Author: Tracy Pesanelli
My career in mathematical optimization software sales has spanned more than two decades, and – over that time – I have witnessed an absolute explosion of growth in terms of:
Interestingly, although mathematical optimization touches practically every aspect of our lives today, many people don’t know what it is – and this is undoubtedly because it’s quite a sophisticated AI technology that is used to solve highly complex, hugely challenging, and large-scale business problems.
Oftentimes, I find that it’s easier to explain mathematical optimization by talking about what it does rather than what it is. For example, when I explained mathematical optimization to my 83-year-old mother, I told her that whenever I travel from Boston to see her in Florida, mathematical optimization is involved in almost every step of the journey – from booking the flight (which involves revenue optimization for the airlines) to the flight itself (which involves flight and crew scheduling optimization) to the ride that I e-hailed to get to her house (which involves vehicle routing and driver scheduling optimization). The same could be said when I send my mother a package via any of the major e-commerce and shipping companies, which use mathematical optimization to determine the best routes, modes, and methods of transport in order to deliver the package as soon as possible and at the lowest cost possible.
Indeed, mathematical optimization is literally everywhere in our modern world and is the driving force behind so many of the processes, products, and services that we depend on every day.
The number of companies investing in and implementing mathematical optimization technologies has increased exponentially over the past few decades. But what are the reasons behind this rise?
In this blog, I will reveal the three main reasons why more and more companies are choosing to use mathematical optimization.
Data is the fuel that propels today’s business world. Most companies have access to huge amounts of high-quality data – historical and real-time, structured and unstructured – on their customers, market conditions, operations, employees, supply chains, and much more from a whole host of sources including IoT and mobile devices, ERP, MES, and PoS systems, and web- and cloud-based databases.
The sheer volume of data is often overwhelming, and the challenge that essentially every company is grappling with is: How can we use our data to make business decisions that foster bottom-line growth?
Today’s companies are sitting on a veritable data goldmine, but in order to tap into this goldmine and extract valuable insights (that can be used to drive decision making), they need the right advanced analytics tools.
Mathematical optimization is one of these tools, as it enables companies to use their data to rapidly solve their complex, real-world business problems and make optimal decisions.
As the quantity and quality of data has increased, there has been a corresponding rise in the number of mathematical optimization applications. Simply put, with more data comes more opportunities for optimization.
One good example of this is financial services companies, which started off years ago using mathematical optimization to address common business problems such as risk management, investment portfolio optimization, and revenue optimization, but have since expanded its use to other areas including marketing (by utilizing data on particular clients to optimize and customize their product and service offerings – so that they can improve both customer satisfaction and revenue growth).
Mathematical optimization empowers companies today to unlock the value of their data – by using it to solve real-world problems, make optimal decisions, and take the necessary actions to achieve their business goals. That is why, with the proliferation of data in today’s business world, we are seeing more widespread adoption and application of mathematical optimization.
In the past, there was the common perception in the business world that mathematical optimization applications were difficult to build and maintain. But now – with the latest advancements in mathematical optimization technologies and ease-of-use improvements – it is possible for just about any company (with the right technological tools and people with the right skill sets) to develop and deploy mathematical optimization applications.
To successfully implement and use mathematical optimization, all you need is:
That’s all you need! With these resources (and access to accurate data), your company can easily build and maintain mathematical optimization applications that enable you to tackle your day-to-day problems, optimize your decision making, and maximize your operational efficiency.
It’s important to note that mathematical optimization can also be used in combination with other advanced analytics tools such as machine learning to increase the business impact of your applications.
The third (and most significant) reason why we have seen such a surge in the number of companies using mathematical optimization is that it consistently delivers tremendous operational and financial improvements.
More and more business executives today are assessing their competitive landscape and seeing:
These results speak for themselves – and so an ever-increasing number of business executives are deciding to invest in mathematical optimization technologies in order to address their company’s real-world problems, make the best decisions, make the best use of their data and resources, and make their bottom line the best it can be, day after day.
For the three key reasons highlighted in the blog (as well as many other reasons!), mathematical optimization technologies are growing in popularity among companies today. With mathematical optimization, companies can conquer the complexity of the modern business world and drive optimal decision making and business outcomes.
I would encourage business leaders, OR specialists, data scientists, and others to evaluate and experience the power of mathematical optimization – to discover how this technology could revolutionize and optimize their operations.
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