Itai Liptz: How Organizations Can Bridge The Gap Between Technology And Human Behavior

Organizations often assume that new systems will correct old problems. The reasoning seems sound: if a tool has sharper features and a cleaner interface, the team should work more smoothly.

Yet that hope rarely plays out. Employees often meet new platforms with hesitation, and not because the software is flawed. They’re trying to protect routines that help them manage pressure and keep work predictable.

Observing industry conversations from leaders such as Itai Liptz helps illustrate how often people describe this tension in real work settings.

“Much of the friction comes from the mismatch between how people think and how tools are designed,” says Liptz. “Many employees build rhythms and unwritten rules that keep their day moving.

When a new platform interrupts those habits, they feel unsettled and sometimes defensive.” This isn’t a refusal to learn, he adds, but more of a reaction to uncertainty about whether the new process will slow them down at moments when time already feels tight.

Leaders sometimes overlook how strong those routines are. They may think improved features will naturally encourage adoption. But people rarely choose tools based only on capability.

They choose tools that feel safe, familiar, and supportive of their judgment. When a platform disrupts that comfort, even without intention, behavior shifts back to older methods.

Recognizing these tendencies early makes technology change easier. Tools that respect daily patterns have a better chance of becoming part of regular work. Tools that expect people to abandon their instincts tend to sit unused, regardless of how advanced they are.

Start With What People Actually Do, Not The Process Maps

Many organizations lean on process maps created long before work shifted. Those documents often reflect planned steps instead of lived ones.

If a new system is layered on top of those idealized paths, it won’t match how people actually work. The disconnect becomes clear the moment the tool requires actions that feel unnatural.

“Observing real behavior gives a more accurate picture,” says Liptz. “Someone might record details in a notebook because it helps them think. Another person might keep personal templates to avoid searching through a cluttered folder.”

These habits occur more often than leaders realize, he says, especially under time pressure. A telling data point comes from a recent review showing that 76 percent of data analysts still rely on spreadsheets, according to Techzine Global. That level of reliance shows how strongly people cling to methods that feel predictable.

It’s common to find team members who still print materials or use older software because official tools feel too rigid. Instead of pushing back on these habits, leaders can treat them as signals. These patterns reveal gaps that a new system should address. When designers acknowledge them, adoption becomes smoother because people see their reality reflected in the final product.

A practical approach is simple observation. Spend time with teams and ask them to walk through their actual steps. Look closely at the informal shortcuts they rely on. A tool designed with those insights in mind will feel more natural and less like a mandate.

Itai Liptz: Simplify The Tech Stack To Reduce Confusion

Technology stacks often grow without a long-term plan. A system is added to solve one problem, then another is introduced to fix a different issue. Over time, the collection becomes unwieldy. People jump between platforms, lose track of where tasks belong, and repeat work because they can’t recall which tool holds the right information.

This pattern becomes even more visible as organizations add automation platforms. A recent report notes that about 76 percent of companies use some form of marketing automation, according to Cazoomi. When new tools keep entering the picture, overlap becomes hard to avoid.

“Cleaning up the environment helps everyone,” says Liptz. “When leaders review the stack, they often find redundancies that no one noticed.” Removing those creates a more predictable workflow. People feel less overwhelmed when they can complete tasks within fewer systems. Even small reductions in tool switching can ease mental strain.

Simplification supports onboarding as well. New employees don’t have to spend weeks learning a maze of platforms. They can focus on understanding the actual work instead of memorizing which software contains which steps. This creates a stronger sense of stability during an already demanding time.

An organization that trims its toolkit also sends a clear message. It shows that leadership values clarity over volume. That message encourages employees to take new tools seriously because they see that the goal is to improve work, not complicate it.

Design Workflows That Reduce Friction

Tools often fail because they introduce small obstacles. A confusing field label or an extra approval step can interrupt someone’s concentration. These disruptions seem minor to designers, yet employees experience them repeatedly. After enough interruptions, people look for ways around the tool.

Reducing friction starts with watching where users slow down. Someone might hesitate before clicking a button because they’re unsure of the outcome. Another person might open several tabs to complete one task. These small pauses reveal where the design needs adjustment. They’re often more informative than survey feedback.

Adding features isn’t always helpful. Extra options can make a tool feel heavy. Most employees want systems that guide them without overwhelming them. A simpler workflow often produces better results because it mirrors how people naturally move through information.

When friction is removed, confidence grows. People begin trusting the system because it feels intuitive. The work becomes less about figuring out the tool and more about completing tasks.

Motivation, Identity, and Social Dynamics Shape Adoption

People gravitate toward tools that make them feel capable. When a system supports their judgment, they adopt it more readily. When it introduces doubt or confusion, they avoid it. These emotional responses often overshadow the tool’s actual capabilities.

Identity plays a meaningful part in this. Someone who is known for reliable work may worry that a new system will disrupt how others view their accuracy. Another employee might feel attached to long-standing methods that have become part of their reputation.

