Data Insights Creating Better Risk Management Decisions

Juliet McKane
June 22, 2020

There will always be risk!

Risk management is never about eliminating risks. In every activity that a business undertakes, they are exposed to risk therefore good risk management seeks to look for as much information as possible whilst breaking risk down into stages.

The broader the pool of information available to decision makers, the greater chance they have of making sound risk assessments. However, information can be overwhelming and subjective. Data, and the insights provided by analytics, empower the mitigation of risk at every stage.

The process of understanding, analysing and actioning information is well understood by risk specialists and is reflected in decision making models used across the emergency services and industry. Critical to this model’s success is having actionable insight to draw on. To this end, Shepherd’s analytical insight supports and informs each stage of the property risk management decision making process.

Learning from Data Analytics

Through combined levels of rich analytical insight, the Shepherd brain is continually learning how a property and its systems perform. Using trend analysis, AI and machine learning this meaningful insight builds a comprehensive picture. This intelligence combined with reporting and real-time alerting provides the ability to adapt accordingly therefore creating a continuous intelligent flow of organisational learning.

Supporting Good Decision Making

The key to good decision making is the quality and quantity of information upon which a decision is made. This is where data analytical platforms such as Shepherd offer an extraordinary opportunity to have comprehensive, consolidated real-time information at the finger tips of risk managers. Similarly, robust risk management policies will always seek to empower decision making at the correct level.

Strategic Approach

Once risks that need managing have been identified, a strategy should be set that:

  1. Explains the level of risk appetite within an organisation
  2. Identifies the criticality of assets/people activity
  3. Sets out the overarching principles that will guide action

Reactive decisions should be taken by those closest to the risk but be informed with the overarching strategy and objectives. Again, an analytical platform-based approach re-enforces this. There is the ability to pre-set risk models according to a site owner’s risk appetite as well as assign asset criticality to give an overview of the risk profile. Alerts are then activated based on these parameters. Alerts are received by those closest to the risk and who can take action.

Good risk management is anchored with sound, informed, timely and compliant decisions. Data driven insights help provide those anchors.

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