Regardless of your company’s goals, you’ve probably considered some form of digital optimization or transformation, whether it’s an ERP implementation, CRM initiative, or AI deployment.  

Today, we’re sharing the top digital transformation trends you need to know as you embark on any type of digital journey. 

Digital Transformation Trends to Watch in 2024 ​

1. Composability ​

Companies are increasingly implementing composable enterprise software. In other words, the software is modular with interchangeable components.  

The benefits of this approach include: 

  • Increased Agility - Composability allows for the rapid creation and deployment of new products and services. It also enables companies to quickly adapt to market changes and shifts in customer preferences.
  • Reduced Costs and Complexity - Modular components eliminate the need for custom development and complex integrations. This streamlines operations and minimizes maintenance costs.
  • Enhanced Scalability - Businesses can easily scale their infrastructure up or down by adding or removing components. This ensures smooth operations during periods of high demand or unexpected disruptions. 

One example that illustrates the benefits of composability is a business creating a custom ERP solution by mixing and matching components from different vendors. The business avoids vendor lock-in and can use open APIs to integrate with new data sources and add new applications, as necessary. 

(Learn about APIs and digital transformation.) 

The 2024 Top 10 ERP Systems Report

What vendors are considering for your ERP implementation? This list is a helpful starting point.

2. AI Production Made Simpler ​

Machine learning (ML) and artificial intelligence (AI) hold immense potential for businesses. By integrating ML and AI into enterprise software, such as ERP systems, businesses can gain deeper insights into their operations and make data-driven decisions.

Unfortunately, putting AI into production can be challenging. As new development methodologies continue to emerge, two such methodologies are proving particularly helpful:

  1. MLOps focuses on automating the ML model lifecycle, streamlining development, testing, and deployment processes. This encourages collaboration between data scientists and IT operations teams, ensuring smooth integration and production readiness.
  2. ModelOps governs the entire lifecycle of deployed models, including monitoring performance, managing versions, and ensuring compliance with regulations. This enables continuous improvement and optimization of models, maximizing their business impact.

Ultimately, the right development approach can put reliable insights into your hands sooner rather than later. However, important considerations include:

  • Initial Investment and Expertise: Implementing MLOps and ModelOps requires upfront investment in technology and skilled personnel.
  • Integration Complexities: Integrating AI tools with existing systems can be intricate, requiring careful planning and technical expertise.
  • Ethical and Bias Considerations: Responsible AI development necessitates careful attention to bias mitigation and ethical implications.

3. Embracing Digital Twins

Digital twins are transforming how businesses monitor, optimize, and predict real-world performance. From buildings and factories to machines and entire systems, every physical asset imaginable can now be digitized.  

For example, in the manufacturing sector, the benefits of digital twins include: 

  • Enhanced Operational Efficiency - Digital twins provide real-time insights into equipment performance, enabling predictive maintenance and preventing costly downtime.
  • Accelerated Product Development - Virtual testing and optimization allow companies to quickly test and refine new products. 

(Learn about the top manufacturing ERP systems.) 

Beyond manufacturing, digital twins are finding applications across diverse industries: 

  • Healthcare – Monitoring patient health remotely and optimizing treatment plans
  • Construction - Simulating building performance and optimizing resource usage
  • Energy - Predicting energy demand and optimizing grid operations 

Sustainable infrastructure is another trend shaping the future of business, and digital twins are playing a key role in its development. By integrating data from smart grids and renewable energy sources to create digital models, organizations are optimizing energy consumption and reducing environmental impact. 

4. Automating IT Operations

As businesses embrace multi-cloud and microservices architectures, the complexity of IT infrastructure management has grown.  

To navigate this landscape, companies are turning to AIOps. This is a set of tools and technologies that monitor, analyze, and automate IT tasks related to network management, application performance, and more.  

For example, AIOps can use machine learning to analyze mountains of data and identify potential IT issues before they disrupt operations. This translates into tangible benefits across the board: 

  • Cost Optimization and Streamlined Processes - AIOps automates repetitive tasks, freeing up IT resources for strategic initiatives.
  • Less Downtime – Proactive problem identification/resolution minimizes downtime and ensures smooth application performance. 
  • Agility and Innovation - AIOps streamlines the process of testing and deploying new technologies, enabling IT teams to experiment with technologies, like AI in ERP, at a faster pace.  

How to Get Started with Digital Transformation

Digital transformation is more than just a technology implementation. It’s a business initiative that requires a cultural shift along with new skillsets. 

In terms of culture, project teams must shift the mindset of the leadership team as well as the workforce at large. A culture that fosters collaboration, innovation, and adaptability is essential for digital transformation success. 

In terms of skillsets, businesses must equip leaders with organizational change management skills, digital fluency, and a strong understanding of emerging technologies. 

If you want your company to be able to quickly adapt to changing market demands, you must take the time to lay some groundwork. Our enterprise software consultants can help you get started. Request a free consultation below. 

Posts You May Like:

Buzzword Breakdown: Predictive vs Prescriptive Analytics

Buzzword Breakdown: Predictive vs Prescriptive Analytics

In today's data-centric world, the terms "predictive analytics" and "prescriptive analytics" are increasingly becoming part of the business lexicon. Both methodologies offer a forward-looking perspective but cater to different needs and outcomes.  Understanding the...

AI Implementation Tips for Savvy Business Leaders

AI Implementation Tips for Savvy Business Leaders

Embarking on an AI implementation can feel like navigating uncharted waters. From virtual assistants to computer vision to deep learning, the knowledge gaps companies face can be vast. However, before you become a data scientist, remember that an AI project is...