Case Studies of Business Process Management Transformation

Emerging industry processes will require businesses to learn to use automated tools, like low-code platforms, in order to streamline business process management. Read on this article which dives into the prevalence of low-code and 3 insightful case studies.

Case Studies of Business Process Management Transformation
Case Studies of Business Process Management Transformation. Photo by Priscilla Du Preez on Unsplash

Table of contents

The cloud widens the community of developers
Automation and rules that write themselves
Case study: Modernization leads to self-service at BP
Case study: Asahi Tekko achieves real-time production management
Case study: BBVA ramps up customer experience, digitally
Conclusion

Digital enterprises, employing artificial intelligence, cloud, and data analytics in innovative ways, are delivering superior customer experiences, faster response times, and more intelligent operations. Every company—no matter how large, how old, or in what industry— can potentially evolve into a digital enterprise, operating with the same agility of a startup.

Achieving this digital nimbleness requires relying on software and data resources that make use of legacy data, as well as the many new sources of data available today, and extend well beyond the traditional capabilities of IT departments. Digital nimbleness is an enterprise initiative, in which employees and executives from all parts of the business play an active role in designing and building solutions.

Enabling a wider group within the enterprise to design or redesign process-driven applications represents the most expedient and effective way to successfully navigate the digital transformation journey. Business processes evolve and change as rapidly as the business changes—meeting customer preferences, releasing new products, pivoting to new markets, and forging new partnerships. Today’s generation of business process management (BPM) and business rules management systems (BRMS) solutions offer a way to rapidly build modern applications with a minimum drain on precious and expensive IT resources.

The only way to advance and compete is to open up software innovation across enterprises— to business users who typically do not have traditional programming skills, but who need to be able to harness the power of technology. This means evolving the way applications are being built and deployed. Indeed, a survey of 324 companies found 76% indicating that at least some portion of their applications were developed outside of their traditional IT departments or IT service providers.

“Without low-code and no-code development, organizations are going to find it increasingly difficult to keep pace with their competitors,” reports SD Times, which quotes Rob Koplowitz, VP and principal analyst at Forrester3: “If we look at basic issues companies have now, what we often hear is, ‘I can’t build applications fast enough and by the time I build them the specs have changed.’

The rise of user-driven development and digital business process management is being made possible in two ways:

  1. The cloud makes application development accessible to a wider audience. Having online, easy-to-use, front-end tools available to non-developers opens up new ways of conceiving and building applications.
  2. Automation, artificial intelligence and machine learning enable a much wider variety of manual processes and tasks to be automated. AI-based engines are now being integrated into business process management, producing rules that write themselves. Low-level tasks also can be rapidly automated through robotic process automation (RPA), in which tasks are managed by intelligent software.

The path to digital transformation varies from organization to organization, of course, since they have invested in countless systems and applications over the years. But all successful efforts have certain common ingredients as well.

In every digital transformation project, new applications and next-generation architectures are built on today’s open standards, using on-demand resources.

For many organizations, digital transformation also means optimizing existing systems and application resources—integrating, replacing, or abstracting key pieces of their infrastructures into services.

By enabling a wider group within the enterprise to do design or redesign process-driven applications represent the most expedient and effective way to successfully navigate the digital transformation journey. Business processes evolve and change as rapidly as the business changes— meeting customer preferences, releasing new products, pivoting to new markets, and forging new partnerships. Today’s generation of business process management (BPM) and business rules management systems (BRMS) solutions offer a way to rapidly build modern applications with a minimum drain on precious and expensive IT resources.

The cloud widens the community of developers

For decades, only individuals with “developer” or “programmer” in their job titles held the keys to the applications that ran their organizations. This was for good reason—most enterprise applications tend to be very monolithic, difficult to understand, and difficult to change. The move from monolithic to microservices, as well as a move from traditional developers to a diverse mix of developers and business people, are reshaping the way applications are created, developed and deployed.

