How to achieve a data-driven approach without friction or data silos?

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With the problem of silos solved, a data-driven approach allows businesses to have a 360-degree view and thus improve the customer experience.
Data silos within organizations prevent or hinder business decision-making and the possibility of implementing effective marketing strategies. Let's see how to reverse this difficulty that has been complicating companies for years and preventing effective data management so that it can be transformed into relevant information.


According to a survey of global marketing leaders developed by the CMO Council in partnership with SAP Hybris based on responses from 170 global B2B and B2C marketing leaders across industries, 55% of car owner database are actively working on systems that enable extended customer-related marketing views. These include information and insights from all points of daily customer interaction. However, 17% are not convinced that they can have a dashboard with live (real-time) data from their company.



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What is the reason for this paradox?
First of all, let's be clear that Data Silos are "depositories" of data that belong to a company but are compartmentalized and divided by areas. This impossibility of sharing information between sectors means that either information is duplicated or it cannot be accessed in a timely manner. As a result, internal communication problems arise, overall performance is affected and many times even bad business decisions are made.

In this context, the problem in most cases is access to all that information. A quarter of respondents indicate that only 25% to 50% of their data is available in real time to take immediate action and 21% say that organizational silos are inhibiting their ability to have the right data to enable customer success. Finally, 20% feel they have the challenge of getting the rest of the organization to be data-driven.

In an efficient business model, marketers need immediate access to data on sales intelligence such as contact information (81%), marketing campaigns (69%), billing and payments (50%) and sales (49%). However, in practice, one fifth of respondents warn that there is too much data to manage effectively and 12% say that the data is not entirely correct or is “dirty”.

The most coveted data sources across the enterprise, but currently inaccessible, include machine learning/predictive analytics (8%), commerce data (11%), psychographic data (12%), HR insights (13%), and batch-based analytics (16%).

Not surprisingly, only 4% of respondents said they are able to engage with customers across all channels in real time to personalize experiences, and 23% said they are a long way from being successful at this. Difficulties in accessing information and the delays caused by internal bottlenecks drive this disengagement. In addition, 30% said they have a strategy to do so but struggle to try to align intelligence, content and channels with the customer, and 23% have only some real-time personalization but then only on select digital channels.