Successful Digital Transformation Depends on Quality Customer Data

November 10, 2020
Rebecca Silver

Rebecca Silver is General Manager, Veeva OpenData.

Companies recognize that their success with digital starts with accurate customer data, but many struggle to manage the overwhelming volume of different data types from hundreds of sources.

COVID-19 has accelerated the industrywide shift toward digital engagement. With digital transformation initiatives well underway across life sciences, companies recognize that their success with digital starts with accurate customer data. Nine in ten commercial leaders say improving customer data is a top organizational priority.1

But many companies struggle to manage the overwhelming volume of different data types from hundreds of sources. Digital transformation can fall short without the right customer data foundation and having a complete and accurate view of healthcare professionals (HCPs) globally.

Effectively merging multiple digital sources and assigning a unique identifier can significantly improve customer reference data quality and help companies make the successful transition to digital.

Centralize data for a complete view of customers

Poor data quality, from incorrect addresses to outdated information about a physician’s specialty and license status, is a common challenge. The majority of life sciences companies are not satisfied with the quality of customer data.1

Every customer interaction generates a high volume of valuable insights that can overwhelm many organizations. The structured and unstructured nature of this data adds complexity, according to Boehringer Ingelheim’s (BI) global lead for data excellence, Philippe Houben.

“Managing multiple data sets from all of the different digital channels is a challenge,” said Houben during a roundtable discussion at Veeva Summit. “In addition, we have external data such as patient information from various sources, including social media.”

Organizations are adopting centralized data management solutions to break down siloes across these rich data sources. Customer data silos can create data blind spots and make it hard to access and capture the data and insights needed to personalize customer engagement.

The majority of commercial leaders have data quality initiatives underway.1 More companies are making the switch to a data partner focused on data quality and providing seamless data integrations. This gives field teams a real-time, consolidated view of HCPs across multiple data streams, including public sources, for comprehensive and accurate customer profiles.

Houben added, “We are integrating unstructured data because it adds a lot of value to get the right quality of data that is accessible in real-time.”

Harmonize data with unique identifiers to improve customer engagement

It is common for pharmaceutical companies to have multiple data management systems across geographies. With numerous, fragmented databases, a single customer can be referenced differently in each separate system.

A key part of data transformation is to replace traditional multi-sourced master data with one unified data source with a global data model. In this framework, each customer is assigned a single unique identifier that is recognized across systems, countries, data sources, and types to create a global record. Data stewards are also key to ensuring information is always kept up-to-date to avoid making business decisions on stale data.

Accurately linking all interaction data to the right customer ensures organizations have a consistent global record for engaging HCPs and account selling. A single data model and complete source of customer reference data helps field teams effectively and compliantly deliver new treatment information to HCPs.

Quality data can lead to better insight-led decision-making across a life sciences organization and drive more valued customer interactions.

“It is critical to break down data silos as much as possible to bring data together and generate more insights,” says Houben. “We are identifying additional data sources that could give a broader perspective on the customer. We want to improve that insight generation and, ultimately, make faster decisions.”

Quality data is foundational to digital transformation

Data quality initiatives are an important undertaking, so much so that many organizations hire a chief data officer to manage these programs on a global scale. Companies recognize the value in harmonizing customer data to effectively make the transition to digital engagement. With a complete view of customers, field teams can leverage different channels for each customer segment, or even each individual customer.

A strong data foundation is key to global digital transformation. Companies can reach new markets and improve sales productivity with better targeting and segmentation. Additionally, organizations can enhance their stakeholder engagement with a holistic view of decision-influencers and improve business decision-making thanks to richer customer insights.

Ultimately, high-quality data allows for more intelligent interactions, which leads to more successful customer engagement and, in turn, greater use of digital channels. It’s a key ingredient in the recipe for successful digital transformation.

Rebecca Silver is General Manager, Veeva OpenData.

Notes

1. Veeva 2020 European Customer Data Survey.
2. Ibid.

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