  • From monoliths to microservices: The process of application development is changing. And the technology employed to build applications is rapidly changing—to containers and microservices architectures that address the monolithic problem, making applications much easier to deploy, easier to change, and easier to understand. As a result, applications are becoming easier to create, deploy, and change. Cloud and container technologies now enable the breaking down of larger, monolithic applications into smaller components which can be managed and modified independently and deployed and scaled.
  • From traditional developers to diverse mixes of developers and businesspeople: Self-service environments make it possible for business users to develop and maintain applications without going through IT departments. The next generation of applications won’t be built purely by IT or traditional developers, but rather by teams that include business users, all contributing their knowledge and experience to these new microservices-based applications. These applications won’t require hard-core coding skills to change or adapt — rather, they need to be interfused with business logic and business know-how. Business users can’t necessarily write code, but they can produce models of their business that include business rules, along with the policies and decisions they make. Essentially, these models serve as source code for applications that can automatically be deployed within a microservices architecture.

Automation and rules that write themselves

Automation is also changing the game, delegating routine manual tasks and decision management to machines, thereby reducing manual work. Digital BPM and BRMS pave the way to AI, machine learning, and robotic process automation, which is revolutionizing the handling of the countless routine and manual tasks that slow down productivity.

Here’s how today’s systems are taking on the heavy lifting of today’s enterprises.

Artificial intelligence and machine learning: Artificial intelligence and machine learning are dramatically reshaping the way enterprises approach business automation. With machine learning, rules are derived automatically from historical records. This is in contrast to traditional decision management and business rules approaches when rules are created based on users’ experiences, and then built out in applications. Machine learning leverages historical data to derive predictive models that can be applied to new information for the next set of decisions.

For example, an application that helps determine whether insurance claims should be paid or denied can leverage predictive models built from historical claims information. The historical data provides an understanding of how claims decisions were made in the past. The claims application can use the predictive model to make decisions about new claims, which will be consistent with past behaviour.

Evolving standards are also facilitating the integration of AI and machine learning into business automation solutions. Predictive Model Markup Language, or PMML, enables predictive models to be encoded and shared among different systems. A relatively new standard, Decision Model & Notation, or DMN, is a graphical language for encoding the rules that make up a decision. DMN makes it easier for business users to create the source code for their decision applications, and to encode complex business logic. In addition, DMN enables business users to incorporate a predictive model into their DMN diagrams as easily as they can incorporate business rules. They can combine both the output of a predictive model with a set of rules in order to arrive at a decision.

In the big picture of application development, this means business users can create DMN logic, which can be employed within a container as a decision service. Or they can automatically feed predictive models from training data into that same process.

Robotic Process Automation: A recent survey by Deloitte finds a majority of enterprises, 53%, are now employing robotic process automation, or RPA. That number is expected to increase to 82% within the next two years.4 RPA enables the creation of software robots that perform repetitive and routine work that might otherwise be done by human workers. The benefits to organizations are reduced costs and headcount by automating work.

In many workplaces today, much time is spent on simple repetitive tasks, such as copying and pasting information from a back-office database into a spreadsheet. RPA enables enterprises to automate many of these routine tasks and functions. Essentially, the software robot records the work people are doing and replays it, with varying levels of intelligence applied. Basically, building out RPA is another approach to developing applications. Ultimately, these robots will be deployed as microservices through containers, supported by the cloud.

4 The robots are ready. Are you? Untapped advantage in your digital workforce, Deloitte, 2018.
4 The robots are ready. Are you? Untapped advantage in your digital workforce, Deloitte, 2018.

Case study: Modernization leads to self-service at BP

BP, a global energy company, had a complex operational management challenge, with hundreds of product teams using various delivery models, affecting application development and deployment. The company wanted to explore a robust, modern, open-source technology infrastructure that could operate worldwide and be accessed by thousands of business users and millions of end customers. It needed a reliable, modern technology infrastructure to speed application development and deployment.

To accomplish this, BP worked with Red Hat to simplify and modernize technology and processes, increasing security and agility and speeding provisioning from two to three weeks to seven minutes. BP used Red Hat OpenShift Container Platform running on Amazon Web Services (AWS) to build the Application Engineering Services’ Digital Conveyor. This platform provides process automation that empowers product delivery teams with self-service capabilities, a DevOps approach, and a continuous integration/continuous delivery (CI/CD) pipeline.

