisfaction and turnover.

The Solution

Partnering with FOUNT, the organization identified and addressed key sources of work friction impacting employee retention:

1. Pinpointing Friction Moments:
   • Key activities analyzed included navigating the warehouse, learning job tasks, discussing pay, coordinating shift plans, and taking breaks.
   • Touchpoints such as supervisor interactions and tool usage (e.g., pallet jacks) were examined for inefficiencies.
2. Data-Driven Interventions:
   • Improved Communication Strategy: Weekly video updates and shift coaches for new hires reduced misunderstandings and improved support.
   • Enhanced Training: A 12-week, app-guided onboarding journey was introduced, ensuring consistency and empowering senior employees to mentor new hires.
   • Reorganized Warehouse Layout: Simplified navigation through re-slotting improved productivity and reduced confusion for new hires.
   • Staffing Adjustments: Increased headcount eased workloads and improved work-life balance for employees, fostering collaboration and reducing burnout.

The Results

After just four months, these targeted actions led to:

• 35% Reduction in Attrition: Average tenure for order selectors increased by eight months.
• $4M Annual Savings: Cost reductions stemmed from improved retention and operational efficiencies.
• 20% Productivity Increase in Year 1: Enhanced workflows and satisfaction boosted overall performance.
• Improved Work Environment: Balanced workloads and better communication created a more sustainable and engaged workforce.

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Fill out the form below to explore how this retail logistics group transformed operations, reduced attrition, and saved $4M annually with actionable insights from FOUNT.

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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.

Listen to industry experts from FOUNT Global, TI People, and PepsiCo as they discuss: 

• Why Friction Data is the leading indicator of AI adoption and the gateway to de-risk digital GBS transformation.
• Understanding the methodology and framework to proactively measure friction in the day-to-day work.
• Learning the power of a unified data model to deliver superior cross-silo experiences to GBS customers.

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KEY TAKEAWAYS

• Organizations may have hundreds of potential AI use cases. But they don’t know which to choose, mostly because they don’t have any solid data to guide them.
• As a user-driven technology, the success or failure of AI depends largely on whether employees choose to adopt the tool – something they’ll only do if it makes their work easier.
• The key with AI is to pinpoint where it is most likely to help smooth out problem areas, remove obstacles, and accelerate work for employees. Work friction data is the most effective way to discover where those areas and obstacles lie.

The AI dilemma is becoming clear. While 79 percent of leaders say they need to adopt AI to stay competitive, 59 percent aren’t sure how to measure its impact. And those questions tend to stall plans and projects – 41 percent of CFOs say they struggle to prioritize AI amid uncertainty. 

It’s a complication that plagues AI adoption for many organizations: they have hundreds of potential AI use cases but don’t know which to choose. Why? Because they don’t have any solid data to guide them.

In reality,the data you need already exists within your organization. It’s called work friction data and it can help you identify the most attractive opportunities. Here’s a look at how.

Rethink How You Deploy AI Tools

Most digital transformations tend to take a classic top-down approach. The organization rolls out a new technology or solution and expects everyone to use it. In most cases, everyone does, often because they have no choice.

And so it goes for many organizations looking to deploy AI tools. Leaders prioritize their AI projects based on which areas of the business are most important to the bottom line, then embark on a traditional top-down implementation. They roll out AI tools in those chosen areas, expecting employees to use them and hoping for productivity gains.

For example, let’s say a firm determines that its IT team and sales team are the biggest contributors to the bottom line. Thinking top down, it rolls out AI tools for both groups: the IT tool helps increase the pace of coding, while the sales tool automates prospect followup.

Three months in, the IT tool has been widely adopted and productivity increases are measurable. But the sales tool hasn’t budged results.

This approach to AI implementation isn’t scalable. To enjoy the benefits of AI across an organization, leaders need a way to know in advance why one AI implementation will work and another won’t. The answer lies in user data. 

Focus on User Data for a User-Driven Transformation Like AI  

Unlike many other digital transformations, AI is entirely user-driven. An AI tool that isn’t designed or deployed to make a real difference for employees is one they won’t use. This is why a traditional top-down rollout doesn’t work for AI.

To know where to deploy AI tools, you need to first understand employee pain points – the issues they’re having in their day-to-day work that you’re trying to solve. Without this information, you’ll never know which areas are most in need of AI.

In the example above, the organization took the seemingly logical approach of focusing its AI efforts on two sets of employees who do work that is important to its bottom line. But while the AI tool for the developers happened to address specific, observable work issues, the tool for the sales employees did not and so they didn’t adopt it.

Use Work Friction Data to Prioritize AI Projects

The purpose of AI is to smooth out problem areas, remove obstacles, and accelerate work for employees. In other words, to remove work friction. That’s why you can’t know the right places to use AI if you don’t know where work friction exists.

Many organizations try to identify employee pain points with traditional data-gathering methods, such as surveys, focus groups, and NPS evaluations. But these methods don’t dig deep enough and can’t be easily scaled.

