Document management platforms rarely work in isolation. On the contrary, in most organisations they exchange data with human resources systems, ERP, access control, cloud storage or client platforms. Usually, these exchanges rely on automatic synchronisations, which copy or update information between systems without human intervention but also bring automatic synchronisation challenges of their own.
Without doubt, automation brings clear gains in time and consistency. However, it also creates risks that are not always considered at the start of a project. In this article, we analyse the main constraints of automatic synchronisations, their causes and the measures that help reduce their day-to-day impact.
What automatic synchronisations are
An automatic synchronisation is a process that keeps data identical, or consistent, across two or more systems. It can work in real time, when an event in one system triggers the update in the other, or in batches, at set times. In general, it uses application programming interfaces (APIs), exchange files or connectors supplied by the vendors.
For example, when a new worker is registered in the human resources system, the document management platform automatically creates that worker’s record. Similarly, when a document expires, the platform can inform the access control system.
Most common types of synchronisation
| Type | How it works | When to use it |
|---|---|---|
| One-way | Data flows from a source system to a target system | When there is a single source of truth |
| Two-way | Changes in either system are replicated in the other | When both systems are edited |
| Event-driven | A change triggers an immediate notification | When the information is urgent |
| Batch | Data is sent at set times | For large volumes and less urgent data |
Two-way synchronisation is the most demanding, because it multiplies the possibilities for conflict. Therefore, whenever possible, it is better to choose one-way flows with a clear reference system.
Main automatic synchronisation challenges
Data and version conflicts
Firstly, when the same data can be changed in two systems, conflicts arise. If one user corrects a worker’s name on the platform and another changes the same field in the human resources system, which version prevails? Without a clear rule, the synchronisation can therefore erase valid corrections or create contradictory records.
Errors that spread
One of the advantages of automation is also one of its risks. Indeed, an error introduced in one system is quickly replicated in all the others. For example, a badly configured import can deactivate hundreds of workers in a few minutes.
Differences in data structure
Each system organises information in its own way, so fields have different names, formats and rules. As a result, mapping between systems requires correspondence tables and transformations that need maintenance. When one of the systems changes, the mapping may stop working without anyone noticing straight away.
Duplicate records
Without unique, stable identifiers, the synchronisation can create the same worker or company several times. Consequently, documents end up scattered across different records and reports are no longer reliable.
Communication failures and technical limits
Connections between systems depend on the network, server availability and authentication credentials. In addition, many APIs limit the number of requests per minute. When these limits are exceeded, or when a certificate or credential expires, the synchronisation fails. In that case, without alerts, the failure can go unnoticed for days.
Security and data protection
It is also worth remembering that each connection is an additional entry point. Therefore, poorly protected credentials or excessive permissions increase the risk of improper access. From a GDPR perspective, synchronisation should transfer only the data needed for each purpose, respecting the principle of data minimisation.
Third-party dependency
Finally, when a provider changes its API, discontinues a version or changes the data format, the integration may stop working. This is one of the automatic synchronisation challenges that is hardest to predict, because it depends on external decisions. As a result, organisations become dependent on update schedules they do not control.
How to reduce automatic synchronisation challenges
| Challenge | Recommended measure |
|---|---|
| Data conflicts | Define a reference system for each data item |
| Propagated errors | Validation before import and limits on mass changes |
| Different structures | Documented mapping, tested after each update |
| Duplicates | Unique identifiers, such as the company’s tax number (NIF) |
| Communication failures | Automatic retries, alerts and error reports |
| Security | Protected credentials, minimum permissions and operation logs |
| Third-party dependency | Version tracking and testing in a pre-production environment |
In addition to these measures, it is advisable to plan periodic reconciliation processes. In other words, compare the data in both systems and correct any differences found.
Indicators for monitoring synchronisations
Monitoring should be continuous and data-driven. In practice, a few simple indicators make it possible to detect problems early:
- number of synchronisations run and failed per day;
- average time between the change at the source and the update at the target;
- number of records rejected due to validation errors;
- differences found in periodic reconciliations;
- mass changes outside the usual pattern.
When one of these indicators moves away from normal values, the person responsible should receive an alert and analyse the cause before errors accumulate.
Practical example: Synchronisation with the human resources system
Consider a services company with 800 workers that synchronises its human resources system daily with a client’s document management platform. One day, several workers are prevented from entering the client’s premises.
When analysing the logs, the team realises that an update to the human resources system changed the date format. As a result, the synchronisation misread the hiring dates and marked workers as inactive. To prevent further failures, the company now validates data before each transfer, creates alerts for mass changes and tests the integration whenever one of the systems is updated.
Checklist before activating a synchronisation
- Objective and data to be synchronised clearly defined.
- Reference system identified for each data item.
- Unique identifiers agreed between systems.
- Field mapping documented.
- Tests with real data in a pre-production environment.
- Alerts for failures and abnormal changes.
- Log of all operations performed.
- Person responsible for monitoring defined.
- Plan for acting when synchronisation fails.
Good practices for integration governance
Beyond technical measures, integrations need governance rules. First of all, each integration should have a business owner and a technical owner. Next, changes to the systems involved should be communicated to all parties in advance. Finally, the integration documentation should be kept up to date, so that someone else can understand and fix a problem in the absence of the person who developed it. In this way, the organisation reduces its dependence on specific people and responds faster to failures.
Common mistakes to avoid
The most common mistake is assuming that, once activated, synchronisation will work on its own forever. In fact, it requires continuous monitoring. Another mistake is synchronising all available data instead of only what is necessary. In addition, many organisations do not define who is responsible for resolving errors, which delays correction. Finally, activating synchronisation directly in production, without testing, is an unnecessary risk.
Frequently asked questions
Is it better to synchronise in real time or in batches?
It depends on the need. Real time is useful when information has an immediate impact, as in access control. Batches are suitable for less urgent updates and reduce the load on systems.
Who should monitor synchronisations?
A technical team with knowledge of the systems involved, working together with the users who depend on the data.
Do automatic synchronisations replace human validation?
No. Automation handles data transfer, but validating critical documents still requires human judgement.
What should you do when synchronisation fails?
First, identify the error in the logs. Then, fix the cause and rerun the synchronisation only for the affected records. Finally, confirm through a reconciliation that the data is consistent in both systems.
Conclusion
Automatic synchronisations are essential for integrating document management platforms with the organisation’s other systems. However, data conflicts, error propagation, communication failures and security risks show that automation requires planning and monitoring.
Understanding automatic synchronisation challenges makes it possible to prevent them and choose the most suitable integration architecture for each case. With clear rules, testing, alerts and defined owners, the organisation enjoys the benefits of integration without losing control over data quality.
Read also: Benefits of system integration with contractors and Implementing document management platforms in multinational companies.
For cybersecurity good practice in system integrations, consult the European Union Agency for Cybersecurity (ENISA).