Guide to sunsetting legacy ECM and EDRM systems

A legacy EDRMS is no longer a fit-for-purpose solution for organizations that wish to limit risk and improve productivity. Learn why and how to move to a modern records solution.

Written by

Brenda Prowse

Reviewed by

Adam Roberts
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Legacy systems create risk

If your organization uses an on-premises electronic document and records management system (EDRMS), it has likely been part of your records management toolkit for a long time. When adopted, it may have been state-of-the-art and allowed records and information management professionals to do their jobs. But over the years, this system has grown increasingly outdated and can now safely be considered a legacy system.  

Modern enterprise organizations face significant cybersecurity threats and many data privacy and records management regulations. When organizations have a growing number of cloud-based platforms and file shares and a growing collection of data, including sensitive data such as personally identifiable information (PII), these challenges are more complex.

With these pressures, a traditional EDRMS is no longer a fit-for-purpose solution for organizations that wish to limit risk and improve productivity. While your technology stack has evolved to accommodate your growth, your legacy EDRMS hasn't changed.

This guide is aimed at organizations worried about the cost, risk, and productivity impact of a legacy EDRMS. The guide will explain the problems of using a legacy EDRMS, how they impact businesses, and show a way forward to leaving these outdated solutions in the past.

Outdated systems are known as legacy systems. These systems lack the ongoing feature development and support needed to help maintain a company's growth. Yet companies continue to use them because they technically still work as intended, and moving to a new system requires investment. The status quo is seen as "good enough." But, sticking with a legacy system will ultimately cause more issues in the long term. Here are a few problems with continuing to use your legacy system:

Higher costs

On-premises systems require in-house infrastructure and ongoing maintenance from your team. Switching to a cloud system can help reduce those costs. A true SaaS product doesn't have additional expenses to cover infrastructure and maintenance costs. A true SaaS product differs from a hosted SaaS, where you must pay additional fees for server licenses, infrastructure, maintenance, and backup and recovery systems.

Don't view a legacy system as something you must continue investing in. Change may be necessary to save on long-term expenses.

Lack of centralized control over data policies

Your current data legacy system may have multiple individual policies to handle all the data it collects. One survey suggests more than 20 percent of companies collect data from over 1,000 sources.  

With so many different sources, it's too easy for inconsistencies to appear. It's complicated to correctly identify and handle sensitive data like personally identifiable information (PII). If you aren't confident that data is classified accurately, it's a big red flag that you're not meeting compliance standards.

Identifying and managing your data may seem impossible, but adopting a centralized platform with blanket retention and disposal policies can achieve this.

Over-reliance on end users

Employees play a crucial role in data retention policies for a legacy EDRMS. They must accurately classify every file, email, and document an employee touches. It's a responsibility with heavy consequences, but even the most diligent employee can make mistakes, especially if data management isn't their core role.  

You can only be as strong as your weakest link. Relying on end users to perform tasks correctly can compromise security and breach compliance standards.

Over-relying on employees also stops the company from having direct control over data policies and enforcement.

Little to no automation or ML features

It's not a secret that your company is drowning in data. The average organization’s data volumes grow by 63 percent per month, according to one survey.

Data professionals are having difficulty keeping up with this amount of data. Manually managing records is not a feasible solution.

Incorporating automation and machine learning into your data management process can help you organize data faster without a hands-on approach.

No data oversight on sensitive information

It's not optional to protect data. By the end of 2024, 75 percent of the world's population will be covered under modern privacy regulations. Your organization risks breaking the law if you don't take the necessary steps to protect it from data breaches.  

But you can't secure sensitive data if you don't know you have it.

Without an accurate picture of your sensitive data, your organization can't manage its security or impose data policies necessary for compliance. In the event of an audit or data breach, your organization could face hefty fines or the loss of public trust.

The future of legacy systems is unknown

Legacy systems are already becoming an assortment of several solutions that don't work cohesively. As competing platforms acquire products, you face security concerns, an inability to receive support, and a lack of timely development.