Work friction data, on the other hand, measures hyper-specific moments of work – like retrieving an answer from the codebase or updating information in a prospect’s file – to find friction points. And it does this in a scalable way so company leaders can see where the biggest employee pain points are.

By identifying specific employee pain points, work friction data can help identify the most promising AI use cases. As an AI rollout gets underway, work friction data can also help determine where to make tweaks or adjustments if things are not going according to plan.

In the above example, work friction data could have provided insight on things that were bogging down the firm’s general business employees, such as too much time switching between email and a CRM. With this more granular information, the firm could have opted for an AI tool that specifically helped with integrating the two systems – something these employees would likely welcome.

Don’t Leave Your AI Investments to Chance

Studies have shown that Gen AI projects can boost productivity by anywhere from 13.8 percent to 126 percent. Those are the kinds of numbers that will make any organization sit up and take notice. But even if you know your organization needs to somehow use AI, you may not know exactly where to start.

Like any other big decision, the more information you have to work with, the better your odds of success. And with a user-driven technology like AI, that means having good user data.

By getting to the heart of your employees’ needs and pain points, work friction data can help you determine where and how to best deploy AI. And with that finer-tuned sense of direction, you’ll be much more likely to see the productivity gains and ROI you’re hoping for.

Trying to decide which AI projects are right for your organization? We can help.

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Alpha Healthcare (pseudonym for Fortune100 Health Insurance Company) had an early turnover problem in its 8,000-employee service center organization, with a 6-month attrition rate over 30%.

Fill out the form below to download a free copy of this comprehensive study and discover how a multi- billion-dollar-company addressed work friction and reclaimed $13.4 million in savings.

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Key Findings from “Quick Quits” at Alpha Healthcare Case Study

The “Quick Quits” at Alpha Healthcare Case Study explores how Alpha and FOUNT collaborated to pinpoint and address the specific moments causing employee dissatisfaction and departure. Through FOUNT’s Saas product, they identified key areas of friction, particularly around career progression conversations and handling complex customer issues.

Top priorities

1. Identifying Moments of Friction
2. Improving Career Conversations
3. Resolving Complex Customer Issues
4. Monitoring and Adjusting Strategies

Top challenges

1. High Early Turnover Rates
2. Complex and Emotionally Charged Work
3. Ineffective Traditional Interventions
4. Access to Support and Resources

Alpha Healthcare’s journey is a testament to the impact of strategic, data-driven interventions in tackling employee turnover. The success of their initiatives not only improved their attrition rates but also paved the way for a broader application of friction management across the organization.

ABOUT THE RESEARCH

The “Quick Quits at Alpha Healthcare” study aimed to tackle the high turnover rates among call center agents at a Fortune 100 health insurance company, referred to here as Alpha Healthcare. Facing a 30% attrition rate within six months, the company partnered with FOUNT, a work friction management platform, to identify and address the underlying causes of employee dissatisfaction. The research focused on analyzing employee experiences to pinpoint specific moments of work friction, employing surveys among 400 call center employees to identify key areas such as career development and handling complex customer issues.

To learn more about the topic of work friction, read our white paper and recent research that exposes a massive gap between employee and employer expectations about what it takes to make work flow. When you’re ready to get started, request a demo of FOUNT.

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Download the Case Study

No organization would throw money at a major investment without plenty of good, solid data. But even companies that understand the importance of data don’t always approach their business problems with the right data.

To wit, any project, issue, or investment that centers on employees and the work they do (and let’s face it, that’s most of them) needs to take into account exactly how that work unfolds. This is where detailed work friction data – which helps uncover employee pain points and the obstacles that prevent them from doing their best work – becomes important.

But what does a work friction approach actually look like in practice? The following five use cases from FOUNT clients (some in composite or with altered details to preserve anonymity) show how having this crucial data at their disposal translated into better real-world results.

1. Accelerate AI Adoption

A large financial firm came to us for help understanding why it wasn’t seeing the expected productivity increases from some of the new AI tools it introduced to its IT division. In fact, productivity was flat, even though AI tools can often improve productivity by 66 percent for complex office tasks.

Particularly surprising: while research shows that junior employees tend to benefit the most from AI tools, this organization’s less-senior developers were actually seeing the worst productivity outcomes.

In surveying the employees working with the new chatbots and code assistants, we uncovered two key points of work friction, specifically for the junior developers. New chatbots were not able to access necessary data, and the output of new AI code assistants required manual reviews.

In short, these now-automated tasks had actually become more cumbersome and time-consuming than they were before the AI.

This work friction data helped reveal the everyday pain points of the tool – things the company would have never known without getting deeper into the weeds of the work itself. Better still, now the firm knew what to adjust with its AI tool to make it easier for its employees to use.

Those fixes ultimately helped the organization realize the productivity increases and cost savings ($5.4 million per year) it had hoped the tools would provide.

