Data truly powers modern businesses, but are you finding that yours is trapped in isolated systems? This can become frustrating when teams work and cannot easily get the information. This common challenge for growing organizations is known as data silos, and we’re going to learn how to overcome data silos.
These data silos slow down how quickly actions can take place. You’ll learn what data silos are, problems they cause, and actionable methods on how to overcome data silos.
Table of Contents:
- What Are Data Silos?
- How to Fix Data Silos for Good
- Strategies to Get Rid of Data Silos
- Ways to Integrate Data
- Examples of How to Break Down Silos
- Common Roadblocks
- Conclusion
What Are Data Silos?
Data silos occur when information gets stored in separate systems or departments. This makes the data inaccessible to other parts of the organization. Fragmented data limits what your company can do.
Think of a company where marketing keeps its customer data separate from sales. Neither team can see the full picture, and the organization struggles to send one concise message because each team’s work is done in isolation.
Why They Form
Several factors cause data silos. One big one is departmental independence, meaning that data is stored separately.
Departments often operate as separate entities, with their own goals and systems. A lack of integrated tools contributes to this issue because it prevents comprehensive data management, which means teams cannot work together effectively.
Rapid expansion and growth within a company can trigger the formation of data silos as well. Companies are better positioned if data is integrated instead of divided and spread throughout, which prevents silos from occurring.
Impact of Data Silos
Data silos create many problems, such as missed opportunities. When data is stored in isolation, departments can’t see trends or get insights that require combining information. Data silos limit what can be accomplished.
Companies might duplicate efforts across different teams because they lack access to other departments’ databases. This will cause customer experiences to become fractured.
How to Fix Data Silos for Good
Poor data quality comes with high costs, including increased costs, and it’s easy to miss out on all of its insights, growth, and profit potential. Data stored in silos prevents teams from seeing valuable metrics, projections, and ways to save or earn more.
Only about a quarter of organizations report that they are actually data-driven, according to Harvard Business Review. That should show you just how big this problem is.
Inefficient Decision-Making
When data is incomplete or out-of-date, leaders tend to make poor strategic choices. Incomplete data makes making informed decisions much harder.
Think about a marketing team using old customer data for a campaign. Conversion rates fall because the campaign isn’t aligned with more recent customer behavior trends.
Reduced Collaboration
Departments that are working in a vacuum do not know to benefit from other departments’ insights. When everyone can view data, more collaboration is possible.
It’s not uncommon for separate departments within an organization to purchase their own technology tools. However, these can lead to data being scattered among databases and storage applications that aren’t compatible with each other. A simple remedy could involve employing big data initiatives, which offer a more comprehensive view.
Increased Operational Costs
Having to reconcile the separate data silos creates duplicate work and costs for manual fixes.
According to a Gartner report, bad data annually costs companies a staggering $12.9 million. You can take their word for it that is it costly and harmful for businesses that fall victim to siloed data. Consider taking a modern data analytics approach to start finding improvements immediately, such as using a data lake.
Poor Customer Experience
Fragmented customer data leads to confused customer experiences, or even ones with incorrect, repetitive information, and a general disconnect in interactions. Forrester research reported knowledge workers spend valuable time, about 12 hours each week, just searching for data. They could have spent valuable time using those resources to be more productive.
One thing that contributes to customers’ negative reviews is being asked to repeat themselves and verify previously verified credentials again and again. It’s a time waster for consumers and employees and leads to wasted overhead and more expenses. It can cause poor customer service and poor internal decision-making because departments can’t quickly agree and move on important strategic company choices.
Strategies to Get Rid of Data Silos
To take a more collaborative approach, with data informing decision-making, consider the following fixes. Breaking data silos apart can really help.
Here are some approaches you might take:
Invest in Integrated Technology Solutions
Implementing tools such as Enterprise Resource Planning (ERP) can connect a business and data, centralizing data, which is great for data integration.
Also, consider Customer Relationship Management (CRM) systems. These also merge customer and client data.
Using cloud-based platforms can further work to centralize customer data. An example might be Salesforce or Microsoft Dynamics since these can unify data across departments and get all of the data sources together.
Foster a Culture of Collaboration
Foster collaboration. Promote a team spirit so employees understand how data and information play pivotal parts in daily functions, decision-making, customer retention, profit increases, growth, and market positioning.
Create cross-functional teams for diverse data inputs on projects. One tip might be using project groups for better communication and shared goals to tear down silo walls.
According to research, businesses on average use over 360 software tools in daily work. This alone demonstrates the great challenge modern-day companies face.
Standardize Data Practices
Create uniform ways of doing things when it comes to data and how to best use the data sets.
Having a common process helps staff collect, store, and share data effectively and consistently. A common data governance framework maintains both data quality and easy access, making it easy to integrate into everyday use. This also greatly helps with data security.
Leverage APIs and Automation
You can use APIs (Application Programming Interfaces) to link up different systems. Marketing and sales departments using both HubSpot and Salesforce is an example of this.
Having a method like that enables teams to share information between platforms easily and in real-time. Automating these pathways makes a business faster and stronger by nature. APIs can really help with tracking data changes.
