Lack of access to data should be avoided in any organisation
Let’s face it. One of the biggest challenges facing data teams or those interested in making data-driven decisions is the lack of easy access to data. Data silos, while common, are vast sources of inefficiency in any department or organisation.
This article will help readers understand what exactly data silos are and how it can be prevented across organisations.
- What is a data silo?
- Questions about Silo
- What is causing data silos?
- 4 Ways to avoid data silos
- In Summary
What is a data silo?
In a recent study, 72% of firms said managing multiple CRM systems across geographies is challenging. The most significant challenge organisations face in meeting their sales objectives is managing data and sharing insights that drive actions across organisational data silos.
A data silo can be represented by a repository of information in a department or an application that is not easily or fully accessible by other departments or applications. Marketing, sales, HR, and other departments rely on specific information to function, and those collections of often overlapping-but-inconsistent data are in separate silos.
As IBM’s own Big Data and Analytics Hub stressed:
What we’ve learned is that many of the most common challenges associated with big data aren’t really analytics problems. In many cases, these problems are fundamental, even traditional, information integration problems
A data silo is also meant to keep private information from the eyes of those who do not need to know. Unfortunately, information that is required by others may also be stored in the data silo. In the worst-case scenario, a silo becomes a dumping ground for data that “might be” useful sometime in the future, and then sits there, never used.
This can result in duplicate and inconsistent records and a significant drag on efficiency. When this happens, large amounts of data will be wasted and go unrecorded.
Questions about Silo
Silos are nothing more than barriers that exist between departments within an organization. This causes people who are supposed to be on the same team to work against one another and cause issues which might affect the overall performance of the company.
And whether we call this phenomenon departmental politics, rivalry, or turf warfare, it is one of the most frustrating aspects of life in any sizable organization.
“For collaboration to take place, managers must give up their silos and their perceptions of power”Jane Ripley
Generally, the employees should ask a valid question of whether an identified silo is good or bad. Questions such as below will make sure a particular silo is not used against them.
- Does the silo serve a purpose?
- Is the silo a necessity for security, data protection?
- Is the silo causing inefficiencies or worse ineffectiveness in its purpose?
- Is the silo detrimental to other goals?
- Is the silo negatively affecting the company culture?
- Is it possible to integrate the silo?
What is causing data silos?
So, why are data silos such a problem?
Data workers spend 90% of their working week (around 36 hours) on data-related activities such as searching, preparation and analytics (searching for and preparing data being the most common activities)The State of Data Science and Analytics report by IDC
Imagine if an organisation has a marketing campaign that runs automated campaigning from the customer data it has. Without proper integration, marketing outreach data is isolated within the marketing department.
The sales information is also siloed, and it isn’t easy to attribute sales to a particular marketing campaign.
Data silos, in general, are standard in a growing organisation. Data silos arise naturally as organisations grow in factors such as technology and company culture where it would limit the sharing of information beyond the walls.
Furthermore, management may — intentionally or not — foster a competitive environment among departments, which can result in duplicative efforts and insulation of data and information flow.
Let us take a look at some of the factors that could cause data silos in an organisation.
Technological – Difference in software
Why is technology an issue? The main reason is that data cannot easily pass between departments of organisations that don’t access proper technology. Companies need to own high-quality applications that can handle quick transfers of information and cross-references.
Also, some teams may be better trained in using the technology for data transfer than other groups, which could lead to problems in the latter being able to access the same information.
This also means that everyone in the department must use and utilise the technology and not only have a certain party to handle the data. The right technology can eliminate this problem by centralizing and combining data from multiple sources, allowing you to make decisions more quickly.
The other reason what might cause data silos to happen is when the organisation has bad data quality. With poor data quality, there could be different segments of data left out, which might cause data silos. Fragmented pieces of information are difficult to assemble. If your data is not integrated or in sync, you’ll surely see conflicting data when trying to cross-check the information from different sources.
Structural – Growth in the organisation
When an organisation starts growing, it becomes difficult for there to be an easy passing of data throughout the organization. There could be far too many levels of organisations or departments.
Also, when organizations become too large too fast, there may be structural issues. It may require several steps for data to be passed down the hierarchy where some data could be missed.
Political – Protecting the data
In dysfunctional organizations, infighting and resentment between different teams may cause them to become insular, protecting their data at all costs. Some amount of interdepartmental rivalry can be helpful. For example, at Amazon, competitiveness drives business growth. Take a look at what Amazon is doing to create positive competitiveness below:
According to the Times, Amazon employees has access to a tool called “Anytime Feedback Tool,” which lets employees criticize or praise their coworkers discreetly. The feedback makes it to upper management, and can often be used in Amazon’s standard weekly or monthly performance reviews.
Departments should always put the success of the overall business first and never seek an advantage by holding back data from other departments. This will ultimately slow down the progress and make the organisation less efficient since there are not proper sharing of data.
4 Ways to avoid data silos
Now, let us look at some of the ways we can prevent or avoid data silos from becoming a true threat to any organisation or businessess.
Businesses can reduce data silos through data governance policies that improve synergy and maximize data effectiveness. Data governance is the set of policies and rules that organizations implement for managing their data.
In general, the main goal of data governance is to ensure usability, availability, consistency, and quality of the data such that none of the data collected is going to be wasted or unused which might only cause millions of dollars to be wasted in the form of data swamp or bad data.
Centralized Technology Infrastructure
Business and organisations can avoid data silios by investing in new and robust technologies or software platforms that integrate siloed data from various platforms into a central location.
This central location should be accessible across the entire organisation to utilise the data. In other words, get to a technological place that your data silos can speak with each other. A single platform can be used to make informed decisions where all the parties involved or have access to the platform can provide feedback or has some form of weight in the final discussion or outcome.
When a company is scaled, it creates different compartments within the same department. It further results in departments working in self-contained niches with little interaction with other departments. This might cause silos to be created without even realising it.
Ultimately, when we develop better working relationships between marketing, customer experience, growth, and other teams out there, we are removing silos between the organisations and promoting harmony between groups, which will boost overall morale in any organisations.
“Teamwork is the ability to work together toward a common vision. The ability to direct individual accomplishments toward organizational objectives. It is the fuel that allows common people to attain uncommon results.”Vince Lombardi
Setting Clear Expectations
Whenever you set out to work on your data, make it clear to the stakeholders and decision-makers to avoid making any headlong decisions about the existing data. This is generally a long-term plan, and once you have devised the right strategy, you need to stay at it.
This will allow you and your team to stay on the right path and not deviate from the goals. Always maintain data backup so that if something doesn’t go according to the plan, you have a copy of data to fall back on. Sometimes, taking some notes or a to-do list of the data that needs to be collected might have its own benefits in the long run.
To round up this article, data silos undermine productivity, hinder insights, and obstruct collaboration. But data silos cease to be a barrier when data is centralised and optimised for analysis. In some ways, centralising data in the cloud could also be done if the capacity is there. Otherwise, its always better to start analysing how the organisation is set up and what can be changed from inside.
To free your company from data silos over the long term, it starts with ensuring you have the right and robust collaborative environment, technologies, having organised operations and integrated tools. This will allow the business and departments to focus on the things that matter, improving and achieving overall business goals.
What is data silo?
Silos are nothing more than barriers that exist between departments within an organization
What are the main causes of data silos?
The main causes for data silos are technology, organisational, political and structural changes or reform that happens in an organisation
What are the ways to avoid data silos?
Proper governance policies, setting clear expectations, having a good company culture and also a centralized technology infrastructure