Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

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Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

Lindsay McGuire
/
February 4, 2018
Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

MIN
/
February 4, 2018
About the Episode
Episode Highlights
Meet our Guest

We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 1 of a 3-part series on data silos: Part 1 examines where data silos come from and how they became a problem in the first place.

If you think data silos are bad for your organization – and unequivocally, they are – consider their negative impact in the healthcare industry:

When doctors at hospitals or private care centers come across an unusual symptom or diagnosis, they will look to repositories of patient data from around the country and world to find a precedent they can act on swiftly to potentially save a life.

Unfortunately, hospitals have been hoarding private patient and treatment data for decades, all in the name of competitive advantage. They don’t want to share their own valuable research with their “competitors” (i.e. other treatment centers that patients might opt to go to instead of theirs). This creates a pervasive environment of data hoarding throughout the healthcare industry – “If you won’t share your data, I won’t either!” – that ultimately inhibits innovation and has an adverse trickle-down effect on the many patients who don’t get to benefit from shared data.

Those same data silos exist in your organization, with your individual teams and their processes playing the role of the hospitals. These silos might not have as dramatic an impact, like saving lives, but they are nevertheless hurting your ability to make the right decisions, and your business’ bottom line.

In order to eliminate data silos, we must first understand them and where they came from. Only then can we recognize their true dangers and, most importantly, how to break them down once and for all.

What Data Silos Look Like

The warning signs of whether your organization works in data silos are clear: Are you ignorant or unaware of key projects taking place in other divisions? Did someone mention a metric, a record or a custom field that sounds totally foreign to you? If you answered yes to either, that’s a telltale sign that the divisions within your company operate in silos.

Data silos can be vertical or horizontal across your organization. There could be high barriers between individual units (i.e. your sales manager and marketing manager don’t share data with each other) or senior leadership could be isolated from lower management levels (i.e. nobody shares data with the CEO or CFO).

Another telltale sign of a data silo is in the number of custom fields you have across your various business systems and pieces of software. Most such applications are built independently of each other, and will have their own custom requirements and data touch points. The more unique pieces of software you need to run your operations, the more custom fields they will each require, and the more siloed your overall company data will become.

Where Data Silos Come From

There are several key reasons why and how data silos get formed in the first place. Are any of the issues below causing data silos at your organization?

Too Much Software

The first has to do with all the software and business systems we mentioned above. CRM, marketing automation, email, finance, and support software are all systems designed to help you market, sell, support, and operate better. And these are only the core systems; we haven’t even scratched the surface of all those tools with very specific niche use cases. A marketing team could have 20 different pieces of software, all doing one little thing that contributes to overall marketing success. All of this was made possible by the rise of the cloud and the proliferation of Software-as-a-Service (SaaS) companies.

The rise of cloud computing made it easier for more niche vendors and products, with very specific use cases, to enter the business marketplace. It also reduced costs and barriers to entry, making it easier for individual stakeholders to purchase these SaaS tools without necessarily having to go through IT or one single overseer in charge of all software and data.

Suddenly, marketing and sales teams were inundating their organizations with software and tools to tackle use cases big and small. Each of these new systems collected volumes of data. Because all this software was created independently of each other, they might have custom fields or objects that aren’t exactly the same as in the other systems you installed. When your systems don’t “play nice” together, that’s how data silos are created. The more software you have, the more data silos will sprout.

Disparate and Unaligned Teams

Another reason for the rise of data silos has to do with the way modern-day organizations are structured. Companies are increasingly divided into disparate teams, with a clear division of labor and responsibilities. And that can be a great thing! When teams and employees stay in their lane, they will have a heightened and sharpened focus that can lead to great performance, while being more accountable within the organization.

Unfortunately, disparate teams also end up becoming misaligned, with each team leader implementing their own processes and, inevitably, the software they feel they need. They don’t communicate with other departments to share their goals, their projects, and the data they’ve accumulated. The silos that naturally occur due to divided responsibilities will translate to the data each individual team works with.

Wanting Control Over Data

A secondary – and ironic – reason for the rise of data silos has to do with the rise of data-driven organizations who want to make data-driven decisions. It’s also one that might sound familiar to the data hoarders in healthcare, and was described in an Aberdeen Group report as “database administrators’ detrimental sense of proprietorship.”

Simply put, whoever is in charge of the data at a given organization tends to be selfish with it, reluctant to give up control of or access to it. This is grossly opposed to the efforts of most companies to become more democratized with their data and making it accessible to all. There are legacy enterprises where a database administrator has been in charge of the data for years, and is not ready to give it up.

Ignoring the Issues

Finally, there is a prevailing sense of “too big to fail” when it comes to data silos. A lot of these problems get built up and ignored over time. It reaches a point where stakeholders recognize the problem and the need to fix it…but where to begin? Do they have to start from scratch in terms of breaking down some of these complex systems that have only added more complex workflows over the years? Do they have to get rid of some systems altogether? Can they sync not only their new data but also all of the valuable historical data they’ve aggregated?

These are complicated questions, with no easy fixes. Because there isn’t always an elegant data integration solution to break down these silos, many companies just end up throwing up their hands in frustration and sweeping these problems under the rug, continuing to operate in silos.

Don’t let that happen to your organization. Knowing where data silos come from is only the beginning, but it’s a great first step. Continuing to operate in data silos will only hamstring your business. Check back to learn more about just how dangerous data silos can be, and how to break them down once and for all.

Now that you know how data silos develop, it's time to discover how they impact your productivity. Dive into the second post in this series, The Danger of Data Silos, Part 2: How Do They Hurt You?, to learn how damaging these data silos can be.


Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

Blog

The Danger of Data Silos, Part 1: Where Do They Come From?

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We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 1 of a 3-part series on data silos: Part 1 examines where data silos come from and how they became a problem in the first place.

If you think data silos are bad for your organization – and unequivocally, they are – consider their negative impact in the healthcare industry:

When doctors at hospitals or private care centers come across an unusual symptom or diagnosis, they will look to repositories of patient data from around the country and world to find a precedent they can act on swiftly to potentially save a life.

Unfortunately, hospitals have been hoarding private patient and treatment data for decades, all in the name of competitive advantage. They don’t want to share their own valuable research with their “competitors” (i.e. other treatment centers that patients might opt to go to instead of theirs). This creates a pervasive environment of data hoarding throughout the healthcare industry – “If you won’t share your data, I won’t either!” – that ultimately inhibits innovation and has an adverse trickle-down effect on the many patients who don’t get to benefit from shared data.

