Most business leaders view application rationalization like cleaning out a garage: a painful, one-time chore to throw away junk to save space. It is often viewed strictly as a subtraction game that overlooks business context. Get rid of legacy technical debt to lower application costs and IT spend.
But this mindset ignores value. A better way to view your application stack is through the lens of a stock portfolio.
In finance, rationalizing a portfolio doesn’t always mean selling off assets to have less. It means rebalancing. You analyze performance, divest from underperformers that are dragging down your returns, and reinvest those resources into high-growth assets that drive wealth.
Your application portfolio requires the same strategic discipline. Many companies struggle with application sprawl. Their application portfolio may include apps that align to different business functions but have similar features, making for redundant applications that lead to rework. To fix this, instead of just going straight to application decommissioning, optimize.
Application rationalization is not just a cost-cutting, IT budget exercise in reducing your application inventory. It is a strategic balancing act. It uses business process intelligence and composability to support future innovation.
Application rationalization requires reordering, not just removing
The term application rationalization is often conflated with application consolidation, but they are not synonyms. Rationalization includes consolidation and retiring applications. It also needs you to reorganize your application portfolio. The objective is business efficiency that aligns with digital transformation goals. With your application inventory optimized, you can apply more attention and innovation to the apps that actually drive value.
Without this reordering, organizations often end up paying for multiple software solutions with the same application functionality. For example, a company might inadvertently provide four different software as a service (SaaS) marketing tools to their sales agents. When you split your resources across four redundant tools, the upkeep and the total cost of ownership are higher. Maintenance and changes are completed less frequently. The tool becomes less effective and contributes to application sprawl.
Effective application rationalization finds overlaps and uses composability to fix these issues. It allows you to take the functions of disparate legacy apps and compose them into a unified solution, rather than maintaining isolated silos. It also lets you add new technology like artificial intelligence to legacy business applications.
How composability enables application rationalization
Composability supports application rationalization by allowing organizations to break down rigid, monolithic legacy systems and instead make their capabilities available through modular, flexible applications. An AI-powered process automation platform can provide that composability. It acts as a bridge that lets you modernize legacy systems in your application portfolio so you can better consolidate the apps in your tech stack.
You can accelerate the transition from legacy requirements to modern applications while improving ROI with AI-augmented development—which turns business requirements into an interactive, visual plan for your application portfolio. For example, when you feed the requirements of your legacy apps into Appian Composer, it combines them into a logical consolidation plan that can be forward-engineered into a single new application.
A platform lets you combine multiple applications or share certain functions across applications. Instead of maintaining three separate legacy apps that all have a customer intake feature, you can build a single customer intake component in the platform and insert it into any workflow that needs it. This supports application consolidation efforts while modernizing legacy infrastructure, making life easier for your IT operations team.
You can’t rationalize what you can’t measure
One of the biggest risks in rationalization is cutting applications in your application portfolio to cut costs without understanding value. A surface-level audit might flag an application for removal simply because user adoption is low.
However, counts for application licenses can lie. You might find an application that only has 20 active users, which looks like a prime candidate for the chopping block. But if those 20 users are your top revenue generators who rely on that specific tool to close deals, cutting it from your application portfolio would be disastrous.
To avoid this, make quantifying value part of your application rationalization criteria so you can make the most cost-effective decisions. Instead of guessing, organizations should use process intelligence to report on the actual ROI that an application or automation within it provides.
Your application portfolio reviews should also include dependency mapping and interviews with application owners. Highly mature applications may have low user counts if they are used in automated processes that result in strong ROI. Examples of this include fraud rules engines, credit decisioning services, and pricing engines. It's not humans logging in to use them but bots, APIs, and orchestration platforms.
By using process intelligence tools and dependency mapping to visualize the work, you can assess the efficacy of the application based on true data-driven IT management.
Modernize by overlaying, not ripping and replacing
Many IT leaders delay rationalization because they fear the downtime and security risks associated with a Big Bang-style application replacement. They assume that to fix their application stack, they must rip out the old infrastructure entirely.
Fortunately, modern platforms offer a path with far less application risk: the ability to overlay. Using a platform with data fabric that acts as an agility layer, you can overlay multiple systems and coordinate work across them. Data fabric allows you to both read and write to data records without the need to migrate data. Whether it’s a CRM or ERP application, or even a relational database management system built in-house, data fabric can connect different data sources into a single, unified model.
Data fabric provides the flexibility to keep legacy systems running in the background—perhaps just as a database—while users interact with a modern interface with ongoing application support. This approach allows you to sunset old systems gradually during application rationalization. Now your IT team can replace systems at a time that is convenient for the business, rather than being forced into a fast, high-risk application modernization effort.
Don’t wait for a merger to start rebalancing
While we often view application rationalization as a housekeeping task, it becomes a business-critical necessity during mergers and acquisitions. When you combine two companies, you are immediately forced to rationalize the applications from each side to create a unified, consolidated holding. In that high-pressure environment, the ability to rapidly merge systems determines how fast the new entity can operate efficiently.
You shouldn't wait for a massive external event like an acquisition to get your application strategy in order. Treat application rationalization as an ongoing effort with continuous monitoring rather than a one-time crisis response. By constantly auditing your portfolio for value with tools like process intelligence and composability, you ensure your organization remains agile enough to pivot the moment the market demands it.
