Traditional risk management reporting is a cumbersome, time-consuming process. Numbers are entered into a spreadsheet, those spreadsheets are combined with others from different sources, and – eventually – a report gets generated. Corresponding pie charts or bar graphs might be created, which are then dutifully copied into a presentation and sent to various departments for review or approval. Next month, the process starts all over again as risk data changes and custom report requests come in.
Data discovery is the key to breaking free of the predefined drill paths, preconfigured dashboards, and other limitations of traditional reporting and business intelligence tools. This easy-to-use, interactive risk management analytical tool pulls and aggregates risk data from any number of sources in a way that makes complex data understandable and – more important – actionable.
A Different Path to Better Analysis
With data discovery, you can follow your own path into risk data analysis and keep digging deeper to find answers to critical questions about why something happened. Built-in collaboration capabilities of data discovery also give everyone quicker access to the risk data, and smart visualization features increase understanding across the organization – all of which help lower critical response times.
Data discovery will help you go beyond the numbers on the page and tell the true story of your organization’s risk environment. You will start to see trends and patterns in your risk ecosystem in areas such as overall spend, number and frequency of incidents, organizational response times, claims by location, and more. And that’s when true business transformation can begin.
Unlock the Insights
The deeper, more meaningful insights that emerge through data discovery can drive organizational change with improved efficiency, heightened shared knowledge, and more effective action. You’ll end up reducing your risk – and ultimately increasing your profitability.
The risk data you need is already there. You just have to unlock it.