What is the most advantageous decision for your company? When it comes to making decisions, feelings are helpful, but reliable data is what should be trusted. Detailed information coming from the various business applications and spreadsheet documents is the best source to rely on.
Data silos can frequently lead to problems within businesses, such as having multiple copies of the same information, obsolete records, and human errors, which in turn prevents the organization from running optimally.
Data repositories that are not connected can limit and impede decision-making, thus preventing your organization from expanding. Having a clear understanding of the issues, the impacts they have on your squad, and the potential solutions makes an immense variation.
What is a data silo?
A data silo is a collection of unprocessed information that can only be accessed by certain parts of an organization and is separated from the entirety of the company. This causes a great deal of opacity, ineffectiveness, and distrust to be present within that company.
This is generally due to information being obtained by an organization’s instrument that is separate from the remaining of their technical environment. In big companies it is quite ordinary to have data silos as distinct teams and divisions have their own objectives and preferences, often operating independently.
Here are some common scenarios in organizations with data silo issues:
1. Issues with Technology
Organizations without suitable technological infrastructure find it difficult to share data between different departments. Organizations must possess superior software that is capable of rapidly exchanging data and linking different pieces of information. Additionally, some groups may have received more instruction concerning how to use the technology to transfer data, which could lead to difficulties for the latter in gaining access to similar details.
2. Growth in Organizations
When a business gets too big, it can be challenging to transmit information efficiently all over the organization. There could be too many branches, locations around the nation or world, or workforce members, that cause a feeling of detachment from the other parts of the firm. When an organization blooms to its maximum size too rapidly, there may be problems with its construction. It may take a series of actions for information to flow through the hierarchy.
As organizations become larger, there could be an increase in rivalry between employees. Certain teams might choose to withhold information from other teams if they wish to retain authority.
3. Decentralized IT Services
In some cases, companies can implement IT services in a decentralized manner, enabling every section to purchase their own specific software and technologies. This results in databases, platforms, and other applications that cannot be interfaced with or linked to other systems that are part of the company. When IT purchases are not coordinated across departments or teams to ensure they work with existing systems, there is a risk of data becoming segmented or isolated.
4. Competetive Gatekeeping
As organizations become bigger, there could be a heightened sense of rivalry among employees. Some teams might not want to share information with other teams if they would like to keep command.
Back to History: How Did Data Silos Emerge?
Let us put the time behind us to observe how the term “data silos” came about.
About fifteen years ago, companies used to have a centralized way of conducting their business. Every activity was interconnected and followed a top-down approach. Managers at the top of the corporate ladder, also knowns as the C-suite, would provide instructions which would be relayed to business users and data personnel at their discretion. Things were happening in an orderly manner, with less chaos and danger, however, this system of doing things had its drawbacks – it suppressed imagination and adaptability.
In order for data and business teams to achieve success in the market, they must be able to respond quickly and have the ability to be flexible.
And hence came data silos into the picture.
Data silos enabled every team to be agile, with distinct functions that allowed them to independently create and ship products/services that met the needs of their market and utilized their own innovations. Teams would be able to create their own applications, select the technology they want to use, and establish tailored deployment process with this.
They managed to create one-of-a-kind products/services which they designed quickly and easily. This action produced major advantages to the clients. It enhanced the customer’s experiences and uncovered their true desires.
It seems like this story about data silos has gotten off to a positive beginning. Teams were given autonomy as well as the added advantage of privacy when data silos were established, allowing them to safely keep their confidential information.
Additionally, a few other factors have contributed to the formation of data silos in contemporary corporate operations.
Why are data silos problematic?
No matter why your business has data silos, it’s clear that they’re not beneficial. So why are they so bad?
1. They give an incomplete view of the business.
Executives at the C-level have the obligation to unify all of the firm’s data. If you are the executive in charge, you can expect your sales team to report any new clients, the marketing team to tell you the amount of leads and visitors they’ve had, and the accounting team to deliver you a statement of expenses and income. But what links all that information together?
Attempting to operate a company without correlating information is similar to assembling a jigsaw puzzle without seeing the image on the cover of the box. Data silos prevent you from having an all-encompassing perspective of your company.
2. They create a less collaborative environment.
Each group finishes operating autonomously when surrounded by data storage areas. They are limited to utilizing the data that they have on hand, so they do not use any other information. This creates a divided organization. Groups do not cooperate together on assignments, rendering it virtually unthinkable for the corporation to establish a unified perspective.
Managers wish to base their decisions on facts and figures. However, if the heads of every side cannot view the entire landscape and merely have restricted access to their own fraction of the data, their specific decisions seldom line up with broad commercial objectives.
In situations where information is stored separately, establishing an atmosphere of candor and reliability is very tough to maintain. Rather than fostering cooperation, you could be generating competition between teams who are concentrating on their own smaller objectives.
