We’re on a mission to expose the dangers of data silos, so you can break them down and start selling, marketing, and operating at a higher, data-driven level. This is part 2 of a 3-part series: Part 1 looked at where data silos come from. Part 2 focuses on just how damaging these data silos can be to your business.
The vast proliferation of cloud-based software with specific niche use cases has led to the increased prevalence of data silos in most organizations. They are sprouting up everywhere, as fast as you introduce new tools, systems, and processes.
These data silos are severely hurting your business by hindering your ability to sell and market better.
Knowing where they come from and how they got there is a good start. But if you really want to eliminate data silos and the problems they cause, you must first truly understand what those problems are.
The 5 Ways Data Silos Hurt Your Business
So, just how damaging can data silos be to your business and its bottom line?
Spoiler: Very damaging.
Data silos are bad for business, but how specifically do they hurt you and prevent your company from functioning at full operational effectiveness and efficiency?
1. They slow you down and prevent you from making real-time data-driven decisions.
Speed is paramount to business success today, and especially in sales and marketing. The best marketers run campaigns based on select prospect triggers, such as visiting your pricing page or downloading a piece of content. The best sales teams respond to leads as soon as they come in. The best business intelligence teams make decisions based on real-time data.
Neither team will be able to strike while the iron is hot as long as your sales and marketing data remains in separate silos. There will be too much lag time in getting the information from one team’s systems to another, and warm leads will get colder and colder. The state of the digital world today necessitates moving fast and executing even faster. Data silos directly inhibit your ability to do so. If you keep slamming into data silos or having to wait for the right data, either by generating a report or asking a database administrator for help, you won’t be able to operate very quickly.
2. Your trust in your company’s data wanes.
Have you ever watched a basketball or soccer team that has played together for years? They’ve developed chemistry with each other that becomes second-nature, something that is made abundantly clear when you watch them zip the ball around to each other unselfishly. The ball flies around the court or field as players pass and move, trusting that their teammates will be at the right spots, make the right decisions, and that everybody is on the same page.
Contrast that with a team that has never played together, and you see the exact opposite: tentativeness, as players second-guess themselves instead of just making fluid, intuitive decisions. Ultimately, it all boils down to one thing: trust.
When you have complete trust of your company’s data, regardless of which system it originated in, the quality of your analysis will be much improved. On the flip side, if you have even a shred of doubt about your data quality at all – Is this the right data? Am I missing something from another key source or system? – you will second-guess yourself, and that will be reflected in your analysis. Data silos, by virtue of their inherent characteristics, breed data distrust.
3. Your analysis will be limited…or flat-out wrong!
Here’s the problem with making data-driven decisions; one wrong or missing piece of data could lead you down a rabbit hole on the way toward making a big decision that will dramatically affect your strategy or tactical execution. But…what if the data that led into that decision was wrong or incomplete? Now you’ve set your company in motion down the wrong path.
For example, if your analysis suggests that your conversion rates in selling to the healthcare industry were especially robust, you might shift your marketing and selling strategy to focus primarily on those types of companies. But what if some of those won deals were tagged with the wrong industry? Or what if those specific deals came in from only one unique one-off campaign? You can’t afford to have wrong data when you’re making these types of data-rooted decisions.
Similarly, your analysis might not be wrong, but it will certainly be limited if you’re only looking at one or a small handful of data sources. You need to expand your scope beyond just your immediate purview, something that is not easy to do when all that data lies hidden in silos.
4. You won’t fully understand the customer journey.
Companies know that the difference between success and failure today is all about the customer. And customer success depends on your complete understanding of the customer journey, from cold prospect to interested, opportunity to onboarded customer, customer to advocate. You have to know what happens at each of these touchpoints and, more importantly, what should happen.
Unfortunately, the nature of marketing, selling, and customer onboarding today will likely mean a journey through a dozen different touchpoints and business systems. Those channels and their data should all be integrated, in order to streamline the overall customer experience and clarify your understanding of that experience. Data silos can be a real inhibitor to that.
5. Your priorities will be misaligned, and your decision-making uncoordinated.
This is really the crux of the issue, and speaks to not just data silos, but organizational silos. Just like their data, each individual team unit in your company have their heads down, working hard on their own projects and toward their own goals. This does not create a welcome atmosphere of collaboration and communication. After all, one team might not even know about key metrics that exist in another team’s systems. Those metrics could make a significant impact on their own decisions.
Data silos create natural barriers where they otherwise might not have existed. They force people and data to stay in their lanes – which can be a great thing, in terms of focus. However, it can also be a devastating thing to collaboration, clouding information clarity and presenting only a small part of the picture. The best teams know when to focus on their own priorities, but also when to balance that with other teams and work together to share data analysis and information. After all, you’re all playing for the same team, and fighting for the same championship.
Now that you know where data silos come from and just how damaging they can be to your company and its bottom line, you can actively start taking measures to knock those silos down and free up all that data.