The Dangers of Siloed Data and How to Avoid Them

What is Siloed Data?

In farming, silos are structures that keep grain separate from the elements. The same concept can be applied in the business world when we think about siloed data. There are different types of siloed data, but the overarching theme is data that is isolated from the entirety of your system, whether it’s restricted to one department’s uses or just not connected to other systems in your business. For instance, if you have siloed data and your marketing department wants to see how its data on MQLs relates to your Sales data, they’d need to ask someone from Sales to access it for them. The data is not shared across the system, but rather broken up from one department to the next, revealing only a fraction of the information.

A subcategory of siloed data takes place at the individual level. Individuals who hold on to data themselves create a roadblock for crucial and accurate reporting. In fact, siloed data is an obstacle to full analysis of big data because the information is scattered throughout multiple systems and various departments. A Forrester study found that, on average, B2B marketers and sellers are basing 48 percent of decisions on intuition or personal/company experience rather than on quantitative information and analysis.

Why is Siloed Data Dangerous for Your Business?

Time is Money

Having data spread out amongst multiple systems makes accurate analytics excruciatingly difficult. Without the capability to search all systems at once, you must go through each individual system and conduct a search to find the desired data. After accumulating various reports, employees attempt to compare the data to create the bigger picture. Although this seems logical, it has its pitfalls. When reports are meshed together, there are gaps, and the resulting data doesn’t disclose the full story. This is a very time-consuming act, and it’s time that could have been used to complete other tasks, like closing a sale or marketing. Time and energy spent locating information costs money to the company, because you’re losing productivity and efficiency. To make up for the lost time, employees often try to do the tasks assigned to them very quickly. Although this may seem like a good concept at first, rushed work tends to be error prone and projects are completed poorly. Faulty data is usually the end result, which strongly correlates with poor, costly business decisions.

Faulty Forecasting

Imagine you are going to a baseball game today. You want to know what to wear, so you check the weather in your town instead of the weather at the ballpark, which is the next town over. The weather by you is sunny and 85 degrees out. You are ecstatic until you arrive at the baseball game to find out it’s cold and pouring rain. Had you looked at the weather data from the town over, you would have known it was supposed to rain. But, because you only saw a portion of what was on the radar, you couldn’t get the full picture on what the weather might be. To truly understand the meaning behind your data, you need to have access to the big picture. One department might seem to be doing well, but when the data is combined with other departments, the results may be starkly different. If a department makes plans based on inaccurate forecasting, all departments are impacted. This could lead to skewed budgets, which can affect employee bonuses and raises, and even the company’s investments. Every company understands how crucial accurate forecasting is, but many rarely achieve it. Removing data siloes is one of the simplest ways to prevent forecasting errors and simplify data analysis.

Departments Rely Too Much on One Another

Siloed data can hide data that overlaps in multiple systems. The data between departments may have minor differences, and if users don’t know which system has the most up-to-date information, it can cause bigger issues. For example: two systems might reflect the same name and phone number for a customer, but a different email address. How do you know which email is correct? Which one is the most current? If the data was integrated, a change in an email address would be reflected on all platforms, preventing employees from referencing the incorrect information to contact the customer.

With marketing and sales so closely knit, a lack of visibility can quickly lead to lost opportunities. Combining data between the two departments gives insights into new patterns, different demographics, and customer buying trends. Data in one department’s system might be extremely beneficial to another, even though they use the data in different ways. 

Resolving Data Silos with Integration

According to Big Data Insights and Opportunities, 2/3 of companies experience some degree of shadow (or rogue) data depositories. Data silos are very common, because they are often created by accident. Departments tend to focus on meeting individual goals and don’t look at the broad view. Data is constantly changing and the volume of data is growing so fast, which makes it hard to keep track of it and keep it current.

The best way to remove data silos is to integrate your major systems together. Integrating makes locating information a more efficient process. An employee will no longer have to sift through multiple systems to find relevant analytics, but can instead pull the complete scope of information into a report for a 360-degree view. Integrating your system keeps everything standard across the board. When a data point is updated in one system, it reflects in all other connected systems naturally. The benefits of syncing this information include:

  • Supporting accurate forecasting & analytics
  • Less data duplicates
  • Process efficiency across all departments
  • Fully leveraging the power of your systems
  • Holistic customer management
  • Better order tracking
  • Simpler departmental coordination
  • Increased visibility and data transparency

Overall, getting rid of data silos saves time, and helps employees make more informed decisions to achieve future goals. Rid your systems of unnecessary data silos by integrating your data-rich systems together. For many companies, these systems include CRM, ERP, and Marketing Automation, but there’s always room to get creative! Does it make sense for your company to integrate social media and CRM? Ask your CRM consultant for help deciding which systems make the most sense for the reporting you need.

Integration variations can open a new world for your data analytics. Learn more about one of these integrations, ERP and CRM, in our blog on the Six Ways CRM and ERP Integration Saves Money.

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