Those same data silos exist in your organization, with your individual teams and their processes playing the role of the hospitals. These silos might not have as dramatic an impact, like saving lives, but they are nevertheless hurting your ability to make the right decisions, and your business’ bottom line.

In order to eliminate data silos, we must first understand them and where they came from. Only then can we recognize their true dangers and, most importantly, how to break them down once and for all.

What Data Silos Look Like

The warning signs of whether your organization works in data silos are clear: Are you ignorant or unaware of key projects taking place in other divisions? Did someone mention a metric, a record or a custom field that sounds totally foreign to you? If you answered yes to either, that’s a telltale sign that the divisions within your company operate in silos.

Data silos can be vertical or horizontal across your organization. There could be high barriers between individual units (i.e. your sales manager and marketing manager don’t share data with each other) or senior leadership could be isolated from lower management levels (i.e. nobody shares data with the CEO or CFO).

Another telltale sign of a data silo is in the number of custom fields you have across your various business systems and pieces of software. Most such applications are built independently of each other, and will have their own custom requirements and data touch points. The more unique pieces of software you need to run your operations, the more custom fields they will each require, and the more siloed your overall company data will become.

Where Data Silos Come From

There are several key reasons why and how data silos get formed in the first place. Are any of the issues below causing data silos at your organization?

Too Much Software

The first has to do with all the software and business systems we mentioned above. CRM, marketing automation, email, finance, and support software are all systems designed to help you market, sell, support, and operate better. And these are only the core systems; we haven’t even scratched the surface of all those tools with very specific niche use cases. A marketing team could have 20 different pieces of software, all doing one little thing that contributes to overall marketing success. All of this was made possible by the rise of the cloud and the proliferation of Software-as-a-Service (SaaS) companies.

The rise of cloud computing made it easier for more niche vendors and products, with very specific use cases, to enter the business marketplace. It also reduced costs and barriers to entry, making it easier for individual stakeholders to purchase these SaaS tools without necessarily having to go through IT or one single overseer in charge of all software and data.

Suddenly, marketing and sales teams were inundating their organizations with software and tools to tackle use cases big and small. Each of these new systems collected volumes of data. Because all this software was created independently of each other, they might have custom fields or objects that aren’t exactly the same as in the other systems you installed. When your systems don’t “play nice” together, that’s how data silos are created. The more software you have, the more data silos will sprout.

Disparate and Unaligned Teams

Another reason for the rise of data silos has to do with the way modern-day organizations are structured. Companies are increasingly divided into disparate teams, with a clear division of labor and responsibilities. And that can be a great thing! When teams and employees stay in their lane, they will have a heightened and sharpened focus that can lead to great performance, while being more accountable within the organization.

Unfortunately, disparate teams also end up becoming misaligned, with each team leader implementing their own processes and, inevitably, the software they feel they need. They don’t communicate with other departments to share their goals, their projects, and the data they’ve accumulated. The silos that naturally occur due to divided responsibilities will translate to the data each individual team works with.

Wanting Control Over Data

A secondary – and ironic – reason for the rise of data silos has to do with the rise of data-driven organizations who want to make data-driven decisions. It’s also one that might sound familiar to the data hoarders in healthcare, and was described in an Aberdeen Group report as “database administrators’ detrimental sense of proprietorship.”

Simply put, whoever is in charge of the data at a given organization tends to be selfish with it, reluctant to give up control of or access to it. This is grossly opposed to the efforts of most companies to become more democratized with their data and making it accessible to all. There are legacy enterprises where a database administrator has been in charge of the data for years, and is not ready to give it up.

Ignoring the Issues

Finally, there is a prevailing sense of “too big to fail” when it comes to data silos. A lot of these problems get built up and ignored over time. It reaches a point where stakeholders recognize the problem and the need to fix it…but where to begin? Do they have to start from scratch in terms of breaking down some of these complex systems that have only added more complex workflows over the years? Do they have to get rid of some systems altogether? Can they sync not only their new data but also all of the valuable historical data they’ve aggregated?

These are complicated questions, with no easy fixes. Because there isn’t always an elegant data integration solution to break down these silos, many companies just end up throwing up their hands in frustration and sweeping these problems under the rug, continuing to operate in silos.

Don’t let that happen to your organization. Knowing where data silos come from is only the beginning, but it’s a great first step. Continuing to operate in data silos will only hamstring your business. Check back to learn more about just how dangerous data silos can be, and how to break them down once and for all.

Now that you know how data silos develop, it's time to discover how they impact your productivity. Dive into the second post in this series, The Danger of Data Silos, Part 2: How Do They Hurt You?, to learn how damaging these data silos can be.


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The Danger of Data Silos, Part 1: Where Do They Come From?

There are several ways data silos form over time. Learn about this rampant data issue so you can better identify data silos within your organization.
Download InfographicDownload Infographic

We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 1 of a 3-part series on data silos: Part 1 examines where data silos come from and how they became a problem in the first place.

If you think data silos are bad for your organization – and unequivocally, they are – consider their negative impact in the healthcare industry:

When doctors at hospitals or private care centers come across an unusual symptom or diagnosis, they will look to repositories of patient data from around the country and world to find a precedent they can act on swiftly to potentially save a life.

Unfortunately, hospitals have been hoarding private patient and treatment data for decades, all in the name of competitive advantage. They don’t want to share their own valuable research with their “competitors” (i.e. other treatment centers that patients might opt to go to instead of theirs). This creates a pervasive environment of data hoarding throughout the healthcare industry – “If you won’t share your data, I won’t either!” – that ultimately inhibits innovation and has an adverse trickle-down effect on the many patients who don’t get to benefit from shared data.

Those same data silos exist in your organization, with your individual teams and their processes playing the role of the hospitals. These silos might not have as dramatic an impact, like saving lives, but they are nevertheless hurting your ability to make the right decisions, and your business’ bottom line.

In order to eliminate data silos, we must first understand them and where they came from. Only then can we recognize their true dangers and, most importantly, how to break them down once and for all.

What Data Silos Look Like

The warning signs of whether your organization works in data silos are clear: Are you ignorant or unaware of key projects taking place in other divisions? Did someone mention a metric, a record or a custom field that sounds totally foreign to you? If you answered yes to either, that’s a telltale sign that the divisions within your company operate in silos.