3. They lead to poor customer experience.
In most businesses, there are multiple customer touch points. Interactions occur through multiple mediums and at multiple stages of the customer’s process. This implies that individuals from different teams such as customer service, accounts, sales, and advertising will be engaged with the same customer or purchaser.
If information is kept separate, it can be difficult to keep up with a customer’s experience with your business — this can be hugely irritating for them if they have to keep on explaining the same thing to different individuals.
4. They slow the pace of your organization.
It’s a waste of time to have data silos. Rather than being able to easily share data between teams, the data is kept separate within individual teams. This suggests that teams cannot access the data until they recognize that it is necessary, track where it is within the company, manually gain permission to access it, and then assess it in order to achieve their goals. By the point in time that you gather the information, it could already be outdated.
5. They create a security risk.
When staff keep Excel files, papers, and other info on their personal computers, the company could be in danger if the right precautionary measures have not been set up. It is challenging to adhere to data protection regulations due to data silos, as it is complex to locate who is able to gain access to which information.
Why Should Business & Data Teams Eliminate Data Silos?
Having gone through a listing of why data silos are problematic, here is a quick summary of the reasons why your teams should eliminate data silos:
- A centralized repository will help provide comprehensive data analysis.
- Your teams gain more visibility into organization-wide data.
- Eliminating data silos speeds up decision-making, and makes your organization more competitive.
- You enable the free exchange of information and collaboration within teams.
- Your data and business teams become agile and responsive to find new ways to grow both the top and bottom lines.
Breaking Down Data Silos
Organizations must find ways to break down the blocks that keep their data apart in order to uncover useful information and knowledge. They should take on a methodical strategy regarding the combination of data, oversight of data, and rules concerning data.
It is essential that the disintegration of data silos does not just come from the uppermost level, but rather is a collective endeavor that necessitates a fundamental transformation to a mentality that inspires the unrestricted sharing of data.
Altering the workplace culture, pushing for communication and cooperation between different business groups, and cutting extraneous intra-organizational rivalry are all productive, but likely to be ignored in an energetic and volatile atmosphere, if not established properly.
Just contemplate these solutions for a bit – You can always work on cultural and political matters afterwards, while developing an effective plan or after you have achieved it.
A genuine answer to the silo issue appears when companies try to devise and execute a data analysis technique that incorporates data administration strategies, examines their specialized prerequisites and innovation abilities, and sets up a strong establishment for data integration.
In order to reach this goal, they must spend money on comprehensive data analytics solutions that can manage different prerequisites: combining data without difficulty, transforming data into desired formats, providing data security, and making actionable information quickly available to customer-oriented business and data teams.
Building a Solid Data Foundation
A strategy to get rid of data isolation is to streamline your software and create custom program connections between various applications. This necessitates producing scripts in languages like?SQL, Python, or any other language in order to shift data from numerous, isolated data systems into a central source of truth. In our opinion, we do not find this task enjoyable whatsoever.
The truth is that the majority of businesses do not have the liberty or the resources to engage data engineers and coordinate their information from varying sources. The difficulty of bringing together data does not diminish – the people managing the data must develop different interfaces for each program, always keep them current, make sure the system has sufficient capacity, and analyze for any possible blunders.
In the digital era, where there are numerous systems recording data, it is important to find dependable and affordable solutions to collect data from a variety of sources such as databases, SaaS applications, cloud storage, and streaming services. Having the information consolidated into a single location (like a data warehouse or data lake) enables teams to gain access to valuable insights.
Nowadays, cloud-based applications are widely used by organizations, making it quite simple to get all data from various data systems and applications and bring it together into one single storage space in a matter of minutes or hours, rather than having to wait for days or months. Cloud-based ETL (extract, transform, load) technologies can aid in getting data from multiple repositories into a single hub efficiently, making use of straightforward connectors and developing fruitful data architectures with data replication that does not cause losses.
Using effective methods of combining data assists in improving the ability to identify, uncover and manage data. Having a single source of truth that everyone has access to ensures that everyone has the same version of the data and it is presented in a unified manner, thus enabling collaboration and data exchange.
Final Thoughts
Many companies put a priority on unifying their operational and experience data by eliminating data silos. In this article, we examined several reasons why data silos can be an issue. Data being more easily accessible and transferable allows for better business judgments being made, as well as data from varied departments being used more proactively.
A progressive, pragmatic strategy is the most efficient way of eliminating the impediments of silos. Key changes in both culture and technology are essential in connecting data silos and unlocking the true potential of data. Collecting information into a single source like a data warehouse accumulates and orders company facts for thorough examination, uncovering of ideas, and making decisions that are backed up.
Companies can utilize automated, scalable, cost-efficient, and maintenance-free ETL solutions like Hevo to join data seamlessly between different tool, files, and databases. Hevo eliminates the intricacies of current data systems by unifying the data containers, permitting the greatest possibilities of consolidated data handling and opening a door to a more anticipatory attitude to data analysis.
