By the end of 2020, it is expected that more than 59 zettabytes of data will be generated globally. With access to data from sources such as social media, news and the dark web, encrypted connected security systems, and public and company-proprietary records and communications, physical security and safety professionals are challenged not only with parsing through this “big” data but transforming it into actionable intelligence.

When you add the fact that 80-90% of data generated today is unstructured, it becomes even more evident that, to ultimately safeguard lives and property, organizations need technology solutions to efficiently unify and contextualize disparate data sources.

Information Sharing Reduces Intelligence Gaps

Throughout my years of experience as a special agent in the counterterrorism and protective intelligence division in the Diplomatic Security Service at the Department of State and in the private sector, I’ve learned that one of the largest problems that plagues protective intelligence teams and program managers is “fragmented” or “disparate” data.

This fragmented data is the disconnect between the security intelligence data you already have on persons of interest, suspicious behavior and incidents, and the new information that organizations regularly acquire. Many security teams have access to years of data relating to an untold number of threats and threat actors but no practical means to analyze it for patterns and trends.

When this data lives in siloes, it forces protective intelligence teams to work in siloes too. This is an ineffective way to operate and can lead to vulnerabilities within an organization. Instead, organizations need to share that information. Sharing data across an organization helps improve the overall company process and encourages departments to work together for its safety and security.

For example, HR and security teams don’t typically interact on a day-to-day basis. However, organizational data from the HR department can be valuable to the security teams when tracking and monitoring a potential threat to the business, especially as it relates to workplace violence from employees. Departments that work together in this way will uncover synergies that ultimately save organizations time and money.

Sharing data on threats can also reduce inefficiencies and intelligence gaps resulting from security teams assessing and investigating threats independently rather than collaboratively. In sum, the optimal choice for improving operations and security efficiencies is a shared platform across several business units.

No single team, regardless of size, capability or dedication, can single-handedly resolve all possible threats on its own. In my experience, more often than not, if someone witnesses suspicious behavior, it’s likely that others have seen the same. Monitoring potential threats becomes far more useful when databasing, sharing and analyzing observation reports over time. Collaborative information sharing will positively impact organizations and allow for better data analysis and monitoring, creating a more accurate and holistic picture of relevant threats and incidents.

Privacy-Safe Data Collection: A Corporation’s Responsibility

But while use of big data can be incredibly useful to security teams to boost situational awareness, consumer privacy is still important even when protecting lives and physical assets. Companies need to reassess their data policies and simultaneously ensure their protective intelligence teams are strategically investing in security programs that have access to and can structure data in a way that safeguards the organization while also protecting privacy.

It’s important to note that there is a collective sentiment in the United States that data security is more elusive today than in the past. In a recent survey, participants were asked whether they think their personal data is less secure, more secure, or about the same as it was five years ago: 70% of adults say their personal data is less secure. Furthermore, 63% of Americans say they understand very little or nothing at all about the laws and regulations that are currently in place to protect their data privacy.

Almost every stakeholder within today’s enterprises, from general counsel to the C-suite to HR, is invested in ensuring the organization’s data collection is compliant and that they’re partnering with best-in-class data providers in the industry who are following the same guidelines. As the data grows, so does the potential risk. There must be a commitment for conducting business in a fair, lawful and transparent manner with all data being compliant with data protection laws and policies such as GDPR, HIPAA and FCRA.

Harnessing Technology to Overcome Fragmented Data

When harnessing data for security intelligence, it’s important to note how to use technology to the team’s benefit. Each protective intelligence program’s stored data has incredible potential to facilitate early identification of emerging threats, however, many organizations still lack a practical method for tapping into this data and, unfortunately, lose out on insights that can keep employees and businesses safer.

Taking advantage of physical security data is only possible when such data is collected consistently and made available to the team members who need it most. Organizations that integrate protective intelligence technology into their analytical data processes stand to gain further insight into potential threats and risk patterns.

It’s also essential that such technology allows for the implementation of assessment methodologies when prioritizing and acting on threats. It’s one thing to get notified of a threat proactively, but another to have a tool within the same platform that allows you to assess the reality of the threat and whether or not your organization should act on it.

While I do frequently wonder how the use of data in these ways would have changed my job 30 years ago, it’s exciting to see that, today, protective intelligence analysts and security practitioners are increasingly seeing the value in structuring and analyzing data proactively and efficiently to benefit their businesses and assist in eliminating risk.