What is information management? Lifecycle, retention and enterprise examples

Information management is how an organization decides what information it captures, where it keeps it, who can use it, how long it is retained and when it is deleted, across every system that holds it. In a large company, those documents are spread over several archives and your ERP.

According to the Market Momentum Index: Intelligent Document Processing Survey 2025 by AIIM and Deep Analysis (2025), 61% of the processes companies automate with intelligent document processing still involve paper documents.

So information management starts at the mailbox and ends with a deletion you can prove. In between, enterprises in insurance, banking and logistics have found ways to keep retention under control across many systems.

Key Takeaways

• Information management covers the full lifecycle of information, from capture to provable deletion, across every system an organization runs
• Information that needs audit-proof retention belongs on one central platform, while working data stays in its source system and is read in place
• Retention works at scale when each document class carries its own rule, with a reference date, a minimum and a maximum period
• US federal retention minimums range from one year for records of hiring and termination to six years for broker-dealer ledgers
• Consolidating legacy archives is a common starting point: DB Systel moved 35 DMS and archive systems onto one platform used by 32,000 people

What is information management?

Information management (IM) is the discipline of planning, controlling and monitoring an organization's information and the systems that process it. Its goal is that the right people can use the right information at the right time. It covers the whole lifecycle, from capture to deletion, whether information arrives as a paper letter or as a record in your ERP.

Most frameworks rest on three principles. Information is a company asset, it is shared with the people who need it, and anything the organization must keep is retained and deleted under defined rules.

Information management vs data management vs knowledge management

The three terms overlap, and the difference lies in what each one manages. Data management looks after raw data, information management adds context and rules, and knowledge management captures what people know from experience.

	Data management	Information management	Knowledge management
Manages	Raw data in databases	Documents, records and data in context	Expertise and experience
Typical content	Customer master data, transactions	Contracts, claims, invoices, personnel files	Best practices, lessons learned
Main question	Is the data correct and consistent?	Who may use it, and how long is it kept?	How do people share what they know?

For most enterprises, information management is the layer where compliance lives. Retention periods, access rights and deletion rules apply to documents and records, so they sit here.

The information lifecycle, from capture to deletion

Every piece of business information passes through the same stages. At enterprise volumes, each stage needs rules that run automatically, because millions of documents pass through them every year.

Capture and classify

Information enters through the mailroom, email and customer portals. At enterprise volumes, nobody can sort it by hand. AI classification reads each incoming document, recognizes its type, extracts the key data and assigns it to the right case and retention schedule as it arrives.

People still check the exceptions, and scanned paper letters go through the same steps as digital files.

Store and organize

Once classified, a document is filed in context, next to everything else that belongs to the same customer, contract or claim. Metadata from capture makes it findable later, and access rights follow the document class, so personnel files stay visible to HR only.

Use and share

Information pays off when it reaches the people who act on it. In large companies, that includes approvers who seldom work in the ERP. Giving each of them an ERP license is expensive, so a workflow routes the document to them for review and approval, with its full file attached.

Retain, archive and delete

Every document class has a legal retention period, and at the end of it, information has to be deleted in a way you can prove. This stage carries the most risk, because an auditor will ask for evidence. The best practices below show how enterprises organize it.

Benefits of information management

The benefits show up where information is used every day: in case handling, in the mailroom, in audits and in IT budgets. Results from Doxis customers show what each one looks like in practice.

Faster decisions and service

When every document for a case sits in one file, the person deciding has the full picture. After moving its legacy archive onto the platform, Raiffeisen Bank International gave customer service central access to customer documents and signature cards, which made service faster.

Less manual work

Classification and routing at intake take sorting off people's desks. The insurer DEVK digitizes incoming mail and routes it automatically to the employee responsible for the case. As a result, the time and resources spent on mail distribution dropped by 75%.

Compliance you can prove

Retention rules per document class and a logged deletion turn an audit question into a lookup. You show when a record was filed, who accessed it and when it was deleted.

Lower costs

Every archive you retire is one license and one maintenance contract fewer. i-PRO Americas replaced an SAP content repository that was no longer maintained and has had no archiving failures since. The manufacturer expects savings of about $348,000 over three to four years.

Information management best practices for enterprises

In large organizations, the lifecycle only works when rules decide where information lives and how long it stays. These five practices make that work across many systems.

Decide which information belongs on a central platform

Most enterprises end up with information in many places: several archives, the ERP, the CRM and file shares. Anything that needs audit-proof archiving and retention control belongs on one platform, from contracts to personnel files. There each document class gets its retention rule, its access rights and its audit trail, wherever the document came from.

Working data in your ERP or CRM can stay where it is. Connectors read that content in place without copying it, so users search one access point across sources. With Doxis, connecting a source system this way takes days to weeks per connector.

Content that stays in its source system keeps that system's retention rules. That is the deciding test: if you need to prove when a document was deleted, file it on the central platform.

Set retention rules per document class

Retention becomes manageable when it is tied to the document class and runs automatically. Each document class gets a retention rule with a reference date, such as an employee's exit date, plus a minimum and a maximum retention period.

