How to break down silos and free your data

As a modern, data-driven organization, you are likely pulling data from a multitude of diverse sources. There’s consumer data from marketing programs, CRM, and point of sale systems, plus financial data from accounting software and banking services. Finally, there is product data from user logs and web applications. With so much data pouring in every day, it feels like you should have everything you need to answer any question that could arise. And yet, so many times you don’t.

Why is it so hard to get to the answers that matter? In one word, silos. Many companies — even those with the most solid infrastructure for capturing relevant data about their customer and products — suffer from fractured, fragmented data practices. Marketing metrics are locked in a marketing automation platform with limited seats, product data is spread across a range of complex back-end systems that only the dev team can access, and so on. Hidden within that siloed data, there could be valuable insights. But how can you bring them to light?

There are a lot of reasons that even simple reporting can be a struggle, particularly for growth-stage companies that are already stretching every available resource to the limit. Data may be stored in proprietary formats that make sense in their native application but don’t translate to the applications used elsewhere in the organization. It may be a challenge to predict which data will be relevant to other parts of the business and which are simply adding more noise to an already-noisy data landscape. Finally— and crucially — the simple function of designing, running, and formatting reports for consumption steals precious time from the workers responsible for running your business.

But don’t get discouraged. It is still possible to find the data you need — and make it available to the users who need it across the organization.

A pragmatic approach to breaking down data silos

It is rare to find a company where IT still holds sole ownership of the entire tech infrastructure. From finance to people ops, every line of business is identifying the tools that make the most sense for their objectives, workflow, and budget. The benefit of this freedom is that each team can build the tech stack that works for them. But the downside is obvious: data silos.

It can be tempting to try to take the problem head-on, smashing silos by trying to enforce laws about which tech tools are permissible and which are verboten. In practice, though, this never works. In fact, for every silo you break down, two new ones will typically sprout up in its place. Draconian, top-down rule structures only give rise to resentment; ultimately, business users will find the applications they need to execute their work, whether IT is involved or not.

You may never have enough bandwidth to fight every data silo. Instead, take that ruthless instinct and channel it into prioritization that aligns with actual business objectives in a clear, two-step process:

1. Don’t boil the ocean. When you try to do everything, you can end up putting collection ahead of insights — remember, the average company lets over 70% of its data go unused. It’s controversial to say, but not every data-producing process or tool needs to make it into your priority list. Maybe that project management tool used by five people in HR isn’t the biggest key to your data strategy, and that’s OK. To make lasting change, you need to think like a product manager: Identify the issues, prioritize solutions, and come up with an actionable plan to address those problems in order of importance.
2. Pick your target. Work with business and technical stakeholders to identify the silos that are actually holding up the business. Start by applying a methodology to your evaluation. Perhaps focus on the problems that are having an impact on the largest number of people or how significantly a given silo is preventing the company from reaching its most critical goals.

Once you know which problem you want to solve, it’s much easier to identify the source, build a battle plan, and execute a solution. For example, maybe sales cycle efficiency is the name of the game this year. Reporting within the CRM almost ensures you're dealing with a data silo, and the gap between current and desired state can feel massive. If your CRM is flooded with bad data, the sales team will be frustrated by the tool and marketing, product, and finance will be left without the customer data they need to plan their programs for the coming quarter. With such a broad impact across the organization, your first silo is clear: Clean up the CRM so that data can start flowing to the rest of the organization.

Consider publishing your backlog so that cross-functional teams know what the company has designated important issues and which might have to wait a little longer for attention. Communication is key, and a public accounting of priority helps others in the business understand the value of each initiative.

By taking a pragmatic approach to breaking down data silos, you’ll get closer to reporting that matters — and everyone will feel the benefits.

The advantages of free-flowing data

Step by step, breaking down silos will bring you closer to cohesive, company-wide reporting. Over time, you build artifacts that add up to a stronger data culture — the creation, viewing, and sharing of common reporting will deliver a common language across departments.

Reinforcing goals makes teams more likely to achieve them. As the free flow of data breaks down the barriers that used to prevent individual teams from reaching peak performance, it’s important to take a moment to align on priorities.

For go-to-market (GTM) teams — including sales, marketing, and customer support — a common understanding of pipeline and revenue drivers will result in a holistic view of the customer experience. Instead of fragmented departments trying to row roughly in the same direction, you can deliver a coherent GTM strategy that optimizes every step of the customer lifecycle. This leads to more effective lead-generation programs, more efficient sales funnels, shorter sales cycles, and longer and more profitable customer relationships.

For product and R&D, the free flow of information forces prioritization and more efficient collaboration. Product and research objectives are tied in with the larger, top-line goals of the business instead of a reactive response to ticket queues. Engineers, developers, and other stakeholders feel more empowered because they can actually see their impact on the business’ strategy and results.

For execs, better reporting and insights put them one step ahead of the market’s next move. They can stay focused on strategy instead of wrangling conflicting sources of truth.

Best of all, your new cohesive reporting strategy will help you fight analysis paralysis. Instead of trying to referee arguments between various stakeholders with different sources of truth, you can have streamlined conversations that focus on what matters to the business.

For a deeper look at how your organization can get the right data at the right time to make better decisions faster, download "The Struggle is Real: Accelerating Time to Marketing and Sales Data Insights." This in-depth report offers helpful tips for achieving data insights faster, spending less time on your data pipeline, and how to work with on the data that you need.