Pathway to Legacy Application Retirement

It is a continuous effort to stay competent with technological advances and stay current. Hence, there is a need for companies to continually evaluate what is obsolete or inefficient and adapt to new tools and approaches. As the data grows over time, we start to observe the operations being slowed down, and with the changes in security standards and increased amount of creative security risks, the application may become vulnerable or cost more to keep it running. Such situations call for an upgrade or replacement of inefficient applications. Choosing more modern, scalable, secure alternatives will increase performance and better fulfill the consumers' demands. This article looks at application retirement from a data perspective, best practices, challenges, and how to manage and leverage data during this process.

Understanding Application Retirement

Application Retirement and Its Importance

Application retirement is the process of shutting down outdated, redundant, or legacy software or business applications while ensuring that critical data is preserved, accessible, and compliant with regulatory standards.

Retiring legacy applications helps reduce operational costs by getting rid of the need to maintain and support applications that are no longer required, redundant, or operationally vulnerable. Next, it improves security by phasing out applications that no longer receive security updates, thus making them less exposed to security threats and more compliant. Furthermore, it enables IT teams to focus on modernizations and innovations that add value to the company and stay current in the market.  

Drivers for Application Retirement

When we start thinking about retiring an application, there must be a level of discovery done and key areas need to be assessed. Below are some of the key drivers of application retirement.

Technological Advancements

With the advancements, new technologies keep evolving and facilitate better performance and productivity, this results in incompatibility with the traditional ones as they end up creating silos which in turn, slows down innovation. Legacy applications frequently need help to integrate with modern tools, cloud platforms, and APIs. Hence, switching to modern, scalable, and more robust systems will better support their business operations. 

Cost Reduction

Oftentimes, maintaining legacy systems requires specialized skills along with non-negotiable high licensing fees. In addition, outdated software/hardware leads to rising operational costs. A good way to work around this problem is to switch from legacy systems to modern systems which will enable the company to save on operational costs, including maintenance, service repairs, and labor costs.

Compliance and Security Risks

In some cases, older applications do not receive any future security updates or patches, which leaves them vulnerable to cyber-attacks and, in other cases, exposes the company to penalties of non-compliance, loss of data, or even reputational damage.

Upgrading to ERP Solution

Many organizations are opting for pre-built solutions that are ready to deploy because they are quick and require minimal configuration. Moreover, off-the-shelf ERP solutions are reliable, stable, cost-effective and need less maintenance. Upgrading to readily available tools helps organizations to deploy applications quickly and can be worry-free about future releases or staying current with the technology.

Performance Issues

When the legacy system is challenged with poor performance, it leads to a less effective user experience. For example, think of a website with very slow response times and security vulnerabilities. Replacing such systems with the latest solutions would enhance the overall performance.

Redundant Applications

It is not uncommon for organizations to accumulate multiple systems performing similar functions over a period. Discovery and assessment of existing applications and laying out the purpose of each tool will help identify overlaps. Retiring duplicate applications or consolidating them into fewer applications will optimize the system architecture, thereby reducing maintenance costs.

Digital Transformation

In a fast-evolving digital world, keeping up with technology is not only needed but is required to thrive in the rapidly changing market. Digital transformation is the path many organizations are opting to align technology and their business goals. Digital transformation empowers businesses to improve efficiency, enhance customer experiences, and stay competitive in the digital world.

Preparing for Application Retirement

In most cases, decommissioning an application can be a long and complex process. Simply because it requires thorough planning, collaboration, and consideration for everyone impacted — whether it’s employees, customers, or other stakeholders. Further, the application can be retired only after a replacement or alternate solution is found.

Identifying Candidates for Retirement

As discussed above, there could be several drivers for retiring an application; however, identifying involves a step-by-step process of conducting a thorough analysis. Factors like technical debt, business value, usage, age, maintenance costs, potential security risks, redundancy with other applications, and whether a suitable replacement exists or not influence the decision. If multiple applications are identified, a carefully curated roadmap has to be prepared so the transition can happen smoothly.

To gather valuable insights and make informed decisions, companies conduct surveys to gather as much information as possible from customers, and business stakeholders. Some of the key aspects that help determine the value and impact are:

• Purpose of the legacy application
• Utilization of the application by users or shadow systems
• Technical health of the application
• Age of the application
• Cost of maintenance, hardware, and licensing (operational costs if any)
• Any redundant applications with overlapping functionality
• Estimated cost and time to implement and adapt a new system
• Feasibility and cost of new implementation

An application retirement follows one of these 3 strategies:

1. Sunsetting: It follows a phased approach where the legacy system is gradually sunset after informing the users of a planned end-of-life date. The old functionality is replaced with workarounds or alternate solutions.
2. Decommissioning: Switching to a new solution altogether by removing the legacy solution from production completely.
3. Consolidation: Combining the functionalities of multiple applications into a single, streamlined system. 

