Risk management

What is the challenge?

Risk management makes possible risks in the company transparent and aims to minimize them. Risk management encompasses complex processes for identifying, analyzing, qualitatively and quantitatively evaluating, assessing, communicating and managing business risks. However, to make these processes successful, companies have to process an enormous amount of dynamic information, internal specifications and external standards and legislation.

What data can help?

• Case-specific variables (probability, magnitude, controllability and vulnerability)
• Risk focus (own financial stability, external image)
• Internal key figures (sales development, return on sales, free credit lines, creditworthiness of customers, bid success rate, dependence on customers and suppliers, replacement of assets)
• External key figures (interest rates, currency developments, business climate index, number and content of press releases)
• Property risks (number of fire incidents and earthquakes)

How can companies use their data?

Data-based support for risk management optimizes the information basis of management decisions. The processing and analysis of data happens automatically and is thus less prone to errors. The human capabilities of analyzing and evaluating risks are thus significantly enhanced. Another benefit is the ability to use forecasts and predictions of risk situations as an early warning system. 

Where is this use of data already being applied?

Advisen offers consulting services in cyber risk management. Based on an extensive database, patterns are identified and risk analyses are driven. Companies can buy these insights to improve their decisions and minimize risks.

Chemical company BASF uses data to use resources sustainably and avoid environmental risks. It does this by analyzing weather data, plant health and soil condition data, and market prices.

Sporting goods manufacturer Adidas uses an advanced analytics team to provide data-driven support for management in making business decisions across all areas of the company and to avoid risks from bad decisions.

Insurance company Münchner Re uses historical data from claims settlements to better calculate the risk of an insurance policy. This also enables better calculation of premium levels and efficiency gains.

How does this use of data contribute to value creation?

When relevant data and methods are used in strategic management, decisions can be made in a more informed manner and risks can be minimized. Value creation changes directly in the improvement and acceleration of risk management processes and indirectly through improved management decisions, which can result in overall increased value creation in the long term. 

Sources: BASF (2017), Adidas (2017), Münchner Re (2018)