Algorithms, Optimization & Business Part IV: Mathematical Optimization in Business

In part four of our 5-part series on mathematical optimization, algorithms and business, we discuss the applicability of mathematical optimization in the business world and its ever-increasing importance. (Click here if you missed part three, Gartner's validation of algorithmic business as the new "it" word.)

It makes sense to incorporate expansion as part of your business model. Without continuous expansion, a business will likely stagnate and implode over time. A business that does not expand — rather, it maintains a steady rate of return — will be overtaken by things like inflation or other modes of economic flux. There's a real momentum to business, and should that be stilted, the push required to "get the ball rolling" again is often costlier than simply abandoning the failed venture. Naturally, any means of ensuring expansion will be sought.

From entrepreneurs and new, small businesses to great juggernauts like UPS, mathematical optimization has been helping consolidate resources such that savings can be turned into expansion capital. This is one of many reasons that mathematical optimization is trending throughout the business world. In a word, mathematical optimization is effective and provides security for new and established businesses alike.

As businesses become successful, naturally they'll look into means of consolidating resources. Just as naturally, the larger a business gets the more practices they'll that aren’t profitable. The downside is, they’re often difficult to identify. There are cases where a department has continued draining a company for decades, but nobody knows because the "leak" was hidden to those who could fix it. Mathematical optimization is a means of holistically examining the entirety of operations such that "leaks" of this nature can be identified and fixed nearly as soon as they are discovered.

A Closer Look at Mathematical Optimization in Business

It's difficult to determine what parameters define a business's yearly profit. In economics, Wall Street moguls refer to something called the "seven year slump", where every seven years there's a predictable economic downturn. Knowing about this downturn changes investment choices. Until mathematical optimization, this cycle was hypothetical — there were no numbers to quantify it. A business operating with even this knowledge will stand to save money through resource consolidation.

But mathematical optimization of a directed, regular application can yield results much more quickly than seven years. (To be exact, it can yield results within weeks). Exigencies like the seven year slump — but specific to the business in question — can be examined closely, and a set of alternatives can be put together. Using mathematics allows identification of alternatives that make the most sense based on a business's specific goals, strategies, limitations etc.

For example, an alternative to a regular supply chain could be on-demand shipping, wherein a product isn't sent to a seller unless that seller specifically requests it. Sometimes, on-demand shipping saves the seller and the manufacturer substantially. Sometimes, the market where a product is being sold could stand to have a supply chain which regularly replenishes a vendor. While analyzing the data after the year's close could reveal which option is the best, mathematical optimization will identify the correct alternative much more quickly, allowing for immediate.

The Power of Mathematical Optimization in Business

Cloud Computing Provides Tangible Alternatives

Another reason the business world is excited by mathematical optimization is that the alternatives it supplies can be directly quantified. Terabytes and petabytes of data can be analyzed in real time through use of cloud computing solutions. When this information is analyzed, those trends which diminish profit can be discouraged or eliminated. Simultaneously, those which increase profit can be encouraged and expanded. There is now software which is able to take critical parameters specific to a business and apply algorithms accordingly. Sometimes entire departments prove themselves anachronistic, but there's no way to demonstrate that mathematically. Mathematical optimization software fixes that problem directly — and it does so in a way that's difficult if not impossible to argue.

Supply Chain Optimization

Oftentimes, supply chains become established and aren't augmented after the fact. But the world isn't static. Supply chains that were once lucrative can become a drain, while those that were merely meeting the bare minimum could become the most successful. The changes involved in these supply chains could happen in the course of a decade, or they could happen in the course of a month. There is solid reason to believe that in the modern world, changes will come not only more regularly, but more quickly. Consider cellular phones. From homeless people to high-powered business executives, everyone has a smartphone today. Yes, that's a blanket statement, but the truth is that this technology was restricted to those groups who could afford it only recently. Now smartphone technology has become practically integral across the socioeconomic board. These changes have come rapidly, within several years. Mathematical optimization could allow an organization to examine and respond to such changes almost simultaneously, depending on what portions of the business model are already in place.

When this kind of thinking is extended to supply chains, suddenly the popularity of mathematical optimization in the business world is nothing but apparent. As the demand and availability of smartphones increased, supply chains had to be optimized. Without modern means of analyzing such data, that optimization could not have traversed the market nearly so swiftly as it did. Not only does mathematical optimization increase the resource consolidation involved in a supply chain, it can increase the amount of business an organization is able to do.

In 2000, Sony brought its first video-game entertainment sequel to the market, the PlayStation 2. The PlayStation 2 launch was marred by a dearth of available units. The demand for the units was capitalized, however greater sales could have been had initially. In 2000, mathematical optimization wasn't nearly so optimal as it is today. However, as it’s developed, Sony has been able to apply lessons from previous trends to subsequent technology releases. It’s been able to maximize the profit a release incurs. The result has been a greater demand for their products, which has allowed continuous regular development of new console options. Video game aficionados will note the current incarnation of the PlayStation is the PlayStation 4.


Another reason mathematical optimization has taken off recently is that, as larger organizations jump on the bandwagon, those companies looking to remain competitive must likewise follow suit. UPS uses mathematical optimization to save time and money in delivery. As a result, FedEx has no choice but to do the same. Even though FedEx has been orchestrating such resource consolidation measures since the sixties, the tools available now are much greater than the tools available then, and neglecting to use them could mean loss of competitive advantage in the market.

Closing Remarks

Mathematical optimization will continue to increase in applicability and will only become more streamlined with time (and more affordable). Cloud computing technology makes mathematical optimization something that will soon be status quo for any business. Metrics have always been used to increase profitability. The business world has found a means of doubling down on those metrics through optimization and the cloud.

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