“The combination of microservices, containers, and a fully automated CI/CD platform provides what developers have been asking for years,” said Paul Costall, head of application engineering services at BP. “They now have full self-service to deliver change from the initial idea, through the innovation, right through to production, as quickly as humanly possible.”

Case study: Asahi Tekko achieves real-time production management

To keep pace with orders, automobile parts manufacturer Asahi Tekko Co., Ltd., needed to speed just in time workflows without expanding its physical footprint. The company needed to replace manual data collection with automated machine monitoring to track and manage quality and productivity.

Achieving these improvements would require increasing machine capacity, but the manufacturer simply did not have the space to accommodate additional machines needed to fulfil larger order volumes. “Although we had a business potential to accept orders up to about three years ahead, the factory’s space was about 3,000 meters too short to accommodate manufacturing all of them,” said Tetsuya Kimura, president and representative director of Asahi Tekko.

To better understand its physical resource use, the company collected operational data from its factory machines, such as production quantity and downtime. However, machine production counters were reviewed and recorded manually, a time-consuming process that lead to incorrect or incomplete entries.

Asahi Tekko employed enterprise open source solutions from Red Hat to create an Internet of Things (IoT) mechanism and business rules engine for automated data collection and real-time insight into machine operations. As a result, Asahi Tekko has cut capital expenditure by around ¥300 million, reduced employee over-work, and even created a Software-as-a-Service (SaaS) offering for other manufacturing companies.

The company created a cycle time monitor, an IoT mechanism that would automatically collect and display operational data to eliminate manual errors and improve productivity. Employees can use this data to focus on repairing or improving slow and broken machines instead of checking each machine’s data. The company deployed Red Hat Enterprise Linux and Red Hat JBoss Enterprise Application Platform as the foundation for this solution.

In addition, the company deployed Red Hat Decision Manager (formerly Red Hat JBoss BRMS) as its rules engine, which includes complex event processing (CEP) capabilities that detect the relationship between massive volumes of information in real time. With these capabilities, Asahi Tekko’s IoT solution automatically detects and visualizes necessary site data—such as line production number and stop time—in real time.

Case study: BBVA ramps up customer experience, digitally

BBVA, a financial group that provides financial services to more than 73 million customers in more than 30 countries, needed to update its technology to better support its digital transformation goals and improve its customer experience. “Customers demand 24-hour-a-day functionality from anywhere,” said José María Ruesta, global head of infrastructure, service, and open systems at BBVA.

“We have to achieve a balance between innovation and reliability. But as a bank, trying to translate these values into technology is difficult. Imagine a datacenter full of different operating systems, languages, and interfaces. There’s no room for innovation.”

BBVA wanted to create a single, global, cloud-native platform that is fully automated and self-service, combining real-time and batch data to help developers work efficiently and to ensure high service availability and reliability. As new functions increased the transaction volume handled by BBVA’s backend systems and applications, the group sought to update its IT environment as part of its digital transformation journey.

The company turned to enterprise open source software—including Red Hat OpenStack Platform and Red Hat OpenShift Container Platform—to build a unified global cloud platform that is fully automated, self-service, and data-centric. With this new platform, the company has increased efficiency and integration to provide a better customer experience and support innovation.

With a global open source platform, BBVA’s developers can quickly and easily deploy code across its branch network, speeding time to market for updates and new services. “Our proprietary platforms created isolation that prevented agile development of new products in line with customer demand,” said Ruesta.

“BBVA is a company with more than 150 years of experience, but the future is never certain. Digital transformation is critical to survival and competitive advantage,” said Ruesta. “Innovation means reinventing ourselves. It’s finding new ways to develop products and services that break the mold of traditional banking.”

Conclusion

The power to accomplish game-changing digital transformation is now available to the business user, who ultimately decides and directs what solutions the business needs. Ultimately, the purpose and intent of such transformation is to deliver value to the customer—quickly, with continuous delivery of quality and functionality. By empowering business users to engage in digital business process management and business rules management systems, enterprises can rapidly deploy and configure business technology to ever-changing processes, when and where it is needed.

Source: Red Hat

Thomas Apel Published by Thomas Apel

, a dynamic and self-motivated information technology architect, with a thorough knowledge of all facets pertaining to system and network infrastructure design, implementation and administration. I enjoy the technical writing process and answering readers' comments included.