Enterprise Risk Management is a method used to identify, assess, and manage an organization’s risks. It is typically a top-down strategy, helping leaders initiate a unified perspective on potential issues and hazards, and establish mitigation tactics to avoid disruptions impacting the organization’s goals and operations.
Three traditional tools used to lay the foundation for enterprise risk management include risk assessments, risk matrices, and qualitative analysis. Each provides different pieces of information and insight that help shape the overall enterprise risk management plan.
- Risk assessments: As the phrase implies, the risk assessment portion of enterprise risk management represents the time taken to review the organization’s processes and activities and identifies potential risks and hazards, from physical risk to cyber risk.
- Risk matrices: This tool takes the information gleaned during the risk assessment phase and plots it out visually to highlight two key factors – the likelihood of projected risks and the potential impact that would result.
- Qualitative analysis: This is the information revealed from the risk matrix. While most often the risks are revealed during this process, it is also possible that previously unidentified opportunities are uncovered as well. With this information, enterprise risk management can really begin.
These three tactics are used today, but instead of relying simply on internal teams to manually cull and input all of this information, technology is available to assist – speeding up the process and often illuminating undetected risks and solutions. This technology is known as augmented analytics and assists in risk reduction.
Manual data sorting may have been sufficient two decades ago, but with the proliferation of open source data, it is now impossible to stay on top of all of the world’s information without the use of technology. And thanks to augmented analytics, which leverages advanced technologies like machine learning (ML), artificial intelligence (AI), and natural language processing (NLP), security teams don’t have to. Augmented data analytics is revolutionizing enterprise risk management – providing actionable insights, improved decision-making, and enhanced overall risk management resilience at speeds that data scientists simply cannot replicate using manual tactics.
Understanding Augmented Analytics
The Definition. The term “augmented analytics” was first used in a Gartner research paper in 2017. Since that time it has become the default approach leveraged by many organizations and security teams, as relying solely on manual data review and compilation simply isn’t possible. With the amount of data shared via open source networks, and the speed in which geopolitical environments experience change, leveraging technology is a must. Augmented analytics makes it possible to automate data preparation, insight generation, and explanation. What would take a human days to review will take a machine mere minutes. The value of leveraging machines and technology is abundantly clear.
The Technologies. Technology tools behind augmented analytics can manage data preparation, including automatic cleaning, organizing, and structuring of data for the analysts to review. The analysts can then apply ML to these data, a technology that uses algorithms to detect patterns and predict outcomes, and even suggest potential actions. Analysts are an integral part of ensuring that ML is used successfully, as they monitor the technology and ensure its “learning” remains on track and relevant to the organization. Elevating the effectiveness of ML is NLP, which enables machines to interpret, understand, and generate human language – making insights more accessible.
The Application. An organization’s use of augmented analytics is not a means to dismiss traditional business intelligence (BI), but is instead a useful evolution – ensuring that data is accrued and processed at speeds dictated by today’s ever-changing geopolitical environments. BI often requires manual data analysis and interpretation. The time needed for these activities often simply does not exist, making augmented analytics a worthy option as it automates these processes while also providing deeper insights. Augmented analytics goes beyond simple reporting by offering predictive and prescriptive analytics as well.
You’ll be hard-pressed to find an industry not leveraging augmented analytics. Take manufacturing, for example. By using augmented analytics, leaders can obtain a real-time perspective on production capabilities, space availability in warehouses, and other valuable pieces of information that inform better decision-making. Someone in the financial industry may use augmented analytics to fine-tune their forecasting. In this scenario, augmented analytics would be used to review historical data to better identify factors and risks that would impact future revenue, expenses, cash flow, and profitability. These are just two examples of how augmented analytics are leveraged; however, it’s being used across the board in healthcare, retail, and much more to improve decision-making, optimize operations, and enhance customer experiences.
The Intersection of Enterprise Risk Management and Augmented Analytics
Augmented analytics is a valuable tool for enterprise risk management. It quickly and accurately analyzes large datasets to identify emerging risks, trends, and patterns that may be missed with traditional methods. Organizations can use augmented analytics to create more accurate and dynamic risk management models.
Dynamic risk management models offer simulation techniques that allow for testing various scenarios and understanding potential outcomes. Augmented analytics can also be used to monitor key risk management indicators (KRIs) and early warning signals. Once KPIs are established, augmented analytics can be used to continuously monitor these, providing real-time insights and allowing organizations to proactively manage risks.
Reporting also benefits from the use of augmented analytics, allowing detailed reports – which include visuals and charts, and natural language summaries – to be created at the push of a button. With the ability to produce streamlined reports in mere minutes, it’s possible to keep leaders and all relevant stakeholders throughout the business informed on risk management strategies, risk events, proactive plans, and mitigation efforts.
