Robotic process automation (RPA) is transforming how businesses operate across the globe, and is the fastest growing segment of the enterprise software market, projected to grow nearly 63% in 2019 to annual revenues of over $1.3B according to Gartner. This terminology refers to using software “bots” to automate and standardize repeatable business processes within a digital environment. Unlike traditional software programs, RPA operates within the confines of existing systems and architecture, resulting in increased accuracy and efficiency, and the ability for organizations to repurpose human capital for more productive and high-value responsibilities. Furthermore, these programs are extremely scalable and can generate material cost and time savings very quickly (what we refer to as digital efficiencies).
Today there are a variety of different companies attempting to automate (with either decision-tree, trigger-based logic or more sophisticated AI) what used to require manual work. There are companies hyper-focused on automating specific tasks for various industries (like Indicator portfolio company Netomi, which automates customer service for enterprise clients) and RPA vendors like UiPath and Automation Anywhere that have a complete software platform with hundreds to thousands of customizable bots and integrations. Competition in this market is intense, with the top-five RPA vendors controlling 47% of the market in 2018, and leading companies have garnered significant valuations based on their outsized growth and potential for continued expansion (UiPath, Automation Anywhere and Blue Prism are each valued well over $1B).
Typically, the objective of each automation initiative is to automate a high-volume, business-rules-driven and repeatable process so that staff can be repurposed to higher value activities, all while eliminating risk and human error. These individual automation initiatives are rolled up into broader IT and finance programs within corporate divisions and across geographies, with the goal of realizing significant business benefits by executing many of these initiatives at scale. While this sounds great in theory, there are a few major challenges associated with deploying this type of service within large enterprises.
To begin, there are many different stakeholders responsible for deploying and managing these initiatives and processes. Additionally, there are budget constraints and deadlines that must be taken into consideration. Furthermore, there are challenges in assessing the actual impact of such initiatives (what is the real ROI?) especially when programs are designed to deliver value incrementally or over extended periods of time. Calculating direct impact of RPA has proven to be incredibly difficult, particularly when you consider that many enterprises are using multiple vendors to patch different processes and initiatives together.
Shibumi is the glue that holds all of these initiatives together, ensures they are rolled out correctly and accurately measures their business value and impact to the enterprise. Companies and their advisors have successfully utilized Shibumi’s unique platform to generate ideas, evaluate the business case of competing initiatives, rank and prioritize opportunities and track the value realization over time. Companies are now using Shibumi to specifically decipher the impact of disparate systems working towards a common goal in a way that project managers and executive stakeholders can easily evaluate and understand. Shibumi has explored 5,000+ RPA opportunities and is working with decentralized teams with sub-12-week delivery times. So far, Shibumi has had a $75M+ impact with 1,000+ high-impact bots in production.
It has become clear that Shibumi’s ability to clearly calculate and depict the impact of different initiatives is inherently valuable to companies implementing RPA and any other strategic initiatives. Shibumi fits squarely in the center of Indicator’s investment thesis revolving around ‘Digital Efficiencies’ and is equally adept at delivering the RPA benefits we highlight above as it is at measuring and tracking portfolio ROI for our own investments.
Technology is great at automating mundane tasks, especially those that require decision-tree logic; but in a large organization it’s not as simple as click, deploy, and realize value. That is why we believe large organizations have been hesitant to deploy true AI (often referred to as RPA 2.0) at scale, and why we feel that RPA has been gaining momentum. However, with RPA, getting buy-in from management and IT support for post-pilot deployment is completely contingent on proving ROI. Shibumi is the perfect platform to bridge this gap and provide a resource for companies to deploy these new initiatives in an easy and efficient manner.
For more on how Shibumi works with RPA vendors, click here.