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Application and data integration began more than 30 years ago as one-off hand-coded systems. These solutions demonstrated the cost-saving benefits and improved efficiency of application integration technology for enterprise IT. Today, there are increasingly sophisticated approaches and specialized integration technology tools available to help us solve integration problems.
However, the evolution of integration over the years and the various integration tools deployed have introduced new layers of complexity. First-generation integration tools and custom point-to-point integrations created isolated silos of automation. A negative value curve often resulted from increased costs and the need for diverse skills that were not reusable across the enterprise.
For instance, many enterprises have adopted SAP, and have been running this ERP for decades. Many first-generation integration technology stacks focused on ERP integration, and thus they were adopted to access SAP data for other uses. As the technology matured, that specific interaction technology was made obsolete by newer more modern integration stacks. As such, that technology becomes a silo, with skills specific to that silo that need to be maintained longer term. As such, the value of that integration becomes negative, and the cost of maintaining that specific stack becomes counterproductive.
While “consolidation” is often used as a catch-all term for any modernization approach, the need for integration consolidation is profound. According to reputable analysts like Gartner, consolidated integration technology can reduce operational costs by up to 30% and enhance organizational efficiency and agility across different technology stacks that include integration, security, and operations. The goal is to streamline the enterprise's technology infrastructure by reducing the number of integration stacks, lowering costs, simplifying complexity, and minimizing the need for diverse technical skills.
Forrester Research highlights specific consolidation benefits, such as a 25% increase in productivity and improved data accessibility for enterprises that deploy integration consolidation technology. Moreover, the International Data Corporation (IDC) reports that integrated systems can reduce data errors and inconsistencies by up to 40%, resulting in more reliable decision-making.
While it’s easy to propose consolidation, the approach and technology you leverage are vital to the success of the effort. By consolidating integration tools, organizations can streamline operations, reduce maintenance costs, improve efficiency, and adapt more effectively to changing business environments and technological advancements.
The current “as is” state of overly heterogeneous and complex integration can be defined when the functions of two or more integration stacks overlap. For instance, integration servers A, B, and C have the same purpose and execution patterns but are sold by different technology providers. It’s often known that one of these servers would be sufficient but three continue to be leveraged due to the time and materials costs of replacement.
The more efficient and optimized “to be” state is often misunderstood. The goal is to select a single integration technology that can provide both data and application integration and the capacity to adapt and expand.
Thus, we are looking for an integration solution that provides the “to be” state more optimally and returns the most value to the business. The idea is to create a business case, fund the consolidation, and then verify the return of value, which is normally many times the consolidation investment.
While consolidation seems like a natural approach to dealing with integration technology, those who study this space also see some impediments to the consolidation of integration technology, specifically:
- The security technology and approaches used in silos can be tough to dismantle. Also, in many instances, their owners and staff have been built around that specific technology.
- There is a cost associated with consolidation and a lack of understanding regarding the business value it can bring. Enterprises are understandably hesitant to spend a dollar if they don’t realize it will return 10 dollars to the enterprise within a few years. Stakeholders need a strategic understanding of consolidation benefits.
- Enterprises often find it difficult to define the investment. Although many understand the value of the effort, the soft benefits, such as reducing complexity, achieving quicker time-to-integration deployment, and improving operational efficiency, are often difficult to define.
The impact of AI on enterprises, given its explosive growth, is undeniable. This drives a few key changes within enterprises.
First, there’s the value of data as training and analytical data sources. This data often exists in silos within enterprises and must be brought together for proper AI model training, both new and ongoing, using tools such as Large Language Models (LLMs).
Secondly, these models need the ability to be accessed by any system that needs them, typically through application programming interfaces (APIs). If the AI model has value to core business processes but cannot access the data or APIs, then its value is greatly reduced. Many enterprises risk being unable to develop and implement AI models if they lack the ability to leverage them appropriately from core business systems. This is perhaps the biggest risk that enterprises face with AI—it may not deliver the expected return on investment. Hundreds of millions of dollars are on the line.
Beyond the challenges in organizational politics and education that arise with transitioning to this upgraded state, there are general steps that can be taken to increase the likelihood of success. Consider the following:
Assess the “As Is” State
Assess how well technology is currently integrated within the enterprise. The assessment should include the tangible financial cost of inefficiencies and complexities as well as the impact on the user experience, agility, time to market, employee satisfaction, and customer relationships.
Determine Metrics for Success
Identify and define the key metrics for success, including:
- Increased Agility: The ability to quickly and effectively adjust and react to changes.
- Increased Efficiency: Improve productivity by streamlining operations and reducing waste.
- Strategic Use of Data: Leverage the effective use of data resources to drive informed decision-making.
- Strategic Use of AI: The strategic incorporation of AI technologies to enhance business processes and outcomes.
Access the Path to Consolidation
Identify the pathways and methodologies for effectively consolidating integration technology. This includes evaluating the available tools, platforms, and frameworks to identify the most appropriate approach for the enterprise's specific needs.
Implementation Planning
Develop a detailed plan that outlines the steps necessary to achieve the consolidation of integration technology. This would involve making strategic decisions, allocating resources, setting timelines, assessing risks, and developing mitigation strategies.
Deployment and Operations
Commence operations by executing the implementation plan and deploying the consolidated integration technology. This step involves monitoring and optimizing the integrated systems to ensure they function as intended, produce value, and meet defined success metrics.
