Organizations have a lot riding on the efficiency and effectiveness of their procure-to-pay processes. Disruptions to an organization’s ability to purchase or pay for materials, goods and services can negatively impact its supply chain, customers and financial standing. Yet, most organizations rely on manual or semi-automated procure-to-pay processes that cost too much, take too long, create too many errors, provide inadequate visibility and frustrate internal stakeholders and suppliers. A big part of the blame can be pinned on the top-down approach that most organizations have traditionally taken to automating business processes. Another contributor is the exploding volume of “dark data” – untapped structured and unstructured data from documents such as invoices, purchase orders and shipping documents. Robotic process automation (RPA) with cognitive automation makes it easier and more cost effective for procure-to-pay organizations to automate. The technology empowers business users with software robots (bots) that automate business processes, such as procure-to-pay, to achieve operational and strategic benefits.

This paper details the challenges with traditional approaches to business process automation, provides an overview of RPA and cognitive automation, and lays out the technology’s benefits in procure-to-pay.

Amidst all of explosive growth in the RPA space, what is keeping organizations from taking their RPA capabilities to the next level? AIIM believes that one answer lies in the unique challenges associated with integrating unstructured information into an RPA environment.

In this eBook, we explore the following questions:

• What is the current state of process automation, what is keeping organizations from moving forward, and how does RPA address a key pain point for many organizations?
• How and where is RPA being used to leverage existing enterprise IT investments?
• What unique challenges does unstructured information create for process automation and RPA engines?
• What does an intention to spend more on RPA tell us about other key organizational priorities and pain points?

RPA platforms represent a hyper growth market, with enterprises investing in new RPA platforms for process and task automation to achieve greater operating efficiency and agility, while allowing the human workforce to focus on more strategic and higher priority projects and tasks. Intelligent process automation (IPA) is in an early phase of its evolution and represents the next frontier for RPA vendors. This Ovum Decision Matrix (ODM) is a comprehensive evaluation to help enterprise IT and business leaders, including chief information officers (CIOs), enterprise and process architects, IT directors, line-of-business (LOB) leaders and process owners, and digital transformation leaders select an RPA platform that is well suited to their specific requirements.

With RPA, companies can automate a wide range of processes they wouldn’t have imagined possible before. These range from very rote tasks, such as cutting and pasting customer data from a CRM system into a back-office ERP system, all the way up to unattended software bots capable of intelligent decision-making based on pre-set logic.

What is clear is that RPA is at a tipping point. But will this growth continue? If so, on what path? What innovations lie ahead?

This e-book will provide Automation Anywhere’s insights about the future, with seven RPA predictions for 2019. These predictions relate to market growth, technology disruptions, platform enhancements and new use cases for RPA.

What cognitive automation is, why you need it, and how to do it right

Adding cognitive capabilities to robotic process automation (RPA) is the biggest trend in business process automation since, well, RPA.

In this eBook, you’ll learn how to succeed with cognitive automation by following six basic steps.