Data silos can be vertical or horizontal across your organization. There could be high barriers between individual units (i.e. your sales manager and marketing manager don’t share data with each other) or senior leadership could be isolated from lower management levels (i.e. nobody shares data with the CEO or CFO).

Another telltale sign of a data silo is in the number of custom fields you have across your various business systems and pieces of software. Most such applications are built independently of each other, and will have their own custom requirements and data touch points. The more unique pieces of software you need to run your operations, the more custom fields they will each require, and the more siloed your overall company data will become.

Where Data Silos Come From

There are several key reasons why and how data silos get formed in the first place. Are any of the issues below causing data silos at your organization?

Too Much Software

The first has to do with all the software and business systems we mentioned above. CRM, marketing automation, email, finance, and support software are all systems designed to help you market, sell, support, and operate better. And these are only the core systems; we haven’t even scratched the surface of all those tools with very specific niche use cases. A marketing team could have 20 different pieces of software, all doing one little thing that contributes to overall marketing success. All of this was made possible by the rise of the cloud and the proliferation of Software-as-a-Service (SaaS) companies.

The rise of cloud computing made it easier for more niche vendors and products, with very specific use cases, to enter the business marketplace. It also reduced costs and barriers to entry, making it easier for individual stakeholders to purchase these SaaS tools without necessarily having to go through IT or one single overseer in charge of all software and data.

Suddenly, marketing and sales teams were inundating their organizations with software and tools to tackle use cases big and small. Each of these new systems collected volumes of data. Because all this software was created independently of each other, they might have custom fields or objects that aren’t exactly the same as in the other systems you installed. When your systems don’t “play nice” together, that’s how data silos are created. The more software you have, the more data silos will sprout.

Disparate and Unaligned Teams

Another reason for the rise of data silos has to do with the way modern-day organizations are structured. Companies are increasingly divided into disparate teams, with a clear division of labor and responsibilities. And that can be a great thing! When teams and employees stay in their lane, they will have a heightened and sharpened focus that can lead to great performance, while being more accountable within the organization.

Unfortunately, disparate teams also end up becoming misaligned, with each team leader implementing their own processes and, inevitably, the software they feel they need. They don’t communicate with other departments to share their goals, their projects, and the data they’ve accumulated. The silos that naturally occur due to divided responsibilities will translate to the data each individual team works with.

Wanting Control Over Data

A secondary – and ironic – reason for the rise of data silos has to do with the rise of data-driven organizations who want to make data-driven decisions. It’s also one that might sound familiar to the data hoarders in healthcare, and was described in an Aberdeen Group report as “database administrators’ detrimental sense of proprietorship.”

Simply put, whoever is in charge of the data at a given organization tends to be selfish with it, reluctant to give up control of or access to it. This is grossly opposed to the efforts of most companies to become more democratized with their data and making it accessible to all. There are legacy enterprises where a database administrator has been in charge of the data for years, and is not ready to give it up.

Ignoring the Issues

Finally, there is a prevailing sense of “too big to fail” when it comes to data silos. A lot of these problems get built up and ignored over time. It reaches a point where stakeholders recognize the problem and the need to fix it…but where to begin? Do they have to start from scratch in terms of breaking down some of these complex systems that have only added more complex workflows over the years? Do they have to get rid of some systems altogether? Can they sync not only their new data but also all of the valuable historical data they’ve aggregated?

These are complicated questions, with no easy fixes. Because there isn’t always an elegant data integration solution to break down these silos, many companies just end up throwing up their hands in frustration and sweeping these problems under the rug, continuing to operate in silos.

Don’t let that happen to your organization. Knowing where data silos come from is only the beginning, but it’s a great first step. Continuing to operate in data silos will only hamstring your business. Check back to learn more about just how dangerous data silos can be, and how to break them down once and for all.

Now that you know how data silos develop, it's time to discover how they impact your productivity. Dive into the second post in this series, The Danger of Data Silos, Part 2: How Do They Hurt You?, to learn how damaging these data silos can be.


We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 1 of a 3-part series on data silos: Part 1 examines where data silos come from and how they became a problem in the first place.

If you think data silos are bad for your organization – and unequivocally, they are – consider their negative impact in the healthcare industry:

When doctors at hospitals or private care centers come across an unusual symptom or diagnosis, they will look to repositories of patient data from around the country and world to find a precedent they can act on swiftly to potentially save a life.

Unfortunately, hospitals have been hoarding private patient and treatment data for decades, all in the name of competitive advantage. They don’t want to share their own valuable research with their “competitors” (i.e. other treatment centers that patients might opt to go to instead of theirs). This creates a pervasive environment of data hoarding throughout the healthcare industry – “If you won’t share your data, I won’t either!” – that ultimately inhibits innovation and has an adverse trickle-down effect on the many patients who don’t get to benefit from shared data.

Those same data silos exist in your organization, with your individual teams and their processes playing the role of the hospitals. These silos might not have as dramatic an impact, like saving lives, but they are nevertheless hurting your ability to make the right decisions, and your business’ bottom line.

In order to eliminate data silos, we must first understand them and where they came from. Only then can we recognize their true dangers and, most importantly, how to break them down once and for all.

What Data Silos Look Like

The warning signs of whether your organization works in data silos are clear: Are you ignorant or unaware of key projects taking place in other divisions? Did someone mention a metric, a record or a custom field that sounds totally foreign to you? If you answered yes to either, that’s a telltale sign that the divisions within your company operate in silos.

Data silos can be vertical or horizontal across your organization. There could be high barriers between individual units (i.e. your sales manager and marketing manager don’t share data with each other) or senior leadership could be isolated from lower management levels (i.e. nobody shares data with the CEO or CFO).

Another telltale sign of a data silo is in the number of custom fields you have across your various business systems and pieces of software. Most such applications are built independently of each other, and will have their own custom requirements and data touch points. The more unique pieces of software you need to run your operations, the more custom fields they will each require, and the more siloed your overall company data will become.

Where Data Silos Come From

There are several key reasons why and how data silos get formed in the first place. Are any of the issues below causing data silos at your organization?

Too Much Software

The first has to do with all the software and business systems we mentioned above. CRM, marketing automation, email, finance, and support software are all systems designed to help you market, sell, support, and operate better. And these are only the core systems; we haven’t even scratched the surface of all those tools with very specific niche use cases. A marketing team could have 20 different pieces of software, all doing one little thing that contributes to overall marketing success. All of this was made possible by the rise of the cloud and the proliferation of Software-as-a-Service (SaaS) companies.

