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Application Rationalization Oversimplified
Most application leaders, or whoever is accountable for the organization’s software assets, come to a point where they are presented with the challenge of application rationalization (App Rat). Sometimes this comes from within IT as an effort to address neglected technical adequacies; sometimes this is more top down as an effort to reduce software costs or enable some initiative that is held back by an overly complex application environment. Regardless, App Rat can solve a lot of different problems and open a lot of doors, which is why it should be viewed as a mainstay process of any IT department. However, it is rarely the quick and easy solution that many suggest.
Let’s first oversimplify application rationalization
A simple description of application rationalization is that it is a decision-making framework applied to your applications. It can be customized for several use cases, but simply put, it helps support decisions regarding the ideal future state of your applications and the effort required to get there.
So what is a decision-making framework? It’s a rules-based system that supports the decision-making process for a specific objective. It can be viewed as consisting of four main components:
- The object, the item undergoing an assessment and having a decision or recommendation applied to it.
- The inputs, information or data points related to the object that will act as criteria for the assessment.
- A rules-based system, a formula, algorithm, or some logic designed to process the information based on established overarching objectives.
- The outputs, which is the resulting decision, recommendation, or prioritized alternatives that inform the decision maker.
Applying this model to App Rat:
- The object is your applications.
- The inputs are application data points, commonly some expression of cost, value, health or risk, and performance.
- The rules-based system is often weighted scorecards, decision trees, or matrices.
- The outputs, often described as a disposition, can range from should the application be kept or retired to more comprehensive decisions like which apps should you move to the cloud, which redundant apps should be consolidated, or which apps should have their maintenance needs and enhancement requests prioritized up the backlog.
This visual illustrates the object, inputs, and output of App Rat.
Why does this make application rationalization challenging?
1. The Object
Often the biggest and most upfront hurdle in App Rat is agreeing on what is the application. Some take a more technical perspective and view every single individually deployable unit as an application. Some take a functional perspective and only consider what the user interacts with. Others see a line item on their budget that needs to be managed accordingly. Applications can be broken down many ways. It is essential to establish a shared definition between those doing the assessment and those who ultimately sign off on a decision. Those who do not, start poorly and fail quickly.
2. The Inputs
To make valuable use of App Rat, you require specific, accurate, and up-to-date information. This will likely include some representation of value, cost, health, and overlapping functionality with other applications depending on the goals of rationalization. That decision-making framework only generates helpful or meaningful outputs when you apply appropriate information. Otherwise, you will likely misinform decision makers on the best possible option and undermine the purpose of this effort altogether.
This is how App Rat can become one large data collection initiative if you let it. Most organizations ignore or struggle to maintain basic application information, especially in overly complex environments where establishing less-tangible data points like business value is challenging. The real value of App Rat comes when applied regularly and as part of an ongoing practice of application portfolio management, where best practices are modified to work within an IT team’s capacity and access to information.
3. The Rules & Outputs
The more complicated the decisions you are trying to support, the more data points you require, and the more rules or logic you need to build within the decision-making framework. If you are executing App Rat as a part of general governance function, such as monitoring the lifecycle of applications and ensuring cost is justified by an application’s value, then it can be straightforward. However, if you’re applying App Rat to enable some larger transformative initiative, like a large migration to the cloud or legacy modernization, you need more specific data and visibility deeper into the application stack to understand the full picture of software components, databases, or even infrastructure.
Some application portfolio management vendors, like CAST Highlight or LeanIX, have built-in features so their App Rat framework supports cloud transitions.
This is why you need to carefully craft a rationalization framework to support those more-complex decisions you are trying to make. Info-Tech recommends your time and effort is better served on discovery efforts and architectural modeling than building or customizing an elaborate App Rat tool.
What is the purpose of application rationalization?
Too often App Rat is applied with hopes of automating the decision-making process. Many believe this will bring ease and speed up realization of the benefits or that it may remove the accountability from any unintended consequences associated with the results.
That’s not how it works.The true purpose of rationalization is to make decisions:
- More consistently
- More aligned to overarching goals established by the business
- Less subjective
It should even be noted that rarely are the results of App Rat for a specific application a mystery. Those familiar with an application and the goals for the portfolio could most likely tell you the most appropriate disposition or action for an application. Beyond a framework to better understand your applications, the real the purpose of App Rat is to:
- Limit the bias of application stakeholders. Ideal App Rat combines several perspectives to arrive at the best possible recommendation.
- Present the logic of the recommendation to the final decision maker. More often than not, whomever gets the final says does not know the full landscape. App Rat shows the data points and the rationale for reaching the best possible recommendation.
There are many vendors that offer a simple approach to rationalization. But if your needs are outside of the simple approach, finding the right tool to perform rationalization is not your largest obstacle. You need to build in the processes of collecting the right information and crafting your own analysis.
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