Why Data Quality is Everyone's Responsibility
Developing a well-defined customer relationship management (CRM) strategy does more than shape the short- and long-term success of your CRM implementation. It plays a critical role in mobilizing a data-driven business program that channels growth and elevates the customer experience. Yet many organizations struggle to harness CRM insights due to a lack of clarity in data management responsibilities.
To compete in today’s environment, businesses are expected to deliver convenient, personalized consumer interactions at every step of the journey. Business leaders are required to make critical decisions when market disruptions occur and shifts in consumer attitudes and behaviors present new challenges and opportunities. From end to end, CRM holds the key to unlocking the data and the experiences organizations need to transform and thrive.
Yet many businesses still struggle to glean a 360-degree view of their customers, despite significant investments in CRM technology. Why? Forrester notes that while organizations recognize the importance of integrated CRM data, many fail to break down the silos that create a fragmented experience for customers and business leaders alike.
Neglecting to unify the CRM strategy not only hampers the consumer experience — it prevents businesses from harnessing the information they need to make informed decisions. All too often, this results in poor or inconsistent data quality and a lack of clarity around whose responsibility it is to fix it.
Who Is Responsible for Data Quality?
Data quality is often taken for granted as the outcome of new CRM technology. The reality, however, is that clear and accurate customer information is the result of an integrated CRM data management strategy that bridges the needs and requirements of the business and the technology organization. But at the end of the day, who is responsible for ensuring high-quality data?
The short answer: Data quality is everyone’s responsibility. Let’s break that down:
Client-facing staff and sales representatives own the data. The responsibility of entering, maintaining and validating data sits with the users of the CRM platform.
CRM professionals set the parameters for successful data entry. Establishing guardrails for data entry ensures that each piece and type of data entered across the organization is housed appropriately to support the data management stream.
Business leaders must articulate the value of seamless data. Drawing a connection between data accuracy and the potential for sales success and revenue growth creates a value system that is motivating and tangible. Raising the profile and the value of clean data within the organization sets a precedent for improvement as a shared responsibility.
Managers hold all CRM professionals accountable for accuracy, from the executive committee to operations. Implementing a routine attestation process allows managers to hold all levels of the organization accountable for the data they record — from the contact, company, account, and opportunity level and beyond. When errors occur, the responsibility of remediation rests with the CRM professionals accountable for the entry.
Managers delegate clear leadership when data is jointly owned. When information is shared across departments or client-facing teams, establish a leader to gather the details and input data accurately. This sets a control for precision and ensures accountability.
Prepare for a Journey to Optimization
Seamless data quality is not a destination; it’s a journey. For many organizations, the road to a data-driven business model merely begins with the implementation of a new CRM system. What follows is an enterprisewide journey of optimization and an evolution of operations to support and advance the CRM strategy.
From implementing new technology to designing data architecture and managing internal culture shifts, businesses must lay the groundwork for digital experiences that increase customer access, improve staff efficiency and spur future growth. Creating these experiences requires rigorous attention to data management roles and responsibilities and a cultural shift in the mindset of the business. Organizations that do this well will reap the fruit of their labor: seamless customer data at a time when nothing could be more valuable.