We’re on a mission here at Bedrock Data to expose The Dangers of Data Silos to businesses, so they 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: Part 1 examines where data silos come from and how they became a problem in your organization 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, diagnosis or treatment, 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 and especially leading private cancer centers 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 and cancer centers. These silos might not have as dramatic an impact in saving lines, 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 and their data 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 individual 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 Do They Come From
There are several key reasons why and how data silos get formed in the first place:
The first has to do with all that 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 not only 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 both 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 natural data silos will sprout.
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.
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, making it accessible to all, but 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.
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.