Implementing Intelligent Enterprise: Exploring Dual Paths for Digital Transformation

Embarking on Digital Transformation projects can be overwhelming, especially when an organization lacks predefined future processes and the requisite skills to implement the necessary technology. Balancing the need to efficiently run daily operations with the demands of this transformative journey poses a considerable challenge. The transition to a new digital platform is a gradual process, requiring time for the organization to fully leverage its capabilities.

The establishment of a digital backbone for an intelligent enterprise is facilitated through modular applications, universal data access, a robust business network, and scalable infrastructure. However, achieving the status of an intelligent enterprise involves a phased approach, encompassing the re-platforming of technology, upskilling the workforce, and a fundamental reimagining of legacy business processes. Despite the time-intensive nature of this evolution, organizations can begin reaping benefits early on by enhancing operational efficiencies and laying the foundation for a digital business.

How Has the Intelligent Enterprise Changed?

Over the last few years, the landscape of the intelligence enterprise has witnessed notable transformations within the Enterprise Resource Planning (ERP) software industry. These changes have primarily unfolded across crucial architectural layers such as Application, Data, Technology, and Infrastructure, culminating in the establishment of a resilient digital platform.

The advent of intelligent enterprise software amalgamates these innovations to propel the subsequent wave of productivity enhancements and business transformation. One pivotal shift is observed in the adoption of modular applications, steering away from the traditional monolithic approach (ECC). Presently, the emphasis lies in connecting and extending diverse best-of-breed applications through API services, offering a more flexible and efficient enhancement process.

The integration of Artificial Intelligence (AI) stands out as a prominent feature, empowering systems to automate repetitive tasks, enhance decision-making through predictive analytics, and facilitate proactive problem-solving. Universal data access emerges as another key facet, enabling real-time access to data from various sources, including customers, partners, industries, and devices. The concept of a Business Network or Connected Business signifies a departure from limitations imposed by internal boundaries, allowing for a more expansive and interconnected approach to data and processes.

Furthermore, the scalability of processing power takes center stage, as cloud infrastructure servers provide exceptional elasticity and the capability to scale rapidly. This collective evolution underscores the intelligence enterprise’s journey towards a more interconnected, efficient, and technologically advanced future.

Two Approaches to Digital Transformation

The process of digital transformation can be approached through two primary methods:

1) enhancing digitization and

2) embracing a ‘digital first’ business model.

The integration of new technologies for the implementation of ‘reimagined’ processes cannot occur instantaneously within organizations. There exists a transition period for the adoption of novel technologies, during which a diverse array of businesses will undergo restructuring to align with the emerging digital platform. (Comparable to how gamers continue playing old video games designed for previous consoles until new games are developed and released to leverage upgraded hardware)

Initial stages of the digital transformation journey for organizations typically involve platform upgrades and a focus on digitization. Efforts concentrate on enhancing efficiencies to realize immediate benefits. As organizations acquire or upgrade skill sets to effectively utilize new technologies and incorporate innovative business processes, the pace of digital business transformation is expected to accelerate.

In regulated industries, certain business processes and standard back-office functions may not necessitate a complete reimagining. Nevertheless, they still demand improved user experiences, automation, and analytical capabilities to drive the next wave of productivity enhancements.

1. Enhancing Efficiency through Digitization:

Organizations often adhere to established processes that are functional but may be compartmentalized. The transition to an intelligent enterprise does not involve abandoning current processes; rather, it entails their enhancement. The objective is to create a digitally refined iteration of the organization, leveraging innovative technologies to augment existing business processes and establish a groundwork for future transformative initiatives. This approach is incremental and differs from the digitization that occurred few years ago when manual and paper-based processes were converted to electronic formats. The improvements now revolve around connecting fragmented processes, enhancing user experience, and implementing automation.

This presents an opportunity for organizations to simplify, streamline, and standardize processes and the underlying data models.

The focus can be directed towards the following capabilities without causing disruption to core business processes:

1. Enhance user experience (Fiori)
   1. Intuitive user interface design
   2. Multi-device and multi-channel experiences
   3. Personalization for improved engagement
2. Boost user efficiency (Automation)
   1. Streamline processes through automation
   2. Implement machine learning-based digital assistance
3. Utilize data and analytics (Datasphere)
   1. Incorporate in-app analytics and dashboards
   2. Integrate forecasting and prediction across various business domains
   3. Implement IoT integration for physical assets
   4. Conduct risk assessments
4. Improve integration (Integration, Network)
   1. Foster connected business relationships with partners and customers
5. Support Sustainability Initiatives (Sustainability Management)
   1. Enhance environmental footprint
6. Support ESG (Environmental, Social, and Governance) principles
   1. Streamline sustainability reporting

2. Embrace a Digital Framework for Overhaul:

In certain industries or operational sectors, a radical shift is imperative. Construct novel business processes from the ground up, distinct from the existing business model, encompassing the introduction of innovative products and/or services.

This transformation has the potential to act as a revenue catalyst for corporations or a value enhancer for governments.

• Business Network: Facilitate process and data integration within the business framework to accommodate pay-as-you-go, subscription, and outcome-based transaction models.
• Digital Twins/IoT/Predictive Maintenance: Enhance asset utilization by supporting subscription and utilization-based service offerings.
• Customer or Citizen Experience: Implement AI/ML-driven self-service solutions to address common scenarios, thereby enriching user experiences.
• Promote New Revenue Streams: Explore opportunities in the Circular Economy, leverage Blockchain for supply chain traceability, and establish micro-power grids based on solar electricity generation.

Challenges in Digital Transformation for Large ERP Systems

Organizations embarking on the digital transformation journey for large ERP systems may encounter the following key challenges:

1. Legacy Processes:

• Deeply ingrained siloed processes that have solidified over the years.

2. People/Organizational:

• Lack of clarity regarding the impact of change, as legacy systems are maintained by a group of technology experts.
• Siloed data and insufficient data quality, hindering the utilization of data as an asset.
• Limited scalability and interoperability issues.
• Unclear objectives for digital transformation.
• Budget and resource constraints.

3. Technology Adoption:

• Policies and standards that lag behind the evolving landscape of business and technology, such as security and cloud.
• A wide array of rapidly changing technology options, making it challenging to make informed choices.
• Difficulty envisioning business processes that can be transformed using the latest technologies, including AI, ML, Cloud, IoT, APIs, Blockchain, etc.
• Skillsets and mindsets primarily focused on legacy or existing technology.

Organizations ought to integrate these strategies according to their specific business domain for transformation. To mitigate the potential for complete business upheaval and minimize the risk of overwhelming transformation, organizations should embrace intelligent enterprise practices to enhance existing business processes in targeted focal areas. Seizing this moment, they should establish a robust foundation by enhancing the skills of their workforce and acquiring technical expertise. This proactive approach will establish a sturdy groundwork for developing and implementing more transformative capabilities over the next 3 to 5 years.