Under the right circumstance, the math behind making the decision to automate a business process, like accounts payable invoice processing or sales order handling, can be done on the back of a napkin and sold to management in minutes.
Those circumstance generally involve that point in time when a company has outgrown the capacity of its existing staff to keep up with a flood of invoices, orders, emails and phone calls related to buying or selling goods or services. The simple math is whether it is cheaper and smarter to put software in place to handle data entry and document filing, or hire another person to do the job, at least until business grows enough to overwhelm them, too.
At the point, the decision is usually a no brainer. Then it comes down to which vendor to work with and which platform or applications to implement.
But it’s not always that simple. And even when it is, tracking and measuring progress and efficiency gains can make an even bigger impact when you want to target the NEXT process to improve, so your employees can do more meaningful work and you can focus more on the top line than the back office.
Beyond that simple math, here are six metrics to keep in mind before, during and after implementing an IPA solution.
Efficiency: This one is a no brainer, but it often means doing some work to measure the current state before you compare to a future state where there may already be dashboards and metrics served up for you. How long DOES it take to process an invoice, start to finish, today? Then compare to the new, automated state and continue to push for new gains by tweaking or even re-evaluating the process.
Error rate: Your automated process should significantly reduce error rates associated with data entry and document misfiling—which often accounts for a large part of the average costs you see associated with processing a single invoice or order. What are your error rates today? How will you track them going forward and what goal will you set?
Consistency: The upside and downside of automation is that automation delivers identical without without variation. The upside is predictability. How predictable are your results today?
Dependability: By applying automated to a process, how will you minimize downtime or maximize output? ONE potential risk with automated processes is that they may not always handle exceptions in a fully automated fashion from day one. BUT, thanks to machine learning, they may be able to adapt and improve exception rates by working with your process owners and learning from instructions. Capturing that data will help to set expectations for ramping up with other processes you may want to automate next.
Auditability: Because automation is based in rules, regulatory compliance can be baked into the process. It should also be easy to follow an audit trail to monitor and maintain compliance. How much time and effort does a process audit take today?
Employee Satisfaction: Much of the hype around innovations like IPA and AI center on potential job losses or disruption. But the reality in most cases for existing employees is that they get to do more meaningful work. This is where qualitative metrics matter just as much or more than hard numbers. Go beyond stats like turnover to talk to employees, get their input and feedback, and share that knowledge and their insights with the rest of your organization.
The clock is ticking
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