To embrace digital transformation, a business must completely rethink how it uses technology in its day-to-day operations. Successful digital transformation requires significant changes to a company’s hardware, software, operational practices, and company culture. And to do this, you need high-quality data that you can attain through robust data quality management.
Detailed data analysis relies on the volumes of data you collect about your business, your market, and your customers to provide reliable insights that determine your organization’s next steps. Here are the ways data quality management can help you successfully digitally transform your business.
- Digital transformation is the use of digital technology to improve business operations.
- Digital transformation depends on accurate data, which is possible only via data quality management solutions.
- Data quality management helps strategize and optimize digital transformation.
- Data quality management is also important when moving from data silos to an integrated data repository.
- Data quality management helps management make more informed decisions and drives business growth.
What is Digital Transformation?
Digital transformation represents a revolutionary change for most businesses. In essence, digital transformation uses digital technology to create new opportunities and to make existing business processes more efficient and effective. In many cases, this involves converting physical data into digital format or automating previously manual processes, although true digital transformation is much more than that, including the use of artificial intelligence (AI) and other technologies to completely modernize a business.
Why are companies embracing digital transformation? According to TEKsystems’ 2020 State of Digital Transformation report, the main reasons include:
- Improve customer engagement (72%)
- Increase operational efficiency (48%)
- Upgrade or replace legacy systems (47%)
- Increase speed to market (29%)
This explains why Deloitte found that two-thirds of business executives believe that organizations that don’t embrace digital transformation are “doomed” to marketplace failure. These executives plan on spending, on average, 0.6% of their annual revenue on digital transformation efforts – 15% more than in the prior year.
How Data Quality Management Enables Digital Transformation
There are several key ways in that effective data quality management leads to digital transformation success. It’s all about providing the high-quality data your business and your digital transformation efforts need.
Helps Strategize the Digital Transformation
High-quality data helps management make more informed decisions – including decisions regarding digital transformation strategy. Informed data analysis helps identify where an organization is in its transformation cycle, where it wants to be, and how it needs to get there.
The first step in any digital transformation is assessing the current state of an organization’s digital efforts. You need to know what data you have, the quality of that data, where it’s stored, and who needs to access it. Robust data quality management supplies that information and ensures that the data you have isn’t infested with incomplete or low-quality information.
Enables the Move from Data Silos to Integrated Data Usage
Most organizations find that digital transformation is hampered by their legacy data quality management systems. In particular, it’s common for essential data to be spread across an entire organization in departmental data silos. You might have separate silos for data in your marketing, sales, and finance departments, or in branches in different locations across the country. The situation becomes more challenging when you try to integrate data from merged or acquired companies, each of which will have their own way of doing things.
All of this siloed data makes it difficult to know what data your organization owns and almost impossible to share that data across departments and locations. It also makes it difficult to ensure the integrity of that data.
State-of-the-art data quality management helps organizations make the move from data silos to integrated data systems. This transition requires not only cleaning the data in each silo but also standardizing it so it can be consolidated into a single data repository. Unstructured data needs to be converted into the proper structure and individual structures need to be standardized into a single structure. And, in the process, incomplete data needs to be fixed or deleted and bad outright data needs to be purged.
With proper data quality management, data can be integrated into a trusted single source that is accurate and reliable. This single source of knowledge makes it easier to share essential data across the entire organization and to make more informed decisions about the ongoing digital transformation.
Reinvents Essential Operations
Businesses of all types depend on data to manage their essential operations, especially as those operations are digitally transformed. Data quality management is key to providing this data quickly and accurately.
Digitally transformed operations are data-driven operations. Data helps inform the analysis that can revolutionize and automate formerly manual processes, and keep those processes running smoothly with little or no human intervention.
Optimizes Digital Transformation Efforts
Few digital transformations go 100% smoothly. There are always bumps in the road and unexpected obstacles that need to be dealt with.
These challenges are best met through a continuing inflow of high-quality data. Real-time data analysis during the transformation can detect gaps in strategy and missteps in execution, enabling management to recalibrate towards a more successful conclusion.
Enables Faster and More Informed Decision Making
Robust data quality management provides the accurate and up-to-date data that management needs to make better decisions. These decisions drive digital transformation, long-term strategic planning, and decisions regarding day-to-day operations. Without accurate data, decisions can be ill-informed and off-target. High-quality data results in higher-quality decisions by all involved.
Supercharges Business Growth
Finally, data quality management is essential for the continued growth of your business. Complete, accurate, and timely data is a competitive advantage in every industry. It enables management to react faster to market changes, better respond to customer needs, and fine-tune ongoing operations – all of which help to drive business growth. It’s ultimately what digital transformation is all about – driven by data quality management.
Let DataBuck Help Drive Your Organization’s Digital Transformation
When you need high-quality data to drive your digital transformation efforts, turn to DataBuck from FirstEigen. DataBuck is an autonomous data quality management solution that uses AI and ML technology to automate more than 70% of the data monitoring process. Our data management system ensures that the data that drives your digital transformation is as complete, accurate, and timely as possible.
Contact FirstEigen today to learn how DataBuck can tie into your company’s digital transformation.
Check out these articles on Data Trustability, Observability, and Data Quality.
- 6 Key Data Quality Metrics You Should Be Tracking (https://firsteigen.com/blog/6-key-data-quality-metrics-you-should-be-tracking/)
- How to Scale Your Data Quality Operations with AI and ML (https://firsteigen.com/blog/how-to-scale-your-data-quality-operations-with-ai-and-ml/)
- 12 Things You Can Do to Improve Data Quality (https://firsteigen.com/blog/12-things-you-can-do-to-improve-data-quality/)
- How to Ensure Data Integrity During Cloud Migrations (https://firsteigen.com/blog/how-to-ensure-data-integrity-during-cloud-migrations/)