Nowadays nobody doubts it: data is an undeniable growth factor for organizations. However, companies struggle to unlock the full potential of their data. This struggle notably stems from data silos, which isolates data in a department of the company. Let’s see what are the consequences of data silos and some possibilities to unlock data.
Data silos are harmless, right? NO.
Data silos are an obstacle to an efficient collaboration across the organization. Indeed, it is essential to centralize and align data to enable better visibility and thus better decisions.
Also, data silos hinder good customer experience. According to McKinsey&Company, 71% of consumers expect a personalized experience. And the best way to offer that experience is to make data visible and usable for everybody in the organization so that they can have a 360° view of the customer’s track record and meet their expectations. Breaking data silos also allows for better communication between departments of the company, which is essential for a good customer experience according to CMSWire. In conclusion, breaking data silos aims to improve customer experience, improve collaboration between different departments of the company, and accelerate innovation.
How can we break data silos?
The simple solution is to create duplicates of the data needed. However, this solution is far from perfect. Indeed, creating duplicates fills up the storage space and it’s hard to monitor the relevancy of duplicated data.
Among the other solutions to break data silos, there is the data mesh. But what is it?
It’s an approach articulated around the notion of data products. These products derived from data represent the important elements that fuel the company’s data strategy. Each data product is managed by a data owner and a data platform which has an architecture focused on data products. The distribution of coherent data across the organization not only allows the company to save time (and money), but it also allows for an aggregation of data from several departments upstream, for usage by every function downstream.
If you want to know more about the data mesh approach, you can read our white paper on the subject.
Breaking data silos takes time and resources, but it is necessary in order to be data-driven and exploit the full potential of data.