Data integrity used to be the domain of data administrators. Now it is a crucial component of an arts organization’s infrastructure and a strategy for success. “At its core, data integrity is the reliability and trustworthiness of data through its lifecycle.” (EGNYTE) From acquisition through use, backup, and archiving, being able to rely on the data in your systems is critical to business success. This concept may seem ridiculous to those unconvinced of digital shifts in society fast-forwarded by the pandemic. But, to those in the trenches, bad data is not only frustrating but a daily failure in a donor message or admission sale.
If you work in your organization’s management systems, how often are you caught by data that you cannot trust? The degradation of data integrity typically comes from human error (entry of data or maintenance), formatting inconsistencies, collection processing errors or data field misalignment, or, for larger companies, data breaches. This article will help clarify how to create ecosystems for data integrity and the opportunity a strong data infrastructure provides for a data-ready future.
Data integrity encapsulates accuracy, completeness, consistency, timeliness, uniqueness, and validity. This requires regular de-duping, maintaining a disciplined data entry process, and regular system updates, including simple steps like running updates with USPS mail changes. Strong data set allows for planning and analysis from intentionally designed and comparable data.
The last component, data validity, allows for worker efficiency, but more so it eliminates excess storage, ensures quality operations and communications, creates systems for data privacy, and increases the effectiveness of customer personalization.
Hence, an individual, if not a designated team of people, should be engaged in the following activities:
Deduping (as mentioned above). This should happen regularly.
Regularly evaluating inputs and processes to guarantee quality data is coming in
Validating data through regular testing
Evaluating for domain integrity of field categories and value settings
Taking time for data and system training
Maintaining updates in systems and re-train accordingly.
Hiring and training for data literacy is a critical component of organizational success in the future. McKinsey estimates that by 2025 our work as humans will be fundamentally changed from what it was in 2000. “Smart workflows and seamless interactions between humans and machines will likely be as standard as the corporate balance sheet, and employees will use data to optimize nearly every aspect of their work.” (McKinsey)
While that might feel very futuristic, the pandemic fueled the workplace environment toward data-information centrality in ways no one could have imagined in 2000. While the arts are human-centered in almost every aspect of work, arts administration must meet the demands of a technological and digital future for their workforce in order to create the impact their missions and artistic work intend.
The interactive McKinsey article identifies 7 key characteristics of a data-informed, if not data-driven, enterprise of the future:
Data is embedded in every decision, interaction, and process
Data is Processed and Delivered in Real-time
Flexible Data Stores Allow for Integrated Data
The Data Operating Model Treats Data Like a Product
The Chief Data Officer’s Role is Expanded to Generate Value
Data-Ecosystem Memberships are the Norm
Data Management is Prioritized and Automated for Privacy, Security, and Resilience
Predictive analytics and automated processes are already in the arts ecosystem within our external relationships and our customer and donor management systems. Using this data and digitally informed models are less common in the arts workplace. Often burdened by siloed operations and hierarchical systems designed from a 1960s business model, core assumptions must be addressed. “Organizations are capable of better decision making as well as automating basic day-to-day activities and regularly occurring decisions. Employees are free to focus on more “human” domains, such as innovation, collaboration, and communication.” (McKinsey)
The infrastructure of our data also must be modernized to accommodate emerging data sources.
Flexible Data Storage from cloud-based computing and connected devices enables Ready-to-Use Data. “Data practitioners increasingly leverage an array of database types—including time-series databases, graph databases, and NoSQL databases—enabling more flexible ways of organizing data. “ (McKinsey)
Flexible data stores of internal data will allow for data sharing in a data marketplace that is already emerging in the ticketing and donor space. Sharing data allows for greater individual and industry expansion. “Data marketplaces enable the exchange, sharing, and supplementation of data, ultimately empowering companies to build truly unique and proprietary data products and gain insights from them.” (McKinsey)
This increased focus on data will actually make the workplace and the marketplace safer. Data security and data privacy are increasingly part of the daily conversation but often as a point of crisis. These concerns will become normalized with a focus on data as a value-set or product. “Organizational mindsets have fully shifted toward treating data privacy, ethics, and security as areas of required competency, driven by evolving regulatory expectations such as the Virginia Consumer Data Protection Act (VCDPA), General Data Protection Regulation (GDPR), and California Consumer Privacy Act (CCPA) . . .. Self-service provisioning portals manage and automate data provisioning using predefined “scripts” to safely and securely provide users with access to data in near real-time, greatly improving user productivity.” (McKinsey)
Hence, creating an organizational culture and ecosystem that prioritizes data integrity today will set the future for meeting the demands for success in the future.
“The Data-Driven Enterprise of 2025.” McKinsey & Company. Accessed September 11, 2022. https://www.mckinsey.com/business-functions/quantumblack/our-insights/the-data-driven-enterprise-of-2025
“What is Data Integrity.” EGNYTE. Accessed September 11, 2022. https://www.egnyte.com/guides/governance/data-integrity
“Data Integrity; Meaning, Best Practices, Examples & More.” Security Studio. Accessed September 14, 2022. https://securitystudio.com/data-integrity/