Data Quality
Data quality as a managed service means that your company's data are secured, accurate, accessible, and structured in one "holistic," centralized system — eliminating the old system of siloed data storage and its many related vulnerabilities.
This is the backbone of your company's strategic business decisions.
Value of Data Quality
Data quality, done right, can exponentially unlock the power of the data you collect. It can drive current marketing and PR practices, IT decisions, and staffing. It can point to future opportunities and support your ability to predict customer preferences.
It doesn't stop there. Data quality as a managed service affects business efficiency and compliance as well.
Unlocking the Power of Data-Driven Customer Satisfaction
An outdated data management system leaves your company vulnerable to outdated information, impeding your momentum and costing your business its competitive edge. On the other hand, a system of data quality as a managed service helps ensure that you maintain that competitive edge through the power of quality data.
Data quality as a managed service positions your enterprise to mine new insights about your customers' habits, preferences, and unmet needs — revealing opportunities that previously remained hidden.
New opportunities could include, to name just a few:
- the need to change a product or service in a way that makes all the difference to customers;
- a new strategic marketing and/or sales approach that reaches the right customers;
- an innovation that offers a breakthrough in a product or service for customers.
In short, data quality as a managed service is key to continued — and improvements in — customer satisfaction.
Business Efficiency
Data quality as a managed service has a multiplier effect when it comes to value. Compliance Week highlights these benefits that accrue from a well-managed, centralized system:
- Your data are complete and unduplicated;
- You need to structure, classify, and aggregate only once in your centralized system;
- One managed, central system leads to more efficiency and a comprehensive level of consistency across data sources; and,
- You get a bonus in lowered initial and ongoing costs to manage your data.
Additional key assets include:
- Enhanced ability to secure data; and
- Facilitated access to more data.
Why do these benefits matter? They lead to the big picture: emerging data-driven business opportunities and more significant successes.
Compliance
Compliance Week emphasizes the value of data quality: "Data quality is the foundation on which all automated, intelligent applications are built. Without quality data, there's no basis for intelligent applications in financial compliance to even begin to understand what constitutes good (compliant) or bad (non-compliant) behavior."
It's that basic and that key.
The EU's General Data Protection Regulation
The General Data Protection Regulation (GDPR) went into effect on May 25, 2018.
If you do any business in Europe, this regulation "applies to all companies processing and holding the personal data of data subjects residing in the European Union, regardless of the company's location."
The GDPR is "designed to harmonize data privacy laws across Europe, to protect and empower all EU citizens' data privacy and to reshape the way organizations across the region approach data privacy."
Key changes include an emphasis on transparency in data collection and use, the right to be forgotten, and data portability. Non-compliance penalties will be costly.
Companies can facilitate their compliance with the GDPR in a way that is cost-effective, seamless, complete, and error-free with a system for data quality as a managed service.
5 Sample Technologies Used in this Space
Savvy businesses increasingly are turning to using data quality tools for marketing. As one industry report summarizes: "Data quality is becoming more important than ever in creating highly accurate and sophisticated customer profiles for marketing."
Key technologies driving this change are:
1) AI and Machine Learning: Since data quality is AI's life support, only systems that eliminate "garbage in, garbage out" lead to useful, effective AI and machine learning systems.
2) Data Quality Portals: Flexible portals enable companies to approach data quality management with both in-house and external tools.
3) Neural Networks: Neural networks offer two options for data mining: rule extraction (extracting symbolic models from trained neural networks) and easy-to-understand networks.
4) The Cloud: This technology enables companies to access computing-as-a-service and technology-as-a-service.
5) DevOps: This hybrid approach to technology development and operations management has led to a new array of tools.
Which tools should you use? Gartner's report on Critical Capabilities for Data Quality Tools shows that tools must ensure that data are "fit for purpose" — that is, the data directly correlate to your business objectives in their contexts.
How to Pick a Partner
Picking the right partner requires that you select a company with the tools and systems that complement your business's data quality objectives.
Gartner applies 15 critical capabilities and 6 dominant use cases to evaluate vendors, including:
- Big data and analytics
- Data integration
- Data migration
- Information governance
- Master data management
- Operational/transactional data quality
Picking the right partner requires that you take a longer view of your business needs. Gartner recommends looking at ways to leverage evolving product capabilities, such as machine learning and predictive analytics, in both current and future scenarios.
A caveat from Gartner's report: vendor-partners may not be able to offer a one-size-fits-all option. One particular vendor may fit one set of use cases but not others.
Forbes' advice on selecting a partner includes:
- Review the partner's plan for improving your data quality. Look especially for clarity, accountability, the license structure, and your contracted rights for using the data.
- Have your own auditing practice for evaluating external sources — with an emphasis on authenticity — of data from vendors. Bring their data in-house to get a comprehensive idea of the customers.
- Reputation and longevity should at least play a small role in your selection. Longevity also speaks to the level of commitment a partner will have over time towards helping you with data quality.
- Seek out partners with customizable software, while considering the costs of software maintenance and upgrades — along with its adaptation to agile development approaches.
In any selection process, examining the potential partner's data security is critical.
In Summary
Unlocking the power of your data can transform your business. At a minimum, customer satisfaction and compliance are driving forces behind the need to pivot now to a system of data quality as a managed service. Undertaking the change will point you to exciting, new opportunities currently hidden in a sea of unusable data, and alter the way you manage marketing, PR, and IT.
The reward? A digital transformation to maintain a competitive edge. Cruz Street stands ready to assist: contact us to see how jumpstarting your data quality opens the door to new possibilities and sets you apart from the competition.