Just one-third of organizations trust the analytics generated from their business operations, despite the critical role these insights play in decision-making

KPMG – Building Trust in Analytics

For large, modern businesses, data is king. Every click, swipe, and purchase generates a wealth of information. But with this abundance comes a challenge: how do you find, understand, and trust your data?

1. Find Your Data:
2. Understand Your Data:
3. Trust Your Data:

Imagine navigating a vast library overflowing with unlabeled books. Finding the specific information you need would be nearly impossible. The same goes for data – without proper organization and context, it becomes a chaotic mess.

Given the power that it holds, trust in D&A should be a non-negotiable business priority. Yet our survey reveals that this may not be the case. In fact, 60 percent of organizations say they are not very confident in their D&A insights. Only 10 percent believe they excel in managing the quality of D&A. Just 13 percent say they excel in the privacy and ethical use of D&A and only 16 percent believe they perform well in ensuring the accuracy of models they produce.

KPMG

Here’s how you can transform your data from a confusing jumble into a valuable asset:

Find Your Data:

• Data Discovery: The first step is knowing what data exists. Employ data discovery tools to identify and locate data sources across your organization. This could include both structured and unstructured data sets like customer databases, marketing platforms, sales records, and internal documents.
• Data Cataloguing: Once you’ve identified your data sources, organize them with a central data catalog. This catalogue should function like a library card system, providing detailed descriptions, metadata, and security classifications.
• Data Accessibility: Once you’ve identified your data sources, ensure they are accessible to those who need them. Break down data silos and implement access controls to safeguard sensitive information.

Understand Your Data:

• Data Definition and Documentation: Define the meaning of each data point within your datasets. Clear documentation helps everyone understand what the data represents and how it should be interpreted.
• Data Quality Assessment: Not all data is created equal. Assess your data for accuracy, completeness, consistency, and timeliness. Are there missing values? Is the data formatted consistently?
• Data Lineage: Understanding the origin and journey of your data is crucial. Tracking data lineage ensures you know where it came from, how it’s been transformed, and who has accessed it.

Trust Your Data:

• Data Governance: Implement a data governance framework to ensure data quality, security, and compliance with regulations. This framework should define roles, responsibilities, and processes for data management.
• Data Access Controls: Define clear data access controls to ensure only authorized users can access specific data sets.
• Data Literacy: Empower your workforce with data literacy training. This will enable them to understand, interpret, and utilize data effectively.

The Benefits of Trustworthy Data:

By implementing these steps, you’ll be well on your way to unlocking the true value of your data. Here’s what you can expect:

• Improved Decision-Making: Make data-driven decisions based on reliable information, leading to better outcomes for your business.
• Enhanced Efficiency: Reduce wasted time and resources spent searching for or correcting inaccurate data.
• Increased Innovation: Uncover hidden insights from your data that can spark new ideas and drive innovation.
• Stronger Customer Relationships: Build trust with your customers by leveraging data to personalize experiences and address their needs effectively.

Conclusion:

In the data-driven world, trust is paramount. By finding, understanding, and trusting your data, you can transform it from a burden into a powerful asset that propels your business towards success. Remember, data is knowledge waiting to be unlocked – invest in its quality and reap the rewards!

Reference:

KPMG, Building Trust in Analytics, 2019

Do you have any tips for finding, understanding, and trusting your data? Share them in the comments below!