What you need to know about the decision-making process

Decision-making is how we navigate the world and make choices, whether we’re looking for a new job or deciding on dinner. In business, it’s an adaptable project management tool that uses linear or non-linear procedures to overcome challenges.

Most organizations need to strengthen one of the core business fundamentals: The ability to analyze a problem and reach an adequate resolution.

Let’s get into everything you need to know about decision making, including best practices.

A decision-making process is a strategy for analyzing a problem, comparing your options, and deciding on the best solution. 

It's essential for everyone in business, from the C-suite to managers and their teams.

The most tried-and-true decision-making processes use seven steps. Let’s check them out.

While decision-making processes vary, almost all involve seven key principles. 

Here’s a simple step-by-step process:

1. Define the decision

Clarify your goals. Ensure everyone understands the issue, your preferred outcome, and how to gauge success.

2. Info gathering

Fact-finding is next. If you’re using self-organizing, integration-friendly research tools, you may already have key information on hand. 

If not, you'll need to gather information to better understand the problem and what a good solution entails.

3. Identify your choices

Summon your creative problem-solving skills and compile a list of the likeliest solutions. What options are available based on the data?

4. Weigh your evidence

Next, thoroughly analyze the options you've compiled. Run each possibility through a cost-benefit analysis, calculate the odds of success, and estimate short- and long-term impacts.

A SWOT (strengths, weaknesses, opportunities, and threats) analysis can help you see the problem at a higher level.

5. Make your choice

Key decision-makers must decide once the critical data, analyses, and options are on the table.

6. Take action

Putting the final decision into action requires a plan for allocating tasks and organizing company resources. Ensure the plan also addresses how stakeholders will monitor progress.

7. Review your decision

The value of a good decision lives on, even after resolving the initial problem. Was the decision successful? Did the issue stay resolved? Will you need to make similar decisions in the future?

Consider these questions even after the pressure subsides. Use the success metrics from step one to adjust your implementation plan or the decision if necessary.

What are the advantages of involving others in the decision-making process?

Decision-making often requires hard work from separate parties, all wielding their skill sets and resources. 

Though it's certainly possible to follow a decision-making process alone, working as a team carries tremendous benefits:

• Combines a greater share of resources

• Raises awareness of a problem

• Shortens research time

• Expands your range of options

• Develops more ideas

• Creates consensus and improves collaboration

Business is inherently social—even entrepreneurs must frequently defer to their customers.

Analyzing customer data is one of the most important types of research for product developers and countless other roles. 

A comprehensive understanding of your customers’ wants, needs, and pain points is essential to frame almost any decision-making process.

Some of the most reliable and widely used customer analysis tools include:

Customer journey maps

All customers go through a unique personal decision-making process when making purchasing decisions. From initial awareness of a problem to final vendor comparison, customer journey maps help researchers adapt their decisions to the customer's process.

Empathy maps

An empathy map displays a team's knowledge of different end-users to reveal insights into their needs. It aids decision-making by clarifying what is most important to the customer base.

User personas

The user persona is useful for distilling research into one or several models representing your ideal customer. While purely fictional, a data-backed user persona can ensure you make the right decisions for your customers.

The decision-making process can create extra challenges, such as:

• Disruption of normal business activities

• Increased time pressures

• Gaps in research or inconclusive data

• Difficulty achieving buy-in

• Disagreement and infighting

Ironically, the most difficult decision-making challenge can be determining the exact problem you need to solve.

That's partly because different problems evoke two distinct psychological patterns in response to problem-solving.

What are the two types of decisions?

A study from the January 2016 issue of the Journal of Experimental Psychology categorized decision-making into two broad categories:

1. Analytic problem-solving

2. Insight problem-solving

Analytical decision-making

Analytical problem-solving entails a sequence of steps progressively leading to a resolution. It challenges participants to track various subtasks while keeping sight of the main goal.

This type of mental work often requires long stretches of undivided attention and high demands on working memory. It also relies heavily on data and incremental analysis.

Complex problems usually require analytical decision-making and can easily consume a team's attention. At its worst, a purely analytical mindset prevents novel, outside-the-box thinking.

Insight problem-solving

Insight-based problem-solving occurs spontaneously, even arising in defiance of a step-by-step process. 