The rise of cloud computing made it easier for more niche vendors and products, with very specific use cases, to enter the business marketplace. It also reduced costs and barriers to entry, making it easier for individual stakeholders to purchase these SaaS tools without necessarily having to go through IT or one single overseer in charge of all software and data.

Suddenly, marketing and sales teams were inundating their organizations with software and tools to tackle use cases big and small. Each of these new systems collected volumes of data. Because all this software was created independently of each other, they might have custom fields or objects that aren’t exactly the same as in the other systems you installed. When your systems don’t “play nice” together, that’s how data silos are created. The more software you have, the more data silos will sprout.

Disparate and Unaligned Teams

Another reason for the rise of data silos has to do with the way modern-day organizations are structured. Companies are increasingly divided into disparate teams, with a clear division of labor and responsibilities. And that can be a great thing! When teams and employees stay in their lane, they will have a heightened and sharpened focus that can lead to great performance, while being more accountable within the organization.

Unfortunately, disparate teams also end up becoming misaligned, with each team leader implementing their own processes and, inevitably, the software they feel they need. They don’t communicate with other departments to share their goals, their projects, and the data they’ve accumulated. The silos that naturally occur due to divided responsibilities will translate to the data each individual team works with.

Wanting Control Over Data

A secondary – and ironic – reason for the rise of data silos has to do with the rise of data-driven organizations who want to make data-driven decisions. It’s also one that might sound familiar to the data hoarders in healthcare, and was described in an Aberdeen Group report as “database administrators’ detrimental sense of proprietorship.”

Simply put, whoever is in charge of the data at a given organization tends to be selfish with it, reluctant to give up control of or access to it. This is grossly opposed to the efforts of most companies to become more democratized with their data and making it accessible to all. There are legacy enterprises where a database administrator has been in charge of the data for years, and is not ready to give it up.

Ignoring the Issues

Finally, there is a prevailing sense of “too big to fail” when it comes to data silos. A lot of these problems get built up and ignored over time. It reaches a point where stakeholders recognize the problem and the need to fix it…but where to begin? Do they have to start from scratch in terms of breaking down some of these complex systems that have only added more complex workflows over the years? Do they have to get rid of some systems altogether? Can they sync not only their new data but also all of the valuable historical data they’ve aggregated?

These are complicated questions, with no easy fixes. Because there isn’t always an elegant data integration solution to break down these silos, many companies just end up throwing up their hands in frustration and sweeping these problems under the rug, continuing to operate in silos.

Don’t let that happen to your organization. Knowing where data silos come from is only the beginning, but it’s a great first step. Continuing to operate in data silos will only hamstring your business. Check back to learn more about just how dangerous data silos can be, and how to break them down once and for all.

Now that you know how data silos develop, it's time to discover how they impact your productivity. Dive into the second post in this series, The Danger of Data Silos, Part 2: How Do They Hurt You?, to learn how damaging these data silos can be.


Collecting payments with online forms is easy, but first, you have to choose the right payment gateway. Browse the providers in our gateway credit card processing comparison chart to find the best option for your business. Then sign up for Formstack Forms, customize your payment forms, and start collecting profits in minutes.

Online Payment Gateway Comparison Chart

NOTE: These amounts reflect the monthly subscription for the payment provider. Formstack does not charge a fee to integrate with any of our payment partners.

FEATURES
Authorize.Net
Bambora
Chargify
First Data
PayPal
PayPal Pro
PayPal Payflow
Stripe
WePay
ProPay
Monthly Fees
$25
$25
$149+
Contact First Data
$0
$25
$0-$25
$0
$0
$4
Transaction Fees
$2.9% + 30¢
$2.9% + 30¢
N/A
Contact First Data
$2.9% + 30¢
$2.9% + 30¢
10¢
$2.9% + 30¢
$2.9% + 30¢
$2.6% + 30¢
Countries
5
8
Based on payment gateway
50+
203
3
4
25
USA
USA
Currencies
11
2
23
140
25
23
25
135+
1
1
Card Types
6
13
Based on payment gateway
5
9
9
5
6
4
4
Limits
None
None
Based on payment gateway
None
$10,000
None
None
None
None
$500 per transaction
Form Payments
Recurring Billing
Mobile Payments
PSD2 Compliant

We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 1 of a 3-part series on data silos: Part 1 examines where data silos come from and how they became a problem in the first place.

If you think data silos are bad for your organization – and unequivocally, they are – consider their negative impact in the healthcare industry:

When doctors at hospitals or private care centers come across an unusual symptom or diagnosis, they will look to repositories of patient data from around the country and world to find a precedent they can act on swiftly to potentially save a life.

Unfortunately, hospitals have been hoarding private patient and treatment data for decades, all in the name of competitive advantage. They don’t want to share their own valuable research with their “competitors” (i.e. other treatment centers that patients might opt to go to instead of theirs). This creates a pervasive environment of data hoarding throughout the healthcare industry – “If you won’t share your data, I won’t either!” – that ultimately inhibits innovation and has an adverse trickle-down effect on the many patients who don’t get to benefit from shared data.

Those same data silos exist in your organization, with your individual teams and their processes playing the role of the hospitals. These silos might not have as dramatic an impact, like saving lives, but they are nevertheless hurting your ability to make the right decisions, and your business’ bottom line.

In order to eliminate data silos, we must first understand them and where they came from. Only then can we recognize their true dangers and, most importantly, how to break them down once and for all.

What Data Silos Look Like

The warning signs of whether your organization works in data silos are clear: Are you ignorant or unaware of key projects taking place in other divisions? Did someone mention a metric, a record or a custom field that sounds totally foreign to you? If you answered yes to either, that’s a telltale sign that the divisions within your company operate in silos.

Data silos can be vertical or horizontal across your organization. There could be high barriers between individual units (i.e. your sales manager and marketing manager don’t share data with each other) or senior leadership could be isolated from lower management levels (i.e. nobody shares data with the CEO or CFO).

Another telltale sign of a data silo is in the number of custom fields you have across your various business systems and pieces of software. Most such applications are built independently of each other, and will have their own custom requirements and data touch points. The more unique pieces of software you need to run your operations, the more custom fields they will each require, and the more siloed your overall company data will become.

