The headlines abound: Enterprise automation software program (a.ok.a. Robotic Course of Automation, or RPA) has helped hundreds of firms get monetary savings by automation of repetitive, tedious duties and enabling staff to deal with mission-critical operations.
Many enterprise course of duties might be automated, however not all of them must be.
An Ernst and Younger research discovered 30% to 50% of RPA engagements fail, citing poor planning because the distinction between success and failure. These planning challenges sometimes happen when enterprise processes are evaluated manually – through a prolonged process involving worker interviews and random spot-checks – leading to inaccurate course of discovery, process frequency and time metrics. Manually discovering processes not solely takes too lengthy, but it surely additionally generates incomplete knowledge for RPA planners and builders. Because of this, RPA bots are sometimes applied the place it’s “best” to use the instruments, not in most crucial areas that may maximize ROI.
RPA brings no worth in the event you have no idea precisely what to automate. Fairly merely, you possibly can’t automate silly.
Not a Fast Repair
One other drawback enterprises encounter is that they try speedy implementation of RPA instruments based mostly on this defective info (directions for bots lacking key various situations). If the enterprise doesn’t take the time or have the instruments to find and optimize enterprise processes, they’re merely “throwing spaghetti on the wall to see what sticks.” This can be a very pricey mistake!
Would an organization rent a brand new worker with out realizing what job they’re hiring for? No. Equally, firms should totally develop an correct “job description” for RPA bots with the intention to maximize their expertise spend. Notably, solely three p.c of organizations have deployed greater than 50 robots, which signifies very low confidence within the worth of broad RPA deployment.
Step one towards maximizing return-on-investment for RPA instruments is to conduct an in depth and correct evaluation of the corporate’s full set of processes utilizing a mix of automated course of mining and process mining applied sciences. This evaluation asks, “On what duties are staff actually spending their time?” in addition to “What precisely are the processes that may and needs to be automated?” The flexibility to acquire end-to-end course of metrics early, on the strategy planning stage, would allow planning based mostly on info, not guesses or assumptions, engaging in most ROI.
Taking Actual Financial savings to the Financial institution
Let’s have a detailed take a look at an precise case research from a significant North American financial institution. The financial institution, with $50 billion in property and greater than 3,000 staff, was trying to streamline and enhance its anti-money-laundering (AML) operations. Regardless of constantly rising the variety of AML reviewers…
- The critiques took too lengthy, making a backlog of transactions.
- The method effectivity was very low, with solely 3-5 p.c of evaluate instances being actual suspects.
- The evaluate course of itself was inconsistent, with some reviewers performing extreme validations whereas others stopping at “simply sufficient.”
Earlier than making an attempt to automate any processes, the financial institution utilized course of and process mining software program to disclose the end-to-end duties carried out by all workforce members. With the expertise, executives had been in a position to visualize the work course of of every reviewer (together with actions, screenshots, and programs used), measure the time every course of exercise was taking to finish and determine non-value-added actions. They had been additionally in a position to analyze deviations and variances from the “optimum path” and generate a dependable “Commonplace Working Procedures” doc for AML reviewers.
Such a excessive degree of accuracy and element permits evaluation even of “unstructured processes,” similar to duties carried out by workers in phrase processing apps, spreadsheets and e-mail. Unstructured processes wouldn’t have a descriptive consumer Interface and are extraordinarily tough to research manually.
After finishing their evaluation, the financial institution applied focused RPA instruments to speed up and enhance reviewers’ workflow and eradicate redundancies, attaining as much as 60 p.c FTE price financial savings in non-post department validation. Moreover, the financial institution initiated a brand new coaching protocol based mostly on the routinely generated SOP paperwork.
Past its AML software, the expertise was used to seek out FTE price financial savings of 40 p.c in funding and onboarding of house fairness traces of credit score and 33 p.c price financial savings in money transaction reporting. In brief, due to correct analysis and evaluation, the robots knew precisely what they wanted to do to assist the financial institution enhance productiveness and finally add to its backside line.
Robots are nice… if you understand what you’re hiring them to do!
Sofia Passova is founder and president of StereoLOGIC, a frontrunner in built-in course of and process mining expertise which helps firms uncover inefficiencies of their enterprise processes and suggests options to enhance workflow and income.