Doxis distinguishes three modes: documents that can be deleted directly, documents under strict retention control, and documents that may never be deleted.

Delete in two steps

When a document reaches the end of its period, it is first deleted logically and can still be restored. It is removed physically once the maximum retention period has passed. For particularly sensitive archives, a privileged deletion requires an administrator to confirm each file, which separates the duty of requesting a deletion from approving it.

If litigation or an audit is pending, a deletion lock keeps the affected documents in place until it is lifted.

Keep an audit trail for every change

Audit trails record who changed what and when, including deletions. When an auditor asks when a personnel file was removed, a single log entry answers the question.

US retention periods by document type

US federal minimums run from one year for records of hiring and termination to six years for broker-dealer ledgers. A bank with an insurance arm keeps the same type of record for different periods depending on the legal entity, which is why each rule is set per document class and legal entity.

Information management examples from large organizations

Doxis customers in insurance and energy apply these practices every day, from the mailroom to contract approvals and personnel files.

Inbound mail goes straight into the right file

At DEVK, the same intake process feeds digital claims, policy and personnel files. Employees search around 400 million documents in 62 million files from one place, so earlier claims and policy contracts open in seconds when a new case comes in.

Contract approvals leave a complete record

Raffinerie Heide, a refinery, manages its contracts in a central file, and every approval runs through a workflow under the four-eyes or six-eyes principle. For each contract, the file shows who reviewed it and when, so the complete approval history is ready for any audit.

The refinery also moved more than 100,000 technical drawings onto the platform in two and a half months.

Personnel files are deleted on schedule

Personnel files combine long retention periods with strict privacy rules. When they are classified at filing, only HR sees them, and a workflow deletes them automatically once the retention period ends. The deletion is logged, so it holds up in an audit.

Common information management challenges in large organizations

The same three challenges come up in most enterprises: information spread across systems, paper at intake and legacy archives that cost more every year.

Information spread across many systems

When a single company runs two content servers plus SharePoint, nobody can search everything at once. Every additional archive needs its own interface and maintenance, and the same customer file ends up in several places.

Paper that keeps arriving

Despite years of digital-first programs, 48% of respondents in the Market Momentum Index (2025) expect their paper use to increase, so capture has to handle scanned letters as reliably as digital files.

Legacy archives that cost more every year

Many enterprises start their information management work by retiring old archives. According to the Market Momentum Index (2025), 66% of the document processing projects enterprises are planning aim to replace legacy systems.

In discovery conversations, the most frequent trigger is cost. Licensing changes and vendor audits push up the bill for archives that teams describe as 20-year-old technology. Hard deadlines force the timing, such as an expiring contract for a legacy platform or the end of support for the server it runs on.

These consolidation projects on the Doxis platform show what changes once the old archives are gone:

Organization	Industry	What was consolidated	Result
DB Systel	Logistics and mobility	35 DMS and archive systems	One platform for 32,000 users and 190 million documents
Raiffeisen Bank International	Banking	Legacy archive with 23 document types	Migrated in four months with zero downtime
FCA Bank	Banking	17 million legacy documents	Switched over without loss of service; paper archive dissolved
i-PRO Americas	Manufacturing	SAP content repository that was no longer maintained	No archiving failures; about $348,000 in expected savings over three to four years
Techniker Krankenkasse	Health insurance	SAP archive	5 TB migrated in six weeks during live operation; 10x faster access to archived data

Migration during live operation is what makes these projects workable. At Raiffeisen Bank International, the archive was migrated in the background while customer service kept full access to customer documents.

Why information management comes before AI

Companies that want AI to classify documents and extract data need governed content first. According to the Market Momentum Index (2025), 78% of the organizations surveyed already use some form of AI, yet most of their document processes still involve paper.

Buyers ask for controlled AI: models that propose a document class and metadata, with clear rules on what is filed where and people checking the exceptions. Once every document class has its owner, its access rights and its retention period, AI can file new documents into that structure.

Manage information across your systems with Doxis

When information sits in dozens of systems, nobody has the full picture when a case needs a decision, and nobody can prove when a document was deleted. With Doxis, you bring the information that needs control onto one platform and keep retention and deletion in hand for every document class.

Doxis combines document management and audit-proof archiving with AI-powered document processing and workflows. An incoming document is recognized, read and routed to the right case, and it is managed according to its retention rule until the day it is deleted. Doxis runs in the cloud, on premises or hybrid.

• One place for every document belonging to a case, whichever system it came from
• Retention rules per document class and logged deletion that holds up in an audit
• Inbound mail classified, read and filed into the right file automatically
• Access to documents from the applications your teams already use, such as SAP & Microsoft 365

Doxis is a Leader in the Gartner® Magic Quadrant™ for Document Management 2026. In a Forrester Total Economic Impact study, SEW-EURODRIVE achieved a 336% ROI with payback in under six months.

Request a free demo below to see how Doxis manages information across your systems.

FAQs on information management