A Practical Guide to Mastering Data Quality
Actionable data is the foundation of a successful business. It plays a crucial role in strategy, informed decision making, and keeping teams on the same page. Yet all too often data quality is sacrificed in the face of more urgent priorities. But maintaining high quality data doesn’t have to be a herculean task, it just requires a well thought out and manageable strategy. In this article, we’ll discuss practical steps for cleaning data and establishing a long term maintenance strategy that works for your organization. These steps are especially relevant to companies preparing to implement AvSight, but are valuable regardless of where you are in your ERP journey.
Data Detox: Preparing & Cleaning Your Data
Before you can establish an ongoing maintenance strategy, starting with clean data is essential. If you’re preparing for an AvSight implementation, now is a perfect opportunity to get your data in order and start off on the right foot. Initial clean up will take some time, but the benefits – reduced errors, streamlined processes, and improved decision-making – are well worth the effort. We recommend starting to prepare your data as early as possible to save time and avoid roadblocks.
Assess Your Data Quality
Before cleaning your data, evaluate its current state by identifying outdated, inconsistent, or erroneous information. Focus on:
- Error hotspots: Where do errors occur most frequently?
- Root causes: Why are these errors happening (manual mistakes, outdated systems, etc.)?
- Data types: Are you working with customer records, inventory, financial data, or something else? Each requires different attention.
Pro Tip: Document root causes to target hot spots and build a strategy for long-term data governance.
Decide What Data to Migrate
Not all historical data needs to be migrated. Be honest with yourself about the data that is relevant to your business. Are you really referencing 20 years old transactions? The more data you bring over, the more time-consuming and costly the clean-up process will be. Being selective will allow you to focus on your most valuable data.
Pro Tip: Most AvSight customers migrate around 7 years of data. Consider whether outdated records, like old quotes or inactive suppliers, are worth keeping. Prioritize fresh, relevant data instead of holding onto everything.
Clean Your Data
With your migration data identified, begin the clean-up process by:
- Removing obsolete data: Delete outdated records, like discontinued products or dormant customers.
- Eliminating duplicates: Merge duplicate records for accounts, products, and other data types.
- Fixing formatting issues: Ensure consistency in dates, text, and numbers.
- Handling missing data: Fill in incomplete records to prevent gaps.
- Managing outliers: Address any extreme values that need attention.
Using tools or third-party services can speed up the process and improve accuracy. AvSight offers data cleansing as an add-on service if you didn’t get a head start before implementation.
Pro Tip: If resources are limited, consider a phased clean-up. Start with the most critical data (e.g., customer accounts or inventory) and tackle the rest over time.
Bonus: Other Steps to Prepare for Your Data Migration
In addition to cleaning your data, consider these steps to avoid surprises:
- Do I have access to download my current ERP database?
- Are any of my data or files encrypted by my current ERP provider? Are there de-encryption fees?
- Who in my organization will handle data issues or questions?
Data migration doesn’t have to be daunting. The AvSight team is here to guide you through the process, but there’s a lot you can do to prepare before you begin working with us.
Building Your Data Management Plan
With clean data as a foundation, you’re ready to develop an ongoing plan that fits your organization’s goals and is practical for your team to implement. This will ensure that your data is clean and reliable and doesn’t require massive clean up projects.
Develop a Data Quality Strategy
A strong data quality strategy sets the foundation for clean, consistent data across the organization. Establish:
- Data rules: Define how data should be captured, formatted, and maintained.
- Data governance: Assign responsibility for ensuring data quality across the organization.
- Key performance indicators (KPIs): Set expectations for tracking and maintaining data health.
Pro Tip: Secure buy-in for data quality across your organization before the ERP implementation kicks off. Treat it as a pre-implementation project to ensure everyone understands the importance of reliable data. This way, when you start working on processes and learning AvSight, your team will be aligned and prepared to maintain high-quality data throughout the transition and beyond.
Correct Data at the Point of Entry
Implement strict data entry standards to ensure that only accurate, consistent data is added to your ERP system. This can be challenging, especially if your organization has been using inconsistent processes for years, but it’s essential for maintaining data quality.
Pro Tip: Make data entry standards part of your new employee onboarding and offer retraining to existing employees. Create clear documentation outlining the standards to follow.
Plan for Continuous Data Maintenance
Keeping data clean is an ongoing task. Set up processes for ongoing monitoring and maintenance of your data. This includes:
- Regular reviews: Run data quality reports to spot any new issues.
- Dashboards: Implement dashboards to track key data quality metrics, so your team can quickly identify and address any problems.
- Automated checks: Consider using software that flags issues in real time, such as data duplication, missing fields, or formatting errors.
Foster a Data-Quality Culture
Creating a culture that values clean data is essential for long-term success. Promote the importance of data quality across all departments, and ensure everyone is on the same page when it comes to maintaining accurate records. Provide training and ongoing support to ensure employees understand the value of clean data and follow the necessary procedures.
Monitor and Improve Data Quality Over Time
Data quality is never “done.” Over time, your data will change and evolve, and you need to keep up. Regularly monitor the health of your data, and look for opportunities to improve the accuracy and reliability of your information.
Pro Tip: Use feedback from users across the business to continuously improve data quality. For example, if users find it difficult to access or interpret certain types of data, work with them to improve the data structure or capture process.
A Strong Foundation for Growth
With a strong data strategy in place, you’ll set your company up for success and growth. You’ll also be prepared to maximize the value you get out of AvSight’s business intelligence and reporting features. Ready to get started on your data-driven business journey? Request a free demo of AvSight.
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