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. If executed poorly, automation can have negative impacts on data usage, processes, employee morale and customer satisfaction. Following the saying “forewarned is forearmed”, let’s find out 10 common automation mistakes and how to avoid them, according to Gartner.
- Falling in love with a single technology
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.
- Believing that business can automate without IT
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.
- Thinking automation is always the solution
Action: evaluate the benefits and drawbacks of automation over system replacement, added functionality and integration strategy.
- Not engaging all stakeholders
Action: assign responsibility of stakeholder management to a specific team member within the automation center of excellence.
- Failing to devote enough time to testing
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.
- Wasting effort on overly complicated processes
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.
- Treating automation as simple task replication
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.
- Failing to monitor in postproduction
Action: overall, establish postproduction procedures to enable operations managers to continuously monitor and audit the automation tools.
- Using the wrong metrics to measure success
Action: focus the measurement of automation success on KPIs that specifically quantify the business outcome the automation deployment is supposed to achieve.
- Ignoring the culture and employee impact
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.
