HOW TO MITIGATE STAKEHOLDER BIASES IN RISK ASSESSMENT
It is common knowledge, or at least it should be, that the quality or integrity of the risk management plan depends on the quality of the risk identification and assessment processes that underpin it. Risk assessments is the primary input to the risk management process.
Therefore, no effort should be spared towards assuring the quality of the risk assessment process and output. It is therefore important to identify and eliminate, wherever possible, the factors that undermine its integrity. Stakeholder bias is one such factor.
The Project Management Institute defines a stakeholder as an individual, group or organization, that may affect, be affected by, or perceive itself to be affected by a decision, activity or outcome of a project. Stakeholder bias, in this case, refers to stakeholder tendency to overestimate or underestimate the likelihood of a risk event or its impact.
However, individual perception of the impact of a project outcome varies based on several factors. Such factors include:
Risk Appetite: Risk appetite is the level of risk that an organization is prepared to accept in pursuit of its objectives, and before action is deemed necessary to reduce the risk. The ISO 31000 risk management standard refers to risk appetite as the “Amount and type of risk that an organization is prepared to pursue, retain or take”.
Risk Appetite may be broadly grouped as follows:
- Averse: Avoidance of risk and uncertainty is a key organization objective. Here, you find a client who goes to great lengths to push risks to the contractor even when he is better placed to manage the risk. Experienced contractors can discern this even in the ITT package and decide how to respond. Inexperienced contractors ignore the signs and get their fingers burnt.
- Minimal: Preference for ultra-safe options that are low risk and only have a potential for limited reward.
- Cautious: Preference for safe options that have a low degree of risk and may only have limited potential for reward.
- Open: Willing to consider all potential options and choose the one most likely to result in successful delivery, while also providing an acceptable level of reward and value for money.
- Hungry: Eager to be innovative and to choose options offering potentially higher business rewards, despite greater inherent risk.
Taking the two extremes of the risk appetite continuum for example, we find the risk averse trying to avoid risks at all costs, and the risk hungry willing to take risks provided the reward is acceptable. The downside of both postures is that the risk averse pays money to transfer risks that do not materialize eventually, while the risk hungry may suffer losses because of being blinded by the potential for high reward.
Of course, we should expect a disparity in their valuation or assessment of risk. In such a case the estimate of the probability or impact of the risk might be greatly exaggerated or minimized. The Project team must find a way to filter out the bias.
Another factor that may introduce stakeholder bias is Proximity to impact of risk. This refers to the situation where one stakeholder is exposed to or bears a disproportionate impact of the risk compared to others. This would make him more sensitive to risk event than others. It may manifest in a tendency to exaggerate the probability and or impact of the risk. Much worse if he also happens to be risk averse.
The bottom line is that this situation introduces a lot of subjectivity into the process and is not likely to yield a sound risk register or plan. Therefore, steps should be taken to establish objectivity and eliminate stakeholder biases from the process.
Although the project team may have many options for doing this, I think employing a panel of subject matter experts, would be most effective. You may complain of the cost of such a venture. But they could be experts within the organization.
To be accepted as an experts the Project Management Institute (PMI), in its Project Management Body of Knowledge (PMBOK 6), specifies that such people must have specialized knowledge or training in in the following topics:
- Familiarity with the organization’s approach to managing risk, including enterprise risk management;
- Tailoring risk management to the specific needs of a project;
- Types of risk that are likely to be encountered on the project in the same area.
- Qualitative and quantitative risk analysis among many others.
The experts can be part of the risk workshops or review the final deliverable (risk register) of the risk workshop conducted by project stakeholders.
But in order to ensure that expert judgment is not biased, the Delphi method might be adopted and adapted as necessary.
Delphi is based on the principle that decisions from a structured group of individuals are more accurate than those from unstructured groups. The experts answer questionnaires in two or more rounds. After each round, a facilitator provides an anonymised summary of the experts’ judgment from the previous round as well as the reasons they provided for their judgments. Thus, experts are encouraged to revise their earlier answers considering the replies of other experts. It is believed that during this process the range of the answers will decrease, and the group will converge towards the “correct” answer
It is not unusual for all participants in the Delphi Method to remain anonymous. Their identity is not revealed, even after the completion of the final report. This prevents the authority, personality, or reputation of some participants from dominating others in the process. Arguably, it also frees participants from their personal biases, allows free expression of opinions, encourages open critique, and facilitates admission of errors when revising earlier judgments.
Because of the critical role risk management plays in successful project delivery and the need for high quality risk assessment to ensure the integrity of the risk management plan, the project team should spare no effort in eliminating stakeholder biases from the process. This can be done by employing expert judgment. In order to also eliminate expert judgement biases from the process, I recommend the adoption and adaptation of the Delphi method.
