Agile Forum
Data Driven Application Modernization Priority:
Imon Rashid
November 11, 2024.
(All Rights Reserved)
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Introduction to Data Driven Application Modernization Priority
As our organization evolves, managing and modernizing legacy applications has become critical to maintaining operational efficiency, security, and scalability. This requires an evaluation to determine their viability in today’s technological landscape. The assessment aims to identify which applications should be maintained, modernized, or retired to better align with organizational priorities and technological advancements.
Given the age and varied functionality of these applications, it is essential to assess each against specific criteria, such as user engagement, frequency of use, strategic relevance, vulnerability, vendor support, and infrastructure costs. This structured analysis will enable us to prioritize investments and focus on applications that continue to add value while reducing resources devoted to outdated or redundant systems.
The findings and recommendations from this evaluation are typically presented to a decision-making team to guide the organization’s long-term technology strategy. By systematically addressing the need for application modernization, we can ensure that our technological infrastructure supports future growth, enhances productivity, and reduces operational risks.
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The Role of Data-Driven Modernization in Application Transformation
Data-driven modernization leverages insights from data analytics to optimize legacy application transformation, ensuring that modernization efforts are strategic, efficient, and aligned with organizational goals. By analyzing relevant metrics—such as user engagement, application performance, cost efficiency, application support, and security vulnerabilities—organizations can make informed decisions on which applications to retain, modernize, or retire.
A data-driven approach enables organizations to assess the actual value each application brings. For instance, applications with high user engagement and critical business functions can be identified as candidates for enhancement or re-platforming, while those with minimal usage or functionality overlap may be considered for consolidation or decommissioning. Analyzing usage frequency, infrastructure costs, and performance trends over time also provides insight into the resource demands of each application, enabling more cost-effective planning.
Moreover, data-driven insights help reduce modernization risks by identifying dependencies, security risks, and operational inefficiencies early in the process. Understanding these factors allows for targeted, strategic investments that minimize disruption and maximize return on investment. Automated analytics tools and predictive modeling can further support modernization by projecting future needs, optimizing resource allocation, and enabling scalable, future-proof technology choices.
Ultimately, data-driven modernization allows organizations to align their technology assets with current and future business needs, ensuring that modernization decisions are based on objective, measurable factors. This strategic approach fosters a resilient and adaptable IT environment that supports sustainable growth and operational excellence.
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Factors to consider in what data is important:
The data required for application modernization efforts will depend on the type of organization, operational needs, and industry.
Assessing which data is essential for application modernization efforts requires a strategic approach tailored to your organization's unique context. Here are expanded factors to consider:
Organizational Goals: Align data collection with your organization's strategic objectives. Identify which applications are critical for achieving short-term and long-term goals. Data that supports these initiatives is crucial.
Operational Needs: Evaluate the specific operational requirements of your organization. Determine which data points are necessary to streamline processes, improve efficiency, and reduce costs. This might include data on application performance, user interactions, and operational workflows.
Industry Standards and Regulations: Different industries have specific standards and regulatory requirements. Identify data that ensures compliance with industry regulations, market trends, and best practices. For example, in the financial sector, data security and transaction integrity are paramount.
Stakeholder Requirements: Understand the needs and expectations of various stakeholders, including customers, employees, and investors. Determine what data is essential for them to make informed decisions and ensure satisfaction. This may involve collecting feedback, usage patterns, and satisfaction metrics.
Data Quality and Integrity: Prioritize high-quality, accurate data. Ensure the data collected is reliable, consistent, and relevant to your modernization efforts. High-quality data enables better decision-making and reduces the risk of errors.
Security and Compliance: Assess data security requirements, especially for sensitive information like personal data and financial records. Ensure that the data collected complies with privacy laws and security standards to protect against breaches and ensure trust.
Cost-Benefit Analysis: Weigh the costs associated with collecting, storing, and analyzing data against the potential benefits. Prioritize data that offers the highest return on investment and contributes significantly to your modernization goals.
Key Stakeholders for Data Collection
Effective data-driven application modernization requires accurate and comprehensive data, which can only be obtained through collaboration with key stakeholders across various departments. The following roles within the organization are essential contacts for gathering relevant data:
IT and Infrastructure Teams
Role in Data Collection: IT and infrastructure teams are responsible for managing the organization's technology stack, including application usage, infrastructure costs, and vendor support details. They can provide insights into application performance, maintenance costs, security compliance, and dependencies on other systems.
Key Contacts: IT Operations Manager, Infrastructure Lead, Systems Administrator.