Where Data Silos Come From

There are several key reasons why and how data silos get formed in the first place. Are any of the issues below causing data silos at your organization?

Too Much Software

The first has to do with all the software and business systems we mentioned above. CRM, marketing automation, email, finance, and support software are all systems designed to help you market, sell, support, and operate better. And these are only the core systems; we haven’t even scratched the surface of all those tools with very specific niche use cases. A marketing team could have 20 different pieces of software, all doing one little thing that contributes to overall marketing success. All of this was made possible by the rise of the cloud and the proliferation of Software-as-a-Service (SaaS) companies.

The rise of cloud computing made it easier for more niche vendors and products, with very specific use cases, to enter the business marketplace. It also reduced costs and barriers to entry, making it easier for individual stakeholders to purchase these SaaS tools without necessarily having to go through IT or one single overseer in charge of all software and data.

Suddenly, marketing and sales teams were inundating their organizations with software and tools to tackle use cases big and small. Each of these new systems collected volumes of data. Because all this software was created independently of each other, they might have custom fields or objects that aren’t exactly the same as in the other systems you installed. When your systems don’t “play nice” together, that’s how data silos are created. The more software you have, the more data silos will sprout.

Disparate and Unaligned Teams

Another reason for the rise of data silos has to do with the way modern-day organizations are structured. Companies are increasingly divided into disparate teams, with a clear division of labor and responsibilities. And that can be a great thing! When teams and employees stay in their lane, they will have a heightened and sharpened focus that can lead to great performance, while being more accountable within the organization.

Unfortunately, disparate teams also end up becoming misaligned, with each team leader implementing their own processes and, inevitably, the software they feel they need. They don’t communicate with other departments to share their goals, their projects, and the data they’ve accumulated. The silos that naturally occur due to divided responsibilities will translate to the data each individual team works with.

Wanting Control Over Data

A secondary – and ironic – reason for the rise of data silos has to do with the rise of data-driven organizations who want to make data-driven decisions. It’s also one that might sound familiar to the data hoarders in healthcare, and was described in an Aberdeen Group report as “database administrators’ detrimental sense of proprietorship.”

Simply put, whoever is in charge of the data at a given organization tends to be selfish with it, reluctant to give up control of or access to it. This is grossly opposed to the efforts of most companies to become more democratized with their data and making it accessible to all. There are legacy enterprises where a database administrator has been in charge of the data for years, and is not ready to give it up.

Ignoring the Issues

Finally, there is a prevailing sense of “too big to fail” when it comes to data silos. A lot of these problems get built up and ignored over time. It reaches a point where stakeholders recognize the problem and the need to fix it…but where to begin? Do they have to start from scratch in terms of breaking down some of these complex systems that have only added more complex workflows over the years? Do they have to get rid of some systems altogether? Can they sync not only their new data but also all of the valuable historical data they’ve aggregated?

These are complicated questions, with no easy fixes. Because there isn’t always an elegant data integration solution to break down these silos, many companies just end up throwing up their hands in frustration and sweeping these problems under the rug, continuing to operate in silos.

Don’t let that happen to your organization. Knowing where data silos come from is only the beginning, but it’s a great first step. Continuing to operate in data silos will only hamstring your business. Check back to learn more about just how dangerous data silos can be, and how to break them down once and for all.

Now that you know how data silos develop, it's time to discover how they impact your productivity. Dive into the second post in this series, The Danger of Data Silos, Part 2: How Do They Hurt You?, to learn how damaging these data silos can be.


We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 1 of a 3-part series on data silos: Part 1 examines where data silos come from and how they became a problem in the first place.

If you think data silos are bad for your organization – and unequivocally, they are – consider their negative impact in the healthcare industry:

When doctors at hospitals or private care centers come across an unusual symptom or diagnosis, they will look to repositories of patient data from around the country and world to find a precedent they can act on swiftly to potentially save a life.

Unfortunately, hospitals have been hoarding private patient and treatment data for decades, all in the name of competitive advantage. They don’t want to share their own valuable research with their “competitors” (i.e. other treatment centers that patients might opt to go to instead of theirs). This creates a pervasive environment of data hoarding throughout the healthcare industry – “If you won’t share your data, I won’t either!” – that ultimately inhibits innovation and has an adverse trickle-down effect on the many patients who don’t get to benefit from shared data.

Those same data silos exist in your organization, with your individual teams and their processes playing the role of the hospitals. These silos might not have as dramatic an impact, like saving lives, but they are nevertheless hurting your ability to make the right decisions, and your business’ bottom line.

In order to eliminate data silos, we must first understand them and where they came from. Only then can we recognize their true dangers and, most importantly, how to break them down once and for all.

What Data Silos Look Like

The warning signs of whether your organization works in data silos are clear: Are you ignorant or unaware of key projects taking place in other divisions? Did someone mention a metric, a record or a custom field that sounds totally foreign to you? If you answered yes to either, that’s a telltale sign that the divisions within your company operate in silos.

Data silos can be vertical or horizontal across your organization. There could be high barriers between individual units (i.e. your sales manager and marketing manager don’t share data with each other) or senior leadership could be isolated from lower management levels (i.e. nobody shares data with the CEO or CFO).

Another telltale sign of a data silo is in the number of custom fields you have across your various business systems and pieces of software. Most such applications are built independently of each other, and will have their own custom requirements and data touch points. The more unique pieces of software you need to run your operations, the more custom fields they will each require, and the more siloed your overall company data will become.

Where Data Silos Come From

There are several key reasons why and how data silos get formed in the first place. Are any of the issues below causing data silos at your organization?

Too Much Software

The first has to do with all the software and business systems we mentioned above. CRM, marketing automation, email, finance, and support software are all systems designed to help you market, sell, support, and operate better. And these are only the core systems; we haven’t even scratched the surface of all those tools with very specific niche use cases. A marketing team could have 20 different pieces of software, all doing one little thing that contributes to overall marketing success. All of this was made possible by the rise of the cloud and the proliferation of Software-as-a-Service (SaaS) companies.

The rise of cloud computing made it easier for more niche vendors and products, with very specific use cases, to enter the business marketplace. It also reduced costs and barriers to entry, making it easier for individual stakeholders to purchase these SaaS tools without necessarily having to go through IT or one single overseer in charge of all software and data.

