The Database Management system is just a tool to manage databases. It does not come with intellectual properties for a specific application domain. You must develop those. You must model, design, and implement your databases with a DBMS. Similarly, you must design, model, and implement your processes with a BPMS. Enterprise reference architectures and stacks are becoming increasingly cluttered and complex. What’s needed is a pragmatic approach that focuses on process and data.
AI is an integral part of Digital Process Automation, and the potential of AI optimizations for on-chain (Blockchain transactions) and off-chain data (IoT, customer, etc.) are tremendous. AI is the nervous system that automates and drives end-to-end digitized value chains to successful completion. AI is an integral part of Digital Process Automation, and the potential of AI optimizations for on-chain (Blockchain transactions) and off-chain data (IoT, customer, etc.) are tremendous. AI is the nervous system of the value chains.
The digital era fosters challenging the hierarchical and centralized control-driven organizations with alternative more democratic robust models that empower the participants. Blockchain could become an enabler – as we shall see. This is very much a decentralization, peer-to-peer execution, and disintermediation trend – the core competencies of Blockchain. A digital and agile organization with empowerment can leverage the innovative talents of its employees and improve their morals. Blockchain within enterprises can also promote alternative flat organization patterns. Blockchain is a distributed and decentralized peer-to-peer database. Applications built on Blockchain can allow organizations to execute smart decisions.
Tasks or activities within an End-to-End Valuechain as well as entire chains of tasks or activities can leverage Blockchain. From financial transactions to contracts such as service levels or quality, End-to-end Valuechains can be modeled and automated with Blockchain transactions at specific steps. Similar to IoT/IIoT, the road to Blockchain success also runs through Digital Process Automation (DPA). Examples of Valuechains include support processes such as on-boarding an employee or IT helpdesk. Valuechains can also be mission critical. There are ample opportunities for leveraging Blockchain in Valuechains.
The most likely scenario of Blockchain for cultural change will be sub-organizations that leverage elements of a Decentralized Autonomous Organizations approach. The focus in this Part 2 is primarily on the cultural ramifications of a decentralized organization that can be realized through Blockchain (or rather deployed on a Blockchain) – including its governance policies, bylaws, voting, and overall operations. Even though the Blockchain revolution is in its infancy, the introduction of Smart Contracts executing on the Blockchain is a key enabler for substantive changes in organizational culture: towards autonomy, flat organizations and robust communities.
IoT/IIoT challenges include skills shortage, standards, security, uncertain ROI, etc. Success can be achieved with top-down business solutions that involve People, IoT/IIoT connected devices, trading partners, and enterprise applications, all collaborating and orchestrating their activities The collaborations are in the context of end-to-end value streams, that are modeled, automated and monitored through Digital Process Automation (DPA) for continuous improvement. IoT/IIoT constitutes a powerful extension the business processes that are supported through DPA.
The transformation of Manufacturing goes beyond the confines of intelligent factories. With smart products, Customers and Business are increasingly connected. This connectivity includes of course the Internet of Things (IoT). But it also involves Artificial Intelligence (AI) as well as end-to-end Value Stream digitization and automation. New business models are emerging and transforming – even disrupting – age old Manufacturer-Distributor-Customer Relationships. Connectivity with AI, evolved CRM, and end-to-end Value streams are enabling new opportunities for Innovation – involving the Customer with ever increasing demands for Personalization.
A software robot automatically achieves the repetitive tasks much faster and with fewer errors. This brings us to the crux of Work automation – viewing it as a spectrum of work types and a spectrum of worker categories. There are many hybrids and ranges of automation in between the categories. The whole idea of humans losing jobs to automation - physical robots or robotic automation in software - needs a much holistic approach. The human factor is very much in play and repetitive jobs will be replaced with much more exciting ones.
We shall focus here on methodologies that are trying to operationalize and realize the most important potential of Digital Transformation and Intelligent Automation. IA is achieved through Digital Process Automation. The four methodologies discussed in this article are quite complementary. There are commonalities, but they do require different skills. They all should be part and parcel of the overall meta-iterations within a concerted digital transformation effort. Each of these methodologies manifests itself in specific phases and iterations of continuous innovation.