But big data isn’t without big problems.

The sheer quantity of data some businesses have can make it difficult to manage and start hindering, rather than helping, growth. If good decisions come from good data, then bad decisions come from bad data.

This problem is becoming more significant because of data silos. But what are data silos, why can they be so destructive and what can businesses do to stop them having such a negative impact?

What is a data silo?

The concept of a data silo comes from a silo on a farm. In this context, silos are large storage areas used to hold grain or rice in separate locations so they don’t spread into one another.

The concept is similar in business, but here instead of grain and rice, it’s staff members, departments and the data they hold.

Though they’re part of the same overarching company, each department is separated out so there’s a clear sense of structure and nobody’s getting in each other’s way.

While this has many benefits, it often leads to data silos. The financial department holds all the information about the finances, the sales team about the sales, the marketing people about the marketing.

If the right processes aren’t in place and the right tools aren’t being used, sharing this information within the company as a whole becomes difficult and so the data is incomplete and ultimately less effective.

Data Silos in Practice

Let’s look at an example. Imagine you own a travel company. You have physical locations around the country and a thriving ecommerce website that plays host to thousands of visitors every day.

That’s at least two data sources – the online wing of the business and the physical wing – but within the online element there are many more.

Firstly, there’s the marketing side of things: all the efforts made to drive people to the site. That means data about the performance of the content marketing, social media, email campaigns and the website itself. Who’s visited, where have they come from and how long did they stay?

Then, there’s the ecommerce side of things. What’s the customer’s buying, what are their preferences, what are they exploring but not actually purchasing?

We can bring the physical store in to play here. Perhaps they’ve been in-store a few times and have enquired about holidays, or are part of some form of loyalty scheme. This can help you gather intelligence about what the customer is buying and how often they’re buying it beyond digital.

What about customer service and the many arms that entails? Customers can contact a business through email, text message, social media, chatbot and the good old telephone. More channels, more data.

Finally, there’s dispatch: actually sending orders out to the customer’s home address. While little data can be collected here, it can certainly be used well by offering discounts and promotions within the package that are targeted around their interests and preferences.

That’s a lot of data and by keeping it siloed, there’s a risk of reducing its usefulness. Let’s keep the example going. Imagine if you could send an email to your customers that’s so personalised you could let them know that the kind of holiday they’re most likely to be interested in is now in an offer.

The chances of grabbing the customer’s attention, converting them through to a sale and building a sense of loyalty with them are huge.

This is possible by bringing silos together. Let’s say that the customer loves visiting France and has booked holidays in the North of France through the website. However, data from physical stores is showing a greater number of holidays booked in the South, and these holidays are booked primarily during the summer.

It’s late April, and many customers are starting to look ahead to the summer. By bringing these two points of information together and taking the date into account, you’re working from a more accurate set of data and so can deduce that the customer will likely be thinking of booking a holiday in the South of France at this point in time.

This can then result in the dispatch of an email that’s highly targeted, highly relevant and highly likely to convert into a sale. It’s the right thing at the right time – thanks simply to bringing data together.

How do you solve the data silo problem?

The first challenge is working out how the silos have emerged. They can crop up for a number of reasons.

Historical: Employees come and go all the time, bringing with them and taking away different approaches. As old goes out and the new come in, the data can get messy and difficult to draw any insights from.

Organisational: Time can be tight and it’s often the case that departments within a business simply get their heads down and get on with the task at hand without thinking much about the needs of other departments. This is exacerbated when these departments have different goals and ways of working.

Political: Some businesses encourage competition among departments; it helps generate an edge where employees go the extra mile. But it can also create problems. When employees are incentivised to find an edge, they may do it by keeping valuable data from other departments.

Technical: From the humble spreadsheet to more advanced systems like Salesforce, there are multiple ways to keep track of data. During a business’ lifetime, these systems will evolve or change entirely, and consistently can be difficult to achieve.

Understanding which issue is causing the most significant problems is key. To do this, the C-suite should collaborate to explore all areas of the business, come to an agreement and decide on a plan to combat the problem.

If it’s historical, form a plan to efficiently on-board new employees. Document the processes your company is using so that everybody is working from the same page and new starters are operating within a defined structure.

If it’s organisation or political, sit down with each department. Understand what’s creating the sharing bottlenecks and identify new methods of collaboration that will drive more togetherness without removing the sense of competition.

Most important, if there’s a technical issue, look for options that’ll help you solve them. Platforms such as Salesforce and Hubspot are all-in-one data platforms that can help you bring everything together in one place. Using them effectively can boost the impact of your data and aid your growth.

In summary

Data silos are one of the biggest and most persistent problems businesses are currently facing. Causes are numerous, but so are solutions.

Finding the right technology to tackle these problems, and breeding a culture makes use of that technology, is the key. By doing this, you’ll get to know your customers better, work out new ways to engage with them and, most importantly of all, drive them through the sales funnel with maximum efficiency.