Application Owners and Product Managers
Role in Data Collection: Application owners or product managers are directly involved in the strategic and operational use of each application. They can provide details about the application's purpose, user engagement, and alignment with business goals. These individuals understand the criticality of each application and its role within the organization.
Key Contacts: Product Manager, Application Owner, Business Analyst.
Finance and Budgeting Teams
Role in Data Collection: Finance teams are essential for assessing the financial impact of each application, including infrastructure and maintenance costs. They can provide data on cost allocations, historical spending, and financial projections that are critical for a cost-benefit analysis.
Key Contacts: Financial Analyst, Budget Manager, CFO (Chief Financial Officer).
Cybersecurity and Compliance Teams
Role in Data Collection: These teams can supply data on each application’s security status and regulatory compliance. They are instrumental in identifying applications that pose security risks or require urgent updates to meet compliance standards.
Key Contacts: Chief Information Security Officer (CISO), Compliance Officer, IT Security Lead.
Human Resources (HR)
Role in Data Collection: HR can provide data on employee roles and user engagement by specific teams, allowing a better understanding of who uses each application and how frequently. They also assist in identifying any training needs that modernization may necessitate.
Key Contacts: HR Business Partner, HR Data Analyst.
Executive Leadership and Decision Makers
Role in Data Collection: Executives and department heads often provide strategic insights, defining long-term goals and priorities for the organization. Their input is crucial in aligning modernization efforts with organizational objectives and in ensuring that high-level goals are integrated into prioritization.
Key Contacts: CEO, CIO (Chief Information Officer), Department Heads.
Line Managers
Role in Data Collection: End users interact with applications daily, providing practical insights into usability, efficiency, and pain points. Their feedback on functionality, ease of use, and frequent issues can reveal essential information for modernization decisions, especially regarding user experience improvements and workflow optimization.
Key Contacts: Team members across departments who actively use the applications in question.
End Users
Role in Data Collection: Line managers oversee teams that use these applications and understand both team needs and application effectiveness in supporting daily tasks. They can identify high-impact issues, suggest specific enhancements, and provide feedback on how well each application meets their team’s operational needs. Their insights are also valuable in assessing the criticality of applications within specific workflows.
Key Contacts: Department or team managers directly managing users who rely on each application.
By collaborating with these stakeholders, the data collection process becomes more robust, ensuring that all relevant metrics are considered. Engaging these key contacts will provide a holistic view of each application's operational and strategic value, supporting a more accurate and effective prioritization for modernization.
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Data Criteria to Consider:
Creating a strategic approach to application modernization is crucial for maintaining efficiency, security, and relevance in today's rapidly evolving technological landscape. To guide this process, it's important to evaluate each application based on a set of key criteria. These criteria ensure that modernization efforts are aligned with organizational goals and resource allocation is optimized. The following list outlines the essential factors to consider when assessing which applications should be prioritized for modernization. By systematically evaluating each application against these criteria, organizations can make informed decisions that support their long-term technology strategy, enhance productivity, and mitigate operational risks.
Number of Users:
Assess the total number of active users for each application. This helps determine the application's reach and its importance within the organization. Applications with more users generally have a higher priority for modernization to avoid disruption to a large user base. Ensure a minimum of two users to justify its continued use.
Frequency of Use:
Evaluate how often the application is used (e.g., daily, weekly, monthly). Applications with high-frequency usage are critical to daily operations and thus may need more immediate attention. Less frequently used applications might have lower priority unless they serve vital functions.
Application Purpose:
Understand the core purpose of each application. Determine if it supports essential business functions, strategic goals, or specific department needs. Applications central to mission-critical operations warrant higher priority for modernization.
Application Vendor Support:
Assess the level of support provided by the application’s vendor. Consider factors like the availability of updates, customer service, and technical assistance. Applications with strong vendor support may be easier to maintain, while those with limited or no support may need urgent modernization or replacement.
Infrastructure Support Cost:
Calculate the costs associated with supporting the application’s infrastructure. This includes hardware, software, and other resources required to keep the application running. High infrastructure costs can justify modernization efforts to streamline operations and reduce expenses.
Security Compliance:
Evaluate the application’s compliance with current security standards and regulations. Applications that handle sensitive data or are crucial for regulatory compliance need to be secure and up to date to mitigate risks. Non-compliant applications may require urgent modernization to address security vulnerabilities.
Maintenance Cost:
Determine the ongoing costs of maintaining each application, including bug fixes, updates, and troubleshooting. High maintenance costs can indicate that an application is outdated or inefficient, suggesting a need for modernization.
Used by Decision Makers:
Identify if the application is used by key decision-makers within the organization. Applications that are critical for executive decision-making processes hold higher strategic importance and may need prioritization to ensure they are reliable and efficient.
