Do people struggle to make decisions? Of course. We all do. Everyone makes hundreds of decisions daily, and with that many choices, there’s bound to be a bit of struggle along the way. So, which decisions do people struggle with the most? How often do people find themselves stuck in the decision making process? In this world of technology, innovation, and advanced systems, what kind of tools or techniques do people use to assist them in decision making? What decision making issues brought you here? 

In this report, we’ll explore the feedback we received through performing live questionnaires pointed at higher-level decision making. We analyzed the tools, systems, and processes people and organizations are using, how they’re going about the process with these resources, and what successes and downfalls they have from them. It’s clear that decisions are being assisted with these tools and techniques — so the question becomes, are there better options? We believe from this research that we have a tool, rooted in deep mathematical science, that will optimize decisions and priorities – expanding on or replacing tools that are already in use.

Several years ago, I had difficulty gaining influence with an employer to develop some tools I believed were fundamental to the growth of our organization.

After months of trying to make a positive impact, it was evident that I would have to use a different method to show them my thoughts. So, I built a decision making and prioritizing tool based on some well researched, but under-utilized, mathematical principles. After using the tool myself and having my employer use it separately, we came to the same conclusion on how to proceed toward our goal. 

After that, the tool sat in my back pocket until I found the right opportunity to build it into something greater. I brought it up with an extremely skilled and bright friend of mine who was incredibly interested in the application’s potential. We determined that we would build this tool out for ourselves, if nothing else, and use start-up and innovation engineering techniques to test viability for other users.

We started listing assumptions related to the concept of decision making and utilizing decision making tools. We ranked them according to risk level, and then we built questions to test those assumptions with phone-driven market research. To preserve integrity, we avoided creating leading questions (as much as possible) and focused on making them open-ended. This is when we reached out to ask for input and referrals. In almost all cases, we expressed our interest in researching decision making and prioritizing, leaving out that there was a potential product in the works.

 We built a tool to record interviews in note format, turning qualitative opinions into usable quantitative data. Our goal was to sort each response into high-level categories that we could tabulate for or against our hypotheses. We also collected demographic data, ranging from age and gender to position and experience. After around 50 interviews, we analyzed the statistics for a predefined go/no-go test to proceed, pivot, or perish the project.

Thrilled with the results, we went forward with our plan for a second round of research. We changed our method for data collection to an online questionnaire that would automatically systematize the results and provide analytical data. Then, to gain deeper insight into the validity of our assumptions, we updated the questions to test more refined assumptions. While the questionnaire continued to gather data, we started to build out the tool.

Assumption 1

People struggle to make difficult decisions/priorities.

Question 1

“What kind of decisions, or priorities, are the most difficult to make for you and/or your team?” This question was intended to determine the percentage of our participants that struggle to make difficult decisions or priorities.

Assumption 2

People will use a decision making tool.

Question 2

“What kind of tools, systems, or processes are you, or your team, using/utilizing to make big decisions or to prioritize?”

This question was intended to give us insight into the methods that people currently use in order to project whether or not they would use a tool to make decisions/priorities

Assumption 3

A decision making tool would be trusted (for validity and that it isn’t being used nefariously).

Question 3

This hypothesis was tested with a combination of three separate questions:

A) “What kind of tools, systems, or processes are you, or your team, using/utilizing to make big decisions or to prioritize?” 

We only wanted to count data points from participants who indicated that they were currently using some sort of tool or process for decision making.

B) “What are some of the benefits of these?” 

We wanted to test how many people got positive, trust-related benefits from using a tool to make decisions.

C) “What are some of the issues you’ve had with these?” 

We wanted to know how many people had negative experiences with the tool(s) they were using in the context of trust.

We wanted to know what strategies/tools people used to aid in making decisions and determining priorities, and then we wanted to examine the trust people have in those tools, systems, and processes. We only counted participants whose answer to question A indicated that they currently used tools to make decisions.  Then, we further categorized responses according to whether question B indicated many benefits AND question C indicated few or minor issues as supporting our hypothesis. Conversely, we categorized responses to question B indicating few benefits AND question C indicating many issues as disproving our hypothesis. All other responses were added to a “maybe” category, as they could neither support nor disprove this hypothesis.

Assumption 4

People make bad decisions.

Question 4

“Can you tell me about a time when you made a bad decision and how it affected you/your team?”. 

We hoped to keep questions as open as possible, but we included this in order to gather more information about the kinds of decision making that people struggle with.

Result 4

This question was thrown out as all respondents (but one) reported to have made bad decisions. This indicated that the question was too biased and of little use.  We gathered a lot of great information about the types of difficult decisions people make, but unfortunately, we do not believe the context could prove or disprove our hypothesis.

Assumption 5

Initially we wanted to test whether “people will use a decision making tool outside of a work setting”.

Instead, our testing was geared more towards the hypothesis that, “in their personal life, people struggle most with making financial and/or big life decisions”.

Question 5

“What kind of decisions, or priorities, are the most difficult to make in your personal life?”

We wanted to know if people may be interested in using a tool outside of a professional setting.

Assumption 6

People struggle to make emotional decisions.

Question 6

“What kind of decisions, or priorities, are the most difficult to make for you and/or your team?”

This is the same question used to test hypothesis 1, but was analyzed separately according to categories assigned to each individual response.

We are still collecting data from the automated questionnaire, so the results are not shown here. Instead, these are the updated demographic fields which respondents enter themselves. Note the significant difference in requesting “Decision Type(s)” rather than “Title” for each of the respondents. Additionally, the “Industry” category was standardized with US government codes.

The results presented here, gained through interviews and the testing of our assumptions, gave us data-driven support to move forward with building our application. It also gave us insight as to what issues people highly value and how they consider different situations. For instance, as an aside hypothesis, we assumed that people would express monetary decisions as being the most difficult. In fact, we found that the majority of responders struggled most with work-life balance and hire/fire situations – both of which take into consideration an emotional aspect, which our tool is great at capturing and filtering. This may be a causal effect from the timing of these interviews, which coincided with the peak of the Covid-19 pandemic. However, we believe that difficult situations intensify and amplify people’s values and personalities, so we believe in the validity of the results.

More research is needed to clearly define the demographic and decision-making level/industry of a target audience for this type of tool to be most effective. However, it appears that tools are already used extensively in different capacities, and our research shows great potential for our targeted tool to revolutionize all types of industries. 

We will continue to build our tool, gather data for more research, and present you with cutting edge technology to ensure you’re making the most informed decisions.