Suddenly, marketing and sales teams were inundating their organizations with software and tools to tackle use cases big and small. Each of these new systems collected volumes of data. Because all this software was created independently of each other, they might have custom fields or objects that aren’t exactly the same as in the other systems you installed. When your systems don’t “play nice” together, that’s how data silos are created. The more software you have, the more data silos will sprout.

Disparate and Unaligned Teams

Another reason for the rise of data silos has to do with the way modern-day organizations are structured. Companies are increasingly divided into disparate teams, with a clear division of labor and responsibilities. And that can be a great thing! When teams and employees stay in their lane, they will have a heightened and sharpened focus that can lead to great performance, while being more accountable within the organization.

Unfortunately, disparate teams also end up becoming misaligned, with each team leader implementing their own processes and, inevitably, the software they feel they need. They don’t communicate with other departments to share their goals, their projects, and the data they’ve accumulated. The silos that naturally occur due to divided responsibilities will translate to the data each individual team works with.

Wanting Control Over Data

A secondary – and ironic – reason for the rise of data silos has to do with the rise of data-driven organizations who want to make data-driven decisions. It’s also one that might sound familiar to the data hoarders in healthcare, and was described in an Aberdeen Group report as “database administrators’ detrimental sense of proprietorship.”

Simply put, whoever is in charge of the data at a given organization tends to be selfish with it, reluctant to give up control of or access to it. This is grossly opposed to the efforts of most companies to become more democratized with their data and making it accessible to all. There are legacy enterprises where a database administrator has been in charge of the data for years, and is not ready to give it up.

Ignoring the Issues

Finally, there is a prevailing sense of “too big to fail” when it comes to data silos. A lot of these problems get built up and ignored over time. It reaches a point where stakeholders recognize the problem and the need to fix it…but where to begin? Do they have to start from scratch in terms of breaking down some of these complex systems that have only added more complex workflows over the years? Do they have to get rid of some systems altogether? Can they sync not only their new data but also all of the valuable historical data they’ve aggregated?

These are complicated questions, with no easy fixes. Because there isn’t always an elegant data integration solution to break down these silos, many companies just end up throwing up their hands in frustration and sweeping these problems under the rug, continuing to operate in silos.

Don’t let that happen to your organization. Knowing where data silos come from is only the beginning, but it’s a great first step. Continuing to operate in data silos will only hamstring your business. Check back to learn more about just how dangerous data silos can be, and how to break them down once and for all.

Now that you know how data silos develop, it's time to discover how they impact your productivity. Dive into the second post in this series, The Danger of Data Silos, Part 2: How Do They Hurt You?, to learn how damaging these data silos can be.


We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 1 of a 3-part series on data silos: Part 1 examines where data silos come from and how they became a problem in the first place.

If you think data silos are bad for your organization – and unequivocally, they are – consider their negative impact in the healthcare industry:

When doctors at hospitals or private care centers come across an unusual symptom or diagnosis, they will look to repositories of patient data from around the country and world to find a precedent they can act on swiftly to potentially save a life.

Unfortunately, hospitals have been hoarding private patient and treatment data for decades, all in the name of competitive advantage. They don’t want to share their own valuable research with their “competitors” (i.e. other treatment centers that patients might opt to go to instead of theirs). This creates a pervasive environment of data hoarding throughout the healthcare industry – “If you won’t share your data, I won’t either!” – that ultimately inhibits innovation and has an adverse trickle-down effect on the many patients who don’t get to benefit from shared data.

Those same data silos exist in your organization, with your individual teams and their processes playing the role of the hospitals. These silos might not have as dramatic an impact, like saving lives, but they are nevertheless hurting your ability to make the right decisions, and your business’ bottom line.

In order to eliminate data silos, we must first understand them and where they came from. Only then can we recognize their true dangers and, most importantly, how to break them down once and for all.

What Data Silos Look Like

The warning signs of whether your organization works in data silos are clear: Are you ignorant or unaware of key projects taking place in other divisions? Did someone mention a metric, a record or a custom field that sounds totally foreign to you? If you answered yes to either, that’s a telltale sign that the divisions within your company operate in silos.

Data silos can be vertical or horizontal across your organization. There could be high barriers between individual units (i.e. your sales manager and marketing manager don’t share data with each other) or senior leadership could be isolated from lower management levels (i.e. nobody shares data with the CEO or CFO).

Another telltale sign of a data silo is in the number of custom fields you have across your various business systems and pieces of software. Most such applications are built independently of each other, and will have their own custom requirements and data touch points. The more unique pieces of software you need to run your operations, the more custom fields they will each require, and the more siloed your overall company data will become.

Where Data Silos Come From

There are several key reasons why and how data silos get formed in the first place. Are any of the issues below causing data silos at your organization?

Too Much Software

The first has to do with all the software and business systems we mentioned above. CRM, marketing automation, email, finance, and support software are all systems designed to help you market, sell, support, and operate better. And these are only the core systems; we haven’t even scratched the surface of all those tools with very specific niche use cases. A marketing team could have 20 different pieces of software, all doing one little thing that contributes to overall marketing success. All of this was made possible by the rise of the cloud and the proliferation of Software-as-a-Service (SaaS) companies.

The rise of cloud computing made it easier for more niche vendors and products, with very specific use cases, to enter the business marketplace. It also reduced costs and barriers to entry, making it easier for individual stakeholders to purchase these SaaS tools without necessarily having to go through IT or one single overseer in charge of all software and data.

Suddenly, marketing and sales teams were inundating their organizations with software and tools to tackle use cases big and small. Each of these new systems collected volumes of data. Because all this software was created independently of each other, they might have custom fields or objects that aren’t exactly the same as in the other systems you installed. When your systems don’t “play nice” together, that’s how data silos are created. The more software you have, the more data silos will sprout.

Disparate and Unaligned Teams

Another reason for the rise of data silos has to do with the way modern-day organizations are structured. Companies are increasingly divided into disparate teams, with a clear division of labor and responsibilities. And that can be a great thing! When teams and employees stay in their lane, they will have a heightened and sharpened focus that can lead to great performance, while being more accountable within the organization.

Unfortunately, disparate teams also end up becoming misaligned, with each team leader implementing their own processes and, inevitably, the software they feel they need. They don’t communicate with other departments to share their goals, their projects, and the data they’ve accumulated. The silos that naturally occur due to divided responsibilities will translate to the data each individual team works with.

