Bad data = Bad decisions: Why Data Leadership Begins in the Boardroom

To quote the CEO of Netscape, Jim Barksdale, "If we have data, let's look at data. If all we have are opinions, let's go with mine". Netscape doesn't exist anymore. It was acquired by America Online (AOL) in 1999. Interestingly, the organization was valued at $10bn in stocks even two decades ago.

It shows an interesting lesson about the power of data. Which is, every bit of data is an asset for any enterprise.

In a data-driven world, irrespective of the industry, enterprises are sitting in a goldmine of information. What makes a business stand out is how you manipulate the data that's acquired.

Bad data = Bad decisions

Approximately 402.74 million terabytes of data are generated daily. [Statista] From analysing customer behaviour to forecasting market trends, data helps enterprises in making better decisions. However, data can also undermine our decisions. The important question is, "Can we trust the data?"

Without proper data optimization, it's impossible to make accurate predictions, leading to disruptions in analytical and predictive systems. Another aspect of bad data is the accountability for its correctness. The concept of a Chief Data Officer and data governance is still new and not present in a lot of organizations.

Should we even bother? Yes, we should. Data is the fuel of a successful business. That's why true data leadership starts in the boardroom.

The Hidden Cost of Bad Data:

Exploring the financial impact

• Poor data quality can affect an enterprise by an average of $12.9 million annually.[Dataversity]
• Bad data leads to wasted marketing expenditure and internal & external resources, causing a loss of up to 15% of the revenue of an enterprise.[Massachusetts Institute of Technology]
• Employees spend 27% of their time correcting bad data. It slows down the decision-making process and increases operational costs. [Actian]

Clearly, poor data quality has a direct impact on the financial performance of an enterprise.

Some real-world examples of ignoring data quality

The repercussions of poor data quality are factual and hard-hitting. Here's what happens when ensuring data quality is not a part of your business operations.

• Unity Software reported a loss in revenue of $110 million and an additional decline of $4.2bn in market capitalization. All this was due to bad data from a large customer.[Dataversity]
• What started as a simple data entry error turned out to be a significant loss in revenue for Samsung. Imagine this - an overstatement of $105bn in financial reports![Monte Carlo Data]
• In 2017, inadequate data security measures led to a major financial and reputational loss for Equifax.[EPIC]

The price you pay for bad data can be catastrophic. It not only affects financially, but also damages reputation and shatters stakeholder trust.

Data governance: The boardroom's role

Data governance is no longer an IT concern. It is also a crucial responsibility of the board of directors. The directors of an enterprise, who are the leaders, understand the value that can be extracted from a dataset, beyond risk mitigation; they can steer their organization towards innovation instead of simply playing defense.

When it comes to demystifying data, there is always an initial hesitation. Why? It's due to the [Dunning-Kruger Effect]. This effect is where a little knowledge develops confidence. However, as you keep digging deeper, learning deflates confidence momentarily before you truly develop expertise.

Here are the elements of a good data governance strategy:

• Implementing transparent data policies: As leaders, you must establish strict organization-wide policies for data collection, storage, and usage.
• Invest in data quality tools: Encourage internal resources to use tools that ensure data accuracy and consistency. Provide consistent and ongoing training to your resources to help them effectively utilize advanced tools.
• Building a culture of data literacy: Make sure every member of your team understands the impact of data quality and is clear on their role to maintain it.
• Audits & monitoring: Periodic reviews help identify and rectify data issues.
• Appreciating the success: Appreciate the hard work and efforts that your team members have put in to ensure the highest form of data accuracy.

As leaders, when you embed data governance into your organization's culture, it reduces risks associated with poor data quality. By developing an environment where data is valued and managed properly, CEOs can drive better decision-making and organizational success.

Conclusion

In the age of information, data is a strategic asset that can propel organizations to new heights or lead them into peril. CEOs must recognize that data governance is not just an IT function but a core component of strategic leadership. By prioritizing data quality and embedding it into the company's culture, CEOs can ensure that their organizations make informed, effective decisions that drive growth and success.