Scott Taylor, the Data Whisperer and Master Data Influencer, believes that everything is data. Whatever you touch is data; data that is clean, high-quality ,and well-managed.
But businesses today struggle with maintaining quality data. 75 percent of companies opine that poor data quality makes it challenging to execute their digital transformation plans.
Companies need to understand that high quality, reliable data accelerates Master Data Management (MDM) deployment. Properly governed master data is the source of common business truth, which makes Data Governance critical. It is used among internal business systems, processes, and applications, as well as externally between enterprises.
Data Management fuels digital transformation. Companies that fail to have a sound data strategy in place, that includes quality data and a reliable data foundation through MDM, never succeed in their digital transformation efforts.
This implies that Data Quality, Master Data Management, and Digital Transformation are inter-connected. As your business undergoes digital transformation, you deliver a delightful customer experience and empower your employees.
In this blog, we focus on why and how data quality accelerates the speed of your business transformation.
Why Prioritize Data Quality?
High-quality, reliable data –
speeds up your Master Data Management deployment, with you directly handling the biggest challenges in such deployments,
clean data builds and improves the single source of truth for your customer data. There is more accurate matching of data at the heart of Master Data Management,
maintains the health of the Master Data Management infrastructure and avoids any type of data degradation, and
assures that downstream systems use reliable data. Business analysts and users use this data for more accurate and smart decisions as well as interactions.
Benefits of Maintaining Data Quality
Identify new cross-sell and upsell recommendations,
Build more accurate customer profiles for effective personalization,
Gain a standardized view of purchase dates,
Detect new relationships between people, things, and places,
Track supplier performance more precisely,
Figure out group purchasing opportunities easily, and
Simplify regulatory processes to build comprehensive reports from clean, reliable data
Automate critical data management functions to minimize your hard-coding efforts,
Fulfil self-service business demands with centralized data critical to your business, and
Recognize sensitive data you need to secure and share across functions, regions, and channels.
How to Ensure Data Quality?
1. Begin with something small – Focus on the quality of your data within a single system, domain, or application. You can then reuse rules and lessons learnt to implement bigger projects.
2. Establish a data quality baseline – Use a data quality dashboard and scorecard before, during, and after your MDM program is live. You can manage only the data you can measure.
3. Ensure Consistent Data Quality – Since data exists across the enterprise, assure data quality is consistent throughout the data lifecycle. The environment may be on-premise, in the cloud, hybrid, or Hadoop.
4. Standardize Your Approach – Create a Glossary and reusable rules. Doing so helps to ensure every team member is on the same page and can collaborate effectively.
5. Automate Your Data – Apply pre-built rules and artificial intelligence (AI) to automate data profiling and discovery. You cannot, of course, manually update data present in millions.
6. Monitor Data Constantly – Monitor your data on a continuous basis and execute a data quality dashboard for the same.
7. Verify Data Inline – You need to guarantee data accuracy, as and when it enters your systems. Conduct inline data verification and avoid inaccurate data, so that there are no errors or issues later.
8. Double-check Your Contacts – While guaranteeing data quality, it is crucial for you to verify postal, phone, and email records. After all, you should be aware of when customers update their jobs, contact numbers, and addresses.
How Data Quality Helps in Digital Transformation?
Effectively managing large and diverse data affects your business’ ability to survive and succeed. Digital transformation needs to happen now and is no rocket science. As you have a focused data management strategy that closes the loop among operational data, master data, and analytics, you can gain valuable data insights, take appropriate actions, and measure results constantly. You can thus make more prudent business decisions and maximize your customer experience. That’s what digital transformation is all about.
In the figure below, we look at how quality data enables successful transformation of your business.
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