Data friction refers to the various obstacles and inefficiencies that impede the smooth flow, processing, and use of data within an organization. These obstacles, often arising from data movement between multiple platforms, significantly slow down data-driven processes.
Sources of data friction
Key sources of data friction include:
- Data silos: When data is stored in isolated systems or departments, making it difficult to access and integrate with other data sources.
- Data quality issues: Poor quality data, including errors, inconsistencies, and duplicates, that requires additional cleaning and validation.
- Incompatible formats: Data stored in different formats or structures that are not easily compatible or integrable with other systems.
- Lack of standards: Absence of standardized protocols or practices for data collection, storage, and sharing.
- Legacy systems: Outdated technology that’s difficult to integrate with modern systems and processes.
These issues reduce the quality and accessibility of data, increasing the time and resources needed to achieve marketing and data objectives.
Why data friction is a problem for enterprise organizations
Data friction causes significant problems for enterprise organizations by slowing decision-making processes, hindering marketing efforts, and increasing operational costs. Addressing data quality issues, incompatibilities, and integration challenges consumes valuable time and resources and leads to missed opportunities and competitive disadvantages.
Additionally, data friction exacerbates compliance risks and security vulnerabilities, as fragmented data is harder to govern and protect. Ultimately, high data friction undermines an organization’s agility and responsiveness, limiting its capacity to leverage data as a strategic asset for growth and competitive advantage.
Issues arising from data friction
Time spent synchronizing data with other platforms
When data is stored in disparate systems with different formats and structures, maintaining consistency and coherence requires significant effort. Manual data entry, transformation, and validation processes delay decision-making and divert resources away from more strategic responsibilities.
This time-consuming and costly synchronization results in outdated customer data being used across campaigns and missed opportunities for timely engagement.
Resources wasted on replicating data
The need to replicate data across multiple systems leads to substantial resource wastage. Organizations often maintain duplicate datasets to meet the requirements of various departments or applications, resulting in increased storage costs and higher maintenance efforts.
This redundancy consumes IT resources and complicates data management, making it difficult to ensure data accuracy and consistency. As data volumes grow, as is the case for enterprise brands, the cost and complexity of managing these redundant datasets escalate, straining organizational budgets and IT infrastructure.
From the marketing team’s perspective, all of this data movement in and out of the tools they use for cross-channel messaging leaves them stuck with an inaccurate version of real-time data. They end up spending most of their time sending data requests and updating IT when they need more data for a campaign.
Broken data feeds
Broken data feeds are a common problem arising from data friction, causing inaccurate insights and disruptions in the flow of critical information. Data integration processes that fail or encounter errors result in incomplete or missing data, severely impacting marketing campaigns that rely on real-time information.
Fixing broken data feeds requires troubleshooting and repairs, which further consume time and resources and delay the benefits of a seamless data-driven approach.
Why legacy platforms create data friction instead of solve it
Legacy martech platforms require brands to copy and store their data within the platform, rather than accessing it directly from the brand’s data warehouse. This siloed approach means data must be continuously exported, transformed, and loaded into the platform.
This process results in data duplication, inconsistencies, and delays, as updates in the data warehouse are not immediately reflected in the marketing platform. As a result, maintaining real-time, accurate customer data across multiple systems becomes challenging, hampering the marketing team’s ability to deliver timely and personalized customer experiences.
How to solve data friction
The best way to solve data friction is to invest in a tool that connects directly to your central source of truth. By keeping your data within the secure environment of your data warehouse, you gain complete control over how it’s stored and managed.
With your customer data centralized, you eliminate failing data feeds, lengthy queries, scattered storage, and data lags. Marketing teams can build advanced audiences and activate data independently, freeing up technical resources from constant marketing requests.
Why data and IT teams love working with MessageGears
MessageGears was built with your data in mind. Our solution is the only warehouse-native customer engagement platform with a built-in CDP and integrates directly with your centralized data repository.
Unlike legacy CDPs and customer engagement platforms that require copies of your data, MessageGears accesses your data from its source. This means you never have to copy, sync, or move your data to build audiences, launch campaigns, or pivot on the fly.
MessageGears gives data teams full control over all customer data and significantly reduces the need for modifying data transfer processes. Sound too good to be true? Let MessageGears show you what’s possible in a demo or a POC using your live data.