Data Silos: When Every System Has Its Own Truth.
Marketing says 2,000 leads. Sales says 1,200. Accounting says 340 paying customers. All three are right. From their own system’s point of view.
What are data silos exactly?
Data silos happen when systems in a company store data without sharing it with other systems. The CRM knows the customer history. The ERP knows the orders. Accounting knows the payments. Three systems, three truths, and nobody pulling them together.
The problem is rarely technical in the narrow sense. It grew organisationally. Tool by tool got introduced, each one useful on its own, but never thought through as a whole. Anyone asking today “how many active customers do we really have” gets a different answer depending on which system they ask.
Breaking down data silos does not mean introducing a new system. It means getting existing systems to start talking to each other.
Three signs that data silos are slowing your company down.
We see these situations in almost every company working with a system landscape that grew organically.
Nobody knows which number is correct
Marketing, sales and accounting present three different customer numbers in a meeting. Everyone defends their own source. Nobody asks why the numbers differ in the first place.
The result: Decisions get made by gut feeling, because nobody dares to say which number is correct.
One person holds the system together
Someone maintains a spreadsheet that manually pulls together data from several systems. That person is on holiday? The numbers go stale. That person quits? Nobody knows how the spreadsheet works anymore.
The result: A single person becomes the single point of failure for running the company.
Data gets entered twice and contradicts itself
A customer changes their address in the customer portal. It gets updated in the CRM. Not in the ERP. The invoice goes to the old address. Someone has to fix it manually, if anyone notices at all.
The result: Duplicate work, errors, and customers wondering whether the company knows what it is doing.
Why do most companies solve this the wrong way?
The obvious reflex: introduce another tool. A dashboard that pulls all the data together, a business intelligence solution, a new CRM that is supposed to do everything.
The problem: a new tool does not fix a missing interface. At worst it adds a fourth system that also does not talk to the others. Now there are four truths instead of three.
The second typical mistake: trying to connect all systems at once. A big integration project, many months, and at the end a Frankenstein system nobody fully understands, which breaks the moment one of the source systems gets updated.
Breaking down data silos does not mean connecting everything at once. It means building the one connection that solves the biggest pain, and continuing from there.
Where do you actually start?
First the question everyone skips: which data inconsistency hurts the most? Not theoretically, concretely. Is it the customer count in the sales meeting? Duplicate addresses leading to wrong invoices? The manual spreadsheet that costs two hours every week?
One interface that solves that single problem delivers more than an integration project trying to solve everything at once but still not running in month six.
And then the second question: which system is the source of truth? Not every system needs to know everything. But it has to be clear where the truth begins and where it flows. Without that clarity you are just connecting chaos to chaos, a bit faster.
Breaking down data silos is rarely one single big project. It is a series of small, clear connections, each useful on its own, that add up over time to a functioning system landscape.
Where could the first thread start?
In the data world there is a term for this: master record or golden record. The one authoritative version of a record that all other systems depend on. Sounds like big theory, but at its core it is a simple question: if CRM and ERP disagree about a customer, which system is right?
The first practical step towards that is often more mundane than expected: just an ID. When a new customer orders, the CRM generates a customer number. The ERP generates a debtor number in parallel. If these two IDs are never linked anywhere, the drifting apart starts right there.
Some companies store the debtor number as a field in the CRM. Others store the CRM ID in the ERP. Both work, as long as it is done consistently.
It gets harder with customers who have multiple locations or different billing recipients. One customer, three delivery addresses, a billing recipient who is not the main contact: this is where CRM and ERP almost automatically drift apart if the structure was not thought through from the start. That is exactly why the ID question is worth asking at the very first order, not once the chaos is already there.
Depending on the setup this can look quite different. Sometimes the ERP becomes the leading system for customer data from the moment a prospect becomes a customer. Sales still stays in regular contact and keeps working in the CRM. Ideally, you agree on which system leads for what, a solution that makes the most sense for your own company. In most cases, though, nobody asks the question at all.
One required field change. A few hours of work. A sales team that stopped guessing.
A company had the classic problem: CRM and ERP knew the same customer, but not the same truth. Revenue was visible in the ERP, but the sales team could not see it in the CRM and decided by gut feeling instead of numbers.
Instead of a big integration project, we made the CRM ID a required field when creating debtors in the ERP. Existing debtors were linked to their CRM ID retroactively in a one-off effort, just a few hours of work. From that moment on there was a clear anchor between both systems, and automation in both directions became possible.
- CRM ID made a required field when creating debtors in the ERP
- Existing debtors linked retroactively in a one-off effort
- Small logic built that displays summed ERP revenue inside the CRM
- Sales team now sees revenue directly in the tool they already use
- Decisions based on numbers instead of gut feeling
- Low effort, but the foundation laid for further automation
“Breaking down data silos does not mean connecting everything at once. It means building the one connection that hurts the most, and continuing from there.”
What you usually ask us about data silos.
No. The most common mistake is trying to solve everything at once. Usually it is enough to build the one connection that solves the biggest problem, and continue step by step from there.
In most cases, no. A new tool does not fix a missing interface, it can even make the problem worse. Usually it is enough to let existing systems talk to each other through an interface.
Look at where data is manually re-entered, corrected, or pulled together. Wherever one person maintains a spreadsheet, or different numbers get debated in meetings, that is usually where the biggest problem sits.
A single, well-defined interface can often be built in days or a few weeks. A complete rethink of the system landscape takes longer, but you do not have to wait for that to solve the first pain point.
YOUR SYSTEMS SHOULD TALK TO EACH OTHER. NOT YOU FOR THEM.
If you want to know where your biggest data silos are sitting and which interface would make the most difference, talk to us.