Existing ML benchmarks lack the depth and diversity of annotations needed for evaluating models on business process management (BPM) tasks. BPM is the practice of documenting, measuring, improving, and automating enterprise workflows. However, research has focused almost exclusively on one task -- full end-to-end automation using agents based on multimodal foundation models (FMs) like GPT-4. This focus on automation ignores the reality of how most BPM tools are applied today -- simply documenting the relevant workflow takes 60% of the time of the typical process optimization project. To address this gap we present WONDERBREAD, the first benchmark for evaluating multimodal FMs on BPM tasks beyond automation.

The rapid development of cutting-edge technologies, the increasing volume of data and also the availability and processability of new types of data sources has led to a paradigm shift in data-based management and decision-making. Since business processes are at the core of organizational work, these developments heavily impact business process management (BPM) as a crucial success factor for organizations. In view of this emerging potential, data-driven business process management has become a relevant and vibrant research area. Given the complexity and interdisciplinarity of the research field, this position paper therefore presents research insights regarding data-driven BPM.

The amount of information we have to deal with day-by-day is large enough not to be able to handle it without specialized software tools. Ordinary events we face daily, from doctor's appointments to upcoming Zoom meetings, are compiled into a system with too many variables to track and manage efficiently. Therefore, at least, the use of a simple task management app is a must nowadays. In business, the stakes are much higher. The volumes of data that constant collaboration with clients generates are too big to efficiently process them manually.

Automation has been used for years, but the full business potential has yet to be realized. Intelligent automation combines data with modern automation capabilities. It can produce cost savings, improve efficiency, and even enable new business creation throughout the value chain. Intelligent automation expands the scope of automation. It moves us from rule-based tasks to the automation of tasks that require human judgment and intelligence. It uses Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Process Mining, Intelligent Document Processing, Business Process Management, and low-code or no-code tools and analytics.

Business process management is now a mature discipline. It has formal approaches, methods, techniques and a rich set of concepts. It has also evolved to the point where it is applied to projects of all sizes and supports both business process improvement and business transformation. As BPM evolved, so did the enterprise's business processes. They became too large and complex to be managed without automated tool support.

Recent years have brought a stream of exciting developments in the field of Business Process Management (BPM). We have seen a breathtaking uptake of business process automation technology, such as Robotic Process Automation (RPA). We have witnessed the rise of process mining, and promising evolutions in the areas of predictive process analytics and digital process twins. In the eyes of a business analyst, each of these technologies offers compelling opportunities to enhance operational excellence. However, if we look at these technologies in isolation, it is easy to miss the bigger picture and the wider space of opportunities that these technologies open when used jointly rather than applied in individual projects or silos.

New for 2019: Solutions Review has mapped the top-20 business process management solution providers for Workflow Management, Artificial Intelligence and Low-Code Development Platforms across a Venn diagram to make it easier for you to pick the best vendor. The BPM Vendor Map offers a guide for companies large and small to navigate the developing challenge of managing business processes and workflows. It also includes profiles of the top-20 BPM vendors. Covering the best providers of workflow management, artificial intelligence, and low-code development platforms, this new research report is a perfect companion to a Gartner Magic Quadrant or our own Solutions Review Buyer's Guide. Information for this report was gathered via a meta-analysis of available online materials and reports, conversations with vendor representatives, and examinations of product demonstrations and free trials.

Robotic Process Automation (RPA) technologies create software-based'robots' that are capable of following pre-set processes in order to complete work that would otherwise require manual labor. Similar to Business Process Management Software (BPMS), RPA offers a solution for enterprises that are suffering from inefficiencies and challenges associated with legacy software systems. Not to say one is better than the other though, because both RPA and BPMS are crucial to process-related solutions and essential to an organization's digital transformation. BPM is known to be a systematic approach to streamlining business processes in a way that drives profitability and ensures maximum efficiency within an organization. BPMS, on the other hand, is a process automation tool.

Intelligent Business Process Management Suites (iBPMS) is defined by Gartner as having capabilities such as validation (process simulation, including "what if") and verification (logical compliance), optimization, and the ability to gain insight into process performance have been included in many BPMS offerings for several years. The iBPMS market today is the natural evolution of the earlier BPMS market, except with added features (above) making it possible for greater intelligence within business processes. In light of this, we recently spoke with Miguel Valdes Faura, Founder and CEO of Bonitasoft, about iBPM software to help provide a more depth definition. He's also provided us with some insight into iBPM solutions, where Robotic Process Automation (RPA) comes into play, and his views on the marketplace. MF: There are a lot of AI related technologies that are complementary to BPM when it comes to improve business processes and applications efficiency, compliance and continuous improvement.

There's a lot of discussion among IT professionals about what digital transformation actually is. From my perspective as a business process management expert, digital transformation results from applications that provide better user experiences for customers and employees. State-of-the-art user interfaces, combined with streamlined backend operations, enable improved business efficiency, smoother processes, faster reaction to market changes, and better adaptation to rapidly changing business environments. As business process-based applications get more sophisticated, however, the effect of delays--or blocked processes--remains a problem. Therefore, I've spent a good amount of effort looking at how to manage these blockages and delays.