Synchronising data: how to plan processes and systems

When many companies talk about synchronising data, they are usually referring to an immediate problem: information exists in several systems, is maintained twice or transferred by hand. This article addresses exactly that question and shows how to synchronise data without thinking only in terms of a single interface, but by planning processes, data sources and responsibilities together. It is aimed at decision-makers, IT management, specialist departments and project leads who are planning, replacing or extending software. One important point: not every synchronisation has to happen in real time, and not every instance of duplicate storage is wrong. What matters is a viable target model. Here, you will learn about typical causes, key planning questions, sensible system architecture at decision-making level, operational risks and a practical approach.

Why data drifts apart in organisations

In many organisations, similar information exists at the same time in CRM, specialist applications, Excel files, email inboxes or portals, but not in the same state. A contact has been updated in one system, but not in another. A case has moved on internally, yet still appears open in the portal. This quickly creates uncertainty about which piece of information is currently valid.

Duplicate maintenance often has an understandable cause: systems were introduced at different times and each was optimised for a single purpose. What initially made sense gradually leads to breaks between departments and tools.

A clear warning sign is manual transfer. If data is moved from one system to another by copy and paste, email or lists, it

• takes more time,
• slows down processes,
• and increases the risk of input errors.

Specialist departments and IT often assess this situation differently. One side experiences the media break in day-to-day work, while the other sees the technical complexity behind it.

What matters here is this: synchronising data does not automatically mean keeping all information identical everywhere. A “leading system” is the application in which a piece of information is maintained as authoritative and from which other systems are supplied.

Established processes also play a part. If responsibilities are unclear, new interfaces alone will not solve the problem. Before choosing technology, it is therefore worth taking proper stock of the current situation, for example with a specification sheet as a planning basis.

What you should define before technical implementation

Before connecting systems, you should first narrow down which data actually needs to be synchronised. Not every piece of information has to be exchanged between applications. Typical candidates are:

• master data,
• cases or transactions,
• documents,
• and status information.

The question of how up to date the data needs to be is just as important. Some data must be available immediately; for other data, hourly, daily or event-based updates are sufficient. “Event-based” means that transfer starts when a defined trigger occurs in one system, such as an approval or a change of status.

You should also define who is allowed to create, change and check data. If such responsibilities are missing, conflicts between systems and teams arise quickly. This applies in particular when two applications store the same information differently. In that case, rules are needed in advance: which source applies, how deviations are identified and who decides in case of doubt.

Another point is the existing data quality. Inaccurate addresses, duplicates or differing names are not resolved by synchronisation; they are often just distributed more quickly. That is why it is worth taking a sober look at the current data first.

Also, do not think only in terms of applications, but in terms of workflows. Sales, service, administration and project work all have different requirements. Synchronisation should support the process rather than create new interruptions.

Topics such as data protection, retention and access rights should be reviewed early on with the relevant stakeholders, and if necessary with legal advisers or data protection officers as well. If you would first like to sort out the requirements and system boundaries involved, a project check, a cost calculator for initial guidance or a no-obligation initial consultation can help. You can also refer to an overview of services covering development, hosting and operations as well as selected project examples.

How to shape processes and systems sensibly

For planning at management level, three basic patterns have proved effective:

• One leading system with distribution: one application is authoritative for specific data, and other systems adopt that information.
• Bidirectional synchronisation between two applications: both systems exchange data in both directions.
• Central data storage for multiple systems: several applications access a shared data base or centrally controlled distribution.

Which model is the right fit depends less on technology than on responsibilities and workflows. Simpler models are often more robust and easier to understand. More complex models create greater flexibility, but require more coordination, clear rules and clean maintenance.

An interface is a defined path through which applications exchange data in a structured way.

What matters is not only which systems are connected, but also when in the process data is passed on. Is a record distributed immediately after capture, or only after checking? Does a status apply during internal processing already, or only after approval? Questions like these influence whether data exchange helps in day-to-day work or creates additional uncertainty.

One example from our own projects is an Azure DevOps extension that connects with planning software. This keeps information consistent between work planning and development. CI/CD also helps here: this means automated processes that check and deploy changes in a controlled way in order to reduce operational errors.

In Microsoft-oriented system landscapes, web applications, databases, Microsoft 365, Entra ID and cloud services can work together effectively if roles, responsibilities and data flows are clearly defined. You can find an overview of services covering app, web and database development as well as hosting and operations on the relevant overview page.

Typical risks when synchronising data

One frequently underestimated risk is unnecessary complexity. If new special rules keep being created for individual exceptions, synchronisation becomes difficult to understand and expensive to maintain. What still looks suitable on paper can quickly become confusing in everyday use.

There are also hidden dependencies. If a field, a workflow or a business rule changes in one system, this can unexpectedly affect data exchange elsewhere. Such effects often only become noticeable once specialist departments are already working with incorrect information.

Typical error patterns include:

• duplicate records,
• outdated information,
• incorrect assignments,
• incomplete transfers.

Monitoring means the ongoing supervision of data exchange so that problems become visible instead of only showing up in day-to-day operations.

Tests for interfaces and data flows are just as important. After all, it is not only individual input screens that need to work, but also the transitions between systems. This is exactly where errors arise that are difficult to detect in normal operation.

You should also not treat synchronisation as a one-off implementation. Processes, systems and responsibilities change. Data exchange therefore also requires maintenance and further development.

If data is also being used for AI functions, for example for searching company knowledge, assistants or document extraction, source, quality and permissions should be planned particularly carefully.

How to start a synchronisation project pragmatically

If you want to synchronise data, it is best not to start with the entire system landscape at once. A more practical approach is a clearly defined use case where the benefit becomes visible quickly and dependencies remain manageable.

A good guiding question for getting started is: where does duplicate maintenance currently create the greatest effort or the highest risk of error?

For preparation, a compact overview is often enough at first. In it, you record:

• which systems are affected,
• which types of data are to be exchanged,
• which triggers start the transfer,
• who is responsible from a business perspective,
• and which special cases need to be taken into account.

This creates a solid basis for the next steps. A project can then be structured from the initial getting-to-know stage through concept and design, development, quality assurance and go-live, followed by support and further development.

An early project check is helpful. A project profile with follow-up questions and a cost range can be created from a description or a requirements specification. If all you need initially is a rough idea, a cost calculator may also be useful. Both approaches help sharpen requirements before technical decisions are taken too far in advance.