Risk is something every organization needs to pay close attention to, and it should inform all business decisions. This blog lays out clear guidelines to help organizations more effectively balance risk and reward to make better risk-based decisions.
Organizations and their employees are involved in making numerous decisions daily. Some are major, such as deciding on strategy or whether to purchase a new system, while many are small, such as whether to take the stairs or elevator, or where to place your coffee on your desk.
The aggregate outcome of all of these decisions is what determines the success or failure of the organization.
Making better, more-informed decisions, must therefore optimize the value of the organization. We can attempt to program machines to make decisions, but the quality of that decision-making is still dependent on the logic programmed by a human. Humans make decisions in more complex and, often, less logical ways.
Much is written on human decision-making, covering the drivers of things such as emotion, fear, perception, and anchored thinking. I will not focus on these but instead focus on the more logical elements of reward and risk that should be factored into all good decisions.
Optimal decisions involve maximizing the reward (reward is taken to mean net reward—being the net of both positive and negative impact) from the decision over the period that the decision impacts the organization (its life).
To better understand this, we need to:
Define what we mean by reward
Determine how reward is affected over the whole of life of the decision and how we can measure reward
Determine how we can assess whole of life reward at the beginning of the decision’s life.
What is reward?
Reward should be measured against the objectives that the decision is aiming to achieve. This may include financial and non-financial, such as customer service/satisfaction, environmental, social, employee well-being, and so on.
This gives rise to the first difficulty: how do we measure non-financial reward? The accounting profession has struggled with this and, as a result, has focused primarily on financial reward.
More recently, developments in integrated reporting have tried to address this by considering non-financial impacts of an organization as well as financial.
Until we become more capable of measuring non-financial impacts, we must do our best with what we have, which is a combination of quantitative and qualitative measures.
The second issue is determining how reward is affected over the life of a decision. We can split the reward of a decision into three parts.
Known reward: This is the income and expense that is known with reasonable certainty. When purchasing a new machine, this would include the capital cost and any known servicing costs, etc.
Estimated reward: This is the estimated future expense and income, which is not certain. This would include revenue generated from the machine and related running costs that would be dependent on output volume. We usually estimate this using a budget.
The impact of uncertainty on reward: This is the effect of future potential events that are not known with certainty and could have an impact on the budgeted reward. This would include unscheduled outages, unforeseen breakages, and other factors affecting the machine such as power failure, fire, etc. These are our risks. Measuring the risk is not easy. Conceptually, we need to consider the range of risks in the decision, assess their probability and impact, and apply probability theory and discounting to give a net present value of risk.
We then need to aggregate three parts to determine a whole of life reward to decide whether the decision is worthwhile and/or optimal.
We generally refer to items 1 and 2 above as “reward” and item 3 as “risk.” Whole of life decision-making is therefore more commonly known as risk/reward decision-making. This brings us to determining how best we can make risk/reward decisions.