ERM and visual risk clusters
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In my previous columns, I proposed implementing enterprise risk management using a hierarchical structure of risk categories aligned with an organization's business model. I've been using "ERM knowledge warehouse" to describe this structure.
At the 2007 Risk & Insurance Management Society Inc.'s annual conference last April, a technology firm offered to build such a warehouse. That has now been done. This article applies a high-tech tool developed by Riskonnect to illustrate risks in a key initiative. The example is a product launch described in a December 2007 Harvard Business Review article.
We start with the risk structure. A visual risk cluster is a representation of a risk category and related subcategories. It shows risk relationships. As we add more risks, the picture can become quite confusing if we do not create a clear hierarchy of risk categories. The critical factor to retain clarity is to limit the number of risks at each level.
A new product or service can be a high-risk venture. In our example, we identify four risk categories:
Figure 1 shows these risks visually. Level 1 is the risk of the product launch. Level 2 has market, product, capital financing and intellectual property exposures. The risks can be color-coded from red (highest risk) to green (lowest).
We can drill down. Let's assign product risk to a risk owner who identifies categories that affect likely success (Figure 2):
Product development. Do our current capabilities fully apply, require significant new learning or not apply at all?
Technical competency. Do we have technological skills that are fully, partly or not at all applicable?
Delivery capability. Is our current distribution system suitable, partly suitable or inappropriate for handling the product?
Support system. Do we have a system currently or partly in place or do we need a totally new system to support the product?
Quality standards. Is the level of expected quality identical to, related to, or different from our current products?
We now have a clear picture of the product risk category in a product launch. We can perform the same analysis for market, intellectual property, and capital financing risks. We can also drill down with all the exposures (Fig. 3).
When we get to Level 3, we see an immediate problem as a result of the interconnectivity of risk. If we go further, we have clutter. The challenge is to allow filtering of relationships among complex risks. From our research, we are learning certain techniques that allow technology to help us avoid clutter as we view exposure linkages:
When we approach risk with hierarchical categories aligned with the business model and when we support ERM with the right technology, we can create visual risk clusters that provide a clearer and faster understanding of risk relationships. In future articles, I will discuss various other aspects of risk mapping, including tagging risks, creating levels of separation, heat profiles, metrics, color-coding and the management of mitigation activities.