Reflecting on a problem in a new way leads to outside-the-box thinking that can lead to novel solutions. 

Still, any concerted attempt at decision-making requires structured effort. What differentiates analytical and insight-based approaches is whether the decision-makers’ efforts use an existing structure or modify it as the process unfolds.

The takeaway is to remain open to adapting your decision-making process, but don't throw it out if you reach an impasse. Friction may reveal flaws that help decision-makers see the issue in a different light.

Most decision-making must work with limitations, which you can use to model an effective process.

When to use decision-making models

A decision-making model is appropriate when generic decision-making efforts create more difficulty than solutions. 

Times to use a decision-making model include:

• Inability to clarify a problem or the type of decision required

• Difficulty prioritizing options

• Communication breakdowns

• Process conflicts that inhibit action

• Uncertainty over democratizing research functions

No decision-making model is best—until a novel, unexpected problem arises. Sometimes, you need confidence in how you’re making decisions to come to the most effective solution.

The following examples of decision-making models may be better for different types of problems, time constraints, and the team's capabilities:

Rational decision-making

The quintessential step-by-step approach to decision-making is best for analytical problem-solving. Rational decision-making involves a linear progression of tasks and is largely prescriptive. 

It also depends on continuous logical reasoning and enough time for frequent meetings and thorough analysis.

Intuitive decision-making

Intuitive decision-making may be the best choice when you lack structure or time. It’s also ideal when decision-makers have a history of sound judgment. Some teams do well with a looser approach. 

While formal structure may be lacking, an intuitive decision-making model usually reveals some hidden pattern below the surface.

Creative decision-making

What happens if a challenge is wholly novel? The answer is to tap into your creative reservoir because nothing but inventiveness will do.

This doesn't prevent you from researching other companies’ solutions to similar challenges, but it primarily hinges on creating a unique solution. 

Creative decision-making requires flexible thinking and a blend of analytic and insight decision-making.

Recognition-primed decision-making

At its core, recognition-primed decision-making has two fundamentals: Assess your problem and compare it to similar challenges you've experienced. It's best for issues you have a wealth of knowledge in.

Like the intuitive decision-making model, the recognition-primed model is generally for fast-paced scenarios. However, its principles are useful for any issue you've effectively dealt with before.

With enough bandwidth and resources, you can even run parallel decision-making models and compare their findings.

No one is born a great decision-maker. Depending on your experience and talents, any of the following may be just the right food for thought on your journey to becoming a master decision-maker. 

Here are 10 tips to improve your decision making. 

Understand your goals

Only you know what you truly want. What works for one company might not work for yours, so ensure your solution truly fits your problem. Choosing goals is key to ensuring you don’t settle for a decision that misses the mark.

Evaluate the impacts of your decisions

Continual improvement depends on routine self-evaluation and putting these efforts to the test. Are your solutions successful? Or do you need to tighten up your decision-making process?

Eliminate the downsides

While acknowledging disappointment is necessary, use setbacks for a better approach going forward. Once you’ve made a mistake, learn from it and use this knowledge to craft an improved decision-making process. 

Compare timeframes

Each decision-making process or model unfolds along a timeline. If you need a fast decision, it might be better to work with intuitive decision-making rather than a drawn-out process.

Be open to new solutions

You probably won’t arrive at a solution with the same mindset as when the problem arose. Keeping an open mind can help you discover novel solutions. 

Use data to evaluate opinions

The best business decisions come from data, especially when they involve customers. However, comparing a high volume of survey responses can be very time-consuming. That’s where a dedicated customer insights platform packed with analysis automation tools can help.

Make decisions

If you lack confidence in your decision-making ability, you’re unlikely to improve without stretching your capacities. Train your decision-making brain and learn from others by working with them.  

Using decision trees

A decision tree is useful for plotting decisions on a flow chart and calculating the costs, benefits, and probable outcomes for each.

Leveraging SWOT analysis

Using a SWOT analysis to assess your strengths, weaknesses, opportunities, and threats makes you less likely to forget your advantages or overlook vulnerabilities.

Using cost-benefit analysis

Weighing the pros and cons of a decision helps you remember your priorities. It may also reveal biases and limitations by challenging your motives.