2. Fix What’s Plaguing Your Digital Transformation Project

About 70 percent of digital transformation projects fail, but most companies don’t know why. For example, one FOUNT client that had recently switched to a new CRM for its sales team was finding decent adoption rates after several months, but no corresponding uptick in productivity. While the firm could easily track adoption data, this information didn’t explain exactly how the CRM was (or wasn’t) working for its sales team or how it might be tweaked to better meet their needs.

By collecting data from sales team members with an eye toward uncovering their work friction, we were able to see that…

• Some employees didn’t like certain aspects of the new CRM and had gone back to doing key tasks such as forecasting on spreadsheets.
• Others were willing to try the forecasting function in the CRM, but because they weren’t sure how to use it they were getting bogged down, hurting their overall productivity.
• Some had gotten frustrated by the system as a whole, so they were logging in to access their contacts (which boosted adoption numbers) but not actively using the CRM for anything else.

With this more granular level of detail, the firm was able to find the “why” that adoption rates alone couldn’t explain. That is, did the problem lie in the tool itself (and, if so, what those problems were), the training, or something else that could be reconfigured? Now there was a clearer path forward for making changes.

Digital transformations are notoriously challenging. Definitive ROI metrics on a new tech tool might not be realized until months or years later. But work friction data helps diagnose in the early stages and in a scalable way where problem areas may lie, allowing you to correct course more quickly.

3. Pinpoint the Sources of Product Waste 

Product waste overruns were becoming a significant headache for one major CPG firm – particularly within its loading and shipping processes. Naturally, the company wanted to find out what was behind the problem.

The firm turned to FOUNT to see if work friction data could help uncover exactly where in the process things were going wrong. We collected data from a variety of employees in loading and shipping roles about their pain points and frustrations.

We were able to determine where these employees were encountering friction in their workdays, such as where there were inconsistencies in packing and loading, when they had to come up with an improvised workaround, and when communication between roles broke down.

With this kind of detailed data in hand, the company had a better understanding of the underlying issues and so knew exactly where to focus its efforts to fix the problem. The changes positioned the company to reduce waste by 20 percent.

4. Hold on to Your Best Employees

Employee disengagement and attrition can cost a median-size S&P 500 company between $228 million and $355 million a year in lost productivity. As an example, in one telecom company we worked with, low engagement was leading people to leave the company at an unacceptable rate. And because hiring and onboarding new employees was such a costly process, the situation was quickly becoming untenable.

We looked at current workers across a wide range of topics, and soon discovered that one significant pain point for many new entry-level hires in particular was the lack of a defined career path. Unable to get any clear parameters for advancement from their managers – and often unable to even have that conversation – many got tired of waiting and decided to leave.

By examining this kind of specific work friction data, the company was able to identify and better understand a major source of frustration that was leading good employees to leave. As a result, the organization prioritized career conversations both in its onboarding system and as an ongoing management focus.

5. Give Your Customers a Better Experience

Many of the issues these companies were dealing with not only resulted in unnecessary costs for themselves; in many cases they eventually trickled down to a worse experience for their customers:

• Product waste issues led to inefficiencies in the supply chain, leaving customers without the inventory they needed.
• A poor transition to a new CRM showed up in several awkward or disjointed sales transactions.
• High attrition led to an influx of inexperienced new hires in customer-facing roles.

Customer experience, of course, can be difficult to quantify, but there’s no question that it is both extremely visible and extremely high-impact. For example, 74 percent of people have experienced a product or service problem in the past year – and about a third of them take to social media to voice their displeasure. 

No company needs that type of negative press. By eliminating work friction, you can help keep it at bay.

Define the Problem to Determine a Solution

Work friction may seem abstract, but as these real-world use cases clearly demonstrate, it has tremendous value in several key areas. It’s the kind of data that can give companies greater insight into the pain points and obstacles their employees are encountering in their work, which in turn not only helps them define problems but points to possible solutions.

In other words, eliminating work friction can result in not only more satisfied employees and customers, but also the kind of measurable improvements in productivity, cost savings, attrition, and more that can make a big difference in any organization.

Curious about how work friction is weighing down your company’s growth? Check the latest Case Study

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Every organization struggles with work friction. It is both ubiquitous and perceived as insurmountable. For large companies with many thousands of employees, the challenge grows exponentially.

Work friction is tied not just to productivity and profit, but to many of their drivers, like employee satisfaction, engagement, well-being, burnout, retention, attraction, likelihood to recommend, and a host of other individual and business outcomes. This white paper offers a clear and comprehensive definition of work friction, broken down into its individual components.

You will learn:

• What work friction is and why it matters
• The difference and relationship between work and organizational friction
• The Top 5 questions people ask about work friction

Are you ready to reduce friction and get work flowing at your organization? Contact us to learn more or book a demo.

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Please fill out the form below to download the whitepaper.