The Data Management Book of Knowledge (DMBOK). lays out 13 hurdles we face when handling data and risk. This article zooms in on one of those hurdles: dealing with the risks tied to data.
Read More: What is Data Management?
To really grasp what we mean by “risk” in the world of data, let’s break it down.
What is Risk?
Think of risk as the uncertainty that things might not go as planned, and those outcomes might not be good. Warren Buffet sums it up pretty well. Risk can swing either way – it could be good or bad, depending on the situation.
The term risk can be used in several ways, and its definition can change on the basis of the field and context.
What is Risk Management?
Now, managing risk means tackling those uncertainties head-on. It’s about planning ahead and setting up safety nets to deal with potential problems. When it comes to data, there are a bunch of “what ifs” we need to consider.
Now, the question is, from what are the uncertainty come with the data?
What could be the uncertainty (risk) with the data? – Data and Risk
We thing the best way to understand the uncertainty (risk) is by asking questions. Here are the few questions, and try to imagine the exact answers. If you couldn’t imagine the exact answer then that is an uncertainty. And even if you know then you will try to avoid it by managing the risk before it materialized.
- What if we miss a deadline for a crucial report?
- What if our sales numbers don’t add up?
- What if we can’t access important data when we need it?
- What if we don’t have all the info we need for required training?
- What if sensitive customer data gets leaked?
These questions highlight the kinds of risks we face in managing data, and why it’s so important to stay on top of them. This is how data and risk is intertwined.
Regulatory Focus on Data and Risk:
The growing importance of information in businesses across all industries has drawn increased attention from regulators and lawmakers regarding its potential benefits and risks. Regulations like Sarbanes-Oxley and Solvency II stress the importance of accurate data for financial transactions and risk assessment. Plus, with people becoming more aware of data privacy issues, there’s a growing demand for businesses to manage data responsibly.
Remember the financial crisis back in 2007? It showed us that many banks didn’t have the right systems in place to handle risks properly. That’s why groups like the Basel Committee on Banking Supervision (BCBS239) stepped in, setting guidelines to help banks improve their data systems and reporting practices.
Keeping data in check means making sure it’s accurate and easy to access, while also minimizing risks like mistakes or misuse. Meeting regulatory standards means being really careful with how we handle data.
Broad Areas to Manage Data and Risk:
To maximize the benefits of data, it’s crucial to uphold its quality at the highest standards. Data should be readily accessible, pertinent, comprehensive, precise, uniform, timely, usable, significant, and comprehensible. Poor-quality data, characterized by inaccuracies, incompleteness, or outdatedness, inherently poses risks as it undermines the reliability of information. Moreover, data can be risky when it’s misinterpreted or abused. Therefore, it’s wise to consider data and risk in tandem when handling data, as a best practice.
Read More: Is data an organizational asset or liability?
Here’s the intriguing part regarding data and risk: all these regulations are created to address the challenge of managing risks linked to data. And here’s the twist: you actually need to manage data to comply with all these regulations.