Operational automation refers to the use of software, workflows, and intelligent tools to automate repetitive tasks which require less manual intervention. By automating repetitive tasks, organizations can improve their ability to produce output consistently while reducing the number of employees required to meet the demands of increasing customers, orders, or requests. Automated solutions exist in many areas including but not limited to finance, customer service, logistics, IT, and the back office.
However, automation does not scale effectively when poorly designed or when poorly defined controls do not exist. Automation that is poorly defined or implemented can result in undetected errors in processes; fragile processes; and new bottlenecks that are difficult to identify.
1. Identify High-Impact Work to Automate First
The first step to successful automation is identifying repetitive, rule-based work that can be easily measured. The most suitable automation targets are:
- Repeated data entry: Moving information from one system to another.
- Standard Approvals: Routine approval processes that involve clear thresholds.
- Routine Reporting: Weekly reports to track progress and status.
- Ticket Triage: Sorting incoming requests into categories and assigning them to the appropriate person.
One effective method of determining if a task is good candidate for automation is to perform a volume and stability analysis. For example, if a process is changing weekly, then the benefits of automation may never outweigh the cost of implementation.
2. Standardize Process Prior to Adding Technology
Automation performs best when the underlying process has been standardized across all team members. When a process varies by individual, then the technology will simply mirror those variations.
To standardize a process prior to implementing automation you should:
- Map your Workflow: Create a document that defines the start of the process, the end of the process and all decision points.
- Define “Done”: Establish a single definition of what constitutes completion of the process and establish a set of acceptance criteria.
- Remove Exceptions: Eliminate special cases wherever possible.
- Define Ownership: Establish who owns the responsibility for maintaining rules and updating steps.
Short documentation of the process helps to avoid the development of tribal knowledge that could become a risk as volume increases.
3. Select the Correct Type of Automation
Depending on the level of structure in a task and how frequently systems change, there are multiple methods of achieving automation. The selection of a method should depend on how much structure exists within the task and how quickly systems will be changing.
Some common methods include:
- Workflow Automation: Creates connections between systems with triggers and approvals.
- RPA (Robot Process Automation): Simulates mouse click and keyboard entry in older applications.
- APIs and Integrations: Provides a more stable link between systems when available.
- AI-Assisted Automation: Supports tasks that are heavy on text such as sorting emails or creating responses.
Simple Rule: Use the simplest method of automation to achieve your objectives. Use complex solutions only when the simplest solution is unable to provide the desired results.
4. Manage Risk Using Monitoring and Human-in-the-Loop Checks
Automation must be treated as a part of an operational system and not a one-time project. Effective monitoring of automation provides the control needed to minimize the costs associated with expensive mistakes at scale.
Some examples of effective ways to manage risk through monitoring and human-in-the-loop checks include:
- Logging and Alerts: Monitor for failures, delays, and unexpected outputs.
- Sampling Reviews: Periodically review a sample of the automated decisions made.
- Fallback Paths: Provide a way to manually process edge cases and outages.
- Access Controls: Limit access to those who have the authority to update rules, bots, and integrations.
It is also important to track clear metrics over time such as cycle time, error rate, rework volume, and customer impact.
Summary
Successful scaling of operations with minimal headcount expansion is achievable when automation is focused on high-volume, stable tasks and is developed based on standardized workflows. Successful automation teams choose the correct tool for the job; track performance metrics; and implement robust controls to prevent small problems from developing into major failures. Automation is not a replacement for poorly defined processes. Instead, it is a disciplined combination of process design; technical execution; and continuous oversight – allowing for growth in capacity, not chaos.