Establishing a Retirement Roadmap

Regardless of the retirement strategy chosen, a well-defined retirement roadmap is critical for a successful application retirement process. This roadmap should outline, but is not limited to, the following:

• Timeline
• Milestones
• Resources required for the project and the cost
• Potential risks and their impact
• Mitigation plans to address any unforeseen challenges

Steps Involved in Retiring Applications

1. Evaluating the Purpose and Impact on Business Operations

Applications are built to help support a business use case or business operations of a company; so, evaluating the impact on business is a key step in the retirement process. Impact analysis uncovers the end-to-end workflows, identifies the dependencies, and discovers any shadow systems. Finally, it aids in developing a mitigation plan to ensure a smooth transition.

2. Engagement

Like in any project, effective communication and collaboration with stakeholders is vital throughout the application retirement process. To get an in-depth understanding of application usage by different types of users, active engagement with stakeholders, internal/external partners, IT teams, business units, compliance officers, and sometimes with sponsors is also required. It provides them with an opportunity to express their concerns and requirements early in the process, enabling the project team to address those so the teams can stay aligned on the project goal.

3. Communication Strategies

Understandably, change is often hard, yet it remains a constant. To mitigate resistance to change and maintain transparency, clear and frequent communication is encouraged to keep all parties informed about the progress and set expectations. Additionally, providing training and support to users transitioning to new systems ensures a smoother adoption process.

4. Data Migration and Archival

When transitioning to a brand-new system, there might not be a lot of flexibility to import or convert everything that we have in the legacy system into the new system. For example, assume you have a legacy system that is 50 years old. You do not necessarily need all the 50-year-old data to be migrated to the new system. There might be only a subset of data that might be essential or critical, which should be transferred to the new system, and there might be another subset of data that should be preserved or archived for historical purposes. In this example, the former subset will follow the migration strategy, and the latter will follow the data archival strategy. For this, first, we need to identify the data assets that fall under each strategy, and, next, classify them based on their importance and sensitivity (e.g., personal data, financial records) to choose the right tool that is compliant.

Strategies for Data Migration and Archiving

Data migration strategy involves exercises such as data mapping, Extraction, Transformation, and Loading (ETL) and this cycle may need to be repeated until all the data is converted and migrated successfully into the new location.

Data archival solutions for storing historical data should support long-term storage, searchability, and data encryption to protect the data stored in it.

Whether it is data migration or archiving, rigorous validation should be done to ensure the correctness and completeness of the data. Strategies like comparing pre- and post-migration data sets can be employed to identify inconsistencies in the data and take steps toward correcting them.

5. Compliance and Security

Regulations such as GDPR, HIPAA, and other standards provide guidelines on how to handle, store, and dispose of data, especially when it comes to sensitive or personal information. Knowing these rules will help you avoid fines and legal trouble.

Compliance During and After Retirement

To comply, you need to have clear protocols for data handling during the retirement process. This includes:

• Documenting data retention policies to decide what data to keep and for how long
• Using secure data deletion methods for data that’s no longer needed so it can’t be recovered
• Keeping detailed records of the retirement process including data migration, archival, and deletion activities

6. Data Security During Migration and Archival

Data security is key during the application retirement process, especially during data migration and archival. Some aspects to consider in keeping data secure are as follows:

• Using encryption to protect data in transit and at rest
• Access controls — who can view or modify data
• Monitoring to detect issues or vulnerabilities

7. Addressing Potential Security Vulnerabilities

Legacy applications often have inherent security weaknesses that can be exploited during the retirement process. Conducting a thorough security assessment can help identify these vulnerabilities. Measures to address these may include:

• Applying the latest security patches and updates to the retiring application before migration
• Using secure data transfer methods to prevent interception or tampering
• Implementing a comprehensive incident response plan to address any security incidents that arise during the retirement process

Tools and Technologies for Application Retirement

Retirement Management Tools    

Several platforms are available that can be used to facilitate the entire application retirement lifecycle. Using dedicated application tools is usually more beneficial than executing each step of the retirement process manually which results in less error and more efficiency. Some of the popular application retirement platforms are as follows:

IBM Infosphere OPTIM

This is an IBM product specifically designed for data archiving and management which is crucial for retiring applications by preserving necessary historical data and using proprietary compression technology enabling space saving for a high volume of data.

Mimecast

Mimecast offers a wide array of sources of data to import from as well as flexibility on the datatypes that can be imported and how they are stored and retrieved — well suited if the archived data has frequent retrieval and reporting requirements.

