Over the last six months, I have hopped onto many, many planes, conference calls, maneuvered through different time zones, and sipped lots of coffee to meet with more than 40 UiPath customers and UiPath partners.
My role is to evangelize Robotic Process Automation (RPA) in Finance & Accounting (F&A) and Supply Chain Management (SCM). The RPA maturity range of the customers I spoke with varied from “we're just trying to understand RPA” to “we have automated 100,000 hours in our first year.”
I read that there are approximately 300 articles on RPA, artificial intelligence (AI), and machine learning (ML) published daily. The number seems conservative but the underlying message here is that organizations’ exposure to those topics is increasing. Business leaders are reading and increasingly looking to RPA as the tool to accelerate their company’s digital transformation. So, what exactly are they saying? That’s what I wanted to understand, hence a 6-month long road trip.
I present the top five questions I heard from customers:
Due to the speed with which this industry is growing, we may need a different time scale because one year seems like an eternity ago!
Nonetheless, about a year ago, most RPA providers were out there talking to buyers and explaining what a Proof of Concept (POC) or a pilot RPA project was. To some extent, we’re still doing that. However, now customers are asking more about how to set the right expectations for the POC.
Forward-thinking executives are willing to dip their feet into trying RPA with a pilot automation project. However, because the scale and scope of a POC is often small, they also want to know where and how to get a bigger return on investment (ROI).
Involving a UiPath business partner can expedite the POC and, eventually, companies can work on a hybrid model by continuously building their own capabilities and reducing dependencies on external partners.
RPA can be scaled at an enterprise level like building with Lego blocks, with each meaningful RPA foundational block fulfilling certain needs, independent of other RPA capabilities, and capable of being combined at a later stage.
However, to reach larger automation goals it is critical to have an overarching RPA strategy. An organization can implement an automation in as little as three months. At the enterprise level, the implementation duration may be relatively longer but is often much shorter than a traditional information technology (IT) deployment.
This is one of the most common questions that I hear from our customers. Customers new to RPA are excited about the road to automation but may be unclear about ‘blind spots’ and ‘what to expect at the next turn’ when at the beginning of their automation journey. RPA isn’t the only question on their minds. Customers also asked me about AI, ML, and wanted to understand how, specifically, we can solve their business needs.
Being a practitioner of Lean and Six Sigma process improvement methods, my natural instincts drive me to look for overall transformation opportunities in an organization and to determine the individual process components of those digital transformation opportunities. Hence, it is important to move the discussion towards a holistic digital transformation and not just how automation can improve specific departments or functions of F&A or SCM.
To effectively accelerate an enterprise-wide digital transformation, organizations should start by identifying and addressing inefficient processes, waste, and clutter.
Fortunately, an organization can still begin to realize the benefits of RPA and AI on processes which fit the automation criteria while also optimizing inefficient processes across the entire organization. Ensuring a successful and sustainable automation journey goes beyond knowing which processes to automate. Companies that start with clear goals and well-defined metrics (see question #5 in this post) combined with effective governance are better prepared to scale their practice.
In the 5S methodology that is part of Lean, the last ‘S’ stands for “Sustain.” DMAIC is the acronym used for the phases of the Six Sigma methodology and the ‘C’ stands for “Control.” I bring both up to illustrate the importance of sustaining and controlling the improved processes an organization is automating—both are needed to ensure organization-wide success in the “automation first” era.
A well-oiled, mature automation practice will have clearly defined roles and responsibilities, escalation matrix and cadence, and an overarching automation operating model (AOM).
There’s a co-ownership between the IT and Business departments and, possibly, a strategic partnership with a third-party provider. It is quite natural that everyone gets excited and charged up about RPA but it also important to drive that excitement forward in one direction. It is like electrons; they are all charged up and ready to jump to the next level but for the greater good, they need to flow in one direction to get a meaningful current and an AOM can help facilitate that.
This digital transformation via RPA will create new job titles, free up capacity, and employees will look forward to doing more meaningful work.
As a result, starting on your digital transformation journey also involves having a human resources (HR) strategy. Part of the HR strategy should include change management tactics because along with RPA excitement, employees can also feel anxiety around how software robots will affect their own positions. It will be a difficult conversation with an employee when his/her tasks get automated so that “they could do something more meaningful” if the organization hasn’t really thought through what that meaningful work may look like.
Security and governance are also among the most common pushbacks from IT teams to business departments when the discussion of RPA initially comes up.
UiPath takes pride in our defense-grade security and compliance—many U.S. government agencies run their Robots on the UiPath Platform. The UiPath Orchestrator can manage thousands of Robots, providing real-time visibility of Robot performance and utilization.
Organizations across the globe spend millions of dollars per year related to creating reports. They hire highly qualified resources to sift through multiple data sources before downloading, transforming, collating, transforming the data again, and finally presenting the data via reports.
Many of the customers I talked with during my multiple-month road trip wanted to know how RPA can help them be more efficient in those data-related processes. My response?
It is all about data. Good data enables good reporting.
So, we look at a two-fold view of how RPA can assist organizations with reporting and analytics.
The first relates to extracting information from the market, e.g. research data, banking information, etc. which requires logging into multiple portals, downloading various data, and collating that data. RPA robots, with the help of AI, can mimic those actions and save a significant amount of valuable analysts’ time.
Secondly, through RPA and ML, organizations can now curate higher quality data sets, if they aren’t already doing so. Sourcing and Category managers must collect and consume a lot of market information to meet their core metric of savings for an organization. The same managers can be assisted in the data collection process by attended robots—enabling managers to create their sourcing strategy.
Similarly, planners could leverage RPA to increase planning accuracy. By leveraging AI and ML, automated reporting will improve and provide more insightful reports.
What if we could reimagine a world where we do not have to do sample analysis because it is not humanly possible to analyze everything? What if a robot could analyze 100% of data with 100% accuracy? Call me a dreamer, but I see this as our potential future.
Learn how UiPath customer Australian Unity has automatically processed over 42,000 transactions with a 94% success rate.
In my opinion, keystroke reduction is the metric most impacted by RPA. Although hard to calculate, I believe this is a key RPA metric, even if some organizations can only view the metric conceptually. Many customers have an automation goal of touchless processing, or to get as close as possible. While keystroke reduction is the metric, touchless processing is the outcome.
I've also found that the key metrics an organization uses to determine RPA success primarily relate to these four major levers in business:
Experience enhancement (for both employees and customers)
My colleague Harish Doddala has written an entire blog post on the key RPA metrics he recommends you use to help measure your own organization’s automation ROI and success. I invite you to check out the post and use the free RPA metrics template to help you track RPA metrics.
RPA success is also subjective. For example, one executive I talked with stated that her goal is to make her organization “RPA savvy.” She did not have a savings target or revenue pressure, yet, I believe, she was striving for experience enhancement of her employees.
While there is no cookie-cutter answer regarding the ROI of RPA projects, our Chief Strategy Officer Vargha Moayed suggests you “identify the benefits on the one hand, and all the related costs on the other.” He outlines how to do so in his post “RPA and the ROI Conundrum.”
In summary, RPA, supercharged with AI and ML, along with a robust AOM and HR strategy can enable an organization to reap the benefits of a digital transformation. Companies may get up to a 25% cost reduction, decrease in Cash Conversion Cycle days (impactive revenue), and be able to run transparent, error-free operations.
Above all, RPA and AI can enhance the experience of their employees, customers, and suppliers—the value of which is often not captured as a part of the RPA ROI calculation.
If you're interested in learning more, get your free copy of our recent report and find out how RPA is transforming F&A.