What is Your Best Approach to Decision Making?

Joe Weinlick
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Thanks to computer technology, software and apps, more and more companies rely on big data to drive their business models. Leaders develop strategies using information compiled and analyzed by computers. Despite all of these advances, there still needs to be a human element behind decision-making in corporations. Experts touted by Harvard Business Review detail the best approach when figuring out how to move forward with a particular strategy.

Elements That Come Together

Three main elements come together when decision-making happens with all of these technology tools in the workplace. First, computers must compile the raw information. Sales figures, revenue, time to market, overhead, supply costs and labor expenses are all raw figures that computers work well with since those machines are great at doing math. Second, a program must analyze the numbers and organize them into usable information. This is when analytics software pays for itself.

The third aspect is that a human must employ decision-making to know what to do with the data. The program created a beautiful chart showing how price affects revenue over time, but what do company leaders do with that information? Business leaders must understand how the software compiles the information and what the numbers mean. People who can't figure out how to handle the data suffer from "big data, little brain," according to HBR.

How to Mitigate the Problem

Experts believe the best approach to alleviate any problems that come from relying on data too much is that business leaders should go with their gut and experience every once in a while. Finding this balance doesn't mean eschewing information altogether, but it's more about knowing what data to pay attention to when decision-making comes into play.

Ironically, there is a way to figure this out using a different kind of computer program. An agent-based simulation, or ABS, examines the behavior of humans, crunches the numbers and then makes a predictive model of what may happen. The U.S. Navy developed ABS in the 1970s when it examined the everyday behavior of 30,000 sailors. This type of program is gaining more widespread use due to better computing power.

There is a ton of information that computers must take into account to make these predictive models. When ABS first started, simulations ran for a year before getting results. In 2017, that timeframe is down to one day by comparison.

ABS uses information from the analytics software and applies it to customer behavior models and decision-making to predict what may happen in the future. This type of program answers what happens when a company changes prices of products, if a competitor adapts to market forces in a certain way and what customers may do when you change a product.

ABS can't predict everything, but it does take into account human expertise. ABS, like any analytics software, is only as good as the data it collects. It makes decisions more transparent because it supports the notion that if a company moves in one direction, then a certain scenario is likely to happen. You must remember to take a risk no matter what path you're on.

Decision-making shouldn't be all data or all going with your guts. However, data gathering certainly makes it easier thanks to the technological tools available to businesses.

Photo courtesy of Stuart Miles at FreeDigitalPhotos.net


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