Take Micro Focus, for example. Over the years, it's been through several mergers and acquisitions (M&A) and was recently bought by OpenText, with its future in question. With every M&A, the priorities of products like Micro Focus could change. You may struggle with knowing what's next for the product's future and if it will still meet your company's needs.

Your organization may already be on the path to moving to another solution, and it's better to make the change now. With a well-timed move, you can save yourself from increased security risks and future turmoil.

A primary concern for your company may be the fear that migrating your records management system will not provide a return on investment. It's a large project to transfer data without impacting business operations, meet privacy and compliance standards during the transition, and set up a new system to work correctly. And that's not even mentioning the costs of purchasing a new records management system and possibly ending contracts with your previous system.

Your organization's leadership team may have a poor understanding of the benefits of strong records management, making the argument for investing in a new system much harder.

But you may need to move forward with sunsetting your legacy systems, given stringent data security and privacy regulations. In the long term, an updated records management system will be easier to manage, ensure compliance, and keep privacy strong.

It's paramount for the transition to be seamless. While not an easy task, making a solid plan and using equally strong tools is possible.  

The first question to answer is if you plan to transform your data for the new system or have a lift-and-shift approach.

Then, you can move forward with an idea of what needs to be done. The migration stage involves three phases:

  1. Planning: Making a plan is vital to a successful migration. You'll need to prepare what data is getting transferred and how it will happen.
  1. Migration: When migrating data, organizations should continuously test to ensure data integrity is maintained, the new system works, and minimize downtime.
  1. Post-migration: Establish testing to ensure data was successfully migrated and create a plan for ongoing management of the new system.

There are a few paths you can pursue to migrate legacy data and sunset your legacy system:

Manage in-place

It's possible to manage existing data in place as a temporary solution. It's a good option for the transition stage because it doesn't interfere with employees' ability to work.

A tool like RecordPoint can gather all your data into one central location. Not only does it add consistency to your data management, but it can also work for modern SaaS solutions or legacy EDRMS.

Migrate everything

Migrating your data to a new data management system may seem a good choice. The lift-and-shift approach doesn't leave behind any potentially valuable data. In reality, this poses some challenges.  

It's a significant effort to migrate high volumes of data. On top of that, transformation may need to happen for the metadata to be supported on the new platform. It may not be worth the effort to transform all data simply to realize you don't need and delete it.

Migrate high-value content

RecordPoint recommends only migrating high-value content. Reducing the volume of data can make it easier and cost-effective to transfer to a new platform. However, this requires an organization to identify and classify its current data. You'll also need to consider what is high-value content. For some organizations, this can include:

Post-migration: Establish testing to ensure data was successfully migrated and create a plan for ongoing management of the new system.

• Personally identifiable information (PII)

• Payment card information (PCI)

• Protected health information (PHI)

• Data as part of a long-term retention plan

• Records for necessary operations

• Data with archival value

The RecordPoint Data Trust Platform can help you migrate with confidence. It can help you identify high-value data and separate it from ROT (redundant, obsolete, or trivial data). This allows you to migrate your vital data without leaving anything valuable behind.  

Read this article to read even more tips on migrating your legacy data.

When moving to a new system, you must pick the right choice for your organization. You need a future-focused solution capable of handling all of your data needs. Here are a few features and benefits to consider when you evaluate a potential new system.

Lower costs

A new data management system should identify and dispose of ROT data. Subsequently, your organization saves on storage costs. There may also be increased work capacity since records managers will no longer need to shift through old data to find relevant information.

You can save significant money by moving to a true SaaS platform. RecordPoint customers realize up to 50% of savings when they leave their legacy systems behind.  


Any new data management system must meet your security and data sovereignty requirements.

Depending on your organization’s security needs, you may have an obligation to select systems that have been assessed under frameworks such as System and Organization Controls (SOC) 2 and Infosec Registered Assessors Program (IRAP), and you may require your data to be held in specific locations.

RecordPoint has completed an independent Infosec Registered Assessors Program (IRAP) assessment, with our products and services assessed to the security classification of PROTECTED. RecordPoint also holds a SOC 2 Type 2 attestation report.

