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 Finance department wants to see how its data 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. You might have experienced problems related to that if a co-worker went on vacation or was out sick and had some document in their email. In fact, siloed data is an obstacle to full analysis of big data because the information is scattered throughout multiple systems and various departments.
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.
Eliminating Forecasting Errors
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. In logistics management, forecasting is the act of predicting demand, supply, and pricing. 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.
Resolving Data Silos
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.
Contact us to see how we can help get rid of siloed data for your imports into the US.