Automation is quickly becoming one of the most essential tools for driving operational efficiency at leading companies across the world. With all the hype around robotic process automation (RPA), artificial intelligence (AI), and machine learning, industry leaders are pushing to implement automation across all of their business units. However, they frequently run into difficulties when trying to decide which processes are good candidates for automation, and which initiatives should be prioritized? This is especially important if this is the beginning of a larger digital transformation initiative.
In this report, we’ll share some insights and advice for implementing automation that can scale. When approaching automation, an assessment should be conducted to compare processes across a number of key automation readiness characteristics. Companies should use an approach that focuses on achieving the right balance of methodical planning with realizing quick wins for framing up their automation roadmap and prioritizing potential initiatives based on a high-level cost-benefit analysis of taking on such endeavors. Laying a solid foundation at the beginning is crucial to enabling a successful pilot and ultimately enterprise roll out.
Step 1: Gain organization buy-in
Successful Automation initiatives start with a shared vision, a willingness for cross-team collaboration and the freedom to work through trial and error. The foundation of implementing successful business process automation lies in choosing the correct processes to automate and selecting the right tools to achieve the desired outcome. Ask Why? Due enough due diligence so you understand what you are getting into. Need to think through organizational challenges, internal resistance etc. Need to baseline with current team. Education critical. Processes first need to be identified in order to conduct the assessment.
Step 2: Assess Feasibility
When starting the automation journey, processes should meet some basic criteria before being considered. Fitting an automation solution on a suboptimal process will not yield the intended results.
Is there a sufficient volume of work that will justify the cost? Some processes might be a great fit for automation but because of the frequency/volume, will not have a sufficient impact or cost saving to justify the upfront and ongoing investment.
Will there be changes to the process in the short term? Processes that use systems which are anticipating changes in the short term should be ruled out to prevent rework.
How many decision points are required? Sophisticated processes that have multiple decision requirements may need a more complex solution (i.e. Artificial Intelligence) and typically should be deferred to a later phase of the rollout.
Is the data structured? While automation can be achieved with unstructured data by combining AI with RPA (e.g., OCR solution), picking processes with structured data offers quicker wins and less complexity.
As a result of these considerations, Finance and Accounting is a great place to begin an organizations automation journey. However, there are multiple use cases across all primary business functions as Figure 3 illustrates.
Step 3: Analyze and Score
To do this, process analysts should:
Collect current-state system architecture
Identify all available tools and documentation for each process
Determine data sources, highlighting structured vs. unstructured
Count the number of decision points that might be needed
Calculate aggregated potential time savings available
Once the team eliminates poorly fit processes from the automation initiative, the remaining options should be scored against a set of characteristics inherent to each process.
The output of this assessment is the feasibility score, representing how easily automation solutions would be to implement for each process, and is the first major factor in the final prioritization.
Process automation professionals have varying opinions about characteristics affecting automation feasibility, but the following are sure to provide a balanced and thorough assessment of each process.
Step 4: Prioritize and Select
There are many factors to consider, and business leaders should align with what their desired outcome would look like and prioritize accordingly. These potential benefits should be ranked and assigned a relative weighting against key business drivers. This will provide a tailored impact score that aligns with the goals of each organization and assists in comparing potential ROI from various initiatives. The ROI calculation should try to include all qualitative and quantitative benefits. Initially at a high level, however once the top processes are selected, a deeper analysis should be completed.
Once the ROI is calculated across each process can be ranked and plotted on a prioritization matrix. This makes it easy to identify quick wins and which processes will require a more significant investment to automate. Upon completing of the prioritization model, a detailed business case can be built to secure buy-in from senior leadership to pursue the automation journey. Multiple solutions should be compared when determining best fit and alignment with specific use cases.
Step 5: Communicate and Scale
Once it is decided to move forward, a team should be identified to lead the initiative. We recommend the establishment a Center of Excellence (CoE) which would be comprised of a small, empowered team that will lead the initial pilot rollout and establish an organizational playbook. This team should govern the full lifecycle because they provide a central point of contact, have built expertise in process selection and estimating ROI and will have insights that can be incorporated in future implementations. This CoE can expand as additional processes are automated. An Agile methodology is recommended as this enhanced flexibility, increases velocity and creates a sustainable capability.
Structure of a Center of Excellence
Steering Committee: Responsible for communicating business drivers, setting budgets, prioritizing automation initiatives, and providing resources to drive project success.
Scrum Master: Responsible for overseeing one or multiple process improvement initiatives and communicating progress, roadblocks, and resourcing needs to stakeholders. Great scrum masters are organizational engineers who constantly compare outcomes to goals and look to delegate details.
Product Owner: Provides guidance to the development team during bot development and implementation to assure all process steps are included in the solution.
SME(s): Liaises with the development team and project manager to assure any required process changes are made to enable RPA solutions to work effectively. In the case of Automation, this could be a process engineer specialist.