Bloomberg Vault

Apart from its wide assortment of data archival features, it also comes with a few regulations’ obligatory features like consolidated compliance, legal search, and retention management. It is highly scalable due to being cloud-based and has custom features catering to the financial industry.

Barracuda Message Archiver

This is one product that excels in archiving messages. It not only offers strong email archiving capabilities but also excels in features like legal hold, retention, and eDiscovery.

Selection Criteria for Choosing the Right Tool

When it comes to selecting the right tool for data archival, one needs to be mindful of a few basic selection criteria:

Compatibility

The source data (which must be archived) can vary from case to case. Not all data archive tools support all data types of file formats. For instance, if the intended decommissioned data is from the mainframe, IBM Infosphere OPTIM may be a good choice as it supports mainframe compatibility.

Scalability

If the requirement demands a constant need to archive data, over an extended period at a variable pace and there are chances that there can be a surge in the volume of data to be archived, using a public cloud-based archival system like Google Vault is recommended.

Compliance Features

Although most archival tools offer some sort of compliance features, if the requirement is to enforce complex regulatory requirements specific to geographies, audit trails, or highly customized data retention policies, then choose the tool that allows you to implement the specific policy. For instance, Mimecast has a wide assortment of options for various compliance needs and may be a good fit for most cases.

Ease of Use

In most cases, there is a requirement for ease of use, where the users implementing data archival solutions are not too technical, all the public cloud-based data archival solutions have decent ease of use. Usually, one needs to be mindful of the tradeoff between ease of use and advanced features tailored to your needs.

Challenges and Mitigation Strategies

Common Challenges

Data Loss and Integrity Issues

Data loss can occur when the archived data gets moved from the source to the destination systems. Some of the main reasons for data loss and integrity issues are incompatibility of the data types, incomplete migrations, or incorrect mapping between source and destination systems. This can potentially lead to the data volume difference in the archival systems, or data formats that make it unusable for retrieval or incompliant with regulations.

Stakeholder Resistance

Often owing to the fear of loss of a system they are comfortable working with over the years, or insecurity over the loss of data querying ability, many business stakeholders often resist data migration initiatives. This leads to user groups getting reluctant to adopt new systems and archive existing ones, leading to operational inefficiency and decreased productivity.

Regulatory and Compliance Risks

When the archived data moves from the source to the destination systems, there is often the risk of non-adherence to the regulatory and compliance standards. Often, the archived data may fail to meet the regulatory checks specific to the destination system and not adhere to the local compliance guidelines, if they are not considered prior to the archival processes.

Mitigation Strategies to the Common Challenges

Comprehensive Data Validation

Rigorous data validation strategies need to be implemented to mitigate data loss and integrity issues. Some of the commonly employed methods include conducting extensive pre and post-archival testing and comparing basic statistics, using automated validation scripts and implementing checksums to ensure data consistency, and regularly auditing data to identify potential data issues before they happen and correct them.

Early Engagements of Stakeholders

It is the key to avoiding stakeholders’ resistance even before data archival initiatives can begin. Communicating early and clearly with the stakeholders during the archival process can allay the fears and apprehensions that they might have regarding the process. Conducting training sessions and supporting them with their queries further cements their confidence in the archival process. It is recommended to involve key users of the stakeholder group in the strategic phase of the archival process to foster ownership and buy-in.

Ensuring Compliance

To ensure adherence to compliance, there needs to be a clear understanding of all the compliance requirements and governance frameworks right from the beginning of the archival process. For instance, if the archived data is getting moved to Europe, the archival process should incorporate processes to adhere to the General Data Protection Regulation (GDPR) which is mandatory in the EU. Furthermore, it is recommended to keep all the detailed before and after record counts and other key figure snapshots and audit trails. Implementing disposal policies and data retention on data objects is another way to meet compliance standards.

Apart from the aforementioned, choosing the right tools can ease the retirement and archival process. Tools that have decent migration features and offer data management compliance features often significantly mitigate common data migration challenges.

Case Study: Archiving Sales Data for a Wholesale Pharma Distributor

Background

A leading wholesale pharma distributor has sales data spanning several decades. Due to compliance regulations, the organization needs to retain only 10 years of data and decommission and archive the prior data. The primary challenge was to securely archive this older than 10 years data while keeping it accessible for Business intelligence reporting.

Solution

As this historical data originated out of IBM Mainframe, this datatype constraint meant that only a few of the existing data archival tools were in consideration. IBM Infosphere Optim was finally chosen as it fit the compliance and business intelligence requirements and there were no scalability requirements foreseen in the lifecycle of the archived data.

The implementation involved several key steps.

