- 40% of organizations have four or more concurrent hyperautomation initiatives underway, with some organizations executing 15 projects at the same time.
- Failure typically stems from three types of mistakes — in approach, implementation and impact.
- To ensure success, prioritize automation initiatives that deliver clear, quantifiable business outcomes and for which the resources already exist within your organization.
Automation promises significant cost, quality and speed improvements, but realizing those benefits requires an action plan on the part of executive and IT leaders that accounts for common mistakes. This is especially the case now that hyperautomation is increasing and IT is managing multiple concurrent automation initiatives.
Watch now: The Executive Guide to Hyperautomation
A recent Gartner survey shows that nearly 60% of organizations are pursuing, on average, four or more concurrent hyperautomation initiatives. “Leaders must treat automation as a principle to be embraced, rather than as a project to be done and ought to be aware of common mistakes that can lead to failures,” says Nicole Sturgill, VP Analyst at Gartner.
Mistake No. 1: Falling in love with a single technology
Once an organization has purchased and implemented a specific process automation tool, such as robotic process automation (RPA), successfully, it’s natural that colleagues want to adopt it more widely. “However, the wrong approach is to drive automation from a single technology perspective. Instead, lead with the business outcome and then align the correct set of tools,” says Sturgill.
Action: Build a toolbox of technologies that provide a more comprehensive set of capabilities to align to a flexible range of business outcomes and redesign approaches.
Mistake No. 2: Believing that business can automate without IT
More and more business users believe that the adoption of RPA and low-code/no-code applications don’t require the assistance of IT. But business users may lack knowledge of how customer and data records work, for example, and there’s a risk of mishandling the information. Additionally, those applications are integrated with other systems, which require regular upgrades. When the IT team isn’t involved, changes during upgrades don’t pass through, causing failed processes.
Action: Establish and fund an automation center of excellence, much like a DevOps center of excellence, that includes individuals who collectively possess a variety of organizational skills and knowledge, such as analytical and process mapping skills, technical skills, business knowledge and IT governance experience.
Mistake No. 3: Thinking automation is always the solution
Automation may be the best long-term option for business and IT processes, but leaders cannot simply use it to cover gaps in a poorly designed process. Automation is not meant to make up for failures in systems or defer system replacement; using automation in that way simply extends the life of suboptimal legacy applications by creating savings that mask underlying inefficiencies.
Action: Evaluate the benefits and drawbacks of automation over system replacement, added functionality and integration strategy.
Mistake No. 4: Not engaging all stakeholders
Automation, by nature, has a broad impact on the enterprise, which means you should engage stakeholders from across the organization for decision making and sign off. For example, if adoption of new automation processes changes the nature of people’s roles, involve HR; changes to access rights and IDs, or server requirements must involve security or IT.
Action: Assign responsibility of stakeholder management to a specific team member within the automation center of excellence.
Mistake No. 5: Failing to devote enough time to testing
Automation technologies only work when the algorithms and rules are exactly correct. The technologies may seem easy to use, but they are unforgiving when programmed incorrectly. They can very quickly wreck business data and fail to deliver the desired business outcome.
Action: Ensure that testing examines the process from end to end and doesn’t just check automation functions and programming. Thoroughly test and audit the data integrity when running your selection of automation tools.
Mistake No. 6: Wasting effort on overly complicated processes
At times, organizations find themselves in a quagmire when automating a process. That most often happens when processes are not well-documented or understood, if the workflow is not consistent or if there are too many variants in the decision-making process. Don’t waste time and effort by failing to halt such processes promptly.
Action: Develop a set of rules or guidelines to drop processes and tasks that are ill-prepared for automation. For example, base guidelines on the number of process steps, number of integrations required or clarity of the existing process.
Mistake No. 7: Treating automation as simple task replication
Using automation tools to copy exactly what is being done manually misses a critical benefit of automation — improving the end-to-end process to create a better customer and employee experience. If process redesign is not part of the automation process, you may use the wrong automation tool and lose the business outcome you hope to achieve.
Action: When looking to deploy new process automation tools, first fully evaluate and apply a process reengineering methodology, such as Six Sigma or design thinking, to ensure automation can deliver outcomes in the best possible way.
Mistake No. 8: Failing to monitor in postproduction
Just like any system implementation, automation projects will require extensive “hands-on” IT involvement after implementation. For example, for RPA rollouts, establish continuous assessment, monitoring and regular quality checks to ensure that robots have been scripted correctly and are continuing to work as expected. This avoids huge data cleanup tasks.
Action: Overall, establish postproduction procedures to enable operations managers to continuously monitor and audit the automation tools.
Learn more: Everything You Need to Know About Data and Analytics
Mistake No. 9: Using the wrong metrics to measure success
It’s typical to measure technology applications and tools to ensure that they are working as designed. However, this doesn’t reflect whether or not the project is successful. Measuring the impact on processes and the enterprise as a whole is key to the success of automation.
Action: Focus the measurement of automation success on KPIs that specifically quantify the business outcome the automation deployment is supposed to achieve.
While it’s critical to focus on how to adopt and scale automation, it is equally important to consider the impact on employees, especially if roles are eliminated or reimagined.
Action: Anticipate how employees may react and make sure your automation teams actively communicate how they will implement change, involving change management and HR, where needed.