Customer Data is a critical asset for every business. But what if you could get better customer data? In this blog post, we discuss how enterprises can start building their customer data supply chains ahead of the implementation of a Pretectum CMDM.
The first step is establishing management responsibilities.
As a first step, the chief data officer or data product manager should name a “customer data supply chain manager” from their staff to coordinate the effort and recruit “responsible parties” from each department (including external data sources) across the customer data supply chain.
The next step is to put issues associated with data consolidation and ownership front and center. You’ll find that most issues melt away, as few departments wish to take a hard stance in the face of regulatory compliance and regulatory matters.
Data supply chains are a way to help you understand where your data comes from and how it’s used. They can also help you create a stronger relationship with the people who make sure that your data is clean and correct.
the customer data supply chain manager’s job would also be to create an audit trail of what happens with customer data at each step along the way so that questions about provenance can be answered quickly without having to engage in the laborious track down that often comes from an issue that arises later on!
Tools that provide collaboration workflow and decisions can help with this.
Identifying candidate use cases.
Customer master data has a wide array of potential use cases for which having access to more or improved data would bring value.
These should be elaborated and prioritized based on anticipated value and anticipated or projected difficulty to implement.
Poor data quality can hurt even the best business use cases, so it is crucial that organizations focus on ensuring that the right methods and people are in control of improving overall quality before they begin executing in support of any use cases.
Mapping out customer data supply chains.
Ideally, each data responsible department involved in the project would have a point person assigned to the effort who will identify all active data flows out of and into their group.
In finance, this might be the gathering of credit information or billing data. In sales, this might be tied to the demographic or economic status of the customer or prospect.
In marketing, this might be a great many characteristics including household characteristics, education, socio-economic status, and other campaign-bound traits.
The compliance and risk team may have different needs and expectations altogether.
Each group will need to identify potential or actual quality issues that may exist—and any new ones that might need to be added as part of this initiative.
Identify the highest-quality sources.
This step is perhaps the most important one on your journey toward building a robust customer data supply chain because it allows you to prioritize which data needs are most pressing or likely to go unmet if addressed last.
In other words, it helps you figure out where you want to start first so that you don’t waste time on things that aren’t high priorities but could become critical down the road given what we know about how business works today.
It’s not enough just for someone somewhere at some point in time saying “yes, I agree!”—that’s what happens when an executive agrees verbally with something but doesn’t put it into writing anywhere else besides their own memory banks!
Final thoughts
Customer data supply chain management is a great way to ensure that your organization collects and shares the customer data it needs to succeed.
It can also help you improve your overall quality by identifying and addressing issues at their source, rather than after the fact.
To get started, identify those parties responsible for sharing data up or downstream from your group.
Prioritize use cases based on anticipated value and difficulty of implementation.
Map out each department’s active data flows—along with any identified quality issues—and add new ones as needed.
Finally, assign point people within each department who will identify all active data flows out of and into their group—along with any identified quality issues that may exist—and any new ones to add as part of your Customer MDM initiative.