Every organization has friction points. Some are obvious: disconnected systems, repetitive tasks, inconsistent data or project handoffs that slow work down. Others are harder to spot because they have become part of the way people work. We explored the downstream challenges of these friction points in a recent blog: Blowing Up the Friction Points in Your Enterprise Workflows.
While at Autodesk University (AU), we led conversations on eliminating these friction points. We had a checklist in our booth where people could identify the friction points plaguing their organization. Over and over we heard people ask: Is there an option for “all of the above?”
In Autodesk’s newly released 2027 State of Design & Make Report our thoughts were validated. The report reinforced an important point: organizations have significant opportunities to improve how work gets done and realizing those benefits requires more than technology adoption. It requires a deliberate approach to connecting data, processes, systems and people.
So how do organizations move beyond working around friction and start eliminating it?
1. Blow Up the Silos Between Your Systems and Data
Data is an organization's most valuable asset, but its value depends on whether people can access and use it when they need it.
When business systems operate independently, information becomes fragmented. Teams may maintain duplicate records, manually transfer data between applications or make decisions using outdated information. These workarounds consume time and introduce opportunities for error, creating organizational friction points.
Autodesk's 2027 State of Design & Make Report highlights that among organizations identified as Pacesetters, 91% connect systems through APIs, compared with 60% of other respondents. These leading organizations are also more likely to establish clear ownership of their internal data.
The takeaway is straightforward: Data connectivity and governance are not simply IT concerns. They are fundamental to how effectively an organization operates.
How to eliminate this point of friction:
• Map where critical information originates, where it needs to go and where manual intervention is required.
• Identify opportunities to integrate business systems and eliminate redundant data entry.
• Establish clear ownership, standards and governance for the information your teams depend on.
• Prioritize integrations that improve the flow of information across departments and throughout the project lifecycle.
2. Blow Up the Workarounds That Have Become Business as Usual
Every manual workaround tells a story. It may indicate that a process is outdated, two systems don't communicate, or a team lacks the information it needs to complete a task.
Over time, these workarounds become embedded in daily operations. Employees may no longer question why they have to perform the same task multiple times or manually coordinate information across teams. They simply accept the extra work as part of the job.
But those seemingly small inefficiencies add up. They can slow project delivery, increase the likelihood of errors and divert skilled employees from higher-value work.
Eliminating these bottlenecks starts with examining how work actually gets done, rather than how a process is supposed to work on paper.
How to start eliminating this friction:
• Identify repetitive tasks that consume time without adding meaningful value.
• Examine handoffs between teams to find where information is delayed, lost or recreated.
• Look for opportunities to automate routine activities and standardize repeatable processes.
• Evaluate whether existing tools are being used effectively before investing in additional technology.
Automation can make a meaningful difference, but only when it addresses a real process problem. Automating an inefficient workflow without reconsidering its design can simply help an organization do the wrong things faster.
3. Blow Up the Barriers to AI Readiness
AI is creating new opportunities across design, engineering, construction and manufacturing. It can help automate repetitive activities, make information easier to access and support faster, better-informed decisions.
The challenge is turning that potential into practical business results.
The report found that 75% of respondents plan to increase AI investment over the next three years. Yet only 40% say they are approaching or have achieved their AI goals. The report also identifies skills-related barriers as a significant challenge for organizations.
These findings point to a critical distinction: investing in AI and being ready to use it effectively are two different things.
AI depends on the quality, structure, accessibility and governance of the data behind it. If information is incomplete, inconsistent or scattered across disconnected systems, AI initiatives may struggle to deliver reliable results. And even when the technology works, employees need the skills and confidence to incorporate it into their everyday workflows.
How to start eliminating this friction:
• Assess whether your data is reliable, accessible, structured and governed appropriately for its intended use.
• Identify specific business problems where AI or automation could reduce effort or improve outcomes.
• Evaluate the systems, integrations and data access required to support those use cases.
• Prepare employees through training, practical application and ongoing support.
• Establish appropriate oversight so AI-generated outputs can be reviewed and validated.
Rather than starting with the question, "Where can we use AI?", start with "What are we trying to improve, and what needs to be in place to make that improvement possible?"
4. Blow Up the Skills and Adoption Gap
Even well-designed workflows and well-connected systems depend on people being able to use them effectively.
The Report highlights skills-related barriers as a major obstacle to digital progress. This matters because technology investments only deliver their intended value when employees understand how to apply the tools, processes and information available to them.
A new application won't automatically improve collaboration. An automated workflow won't deliver its full value if employees continue relying on the old process. And AI won't become a useful part of daily work simply because it has been made available.
Organizations need to treat adoption and workforce development as part of the solution, not as activities that happen after implementation.
How to start eliminating this friction:
• Evaluate where employees struggle with existing tools and workflows.
• Provide role-specific training tied to the tasks people perform every day.
• Document repeatable processes and capture institutional knowledge.
• Involve employees in identifying bottlenecks and evaluating potential improvements.
• Measure adoption and workflow outcomes, not just training attendance or software deployment.
When people have the knowledge, information and support they need, technology becomes easier to use and improvements are more likely to stick.
Getting Started
Eliminating friction doesn't require an organization to transform every process at once. In many cases, the most effective approach is to identify one persistent problem, understand its root cause and make a targeted improvement.
Start by asking a few questions:
• Where does work routinely slow down?
• Which processes require employees to recreate information or rely on manual workarounds?
• Where do teams lack access to the data they need?
• Which repetitive activities could be simplified or automated?
• What needs to be in place before an AI initiative can deliver meaningful value?
Once the friction points are identified, prioritize them based on their impact on productivity, quality, cost, risk or customer outcomes. Establish a baseline so you can measure whether the changes make a difference.
The right metrics will depend on the problem. They might include hours spent on manual tasks, turnaround time between project handoffs, rework rates, data errors, software adoption or the time required to retrieve critical information.
From Friction to Flow
Data must flow between systems. Processes must support the way people work. Employees need the skills to use technology effectively. And AI initiatives need a foundation that supports reliable, practical applications.
At IMAGINiT, we help organizations address these challenges through technology integration and migration, workflow automation, data management, digital transformation assessments, AI readiness and workforce development. Our focus is on understanding where friction exists and helping customers connect the systems, information and processes that enable better outcomes.
Every organization has friction. The opportunity is to stop working around it and start blowing it up.
