By Zahn Alimbay in Program Effectiveness — Nov 9, 2023

Data never lies. Or does it?

Embracing technological progress, our fascination with data has intensified. We look at numbers as if they hold all the solutions, like a mystical crystal ball. The compliance field is no exception to this trend. But it’s not the data itself; it’s what we do with it matters. And that’s where the problem lies.

We are data hoarders.

Nowadays, organisations collect unthinkable amounts of data. Daily, ERPs and GRC systems, compliance process automation, communication exchanges - emails and messaging tools, and other business systems produce terabytes of information. We rarely analyse the data we collect, though, and hardly use it to drive change.

Hang on! But we measure and track.

Yes, we do. Compliance teams routinely use graphs to illustrate the training statistics or, for example, to identify relationships between compliance incidents and the amount of policy communications and training. However, more often than not, the goal is to track and visualise compliance efforts rather than address the unseen issues. But there is a lot more we can and should do with the data we collect.

First thing first, let’s clear the headline.

Numbers are numbers. But without context, they are pointless. And that’s where the issues start.

When we put numbers in play, we often do this to prove or explain our point. This means we already made up our minds about the cause of the issue. We use numbers to support the conclusion. Let’s look at an example. As many compliance professionals might have observed during their professional careers, an increase in the amount of compliance training and communication leads to a spike in compliance allegations reporting. To substantiate this, we tend to combine two trends and now have a case for a higher training objective.

But what if we are wrong in this assumption? What if there are other factors at play here? Correlation is not causation, after all.

Decision intelligence can help us to do better.

What is Decision intelligence anyway? As Google’s first Chief Decision Scientist and guru in the field, Cassie Kozyrkov put it, “Decision intelligence is the discipline of turning information into better actions at any scale.” (Read her brilliant Introduction to Decision Intelligence | by Cassie Kozyrkov | Towards Data Science).

We should let data talk. Or, more precisely, use data to identify patterns of behaviour and help us understand what drives the conduct in the first place. Once we know the root causes, drivers and derailers, we can use those insights to design targeted preventive strategies focused on desired outcomes, maximising the impact and leading to higher Compliance ROI.

Look beyond the numbers.

But data is not all.

Step One: Identify the problem area. What is the specific issue you are trying to address? Are you examining the trends in incidents related to a particular type of activity? Or decrease in allegation reporting?

Step Two: Zoom in. Understand the risk environment, conduct and decision-making in the context of business drivers. What internal and external factors are in play? What are the rules, and how do business processes and internal controls operate? What is happening on the ground? What is the chain of events, and how do actions lead to outcomes? What are the factors affecting individual behaviours? Drivers and derailers? Build a map.

Now, let’s talk about data.

While data quality is essential for any analysis, there are other important factors to consider. Start by identifying the data sources. Build collaboration and cross-functional support around the exercise. If you don’t have the required data, consider a targeted dive-in.

And don't overlook intangibles - those often “hard-to-measure” components such as trust, moral attentiveness and engagement, and corporate culture that are key to unlocking a deeper understanding of behaviours and their underlying causes. Speaking Up is a great example of how intangibles can affect the outcomes (see our earlier newsletter here: https://www.linkedin.com/posts/comhlaic_esg-ethics-compliance-activity-7108698494558724096-Taa4?utm_source=share&utm_medium=member_desktop).

Then, let your data analytics team do their work. And importantly, it’s the data that shall inform the analysis. Don’t let confirmation bias get in the way.

Once you see the emerging patterns, look at those through the prism of root-cause analysis, cause-to-effect links and lessons learned from past compliance incidents and misconduct. Does it all make sense? Are there any anomalies in the data? Something unusual? What do trends show? Dive in.

AI and Machine Learning opened enormous opportunities which can help us to overcome the modern-day complexity ceilings. But the most critical success factor – the not-so-secret ingredient – is a compliance professional at the centre of it all. No AI or ML can substitute the expertise of a skilled professional.

All the best on your journey! And if you need a little help, get in touch. We are here to help!

We will be back in two weeks!

Comhla Intelligent Compliance

At Comhla, we are driven by a mission to revolutionise the way organisations approach compliance and misconduct prevention. We leverage cutting-edge applied research in behavioural science, actionable data insights, compliance, internal controls and regulatory expertise to help our clients identify and target conduct risks before misconduct occurs. We believe that each organisation should be proactive about maintaining business integrity. By going the extra mile to provide evidence-backed solutions tailored to our customer's unique needs, we enable them to maximise Compliance ROI while increasing the effectiveness and impact of the prevention strategies.

Learn More https://comhla.co

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