These pressures influence how people respond to change. A new review found that between 52 and 56 percent of employees across major age groups want more influence over how workplace technology is chosen, according to Gallup. That desire for involvement shows how closely people tie technology to their sense of control.

Recognition also shapes adoption. When people feel seen during transitions, they’re more willing to learn. Brief acknowledgments can ease uncertainty during the early stages of use. These moments help employees feel supported rather than evaluated.

Social groups influence adoption in powerful ways. Teams with strong internal trust often move together. If a respected colleague embraces a tool, others follow. If that person avoids it, adoption slows. Understanding these informal networks helps leaders plan rollouts that match how influence travels through an organization.

Make Change Social, Not Instructional

Traditional training sessions cover a lot of information, but rarely stick. Employees return to their desks and struggle to apply what they heard. The gap between training and real work becomes obvious right away.

Shorter sessions that focus on immediate tasks tend to work better. When people practice the workflow while learning it, the information stays with them. Smaller groups also lower the pressure. Participants feel more comfortable asking questions, which leads to a stronger understanding.

Colleagues have a strong effect on adoption. When someone sees a peer using a tool confidently, they’re more likely to try it themselves. This isn’t imitation for its own sake. It’s a sign of trust between people who face similar challenges.

Informal communities can help the transition feel smoother. Small groups that share tips or troubleshoot together create steady progress. When employees learn as a group, the tool becomes part of a shared routine instead of a solo obligation.

The Feedback Loop Problem

Organizations often collect feedback during rollout but stop once the tool is in place. This leaves users without a path to express concerns. Problems accumulate quietly and lead to frustration. Over time, people adapt the tool in ways that reduce its value.

Feedback doesn’t need to be complex. A quick form or a short conversation can uncover meaningful insights. These small touchpoints help leaders stay aware of real challenges. They also prevent minor issues from growing.

Some employees hesitate to speak up because they worry about appearing uninformed. Others assume their problem won’t matter. Leaders who pay attention to subtle cues, such as repeated hesitation at a particular step, gain insight into issues that might never be shared directly.

“Closing the loop builds trust,” says Liptz. “When employees see their input reflected in actual changes, they feel encouraged to speak up again. This helps the tool stay relevant as work evolves.”

Introduce Automation Carefully

Automation can help when it removes repetitive tasks. Yet the idea of automation can create tension. Employees may wonder whether it will reduce their responsibilities or affect their control over their work. These reactions reflect concern about stability rather than resistance to innovation.

Focusing automation on predictable tasks creates smoother experiences. When the tool handles background work, employees gain more time for judgment and problem-solving. This helps them see automation as a support rather than a threat.

Issues arise when automation behaves unpredictably. If the system makes changes without explanation, trust weakens. Employees may feel the need to double-check automated tasks, which adds more work.

Clear communication helps ease these worries. When people understand what the automation does and why, they feel more comfortable trusting it. Introducing changes gradually helps employees adjust without feeling rushed.

Don’t Ignore Edge Cases

Systems designed for the average user often miss important groups. Some employees work from mobile devices. Others interact with the system only occasionally and need extra clarity. High-pressure roles may require faster access to information. When these needs aren’t supported, the system feels unreliable.

Supporting edge cases doesn’t require major redesigns. Clearer messages, simpler layouts, or task-specific screens can make the system much easier to use. These improvements benefit everyone, not only the outliers.

When a tool fails for a small group, frustration often spreads. Someone shares a negative experience, and others become hesitant to adopt the tool. Addressing edge cases early helps avoid this.

A system that supports different kinds of users feels more reliable. People feel confident that it will work during unusual or stressful situations.

Leadership’s Real Role

Employees pay close attention to leadership during technology changes. If leaders use the tools themselves, adoption improves. If they continue relying on older methods, employees assume the new system isn’t necessary.

Leaders don’t need to be experts. They only need to engage consistently. When they ask questions or experiment with features, they show that learning is normal. This helps reduce the pressure employees may feel.

Tone makes a difference. Leaders who respond with patience create an environment where employees can speak openly. This helps problems surface sooner and makes them easier to solve.

When leadership treats technology as a shared effort, adoption feels more collaborative. Employees feel supported rather than directed, which helps the new system find a place in daily work.

Technology Only Works When It Respects Human Behavior

Technology becomes effective when it fits the way people think and work. Tools that align with natural habits support productivity. Tools that conflict with those habits create friction, even if they’re well designed.

“Understanding human behavior requires attention and flexibility,” says Liptz. “Leaders who listen and adapt find that employees accept change more willingly. Instead of forcing new methods, they shape the tools around daily reality.”

When organizations take this approach, adoption becomes steadier. People see their needs reflected in the design, which builds confidence. Over time, the system becomes reliable because it’s grounded in human behavior rather than idealized workflow models.

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