Customer data is a critical resource for every lol买外围用什么软件health and life sciences organization. Pharmaceutical, medical device, and healthcare companies count on this data to shape commercial strategy and tactics, track performance, and address compliance with the Sunshine Act and other regulatory requirements.
Even so, organizations of all sizes continue to face customer data challenges. What follows are three of the most common scenarios — along with opportunities to solve for each through more effectivedata governance and stewardship。
Customer Data Challenge #1: Duplicate Data
销售代表希望将新客户添加到您的生态系统中。您当前的流程依靠每个代表，以在客户关系管理（CRM）或主数据管理（MDM）环境中搜索该客户。一些代表仅执行粗略的搜索；其他人完全忽略了请求。这种不一致导致客户资料，客户地址和有关其隶属关系的数据的复制。
Compounding the issue is a lack of business match/merge rules for processing inbound data from other sources.
为了解决这一挑战，请考虑进行正式的分阶段数据清理。此过程应包括一次性练习，以删除已确定的重复项并合并客户个人资料重复。为了防止将来的数据负载重复，评估并在需要时修改摄入规则。
Customer Data Challenge #2: Incomplete and/or Inaccurate Data
Your reps and other end users are empowered to create customer profile records. When data sources are loaded, there’s no validation of business rules before that customer data floods your MDM ecosystem. Both practices lead to data that’s incomplete, inaccurate, or both.
This is another challenge you can address with a phased data cleanup. Focus this effort on closing information gaps — including resolving “unspecified” medical specialties and ensuring that providers’ professional designations are captured correctly.
结合清理，定义和实施数据负载验证业务规则。这些规则有助于捕获和报告例外，然后再将其引入您的生态系统。
客户数据挑战＃3：客户地址信息
准确的客户地址信息对于支持许多下游业务流程至关重要 - 从通知商业活动到满足合规性要求。但是，如果没有用于创建和更新客户地址的标准方法，您最终可能会获得脱节的，不可靠的信息。
To ensure that you’re capturing consistent address information from any inbound data source — including your own reps — introduce business rules for validating data entry and data loads. Consider engaging a third party with focused experience in, and proven approaches for, establishing this kind of formal data oversight.
Accelerate the benefits of data governance and stewardship
为了有效的端到端信息管理，您的组织需要数据治理in the form of an information strategy and high-level policies and procedures — along withdata stewardship通过一致，纪律处分和实施。
通过有效的数据治理和管理，您可以提高客户目标列表的准确性和呼叫计划的精度。同时，合并的客户个人资料记录使您能够在识别提供商的隶属关系方面变得更加复杂，这是支持基于帐户的参与度并扩大您的覆盖范围和频率的关键功能。合并这些记录有助于您提高销售报告的准确性和奖励薪酬。它还按照《阳光法》的要求简化并简化了透明度报告。
If you lack the breadth of expertise and/or scalability to tackle this on your own, considerIQVIA数据治理和管理服务。我们的团队提供数十年的经验和一套加速器，以帮助您获得（并留在您可以信任的客户数据的道路上）。我们可以支持您制定信息策略和数据治理政策，评估和改善数据质量以及根据您的策略和程序维护客户数据。无论您喜欢的工具或数据源如何，我们都在这里帮助您加速您的旅程，以更好地客户数据治理和管理。/P>
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