Wanting Control Over Data

A secondary – and ironic – reason for the rise of data silos has to do with the rise of data-driven organizations who want to make data-driven decisions. It’s also one that might sound familiar to the data hoarders in healthcare, and was described in an Aberdeen Group report as “database administrators’ detrimental sense of proprietorship.”

Simply put, whoever is in charge of the data at a given organization tends to be selfish with it, reluctant to give up control of or access to it. This is grossly opposed to the efforts of most companies to become more democratized with their data and making it accessible to all. There are legacy enterprises where a database administrator has been in charge of the data for years, and is not ready to give it up.

Ignoring the Issues

Finally, there is a prevailing sense of “too big to fail” when it comes to data silos. A lot of these problems get built up and ignored over time. It reaches a point where stakeholders recognize the problem and the need to fix it…but where to begin? Do they have to start from scratch in terms of breaking down some of these complex systems that have only added more complex workflows over the years? Do they have to get rid of some systems altogether? Can they sync not only their new data but also all of the valuable historical data they’ve aggregated?

These are complicated questions, with no easy fixes. Because there isn’t always an elegant data integration solution to break down these silos, many companies just end up throwing up their hands in frustration and sweeping these problems under the rug, continuing to operate in silos.

Don’t let that happen to your organization. Knowing where data silos come from is only the beginning, but it’s a great first step. Continuing to operate in data silos will only hamstring your business. Check back to learn more about just how dangerous data silos can be, and how to break them down once and for all.

Now that you know how data silos develop, it's time to discover how they impact your productivity. Dive into the second post in this series, The Danger of Data Silos, Part 2: How Do They Hurt You?, to learn how damaging these data silos can be.


We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 1 of a 3-part series on data silos: Part 1 examines where data silos come from and how they became a problem in the first place.

If you think data silos are bad for your organization – and unequivocally, they are – consider their negative impact in the healthcare industry:

When doctors at hospitals or private care centers come across an unusual symptom or diagnosis, they will look to repositories of patient data from around the country and world to find a precedent they can act on swiftly to potentially save a life.

Unfortunately, hospitals have been hoarding private patient and treatment data for decades, all in the name of competitive advantage. They don’t want to share their own valuable research with their “competitors” (i.e. other treatment centers that patients might opt to go to instead of theirs). This creates a pervasive environment of data hoarding throughout the healthcare industry – “If you won’t share your data, I won’t either!” – that ultimately inhibits innovation and has an adverse trickle-down effect on the many patients who don’t get to benefit from shared data.

Those same data silos exist in your organization, with your individual teams and their processes playing the role of the hospitals. These silos might not have as dramatic an impact, like saving lives, but they are nevertheless hurting your ability to make the right decisions, and your business’ bottom line.

In order to eliminate data silos, we must first understand them and where they came from. Only then can we recognize their true dangers and, most importantly, how to break them down once and for all.

What Data Silos Look Like

The warning signs of whether your organization works in data silos are clear: Are you ignorant or unaware of key projects taking place in other divisions? Did someone mention a metric, a record or a custom field that sounds totally foreign to you? If you answered yes to either, that’s a telltale sign that the divisions within your company operate in silos.

Data silos can be vertical or horizontal across your organization. There could be high barriers between individual units (i.e. your sales manager and marketing manager don’t share data with each other) or senior leadership could be isolated from lower management levels (i.e. nobody shares data with the CEO or CFO).

Another telltale sign of a data silo is in the number of custom fields you have across your various business systems and pieces of software. Most such applications are built independently of each other, and will have their own custom requirements and data touch points. The more unique pieces of software you need to run your operations, the more custom fields they will each require, and the more siloed your overall company data will become.

Where Data Silos Come From

There are several key reasons why and how data silos get formed in the first place. Are any of the issues below causing data silos at your organization?

Too Much Software

The first has to do with all the software and business systems we mentioned above. CRM, marketing automation, email, finance, and support software are all systems designed to help you market, sell, support, and operate better. And these are only the core systems; we haven’t even scratched the surface of all those tools with very specific niche use cases. A marketing team could have 20 different pieces of software, all doing one little thing that contributes to overall marketing success. All of this was made possible by the rise of the cloud and the proliferation of Software-as-a-Service (SaaS) companies.

The rise of cloud computing made it easier for more niche vendors and products, with very specific use cases, to enter the business marketplace. It also reduced costs and barriers to entry, making it easier for individual stakeholders to purchase these SaaS tools without necessarily having to go through IT or one single overseer in charge of all software and data.

Suddenly, marketing and sales teams were inundating their organizations with software and tools to tackle use cases big and small. Each of these new systems collected volumes of data. Because all this software was created independently of each other, they might have custom fields or objects that aren’t exactly the same as in the other systems you installed. When your systems don’t “play nice” together, that’s how data silos are created. The more software you have, the more data silos will sprout.

Disparate and Unaligned Teams

Another reason for the rise of data silos has to do with the way modern-day organizations are structured. Companies are increasingly divided into disparate teams, with a clear division of labor and responsibilities. And that can be a great thing! When teams and employees stay in their lane, they will have a heightened and sharpened focus that can lead to great performance, while being more accountable within the organization.

Unfortunately, disparate teams also end up becoming misaligned, with each team leader implementing their own processes and, inevitably, the software they feel they need. They don’t communicate with other departments to share their goals, their projects, and the data they’ve accumulated. The silos that naturally occur due to divided responsibilities will translate to the data each individual team works with.

Wanting Control Over Data

A secondary – and ironic – reason for the rise of data silos has to do with the rise of data-driven organizations who want to make data-driven decisions. It’s also one that might sound familiar to the data hoarders in healthcare, and was described in an Aberdeen Group report as “database administrators’ detrimental sense of proprietorship.”

Simply put, whoever is in charge of the data at a given organization tends to be selfish with it, reluctant to give up control of or access to it. This is grossly opposed to the efforts of most companies to become more democratized with their data and making it accessible to all. There are legacy enterprises where a database administrator has been in charge of the data for years, and is not ready to give it up.

Ignoring the Issues

Finally, there is a prevailing sense of “too big to fail” when it comes to data silos. A lot of these problems get built up and ignored over time. It reaches a point where stakeholders recognize the problem and the need to fix it…but where to begin? Do they have to start from scratch in terms of breaking down some of these complex systems that have only added more complex workflows over the years? Do they have to get rid of some systems altogether? Can they sync not only their new data but also all of the valuable historical data they’ve aggregated?

