5 steps to effective enterprise risk management

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There are a number of ways in which companies can transform basic enterprise risk management to risk-based decision support that adds real value to a business.

Many companies view their enterprise risk management initiatives as languishing and ineffective, largely because most are merely complying with regulations rather than finding the actual drivers of risk and leveraging that insight to benefit the business, an Accenture report has claimed.

It suggested that in some cases, executives believe risk management increases the internal business burden, slowing them down and wasting corporate resources on an initiative that is not adding value.

Typically, companies that are dissatisfied with their enterprise risk management have hit one or more of five barriers: a company may be stuck in risk assessment; risk management is viewed as an “extra” rather than an integral part of the business thought process; or leadership is not sure how they are supposed to make use of risk management.

Other barriers might be reporting systems which do not produce the right information in a timely way to provide direct decision support; or the fact that risk management leadership does not have a clear view of the value the capability can add, and fails to deliver a clear message on how it will tangibly impact profit and loss.

The report, Enterprise Risk Management and the New Market Realities, listed five points to help begin the transformation from basic enterprise risk management to risk-based decision support that adds real value to a business/

1. Break out of the value fog. Define the value you expect your enterprise risk management efforts to yield in the organisation and hold the program accountable for getting there. Even the simplest of these efforts should be adding value by supporting risk-based decision making (measured by business results), increased identification of opportunities and enhanced strategic planning. For greater value, the program might be targeting predictive analytics and better leveraging of the company’s risk-bearing capacity to fuel growth and profitability.

2. Establish clear risk governance structures. A logical governance structure, with its clear delegation of authority, makes it possible to see how decision making flows in the organisation and to track what decisions are being made at different points. This increased visibility supports a systemic view of risk. With that, the company can see what is happening in all areas of the enterprise and make linkages that lead to value-adding decisions. Governance, in this way, is an important enabler and supporter of the risk program.

3. Support your risk efforts with timely, insightful and readily accessible reports and information flows. This is a common failure point in many companies. The problem is not a lack of reporting but rather a lack of timely, focused and relevant reporting. The company’s reporting system should feed the right information at the right time to the right decision makers. Consistent and timely reporting needs to be put in place to include metrics, not just on action taken, but also on their effectiveness and what comes next.

4. Ensure that you have the right analytics in place. There is no shortage of powerful, analytical risk management tools and techniques available to support decision making by the company. The question is, are these tools and techniques actually being used at the right time and place to yield insightful decision support? If not, the reason often gets back to the company’s underestimation of what enterprise risk management can do for the business and how enhanced predictive analytics can add value.

5. Be bold. First, define the value that enterprise risk management can bring to the business. This is the moment to go to the executive team and present clearly and emphatically the reasons why the program is taking a bold path forward and what specific value it is expected to deliver. Second, challenge the value and effectiveness of executive decisions. If they are being made without strong analytics support, those decisions are not going to be as good as they need to be.

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