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What Is Decision Modeling, And Why Do You Need It?

Decisions, decisions. Nothing is more stress-inducing — particularly in business, where decision-makers are often under pressure to act quickly— than having to make a big decision. 

There are so many things that can go wrong with a decision like that. You might be working with an overwhelming amount of data. Profit, share value, or even people’s jobs, may hang in the balance. You may be so concerned about making the right choice that stress clouds your judgment. 

But what if there were a safe way to make that decision without really making it? What if you could consider every bit of a huge dataset and based on that, examine every possible outcome before making your decision in the real world? 

Well, you can. That’s what decision modeling is. More specifically, that’s what computer-based decision modeling is: a computerized way to predict the outcome of decisions. 

Here’s a more comprehensive definition from BusinessDictionary.com

A computer based system that predicts the outcomes of decisions. The relationships between elements of the decision and the forecasted results are mapped in order to understand or control problems. The decision model may also predict what will happen if a certain action is taken. 

Why Businesses Need Decision Modeling, or, Machines Don’t Get Hangry 

Decision modeling is growing in importance and popularity because more companies are capturing "big data," gigantic datasets, that are difficult — if not impossible — for human beings to parse. Decision modeling software uses that data and advanced algorithms to make accurate predictions or help optimize confusing choices. 

Humans are notoriously bad at making decisions: we’re not rational, we trust our “gut” and no matter how fair we think we’re being when we make a decision, we’re informed by our own biases. To make matters worse, our decision-making process is affected by how tired, hungry, or stressed we are at the time. Scientists studied this phenomenon a few years ago — researchers followed eight judges for 10 months as they ruled on prisoners’ applications for parole. Prisoners whose cases were heard earlier in the day were more likely to have their parole granted. But clemency dropped sharply just before meal breaks and the end of the day.  

Machines don’t have these issues. The main advantage of big data and decision modeling is that since it's based on data it can help companies make decisions without the biases (or hanger) that humans bring to the table. 

Machines can also do another thing we don’t do well: parse Big Data. Humans just aren’t designed to take in the amount of data most organizations are generating. We’re likely to overlook something important, or simply get overwhelmed. 

Decision modeling allows an organization to take in that information, analyze it, and generate decisions not informed by human bias. 

How Does Decision Modeling Look in Business? 

Businesses use decision modeling in all sorts of ways: 

  • Farmers have sources for planting crops that use decision modeling fed by weather and yield data.
  • Retailers learn about customer behavior by looking at shopping patterns. They can experiment with price changes and watch how sales are impacted. That data can be fed into a decision model and over time, be used to predict behavior.
  • Banks and insurance companies use decision modeling to approve loans or extend coverage.
  • Gas producers and utility firms can look at supply, demand, geo-politics and weather conditions to predict gas prices and choose when to lock in favorable terms.
  • Credit cards use decision modeling paired with real-time feeds of transactions to detect credit card fraud.
  • The wine industry can look at rainfall and growing season temperatures to feed a decision model to predict wine quality.
  • Manufacturers can use large maintenance and repair datasets to predict component failure in manufacturing equipment.
  • Healthcare providers can use operational, usage, and economic data paired with demographic and health trends to create decision models that help them decide whether to extend an existing facility or build a new one. 

Want to Learn More? 

If you’re anxious to get better decision-making tools within your company, contact us. We can evaluate your current technology stack, business dashboards, or databases and make recommendations on how to get started.

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Eric Evans

About Author Eric Evans

Eric has spent his career leading large client-consultant teams, managing multi-year engagements, budgeting, estimating, and recruiting to the needs of his clients. Currently, he oversees day-to-day operations to support the growth and add to the bottom line of Omni. He has worked with multiple Fortune 500 clients with a focus towards bringing business value to all levels of the organization. In addition to being a dynamic leader, Eric has been a manager or people, an architect, a programmer, a project manager, a steel salesman, and a paratrooper in the 82nd Airborne Division of the United States Army.