Part 1: Utility analysis
We have all been in a situation where we need to take a decision but are unsure what to do. Maybe you are developing a new product and find it difficult to decide which of the alternative compounds is best. According to Munich-based psychologist and neuroscientist Ernst Pöppel, we all take an average of 20,000 decisions a day, many of them subconsciously within fractions of a second. The more complex and more important a decision, the more time and energy we invest in it. Starting with this issue of the Kuraray online magazine, we will be looking at some tools that could help you and your team take decisions faster and better. The first article in this series looks at utility analysis.
The risk of an uncertain future
Why do we find some decisions harder than others? Legendary investor Warren Buffet once said: “If you don’t make mistakes, you can’t make decisions.” That hits the nail on the head, because every decision we make relates to future developments – and the future can rarely be predicted reliably. Consequently, every decision involves uncertainty. To minimize our risks, we therefore need to get the best possible picture of what might happen in the future. To do that, we use our knowledge and experience and gather relevant information. For example, if you are trying to choose the right plastics, you might read specialist journals, consult your suppliers, and consider the new materials your competitors are using.
“When decisions relate to innovations, it’s often difficult to establish a sound factual basis,” says Johanna Krauthauf, Head of Business Transformation & Marketing at Kuraray. “Let me give you an example. Every year, Kuraray’s management provides a budget for innovative projects. Colleagues can submit ideas and may be invited to present them. So many good ideas are presented that deciding which to choose is often really difficult – not least because many factors are difficult to assess or cannot be quantified. A utility analysis can be helpful in such situations.”
A bridge between reason and intuition
A utility analysis is particularly suitable for highly complex decisions. One benefit is that it is not based solely on quantitative data; it also includes soft (qualitative) factors, ranging from individual values to intuition and gut feeling. Imagine your company has to two decide between two equal innovation projects. The first step in a utility analysis is defining criteria, for example, whether the project is a good fit with your company’s long-term goals or what specific benefits it offers you and your customers. In the next step, you weight the criteria by relevance. That provides a clear outcome, which – ideally – helps you take a decision. The box summarizes the steps in a utility analysis.
“What our team finds useful about this tool is that we can include both hard facts and soft factors such as intuition,” says Daniela Niemeyer, Specialist Organizational Development. “However, that is also a challenge, for example, when we work with other teams in larger groups. Selecting and weighting the criteria is very subjective, which makes it difficult to define a uniform evaluation that everyone in the group finds acceptable.”
Steps in a utility analysis:
A utility analysis is a tool that facilitates complex decisions where not much reliable data is available. You can use a utility analysis, for example, to help you select an innovation project to drive forward your company:
1. What is the objective? We want to strengthen sustainability in our company.
2. What decisions have to be taken? We have four innovation projects that could help drive forward sustainability in the company, but our budget only allows us to support one of them.
3. Define the criteria for selecting one of the options:
In this step, you define the quantitative, qualitative, and knock-out criteria influencing the decision:
- Quantitative criteria: The innovation project should improve our carbon footprint by 10 percent.
- Qualitative criteria: The innovation project should be good for our image.
- Knock-out criteria: The innovation project must not reduce production capacity.
4. Create a table: Select the five most important criteria.
Create a column for each criterion and a row for each of innovation project. Then perform the following four steps:
- Evaluate the extent to which each project meets each criterion on a scale of one to ten (utility factor).
- Weight each criterion by allocating 100 percentage points among the criteria. Attributes that are particularly important for the selection of the project are given more points than those that are less important.
- Multiply the utility factor by the weighting of each criterion
- Add together the scores for each innovation project If you have selected the criteria well, the outcome will give a clear indication of which project should be given preference in the decision-making process.