Flying Blind: How Bad Data Undermines Business and How KOIOS Solves It
As businesses increasingly adopt data-driven systems and processes, leaders are striving to “Moneyball” everything from operations to decision-making. But as data volumes continue to soar, the quality of that data has become a critical challenge. KOIOS offers a revolutionary approach to tackling this issue, transforming fragmented, unstructured data into high-quality, machine-readable information, creating a single source of truth for global supply chains.
With AI, machine learning (ML), and the Internet of Things (IoT) now contributing massive volumes of data daily, the need for robust data quality standards is more urgent than ever. KOIOS addresses this head-on by using international data standards like ISO 8000, and by housing data within its Product Data Library, ensuring that product information is accurate, standardized, and interoperable across global systems.
The High Cost of Low-Quality Data
The cost of bad data is staggering. According to Gartner, businesses lose an average of $15 million per year due to poor data quality. Meanwhile, IBM estimates that poor data quality drains a whopping $3.1 trillion from the U.S. economy annually. These losses stem from inefficiencies such as lower productivity, system outages, and higher maintenance costs, all of which KOIOS mitigates through its structured, interoperable data solutions.
The problem is exacerbated by the lack of trust in existing business data. A Vanson Bourne study found that 91% of IT decision-makers recognize the need to improve data quality, with 77% reporting a lack of trust in their organization’s data. KOIOS directly addresses these concerns by offering a robust platform where data is consistently verified against a trusted single source of truth—the KOIOS Product Data Library.
The KOIOS Approach: Data Quality and a Single Source of Truth
KOIOS distinguishes itself through its rigorous approach to data governance. Unlike traditional systems, KOIOS builds data quality from the ground up by leveraging AI and ML to onboard, cleanse, and validate data against its Product Data Library. This library acts as a central repository of authoritative product data, ensuring all data is compliant with international standards and ready for real-time, global use.
By focusing on data interoperability, KOIOS removes the silos and inconsistencies that often plague supply chain and enterprise data systems. Every product, process, and actor is mapped to global standards (such as GS1, ISO 22745, and ISO 8000) to ensure the data can flow seamlessly between different systems, eliminating the operational inefficiencies caused by bad data.
A Case for Data Quality Standards
Consider the airline industry, where poor data quality often results in “mistake fares,” causing airlines to either lose revenue or face public backlash. In global supply chains, the cost of bad data can be even higher—misclassified products, incorrect tariffs, and regulatory fines are just a few of the consequences. KOIOS provides businesses with the tools they need to prevent these costly errors by delivering real-time, accurate data that meets the highest quality standards.
For example, financial services depend heavily on accurate credit scoring algorithms. When bad data feeds into these systems, it can cause consumers to be misclassified as risky borrowers, leading to what’s known as “algorithmic bias.” KOIOS prevents these scenarios by ensuring that all data within the system is properly cleansed, standardized, and validated, creating trust across the supply chain.
Ensuring Data Integrity with KOIOS
KOIOS goes beyond just fixing data; it ensures that businesses never face bad data issues in the first place by establishing a robust data governance framework. Here’s how KOIOS ensures data integrity:
1 – Single Source of Truth: All data is validated against the KOIOS Product Data Library, a repository that serves as the authoritative source for product and supply chain information. This eliminates the discrepancies often found in unverified or manually entered data.
2 – Interoperable Data: KOIOS uses global standards, ensuring that product data can be seamlessly exchanged across different systems, regions, and supply chains. This interoperability enhances data consistency and eliminates the bottlenecks caused by incompatible formats.
3 – AI-Driven Data Cleansing and Governance: KOIOS leverages AI and ML technologies to continuously cleanse and govern data, ensuring ongoing compliance with international standards such as ISO 8000. This prevents data decay over time, ensuring businesses maintain long-term data quality.
KOIOS: The Solution to Low Data Utilization
Forrester Research estimates that less than 0.5% of all data is ever analyzed and used, but even a 10% improvement in data accessibility could add $65 million in additional net income for a typical Fortune 1000 company. KOIOS enables this by improving both the quality and accessibility of data across the enterprise. With KOIOS’ Product Data Library, businesses can unlock insights from their data without the need for costly manual cleansing efforts.
The Future of Data Quality with KOIOS
KOIOS’ AI-powered platform ensures that businesses don’t fall victim to the high costs of bad data. By delivering interoperable, high-quality data directly from the source—whether manufacturers, suppliers, or distributors—KOIOS enables organizations to maintain a high level of trust and accuracy in their data.
Data is more than just an asset; it’s the foundation of strategic decision-making. With KOIOS, businesses can ensure that their data is not just accessible, but also trustworthy, compliant, and ready for the digital future. KOIOS prevents the costly repercussions of bad data by delivering a comprehensive solution that focuses on real-time accuracy, compliance, and long-term data governance.
By using KOIOS, companies can avoid flying blind and instead make data-driven decisions with confidence, knowing that their data is validated, interoperable, and aligned with the highest quality standards.
