DATA SILOS - an underestimated risk for your company?

Ana Lucia Freyre Ich habe fünf Jahre bei IBM gearbeitet und im Anschluss meinen Master in IBE in Hohenheim gemacht. Seit Januar 2022 bin ich als Account Managerin bei Fischer.

If you've ever wondered if data silos are a risk for your company, you're undoubtedly right. In the following article, we will first explain what data silos are, how they can become a problem for your enterprise, and finally how to break them down. All so you can start operating at a higher data-driven level.

Tabel of contents:

    What are data silos?

    Data silos are sources of information that are difficult to transfer between systems and applications. They can extend vertically or horizontally across the enterprise and can arise for a variety of reasons.
    Examples of what data silos can arise from:

    • Communication problems between old and new systems
    • Misunderstandings between on-premise and cloud systems
    • Different storage systems
    • Mergers and acquisitions of new companies with differently configured systems

    For business users, it is difficult to access and understand all the data available in the company due to data silos, such as those that can be created by an enterprise resource planning (ERP) system. In the process, if data is insufficient or incorrect, data silos can also lead to inaccurate results or conclusions, as well as delayed decision making. Experience has shown that the lack of a single source of information can also raise questions about the reliability of the data.The problem with data silos is that no one can retrieve all the information quickly. Instead, each data silo must be accessed independently. Then, to get a picture of the overall situation, the results must be combined manually. This process is inefficient, costly, error-prone and time-consuming.


    Data silos exist everywhere, including in the healthcare industry, for example. In an ideal scenario, every time a doctor faces an unusual diagnosis, he or she can check patient databases around the world to see how other doctors have successfully treated the same condition.

    But unfortunately, it's not that simple. Currently, hospitals keep health data locked away and use it as a competitive advantage. The healthcare industry is not sharing useful data to drive potential solutions and treatments. Thus, innovation is inhibited. This negatively impacts patients. The benefit of shared knowledge is thereby lost.

    The same effect occurs in companies, particularly along the supply chain. To draw a parallel with the hospital example: In our metaphor, the departments involved in the supply chain stand for the individual hospitals. Information and data are collected there. Unfortunately, however, it is often the case that it is not possible for support, for example, to access the data silo of manufacturing. An error reported by the customer or a defect that may already be known in production may be new to support. Similar to the healthcare system, known (fault) diagnoses and a possible course of action were not directly communicated. Causes and solutions to the problem either have to be researched by the customer or are time-consuming to find out. Valuable time is lost as a result of the data silos that have developed in the departments. The end customers/patients are the ones who suffer. The information that is difficult to access has a detrimental effect on them.

    Our goal is to break down data silos. To break down data silos, the first step is to identify them. By the end of this article, you will be able to identify the risks of data silos and then successfully break them down.

    Breake down Data Silos – with Sherlock

    How are data silos created?

    Let's take a closer look at a company. For example, if a department in your company maintains its own content management system or CRM, collecting data for its own benefit, this data is not necessarily available to the entire organization or to all participants in the supply chain. This incomplete or missing exchange of information then creates data silos. As mentioned earlier, data silos can develop over time. Although the term data silos sounds seemingly innocent and harmless as knowledge repositories, they hinder information sharing and collaboration between departments. These difficulties can have an impact across the entire supply chain. Customers, suppliers or partners are affected.

    Let's look at some reasons for data silos:

    Let's look at some reasons for data silos:

    In many companies, technical tools, data management systems and software of various kinds are used to support sales or marketing, for example. In doing so, processes and workflows are optimized through collected data and information. Typically, however, these data sets are difficult or impossible for other departments to access. The result: closed knowledge stores, i.e. data silos. The rise of cloud computing and software-as-a-service has accelerated the adoption of various technology solutions in many organizations. Departments use different programs and or tools to support their operations, such as spreadsheets, accounting software, or a CRM system. Most of these technology solutions were not designed to facilitate information sharing and the data stored is controlled in different ways.

    So, because numerous systems with different software are used throughout the company, the large amounts of data captured in the various programs are not linked. This can significantly complicate company-wide information sharing and communication.

    Improperly aligned communication using the example of supply chain management - are we misaligned?

    Example supply chain: In today's world, a value chain comprises numerous departments and participants. From the supplier to manufacturing, warehousing, transport to marketing / sales and the customer. The challenge here lies in transparent and efficient communication between the various parties. Each individual has different challenges to overcome, guidelines to adhere to, and processes to optimize in order to meet the goals set. This interaction can be a wonderful way to guarantee flexibility. At the same time, the differences between teams in terms of collecting and storing the information they need can lead to hard-to-access data silos that need to be broken down.

