Decision Data

Decision Data

When you want to make an important decision, your decision data can make or break the decision making process. It is about the old adage "Garbage in, garbage out." What you want is "Good data in, good decisions out."

Data is the key to making informed decisions. Without it, we would be unable to accurately assess the situation or determine the best course of action. The first kind of data that you want when making a decision is data that correctly defines the problem or decision to be made. This should detail what is at stake. Also, consideration should be given of what needs to be done before taking action.

Data analysis can help you identify trends and patterns that could help your decision-making process. By collecting and analyzing relevant data from various sources, you can make better-informed decisions.

The Importance of Data in Decision Making

Decision data is like the ultimate key to success in any business or organization! It's like, totally crucial in today's fast-paced world where everything is always changing. But what is it, you ask? It's basically all the day to day data that is crucial for making good decisions.

And there's so many forms it can take, from basic metrics to super complex data sets that need fancy algorithms. But the bottom line is that it helps you make decisions that are way more informed and  spot-on.

But decision data does way more than just help you make decisions. It also helps you spot trends and patterns that might be missed otherwise. And that means you can make better decisions about everything from developing products to coming up with killer marketing strategies.

And, like, don't forget about how decision data helps you identify areas where you need to improve. It's all about tracking those key performance indicators, so you can like, see where you're falling short and figure out what to do about it. Maybe you need to hire more staff or try some new tech or something.

But the best thing about decision data? It helps you make decisions way faster. And speed is like, everything in today's super-competitive business world. By having the most up-to-date and accurate data, you can make decisions like lightning and totally leave your competitors in the dust.

Of course, none of this matters if your data isn't like, top-notch. You need to make sure it's accurate, reliable, and super relevant if you want to make the best decisions ever. And don't forget about data governance either. You need to have all sorts of policies and procedures in place to make sure you're using your data like, super ethically and in compliance with all the regulations.

So yeah, decision data is pretty much like the most important thing for a successful company. It helps you make decisions, spot trends, identify weaknesses, and make decisions faster than anyone else. But you have got to make sure your data is like, totally amazing if you want to get the most out of it.

Example of Decision Data

Data Analysis

Your company ABC Corp has received a request from one of its divisions to purchase a backhoe. The backhoe requested will cost $75,000. You, a new business analyst, decide to gather some decision data. Upon investigation, you find that the requesting division only used a backhoe 4 times for 12 days total in the current year. In the previous 2 years, it was 10 days and 15 days. Rental on backhoes is $250. / day for an average cost of $4,000. / year. Using just a rough and dirty payback method of economic analysis without even considering time value of money, you find that the payback time is about 19 years. Hardly a capital project that gets a CEO excited. With the data that you have collected so far, you would probably make a no decision.

You decide to dig a little deeper. You find that because that division is in a small town they have also have to rent a flat bed truck to transport the backhoe from a rental yard that is 50 miles away. That adds a cost of about $3,000 per year. In addition there are 2 other companies in the same town that use backhoes. They must rent and transport also. Their average combined usage is about 40 days per year. An inquiry finds that they would be willing to rent your backhoe to save transportation cost. Now you economics look like this:

Backhoe cost $75,000 Annual savings 7,000 Annual revenue is 10,000.

The payback of about 4 years is much more attractive. It is well worth doing a more accurate analysis. Doing a thorough job of researching the data turned a bad capital project into a good one.


Good research to gather decision data is important in 2 major areas of the decision process. First you gather enough data to really determine what the problem is. If you don't really understand the problem or the decision to be made then you are just wasting time. Second, you can't make good decisions if you don't consider all options. You should gather an exhaustive list of the feasible alternatives to solving the problem or making the decision. The goal is to make the job of the decision maker easy.

Don't make a decision in the dark - Get the light of data.