1. Data assessment and classification: The sales data was classified based on the value of the business, relevance to end-user reporting, and scope of applying retention policies. Furthermore, the data that qualified for retention was sub-classified into regulatory policies and historical value.
2. Secure data migration: The Archival tool was employed to convert the data from the source format to archived format and then migrated to the new migration vaults for safe storage. Retention and regulatory hold policies were applied to individual data objects so that after each year, older data gets deleted by itself and it is also ensured that some perpetual data objects are never deleted. Check sums, counts for pre and post migration and compared to ensure there is no loss of data. Audit trail is retained for compliance.
3. Stakeholder engagement: Key stakeholders in the business were engaged throughout the process. People who depended on this data for analytics reporting were familiarized with the revised process of reporting from the archives. Compliance teams were familiarized on how to ensure that retention policies have worked or not.

The implementation resulted in several benefits for the pharma distributor.

1. Enhanced compliance: This effort ensured that the organization stayed within the compliance mandate, while still providing easy accessibility of the data to the stakeholders.
2. Improved cost savings: The decommissioning of the erstwhile application and the associated data saved 30% cost associated with storage and maintenance of those applications translating to several thousand dollars in annual savings.
3. Improved data accessibility: Despite being archived, the portion of the data that has business value remained accessible to the users using business intelligence applications and historical analysis initiatives.

This case study is a testimony of how a wholesale drug distributor effectively managed the decommissioning and archival of an astonishing amount of historical sales data using IBM Infosphere Optim to stay in the path of compliance and regulatory guardrails, still delivering data accessibility to the stakeholders and secure a healthy cost saving.

Future Trends in Application Retirement

AI-Driven Data Management

Application retirement and data archiving are set to be revolutionized by automation in data management using AI. AI-based tools can automatically identify and classify data more precisely which enables the preservation of relevant data. This automation ensures lessened human intervention which leads to increased data quality performance and a more streamlined and cost-effective retirement process.

Automation in Migration and Archiving

Automation technologies are playing an important part in data migration and archiving. Automation workflows can handle repetitive tasks in the data engineering and integration domain, specifically in Extraction, Transformation, and Loading (ETL) with increased speed and precision. Also, it allows for the integration of a wider array of data sources.

Scalability With Cloud-Based Archival Solutions

Cloud-based data archival applications have the inherent feature of scalability which is particularly useful for cases where the data archival process will likely continue for a large duration and unexpected volume surges may occur. Organizations in such scenarios do not need to plan about provisioning storage in advance and avoid the cost of hefty upfront storage investments for archived data.

Enhanced Security and Compliance in Cloud Archival Solutions

Most of the cloud archival solutions have inbuilt advanced security features like encryption and multi-factor authentication, which seamlessly ensure the security of the archived data during migration and throughout its lifecycle. Additionally, they offer built-in compliance tools that help the users adhere to the regulatory guardrails more effectively.

Leveraging Historical Data

As the impetus to incorporating machine learning models in the enterprise grows, with it grows the need to train those models with historical data. As such, archived data are good sources for not only business intelligence reporting, but also are very useful in training machine learning models. As such, by leveraging historical data, organizations can gain previous insights into patterns, trends, and overall customer behavior. It is anticipated that leveraging archived data for Business Intelligence and machine learning will be an integral component of the archived data lifecycle.

Conclusion

As and when enterprises look to modernize their applications and upgrade to newer infrastructure, generally to avail new features, reduce operational costs, or just to remain compliant, there arises a need to decommission the existing applications and archive the associated data. This helps organizations seamlessly transition to modern and mode efficient solutions while still retaining the capability to look back at their historical archived data whenever they need to. This unique capability avoids risks with data loss, regulatory non-compliance, and security vulnerabilities while maintaining operational efficiency.   

Key Strategies for Success

There are several key strategies that can ensure a successful implementation of a data archival endeavor. To begin with, a comprehensive data validation before and after the data archive state ensures data integrity and quality, while engaging stakeholders early in the archival process ensures smoother participation. Lastly, implementing a reliable governance framework in the archival process is the key, and while doing so, several tools have these built features that make life much easier while implementing. Leveraging AI in this whole process has its own set of benefits like increased automation in the data preprocessing and transformation phase. It is also equally important to remember that data is gold, so there must be a clear strategy for the accessibility aspect of the archived data. While business intelligence out of the historical data is an apparent benefit, it can do wonders in training the ML models with historical data too.

Final Thoughts

In conclusion, application retirement and data archival is not just a business requirement and technical necessity but a strategic opportunity as well. Organizations can adopt the best practices of data archiving aided by the right tools to turn the decommissioned archived data into a pathway for modernization, cost savings, and strategic assets which fuels future growth and innovation. Embracing data archival the right way will propel organizations to the pathway of modernization, with clear accessibility to their past.