    Agile working promotes innovation in this context, but is a major reason for the rise of data silos. Managers find their own methods, applications and different software solutions. Important information is often not communicated beyond one's own team. As a result, the very data silos that need to be broken down are created along the entire supply chain. Modern departments often work in an agile manner. In the long term, this usually leads to a reduction in costs, ensures better performance and guarantees better collaboration. It is therefore important to enable agile working along the entire supply chain with the right software, without accepting the risk of data silos.

    Corporate culture and desire for control over data

    In many companies, entire business units have complete autonomy over their decisions, processes and challenges. So each division could be viewed twice. As part of the parent company and as a micro-enterprise that has its own goals to fulfill and acts autonomously. The business units can almost be considered as separate companies with their own management and internal company structures. Even though some companies are just starting to develop a working culture of data sharing and knowledge transfer, such corporate structures have already led to data silos.

    Let's assume that the individual business unit managers do not want to make their data available to the company, or only to a limited extent. They don't care to relinquish control or access to the data, then this can lead to the creation of data silos. Another common example: the departure of one of the company's data stewards. In this worst-case scenario, any information that this employee did not disclose is lost. This significantly affects the company's future decision-making.

    Unternehmenskultur – Wunsch nach Kontrolle über Daten

    In vielen Unternehmen haben ganze Geschäftsbereiche völlige Autonomie über ihre Entscheidungen, Prozesse und Herausforderungen. Jeder Bereich könnte also doppelt betrachtet werden. Als Teil des Mutterkonzern und als ein Mikrounternehmen, das eigene Ziele zu erfüllen hat und autark agiert. Die Geschäftsbereiche können fast als getrennte Unternehmen mit eigener Leitung und firmeninternen Strukturen betrachtet werden. Auch wenn einige Unternehmen gerade erst dabei sind, eine Arbeitskultur der gemeinsamen Nutzung von Daten und des Wissenstransfers zu entwickeln, haben solche Unternehmensstrukturen bereits zu Datensilos geführt.

    Nehmen wir an, die einzelnen Verantwortlichen der Geschäftsbereiche wollen ihre Daten nicht oder nur eingeschränkt dem Unternehmen zur Verfügung stellen. Sie sorgen sich nicht darum, die Kontrolle oder den Zugang zu den Daten abzugeben, dann kann dies zum Entstehen von Datensilos führen. Ein weiteres häufiges Beispiel: Das Ausscheiden eines Datenverantwortlichen des Unternehmens. In diesem Worst Case Szenario gehen alle Informationen, die dieser Mitarbeiter nicht preisgegeben hat, verloren. Dies beeinträchtigt maßgeblich die künftigen Entscheidungsfindungen des Unternehmens.

    Why you shouldn't ignore data silos!

    Now that we know what data silos are and where they come from, the question can be answered: Do data silos represent a risk to your company? Many of the causes for the rise of data silos have been known in companies for years. People are aware of the reasons for the emergence, but these are more or less deliberately overlooked. It is ignored until those involved in the company recognize the problem and want to take action to eliminate it. Only then do the questions arise, "Is it possible to break up data silos?" "Is it possible to break them up?"

    3 ways data silos can hurt your business

    Important: The more time passes, the more serious the problem of data silos becomes. The earlier one deals with making data silos accessible, the easier it is. The longer structures exist, the harder it is to break them up or change them.

    1.          Restricted data view

    Relevant data is not shared due to silos. Each department is limited in its view by its own perspective. You might say they wear blinders. Without an enterprise-wide view of the data, there is no way to find inefficiencies and data to help make decisions.

    2.          Risk of data integrity

    Inconsistencies occur when information is not shared across the enterprise and the same information is stored in different databases. When someone searches for information, it is very likely that the information becomes less accurate and therefore less useful as it matures. In addition, the manual effort required to obtain the information needed is many times more prone to error. 

    3.          Difficulties with cooperation

    Silos are formed by corporate culture, and silos reinforce that culture. Collaboration is seen by data-driven organizations as a powerful tool for discovering and leveraging new insights. Departments need a mechanism to communicate their data and foster collaboration. The ability to collaborate is compromised when sharing data is difficult or impossible.

    How can data silos be broken down?

    Data silos inhibit productivity, prevent insights, and hinder collaboration. But when data is centralized and optimized for analysis, silos become obsolete. The cloud has been optimized to enable centralization. That's why Fischer Information Technology developed Sherlock. An information platform that is suitable for small, medium and large businesses in a variety of industries and is already being used successfully to break down data silos. Sherlock enables your company to consolidate and integrate your data from different data sources in the cloud via RestAPI. Sherlock customers thus succeed in achieving their digital transformation goals by breaking down data silos and making data available to internal and external stakeholders in a user-centric interface. Curious? Very good! Find out more about Databrain Sherlock on our website.