Central location for all data

Keeping track of all your data in one location allows consistent data policy management. Whether your data is structured or unstructured or sourced from hundreds of places shouldn't matter.

An ideal new system should connect all your data sources and implement a blanket data management policy.

RecordPoint uses Connectors to connect thousands of unstructured and structured data sources into one central location, creating a single source of truth so employees can see the complete picture and glean meaningful insights.

Focus on automation and ML systems

An automated system can apply record policies at scale. Machine learning systems will get smarter over time and improve your organizational efficiency.  

Introducing automation into your data management process can remove tedious records management tasks from your team. It also serves to make the overall classification process more accurate and efficient.

There is no need for over-relying on employees to make highly accurate record classifications.

Zero impact on end-user workflows

Pick a new system that will have no negative impact on employee workflows.

They can keep using tools essential to their role without learning a new records management system, eliminating the need for a change management program and further reducing migration costs.

But it goes beyond not affecting end-user workflows. A new data management system can also increase efficiency and work capacity. These benefits free up employee time to work on other valuable projects.

Efficient data oversight  

The most significant outcome you should look for is gaining oversight of your data. You should have a complete picture of all data sources, classification, disposal policies, and who has access to what data.  

If you don't understand what data you have, you cannot protect it.

Once you have a system to classify your data corpus accurately, you can assign appropriate policies to manage sensitive data like PII. Without those crucial data insights, you risk security failure and breaching legal regulations.  


Adopting a new platform is an excellent opportunity to broaden your focus. What are your organization’s requirements beyond “records management”? Are you subject to data privacy regulations, and do these regulations include a data minimization requirement? You have the chance to select a system that can allow you to meet these requirements more effectively.

While you may understand the need to move to a modern data management system is the right call, getting relevant stakeholders to agree with you can take some convincing.  

They might think a data migration is a hassle or too expensive. They may think the current legacy system is "good enough.” Or they may want to prioritize other projects. Again, many organizations have a poor understanding of the records field and its impact on risk.

Persuading executives and stakeholders to make the switch can be done, though. Here are the five steps to take to make the argument:

  1. Share current problems with the legacy system: Make stakeholders aware of the challenges of the legacy system. For example, they might not know they lack the tools to protect sensitive data and comply with data regulations.
  1. Focus on the difference between prevention and remediation: It is easier and less expensive to improve an organization’s data privacy posture now rather than deal with the impact of a data loss or data breach event and the associated financial, legal, and reputational damage.
  1. List benefits of a new system: You could discuss how it lowers security risks and costs, all while improving privacy and compliance. You might want to prepare data and metrics on how a switch can save costs and improve work capacity in the long term.
  1. Address stakeholder concerns: Listen to people's concerns about moving to a new system and be prepared to have answers. Maybe they believe migration will impact employee workflows, and you can share how RecordPoint's Connectors can help mitigate issues.
  1. Let stakeholders view a demo: Seeing is believing. A demo of a new data management system can reveal what the organization has to gain by switching.
  1. Show the strategy: Having a plan is crucial to getting everyone on board with you. Consider everything that needs to happen for the switch to succeed and benefit the organization. These points will help persuade stakeholders to see your vision.

The RecordPoint Data Trust Platform can help you manage your structured and unstructured data and help make the migration process seamless.  

It starts with a pre-migration analysis. We'll assess your legacy data with our File Analysis tool and identify the value and risk of your entire data set. The file analysis will classify ROT data, so you don't have to migrate it to your new system.

Meanwhile, Connectors will allow you to discover and manage your data from a central location so you can begin governing your data consistently during the transition process.

Once you have transferred the high-value data, you can use RecordPoint to manage all your data sources. The platform will classify ROT and PII and implement the necessary data disposal policy for that classification.  

RecordPoint is an efficient and empowering tool to gain control over your data – no matter where it's stored. You can manage data at scale while reducing risk, improving workflows, and saving on expenses.