These are complicated questions, with no easy fixes. Because there isn’t always an elegant data integration solution to break down these silos, many companies just end up throwing up their hands in frustration and sweeping these problems under the rug, continuing to operate in silos.

Don’t let that happen to your organization. Knowing where data silos come from is only the beginning, but it’s a great first step. Continuing to operate in data silos will only hamstring your business. Check back to learn more about just how dangerous data silos can be, and how to break them down once and for all.

Now that you know how data silos develop, it's time to discover how they impact your productivity. Dive into the second post in this series, The Danger of Data Silos, Part 2: How Do They Hurt You?, to learn how damaging these data silos can be.


We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 1 of a 3-part series on data silos: Part 1 examines where data silos come from and how they became a problem in the first place.

If you think data silos are bad for your organization – and unequivocally, they are – consider their negative impact in the healthcare industry:

When doctors at hospitals or private care centers come across an unusual symptom or diagnosis, they will look to repositories of patient data from around the country and world to find a precedent they can act on swiftly to potentially save a life.

Unfortunately, hospitals have been hoarding private patient and treatment data for decades, all in the name of competitive advantage. They don’t want to share their own valuable research with their “competitors” (i.e. other treatment centers that patients might opt to go to instead of theirs). This creates a pervasive environment of data hoarding throughout the healthcare industry – “If you won’t share your data, I won’t either!” – that ultimately inhibits innovation and has an adverse trickle-down effect on the many patients who don’t get to benefit from shared data.

Those same data silos exist in your organization, with your individual teams and their processes playing the role of the hospitals. These silos might not have as dramatic an impact, like saving lives, but they are nevertheless hurting your ability to make the right decisions, and your business’ bottom line.

In order to eliminate data silos, we must first understand them and where they came from. Only then can we recognize their true dangers and, most importantly, how to break them down once and for all.

What Data Silos Look Like

The warning signs of whether your organization works in data silos are clear: Are you ignorant or unaware of key projects taking place in other divisions? Did someone mention a metric, a record or a custom field that sounds totally foreign to you? If you answered yes to either, that’s a telltale sign that the divisions within your company operate in silos.

Data silos can be vertical or horizontal across your organization. There could be high barriers between individual units (i.e. your sales manager and marketing manager don’t share data with each other) or senior leadership could be isolated from lower management levels (i.e. nobody shares data with the CEO or CFO).

Another telltale sign of a data silo is in the number of custom fields you have across your various business systems and pieces of software. Most such applications are built independently of each other, and will have their own custom requirements and data touch points. The more unique pieces of software you need to run your operations, the more custom fields they will each require, and the more siloed your overall company data will become.

Where Data Silos Come From

There are several key reasons why and how data silos get formed in the first place. Are any of the issues below causing data silos at your organization?

Too Much Software

The first has to do with all the software and business systems we mentioned above. CRM, marketing automation, email, finance, and support software are all systems designed to help you market, sell, support, and operate better. And these are only the core systems; we haven’t even scratched the surface of all those tools with very specific niche use cases. A marketing team could have 20 different pieces of software, all doing one little thing that contributes to overall marketing success. All of this was made possible by the rise of the cloud and the proliferation of Software-as-a-Service (SaaS) companies.

The rise of cloud computing made it easier for more niche vendors and products, with very specific use cases, to enter the business marketplace. It also reduced costs and barriers to entry, making it easier for individual stakeholders to purchase these SaaS tools without necessarily having to go through IT or one single overseer in charge of all software and data.

Suddenly, marketing and sales teams were inundating their organizations with software and tools to tackle use cases big and small. Each of these new systems collected volumes of data. Because all this software was created independently of each other, they might have custom fields or objects that aren’t exactly the same as in the other systems you installed. When your systems don’t “play nice” together, that’s how data silos are created. The more software you have, the more data silos will sprout.

Disparate and Unaligned Teams

Another reason for the rise of data silos has to do with the way modern-day organizations are structured. Companies are increasingly divided into disparate teams, with a clear division of labor and responsibilities. And that can be a great thing! When teams and employees stay in their lane, they will have a heightened and sharpened focus that can lead to great performance, while being more accountable within the organization.

Unfortunately, disparate teams also end up becoming misaligned, with each team leader implementing their own processes and, inevitably, the software they feel they need. They don’t communicate with other departments to share their goals, their projects, and the data they’ve accumulated. The silos that naturally occur due to divided responsibilities will translate to the data each individual team works with.

Wanting Control Over Data

A secondary – and ironic – reason for the rise of data silos has to do with the rise of data-driven organizations who want to make data-driven decisions. It’s also one that might sound familiar to the data hoarders in healthcare, and was described in an Aberdeen Group report as “database administrators’ detrimental sense of proprietorship.”

Simply put, whoever is in charge of the data at a given organization tends to be selfish with it, reluctant to give up control of or access to it. This is grossly opposed to the efforts of most companies to become more democratized with their data and making it accessible to all. There are legacy enterprises where a database administrator has been in charge of the data for years, and is not ready to give it up.

Ignoring the Issues

Finally, there is a prevailing sense of “too big to fail” when it comes to data silos. A lot of these problems get built up and ignored over time. It reaches a point where stakeholders recognize the problem and the need to fix it…but where to begin? Do they have to start from scratch in terms of breaking down some of these complex systems that have only added more complex workflows over the years? Do they have to get rid of some systems altogether? Can they sync not only their new data but also all of the valuable historical data they’ve aggregated?

These are complicated questions, with no easy fixes. Because there isn’t always an elegant data integration solution to break down these silos, many companies just end up throwing up their hands in frustration and sweeping these problems under the rug, continuing to operate in silos.

Don’t let that happen to your organization. Knowing where data silos come from is only the beginning, but it’s a great first step. Continuing to operate in data silos will only hamstring your business. Check back to learn more about just how dangerous data silos can be, and how to break them down once and for all.

Now that you know how data silos develop, it's time to discover how they impact your productivity. Dive into the second post in this series, The Danger of Data Silos, Part 2: How Do They Hurt You?, to learn how damaging these data silos can be.


Lindsay McGuire
Lindsay is the Content Marketing Manager at Formstack, splitting her time between creating blog content and producing Formstack's Ripple Effect podcast. She is a graduate of the University of Missouri School of Journalism and enjoys all facets of marketing.
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