Train Employees on Data Literacy
Data literacy equips everyone on your staff with how to effectively get more from the tools you’ve installed to centralize information flow.
You can provide team members online or on-site courses. They teach data best practices and demonstrate different uses to inspire workers to utilize accessible data to increase metrics that impact profits.
Ways to Integrate Data
Now that you have some steps you might consider to remove barriers between systems that collect and house data, think about ways to go from disparate systems to one centralized hub. Proper data integration is a great solution.
Think about the following options:
| Method | Description | Benefits |
|---|---|---|
| Custom Scripts | IT can custom code movement of data by writing their own pathways | Full custom control of your method |
| On-premises or cloud based ETL (extract, transform, load) tools | Extract from systems, format to integrate together, and upload into one area | Can consolidate, automate, centralize from different origins easily |
| APIs | Bridges between systems, connecting communication channels | Can unite software programs, so information is mirrored as it’s entered, collected, and adjusted by authorized users |
| Webhooks | Provides real-time transfer of information to keep tools connected | Automated actions between tools once certain trigger is activated |
| Data warehouse | Data lakes in these warehouses are ideal storage spaces to gather data, house them together | Can work with other platforms, like your business’ financial services tools |
Examples of How to Break Down Silos
Think about how you might find successes in your data collection once silos aren’t blocking flow, insights, collaboration, and transparency anymore. These things are critical for business operations.
For example, consider the following:
Case Study 1: Retail Integration
A retail company could start connecting its inventory and sales numbers. It will improve the customer experience, helping manage its stock to satisfy shoppers. This is key for discovering business opportunities.
When retailers avoid running out of popular stock before, they win, and customers appreciate getting what they came in search of. Having a consistent source to know this ahead of demand offers a business strategic timing. The ability to have quality data leads to better experiences.
Case Study 2: Healthcare Records Fix
In healthcare, centralizing patient records lets staff see and work together to reduce errors, inconsistencies, or duplicate data.
Medical is notorious for data silos, and Forbes once deemed it the industry’s “silent tragedy.” One solution may come through extracting and storing the right information to put into tools to coordinate for an easy reference for medical providers to rely on.
Case Study 3: APIs For Tech Connection
Tech startup companies have leveraged APIs as solutions too.
Some use this technology to get their customer-facing support, marketing departments, and internal teams on one central page. Those pathways can automatically send and display any newly updated information, boosting both retention and better and faster customer interactions. APIs are a key component of integrating data.
Polaris Adventures partnered with Zendesk to centralize systems across multiple data entry points, making life easier for its customers and staff alike.
Common Roadblocks
Fixing this systemic approach might sound challenging. So know that there are several solutions for those kinds of obstacles.
Resistance to Change
You will likely see teams show hesitancy in accepting data sharing if they feel it risks autonomy and job function. There might be fear in the business unit.
You might handle it by making the change easy for everyone to understand, explaining exactly how using a new centralized data approach benefits. Also, offer thorough training so they’re skilled to confidently approach this new tool. Be prepared that staff may feel that information sharing might remove their individual departmental value and that it impacts the critical business.
Budget Constraints
New software, staff training, re-doing policy, and rolling out that new plan all cost resources.
This might be a common hesitation managers use to avoid updating their operations. Start with small updates. Make them simple enough for staff to absorb. And pick a single, high-impact area. Show its potential to save time, boost profit and work towards building trust.
Data Security Concerns
Centralized data might worry stakeholders, triggering fear over privacy. Having strong access controls in place is important.
This requires securing data by robust and top-tier practices. The financial industry averages $4.35 million in data breach expenses. Compliance standards might keep businesses better accountable for securing the info collected and housed in systems. Using things like artificial intelligence could make things more secure.
Conclusion
Data silos don’t have to impede your team’s efforts or limit your overall success. With the right technological investment, data standardization, and comprehensive training, you can break down barriers between departments and remove the obstacles that prevent smooth collaboration. By eliminating data silos, you can enable seamless communication across all areas of your organization, leading to better-informed decision-making and increased productivity. This structured data flow empowers your business to move forward and avoid the inefficiencies caused by fragmented systems, ultimately reducing productivity that arises from miscommunication, delayed access to critical information, and duplicated efforts.
When you remove data silos, you unlock the potential for greater efficiency, uncover insights that drive strategy, and eliminate unnecessary financial waste. Most importantly, you can enhance your connection with loyal customers, providing them with personalized experiences that align with their needs and preferences. Overcoming data silos also enables businesses to anticipate future challenges and opportunities, making it easier to adapt and grow. By minimizing reduced productivity, you set the stage for smoother operations and better alignment across teams.
To sustain these improvements and continue building on your team’s productivity, it’s essential to focus on areas with the highest integration potential. By optimizing data storage solutions like data warehouses and strengthening your team’s understanding of structured data, you can maximize your return on investment (ROI). This strategic approach ensures that you’re not just overcoming data silos but turning them into assets that fuel future growth, reducing productivity loss, and setting your business up for long-term success.
