Enhancing Data Privacy Through the Application of Process Mining

We should list some of these challenges to understand how data privacy can be enhanced. This way, you know where to focus your efforts. So, some of the biggest challenges you’ll face are:

• Data breach detection: It’s hard to tell when an account breach has happened. Sure, a new device is an obvious sign, but this is not always indicative, and you need more data to increase certainty.
• Access control and permission: While the majority of project management tools and collaboration tools have an in-built system for granting access and permissions, this is not always done the right way. Ensuring this is configured properly can be more challenging than you think. This means it will require a deeper analysis. Controlling access is especially important since some of your coworkers may have bad passwords or be susceptible to phishing.
• Privacy compliance monitoring: The more pages you have, the more users you have; it becomes harder and harder to ensure compliance with all data privacy regulations (like GDPR). By tracking these processes in real life and enhancing your monitoring methodology, you can get closer to your aim.
• Data deletion: Handling a triage of which data to keep and which to delete permanently is difficult and potentially risky. Contrary to popular belief, you’re not deleting data to free up storage (it doesn’t take that much storage) but to eliminate a potential leak.
• Continuous improvement: While data privacy is a gaping abyss you’ll never close, sometimes, when things run smoothly, it will be hard to find ideas for further improvement. This doesn’t mean that there’s no need to improve.

Each of these has something to gain from process mining.

The simplest way to explain process mining would be to say that it extracts insights from data, analyzes it, and turns it into actionable information.
To be even more usable, it heavily depends on the visual presentation of these processes. More often than not, you’ll get results in the form of a process flowchart. This can make complex workflow understandable, reveal all inefficiencies and bottlenecks in the process, and more. The best part is that visualization allows for a quicker understanding of the situation. After all, humans process visual information faster than text-based ones.
Adaptability and improvement are always challenges, but process mining is great at giving myriad variations, unlike A/B testing, which gives you a small number of variants to test and compare. Examining these variations allows you to uncover hidden problems and bottlenecks and plot the optimal course for your product/enterprise.
Most importantly, process mining can be used for a more accurate performance analysis. This way, you can see the costs, quality, and scalability of any decision you implement.
With the help of predictive insights, you have a much easier job of being proactive. We’ve mentioned bottlenecks several times before, and this is the best possible way to predict them. Knowing what lies ahead is the key to developing a specific preparation.

Arguably, the main reason why process mining can be applied to fix your issues with data privacy is because of the many solutions it brings to the table. Some of these solutions are related to the challenges we’ve discussed earlier. For instance:

• Early data breach detection and response: Data breaches will happen no matter what. They may not happen to you. They may not happen for years, but they’re an eventuality for anyone hooked on the internet. With the help of process mining, you may have an easier job figuring this out early on and crafting an adequate (and timely) response.
• Data mapping and classification: Even with physical documents in your home, you’re not putting them all in the same drawer. Some of the documents go into special folders; others are as concealed as they can be. The bottom line is that you can use process mining for more efficient data mapping and classification of sensitive information. This way, everything is properly tagged and protected.
• Auditing trails: Your job is not over after a data breach. It’s not as if you should acknowledge your failure and go home to fight another day. You need to audit trails and figure out what transpired. This is also where variants are great since you can see if any of the other methods used could have been better or worse in this particular scenario.

With so many tools, these processes can be made far more effective.

You need reliable process mining software to access these perks and benefits. In the past, you had to resort to several different tools to get this intelligence processing. Today, you can do this from a single centralized platform. This allows you to turn process intelligence into business value in the simplest, most direct way possible.
The most important aspect is handling various data formats and quickly (and accurately) transforming data into usable event logs. The platforms you get on your list have free accounts or trial periods; test them on the same data bundle and see how they perform. Compare these logs to see if they’ve been delivered differently.
Next, you want to take a look at the interface. Sure, the process is incredibly complex, and the power of analysis counts, but at the same time, this interface is something you’ll spend hours watching and analyzing. You need something that feels right and intuitive.

You also want to watch out for the compatibility and integration potential. You’re already using so many tools, and you don’t want to have to change your business model too much, especially when so many process mining tools already support the software you’re currently using.
Most importantly, you need to think about the scalability. Now, this shouldn’t be an issue. Namely, most of these tools are quite potent by their very nature. Still, you need to ensure they’ll be able to accommodate larger databases and more complex processes that you’ll encounter in the future.

To keep data secure, you need to keep it safe every step of the way. Now, you can’t do this without first identifying some data sources. These data sources are usually:

• Databases
• Applications
• User interfaces

Then, you need to document these data elements. This means cataloging different elements to distinguish between different types of information. These can be things like personally identifiable information or financial data. There are several other formats, but these two are the big ones.
Most importantly, you need to track data across processes. You need to know exactly where data is collected, how it’s processed, and how it’s shared within the organization. In terms of financial data, handling it is a lot easier with adequate financial reporting system in place
This data movement is often also referred to as data flow, and one of the perks of using a process mining tool is that you get the visualization of the process. You get to track access and transformations and check for compliance in all the stages (since violations may happen in the process). Most importantly, since no system is ever fully incident-proof, you get amazing incident response mechanisms.

The key point of this entire concept lies in uncovering problems so that you can fix them. Sometimes, this requires a simple optimization, but in some instances, process redesigning will have to take place.
For instance, you may take a privacy-by-design approach, which means you can implement anonymization or pseudonymization of data at the entry point. This would provide the necessary protection for sensitive information from the very start.

Then, there’s the issue of consent management integration. This way, you can set up the system to use only the data provided by the individuals (along with their explicit consent).
Data minimization is the simplest way to protect data under these circumstances. It involves only taking the data that you need. This minimizes the amount of potential data that can be lost. The fewer pieces of data you handle, the lower the overall risk.
Regarding the optimization, you only need better access controls and continuous monitoring. At the same time, you might decide to leverage some of that computing power and integrate predictive insights into the process.

Keeping data safe will often feel like an uphill battle, but properly using process mining can make things easier for you. First, research the process and see where it fits the big picture. Then, find the right tool and start using it.