Businesses are under increasing pressure to reduce their carbon footprint and adopt sustainable practices as the world becomes more aware of climate change and its impact on the planet. This pressure is especially intense on electric utility companies with power generation and transmission assets, which contribute significantly to carbon emissions.
Fortunately, technological advancements have made it easier for these businesses to achieve their sustainability objectives. Modern enterprise asset management (EAM) platforms and application resource management (ARM) software can assist power utilities in optimizing their resources and lowering their carbon footprint while maintaining high efficiency.
In this blog post, we will look at how integrating IBM Maximo and IBM Turbonomic can assist electricity utility companies with power generation and transmission assets in meeting long-term targets and goals while also optimizing ESG ratings.
An earlier article, Role of Blockchain in the Digital Transformation of the Global Shipping industry, gave a brief introduction to the application of blockchain and the many benefits that the technology brings to the global logistics and shipping industry. As a follow-up, this article intends to share how technology enablers drive the hyperautomation of internal business operations. The use of AI-driven digital platform supports continuous business improvement by increasing the visibility of internal business processes. At the same time AI technology simplifies the task of re-configuring existing processes. All these improvements help to drive business agility and resiliency.
Gartner has pointed out that hyperautomation is one of the top strategic technology trends that drive creation of new business models for improved business resilience. Gartner predicts that by 2022, 55% of Enterprise Architecture (EA) programs will be supported by artificial intelligence (AI)-enabled software, freeing enterprise architects to focus more on internal management consultancy work.
Hyperautomation also resonate well with the Malaysian government initiatives outlined in the 2021 Malaysia Budget, such as the SME Digitalization Grant, Automation Grant and National Supply Chain Finance Platform. These programs encourage the adoption of automation and digitalisation to drive long-term productivity and accelerate Malaysia’s transformation towards a high-income economy.
The following diagram gives an example of how to leverage on hyperautomation to support blockchain transactions for timely and accurate reporting that draws on immutable data sources.
Shared ledger of TradeLens Blockchain platform and business network provides the following business benefits:
It reduces manual effort and operation cost required to perform reconciliation & resolve disputes.
It accelerates settlement by removing third parties previously needed for transaction verification & validation.
It enables real-time reporting on distributed transactions for compliance purposes.
Increased transparency of TradeLens Blockchain requires timely and error-free participation of parties in the business network. Each party must act within the expected window of opportunity. Such performance expectations of Blockchain business networks require high levels of automation & repeatability in your internal business operations.
It requires the following types of support in your digital operation platform:
Integration modernization with legacy systems to automatically generate letters of credit and quickly resolve exceptions through structured and auditable process flows
Automation of sender/beneficiary onboarding with ability to perform real-time settlements and reduce false rejections. Automation uses business rules to increase straight through processing and to provide timely fraud detection. Business rules are externalized to make them repeatable and they can be frequently and easily updated to meet changing business conditions and policies
Integration of source systems with audit systems to minimize manual errors and automate audit and exception processes by involving both human and systems in the digitized compliance checking process.
Documents to be submitted to the business network or documents pulled from the network are digitized and hashed for storing in enterprise content services to ensure originality, security, and accessibility.
Through deep learning, it eliminates the need to provide a lot of document samples for training during document digitization and intelligent content extraction, hence, enabling fast deployment and quick ROI. Automation Document Processing uses low-code AI-led training to reduce setup and maintenance and does not need 100s to 1000s of zonal-based fingerprints to read highly variable documents. There are some pre-trained models for common document types like invoices, purchase orders, bill of lading, etc. Deep learning is able to transfer learning from documents that have been processed to improve quality and accuracy of document processing for new document types.
Blockchain has highlighted the need for timely, auditable and accurate process performance through low code AI driven hyperautomation to avoid having inconsistent or undocumented processes, unnecessary manual work and rework due to limited, ineffective and siloed automation of workflows and business policies with poor end-to-end process visibility and slow, inefficient exception handling.