Augmented Analytics at Work: A Real World Case Study
To showcase the power of augmented analytics, let’s review how one global organization is using the technology to help manage their security operations. This organization is involved in the aviation industry, offering comprehensive maintenance, repair, and operation (MRO) services to a diverse client base, including commercial airlines, private jet operations, and military aviation units. With operations in more than 33 countries involving more than 230 airport locations, the scope of the organization’s security team to remain informed on risk management is extremely large.
Along with a diverse range of physical locations to monitor, the team also faces a variety of security challenges. The organization is responsible for aircraft charter services, aircraft fleet management, and maintenance, which necessitates the handling of sensitive information and the management of clients’ critical infrastructure. The global nature of the organization’s operations exposes the company to a wide range of geopolitical, regulatory, and environmental threats that could disrupt its business continuity. The organization needs to know where they can safely land their aircraft, and ensure the security of their travelers and personnel at their destinations. Managing risk at this organization is a significant task, whether through enterprise or traditional risk management practices. One that a team of skilled experts cannot manage alone.
The leadership team decided a technology partner was needed and identified a comprehensive threat intelligence solution that leverages cutting-edge augmented analytics and supporting technology to provide timely, accurate, and actionable insights. With the support of their chosen vendor, Seerist, the organization has been able to achieve all of their risk management goals.
Using Seerist’s augmented analytics solution, the organization is able to pre-package reports for clients and pilots prior to departure. Seerist also enables the team to enhance bespoke security briefings that provide clients and pilots with information related to any potential risk management issues they might encounter when traveling to new locations. This is a significant differentiator for the company and the value of services it provides to clients. Thanks to Seerist’s intuitive interface and powerful analytical tools, the organization is now able to accomplish:
- Asset Tracking – The Seerist client is now tracking more than 75,000 assets and can see all locations on a map to easily monitor any potential threat events that could impact operations or people’s safety.
- Threat Alerting and Identification – Seerist’s advanced augmented analytics, including data aggregation and ML algorithms, allow the organization to quickly identify and prioritize a wide range of risks and security threats. They can build alerts on each of their assets to ensure the team doesn’t miss a potential threat.
- Threat Analysis – Via comprehensive threat reports and customizable dashboards, the organization has in-depth analysis of the identified threats, including potential impact, likelihood of occurrence, and recommended mitigation strategies, at the push of a button. Their security team can spend time strategizing and implementing safety measures instead of building these reports.
- Threat Monitoring – Real-time monitoring capabilities help the organization stay informed on occurring and emerging threats, empowering the team with the information needed to adjust their risk management posture and incident response plans.
- Collaboration and Reporting – With intuitive collaboration tools and reporting features, the organization can easily disperse valuable information to key stakeholders, improving their overall risk management strategies.
These capabilities are available to any organization using Seerist. Organizations benefit greatly from augmented analytics. Their internal bandwidth increases, and organizational leaders and security experts can spend valuable time creating and implementing safety measures instead of monitoring the millions of datasets required for global risk management.
Trends and Considerations
What does the future look like? AI will undoubtedly have a prominent role in augmenting enterprise risk management, making processes even more intuitive, user-friendly, and efficient, along with delivering more sophisticated risk management insights. While AI won’t eliminate widespread problems such as cyber and physical threats, and global instability, it can help leaders stay ahead of these issues by delivering rich and robust information quickly on the most significant risks. And this has massive benefits. Leaders can make more informed decisions through strategic planning. Security teams can develop more specific mitigation tactics. It’s a true win-win for organizations and their mission to keep their people, operations, and assets out of harm’s way.
A chief risk officer plays a key role in overseeing and implementing such technologies within an organization, ensuring that they align with strategic risk management goals. It will also be paramount for organizations to ensure their tools aren’t tracking misinformation and disinformation, which, unmonitored, could become a greater issue than at present. For this reason, it is critical that humans and machines work in tandem.
Making Room for Augmented Analytics In Your Organization
Looking to elevate your security plans and mitigation strategies? Leveraging augmented analytics will enhance the enterprise risk management process by providing actionable insights, improving decision-making, and boosting risk management resilience. But technology alone is not enough. Having a seasoned security team and intelligence analysts will continue to be essential; these experts will bring insight and perspectives to data that machines simply cannot. Additionally, the effectiveness of AI is dependent on the quality of the data it is reviewing and using. This is another instance where analysts remain critical, along with governance practices.
Along with support from security experts, technology will continue to need high-quality data to do its job well. Organizations must remain diligent in ensuring that there are regulations in place to ensure data quality and integrity, and to fight against misinformation and disinformation, which, unmonitored, could become a greater issue than at present.
Managing all elements of risk management and risk management processes can be an impossible task. Organizations that attempt to handle activities internally often find teams overwhelmed and underperforming in important areas. Partnering with an augmented analytics expert is a key way to arm security teams with the intelligence they need and ensure internal experts are spending their valuable time in protecting people, assets, and operations in an increasingly complex risk management environment.
If you’re looking for a new partner, would like more information on how augmented analytics could help your business, or would like to trial a solution, please reach out to info@Seerist.com today.