Alternate Application Availability:
Check if there are alternative applications available that can serve the same purpose more efficiently. If a modern and supported alternative exists, it might be more cost-effective to transition to the new application rather than investing in modernizing the old one.
Considering these criteria will help create a comprehensive evaluation framework for determining which applications should be prioritized in your modernization efforts. This structured approach ensures that resources are allocated effectively, addressing the most critical needs first.
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Create a Matrix :
Create a matrix for prioritizing application modernization efforts using the collected data, follow these steps: Begin by identifying key criteria such as user engagement, frequency of use, strategic relevance, vulnerability, vendor support, and infrastructure costs. Assign weight to each criterion based on its importance to your organization’s goals. Next, evaluate each application against these criteria, scoring them on a consistent scale (e.g., 1 to 10). Multiply each application’s score by the corresponding weight for each criterion, then sum these weighted scores to calculate a total score for each application. The resulting scores will indicate which applications have the highest priority for modernization based on their overall importance and impact. This matrix provides a structured and objective approach to decision-making, ensuring resources are allocated efficiently to enhance operational efficiency and support strategic growth.
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Sample Process to Create the Matrix:
To create an Excel matrix that helps evaluate which legacy applications should be modernized or discontinued, use a weighted scoring approach for the given criteria. Here is a basic framework for your requirements, which can be translated into an Excel sheet:
Applications : Each application should have its own row.
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Criteria Weighting:Â You need to assign a weight to each criterion, as some are more important than others. Below is a sample example of weighting suggestion:
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              Number of Users                                                                        (Weight: 15%)
              Frequency of Use                                                                       (Weight: 10%)
              Application Purpose                                                               (Weight: 15%)
              Vendor Support                                                                          (Weight: 10%)
              Infrastructure Support Cost                                                 (Weight: 10%)
              Security Compliance                                                               (Weight: 15%)
              Maintenance Cost                                                                     (Weight: 10%)
              Used by Decision Makers                                                     (Weight: 10%)
              Alternate Application Available                                         (Weight: 5%)
=================================================
Total                                                                                                    ( Weight: 100%)
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Scoring: You need to define scoring values for each criterion. For example:
Number of Users:
·  0-1User: 0 points
·        2-10 Users: 3 points
·        10+ Users: 5
Frequency of Use:
·        Daily: 5 points
·        Weekly: 3 points
·        Less frequent: 1 point
Application Purpose:
·        Operational: 5 points
·        Supports Operation: 3 points
·        Informational: 1 point
Vendor Support:
·        Supported: 1 point
·        Discontinue 1-2 year: 3 points
·        Not supported: 5 points
 Infrastructure Support Cost:
·        Low: 1 points
·        Moderate: 3 points
·        High: 5 point
 Security Compliance:
·        Compliant: 1 point
·        In-risk of non-compliance: 3 points
·        Not compliant: 5 points
  Maintenance Cost:
·        Low: 1 point
·        Moderate: 3 points
·        High: 5 points
  Used by Decision Makers:
·        Yes: 5 points
·        No: 0 points
  Alternate Application Available:
·        No: 5 points
·        Yes: 0 points
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Weighted Score Calculation:Â In a spreadsheet, use formulas to calculate the weighted score for each application.
               Example formula: `= (Number of Users Score 0.15) + (Frequency of Use Score       0.10) + ... + (Alternate Application Score * 0.05)`
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Matrix Layout: In the spreadsheet, the columns will be:
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 Decision Criteria: After calculating the weighted score for each application, you can sort them by score to prioritize which applications to modernize, maintain, or discontinue.
This approach should help in presenting a clear, data-driven recommendation to the decision-making team.
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Conclusion
This data-driven framework for application modernization prioritization provides a structured approach to assess legacy applications based on criteria like user engagement, operational relevance, and cost efficiency. However, it’s essential to recognize that this is not a one-size-fits-all solution. Each organization’s unique context, goals, and constraints should guide the application of this framework.
The importance of each criterion may vary depending on specific organizational priorities, industry standards, and operational needs. For instance, in some organizations, security compliance may outweigh user engagement, while in others, cost efficiency could take precedence. Decision-makers should carefully tailor the weighting of criteria and the scoring methodology to reflect their organization’s strategic objectives and operational realities.
In essence, this framework serves as a flexible guide to help navigate the complexities of application modernization. By customizing it to your organization's unique requirements, you can ensure that modernization efforts are both strategic and aligned with your long-term goals, ultimately fostering an IT environment that is both resilient and adaptable to future demands.
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