The AI age is upon us and the emergence of Agentic AI (autonomous systems) will fundamentally change the way we work and live.

As of last year, 65% of organisations have adopted AI in at least one business function (up from 33% the year before – McKinsey, 2023).

But AI relies on data. How good is your data quality?

In this blog series we will outline how to;

1. Fix your current data quality issues and stem your value leakage
2. Start generating more value from your data by managing it as an asset
3. Strategically build your corporate data maturity for competitive advantage
4. Manage the emergence of shadow AI for business agility while reducing risk and cost

Stem Value Leakage Caused by Poor Data Quality

Data quality is a key concern for organisations around the world, in every industry and market. We all struggle with managing disparate data sources, complex integration landscapes, out of sync systems and data errors.  All of this erodes our efficiency, constrains growth, and increases business risk.

The bigger we get, the bigger the problem.

79% of organizations have over 100 data sources, with 30% using more than 1,000 (Inteligent CIO, 2021).

77% face data quality issues, and 91% say these impact performance (AIDATA, 2022).

25% of critical data contains errors (Forbes, 2023).

But while poor data quality is a ubiquitous challenge, it is also readily solvable.

What Is Your Data Quality Costing You?

The impact of poor data quality is hidden most of the time.  Most organisations accept data errors as ‘business as usual’ and forget it consumes valuable resource capacity.

I recently worked with a large media company with over 10M subscribers. This company knows it has data errors but hasn’t measured the impact. If it only suffered a 2% error rate (very conservative), and each error took 10 minutes to resolve and rework, that adds up to 200,000 transaction errors annually, consuming over 30,000 hours to resolve (~17 FTE) and costing in the order of $1.4M operational budget. Scale matters.

I also worked with a global medical equipment provider where we found 33 FTE across the organisation whose time was consumed in fixing data issues, at an annual cost of around $4.6M.  One of the additional “hidden” costs was an increase in calls to the company’s call centre due to customer data errors. Answering these calls and handling the issues was estimated to consume over 7000 hours of effort from staff.

The problem is not so much the $300,000+ operational cost of those calls, but the unmeasured missed revenue opportunities (the call centre is a primary upsell/cross-sell revenue generator for the organisation.)

The First Step Is To Admit You Have a Problem

Have your data or IT team review your data quality for:

• Incomplete data
• Inconsistent data
• Inaccurate data
• Obsolete data
• Non-compliant (invalid) data
• Duplicate (non unique) data

In addition to considering the types and extent of your data problems, it is critical to note what parts of your business are impacted and the criticality/sensitivity of the data involved (i.e. are you handling PII or compliance data?)

How To Improve Your Data Quality

To improve your data quality and reduce your business value leakage:

1. Establish a Data Governance Framework: The first thing you need to do is manage your data in a consistent manner.  A strong governance framework ensures data accuracy and consistency.  Standardise data integration, storage, and management to ensure consistency and security.  Allocate data stewards to manage data usage and interpretation for the greatest advantage (typically the business owner).  A report by IBM states that companies that prioritize data governance achieve a 33% increase in revenue as a result of improved data quality (Vorecol, 2024).

2. Implement Data Synchronization: Once you have a consistent governance framework, you need to connect and synchronise your data.  Ensuring all of your systems share a consistent data set is key to improving quality. A survey conducted by Harvard Business Review found that organizations that invest in realtime data synchronization see a 25% increase in operational efficiency and a 32% improvement in overall decision-making processes. (Vorecol, 2024).

3. Invest in Real-Time Data Validation: Once integrated and synchronised, apply real-time data deduplication and validation rules to ensure your data is persistently up-to-date, complete and accurate across all of your systems.

A $2B+ organisation I have worked with has done this, and is now reaping the rewards. On top of the immediate organisational value, it has seen approximately 80% of new business projects benefiting from the availability of an accurate and consistent data set. This has reduced project effort by up to 25%.

Next Steps

Review your existing data management capabilities and reach out to Boomi if you need help.  The Boomi Enterprise Platform helps businesses across the globe grow their digital maturity by connecting systems, cleaning and synchronising data, managing and securing your external data exchange, and providing real-time automation and AI orchestration capability. It is the one platform businesses need to thrive in the era of AI-driven automation.

Contact Boomi experts to help you take the next steps toward data quality optimization.