Are you sure data can be trusted?

As businesses continue to increasingly rely on data to inform decisions, the importance of trust within that data becomes critical. Companies need to be confident that the information they are basing their strategies and decisions upon are accurate and reliable.

Without trust in data, decision-making can become risky and costly. Inaccurate or incomplete data can lead to poor decisions, wrongful actions, missed opportunities, and potential legal or reputational issues.

Cycle Time to Value integrated into your business

Therefore, building a culture of trust around data is essential for companies to thrive in today’s data-driven world. This requires a shift in mindset to lead on data management, providing employees with a strong commitment to data quality, data governance, and data security, as well as an understanding of the role that data plays in driving business outcomes.

By prioritizing trust in data, companies can gain a competitive advantage, improve operational efficiencies, and enhance customer experiences. Trust in data can also enable better collaboration across departments and foster a more transparent and accountable organizational culture.

In short, trust in data is not just a nice-to-have; it is a must-have for businesses that want to succeed in today’s data-driven economy. As leaders, we must prioritize building a culture of trust in data and make it a foundational element of our business strategy.

The cost of poor data quality

Cycle Time to Value integrated into your business

There is also a financial cost for organisations that have poor data management practices and a low trust in their data. They can include:

  1. Data Breaches and Cybersecurity Incidents: Poor data management practices can leave organizations vulnerable to data breaches and cyber-attacks. According to a study by IBM and the Ponemon Institute, the average cost of a data breach in 2021 was $4.24 million. (Source: IBM, “2021 Cost of a Data Breach Report”)
  2. Inefficient Data Management Processes: Inefficient data management processes can lead to wasted time and resources. According to a report by Experian, inefficient data management practices can cost companies up to 30% of their revenue. (Source: Experian, “Data Management Benchmark Report”)Lost
  3. Productivity: Poor data management practices can also lead to lost productivity. According to a study by IDC, employees spend an average of 2.5 hours per day searching for information. This lost productivity can cost organizations up to $5,700 per employee per year. (Source: IDC, “The High Cost of Not Finding Information”)
  4. Non-Compliance Penalties: Poor data management practices can also lead to non-compliance penalties. For example, the EU’s General Data Protection Regulation (GDPR) can impose fines of up to €20 million or 4% of global revenue for non-compliance. (Source: European Commission, “Data protection in the EU”)
  5. Data Quality Issues: Poor data management practices can lead to data quality issues, which can have a significant impact on an organization’s bottom line. According to Gartner, poor data quality can cost organizations up to 25% of their revenue. (Source: Gartner, “Measuring the Business Value of Data Quality”)

Investing in data management saves costs and improves Cycle Time of Value©

Building trust in data through better organised management allows the entire organisation to pull from one co-ordinated and collaborated source significantly reducing the cost of data across the organisation. Eliminating the dreaded reconciliation and allowing decisions to be made much faster.

To give a couple of examples when I implemented it in my last company we took projects from waiting months for data to weeks, we had all of our top strategic projects linked to one source of data, so any improvements benefitted all of the projects.

It also makes analytics a trusted, integral part of the business

Thanks to a trusted data set, our data science program was leading on the largest project looking to deliver 9 figures to the bottom line of the profit and loss.

We also used the same data set to do a data and analytics hackathon alongside some of the best experts in the business to build direction and create decisions for our biggest transformation for many years. It took longer to get the experts in one room than it did to get the hackathon data set up.

Whilst building trust in your data takes vision, effort, commitment from leadership and a couple of years to start really bearing fruit, the benefits far outweigh the alternatives and if you wish to understand the benefit potential for your organisation the please get in touch.

Sources:

  1. IBM, “2021 Cost of a Data Breach Report”: https://www.ibm.com/security/data-breach
  2. Experian, “Data Management Benchmark Report”: https://www.experian.com/globalassets/decision-analytics/brochures/dm-benchmark-report-2021.pdf
  3. IDC, “The High Cost of Not Finding Information”: https://www.idc.com/getdoc.jsp?containerId=US40546516
  4. European Commission, “Data protection in the EU”: https://ec.europa.eu/info/law/law-topic/data-protection_en
  5. Gartner, “Measuring the Business Value of Data Quality”: https://www.gartner.com/en/documents/2812316/measuring-the-business-value-of-data-quality