The next time your plane lands safely, your new car starts, or your package arrives on-time, either thank your lucky stars or thank an algorithm. Computer scientists and engineers are working closely with marketing professionals to use mathematics and today’s computational power to improve the customer experience. This “hidden mathematical world” has the power to change marketing forever!
With exponential trends of data growth and computational power colliding, the world is literally drowning in data. There’s too much data, and not enough analysis. Fortunately, companies are using technology to capture and integrate data and sophisticated mathematical procedures to analyze data and make better decisions–decisions that ultimately improve the customer experience.
An article from The Economist, “Business by the Numbers“, highlights how companies are using algorithms to make book recommendations, choose optimum delivery routes for packages and even route calls to agents that can best diagnose a particular problem.
While the term “algorithm” sounds like geek-speak, the article notes algorithms are nothing more than, “a step by step method for doing a job.” Some algorithms are simple, and some are very complex. Coupled with the power of a computer, “algorithms can execute tasks with blinding speed using vast amounts of data.”
But how do algorithms improve the customer experience?
Take for example, something that on the surface sounds easy, but actually is very complex–package delivery. We often take for granted the operational efficiencies and supply chains of companies we rely on for package delivery. For example, we need a package delivered to Manhattan by 10am the next day. Using any of the global shipping companies, we would have a high degree of confidence in that package arriving on-time. However, peer behind the curtain and you’ll see some pretty advanced algorithms make all this possible.
The Economist article mentions how UPS uses algorithms to route millions of packages each day:
“The simplest routes are easy to draw up. If a driver only has three destinations to visit, he can take only six possible routes. But the number of possible routes explodes as the destinations increase. There are more than 15 trillion, trillion possible routes to take on a journey with just 25 drop off points–and an average day for a UPS driver in America involves 150 destinations.”
Now add other variables such as transportation schedules, special delivery times and shipping options (plane, train, truck, boat etc) and you’ll begin to see there is a real science to ensuring timely package delivery. Algorithms help tackle complicated challenges–especially necessary as marketers race to take care of their “best” and/or most profitable customers.
Suppose you are a frequent flyer on a particular airline and have achieved some level of “status”–say Platinum. You’ve checked baggage for a flight to New York City, with a connection through Denver. Due to unforeseen circumstances, however, your flight into Denver is an hour late. In Denver, you barely make the connection and at this point are unsure whether or not your bags made the flight.
About fifteen minutes into the flight, and just after the plane has reached cruising altitude, a flight attendant taps you on the shoulder and says, “Rest assured, your bags are on the plane.” Whew! You breathe a huge sigh of relief–especially because your business suits are in those bags!
Getting back to your flight attendant–how did he know your bags are sitting in the cargo hold? And how did you make your connection? Was it just luck? Perhaps fate?
While we cannot rule out the effects and benefits of luck in this instance, the more probable cause of making your flight (both you and your bags) is a combination of complex algorithms, scanning and sensing systems, processes and people executing in perfect harmony.
Ideally, the cause of the delay (weather, mechanical problems etc) was identified by systems or airline personnel. This caused a chain of events to take place with systems (running algorithms) that then started to identify possible alternative options (flights, aircraft, schedules) for you to make your connection.
Some systems examined the passenger records and recognized top tier customers (based on miles, profitability or some combination thereof). Other systems checked baggage and identified your particular suitcase in transit. Computers then sorted through thousands (if not millions) of options and either made automated decisions, or decisions supported by airline personnel to ensure that you and your bags arrived on-time. And of course, the flight attendant was notified via in-flight systems to tell you … a valuable customer–that your suitcase had made the flight.
Our world is becoming more–not less–complex. As data volumes and decision options increase, algorithms and the systems that run them take on added importance.
Powerful and well designed algorithms are only part of the story in how companies are taking better care of customers. As the Economist article points out, an algorithm is only as good as the systems, data, processes and people behind it. Nonetheless, algorithms are helping companies increase competitiveness, improve efficiencies and enhance the customer experience.
Algorithms are all around us–helping marketing and other business professionals meet complex challenges, but sometimes we take them for granted.
So, the next time you decide to buy that book Amazon recommended, pause for a minute, and thank an algorithm.
Tags: algorithm, analyze, artificial intelligence, complex event processing, complexity, customer experience, data growth, exponential growth, optimization, scan and sense, speed in decision making, Technology
Paul,
Thank you for explaining algorithm. As a frequent viewer of “Nuumbers”, I had no clue how math helped capture bad guys. Now I get it (not really, but it makes more sense now).
Paul,
If nothing else, I think articles and posts on topics like this should remind Americans how important it is to make sure no matter what party one belongs to or what side of the issues one sits on, improving America’s education–especially in math/statistics, sciences, and informational technologies–is vital to the health of our nation.
On the lighter side, whenever I hear about lost luggage, I think of Meet the Parents.
Ben Stiller’s character on the phone with an airline employee: “Yeah, you gave me the wrong suitcase. Uh-huh. Yes, it’s a black Samsonite. Uh-huh. Ok, well don’t you think that the Samsonite people, in some crazy scheme in order to make a profit, MADE MORE THAN ONE BLACK SUITCASE?”
Lewis, thank you for commenting. I’m with you–now that I’m aware of this hidden mathematical world, I’ve discovered some amazing case studies of companies using analytics to compete and win.
Algorithms are all around us, often undetected and behind the scenes. They can really speed up both routine and complex decision making.
Michael, you bring up a good point. Thinking by the numbers is a change in mindset for most companies, instead of “fly by the seat of your pants” decision making.
I’ve often heard the argument that this type of thinking is at a high level only for the quant jocks and at a low level just for the bean counters. You rightly point out that competitive advantage (on a national, company, or personal level) highly depends on our continued mathematical prowess.
Paul,
Well said.
I would say only someone who has not dealt with algorithms would think they’re easy for anyone.
Isn’t that quote, “The more I learn, the less I know.” ? I always figured that meant the more you learn, the more you learn there’s more complexity to the universe than you’ll ever understand. The people who think anything involving intellectual thought is easy are likely to be more arrogant than intelligent. I would guess (based on my experience) the most intelligent people in the world are some of the more humble.
I always knew that algorithms were involved in computer programming, but this explanation puts it into better perspective. Thanks, Paul.
Good rationale here for schools and universities to keep math mandatory throughout the educational experience.
Elaine, thank you for commenting. Marketers are using algorithms (whether we know it or not) through some of the applications we use (next best offer, call routing to “retention specialists” etc. Anywhere simple or in most cases complex problems need solving – algorithms are at work.
Companies are even listing “our proprietary algorithm” as a competitive advantage to customers and analysts.
Great post, Paul. You know in some ways the world paradoxically *seems* less complex because of algorithms.
When I order from Amazon, my package arrives efficiently and fast. When I fly I print my boarding pass out at home and that is one less thing to think about. When I need information, I google it.
Thank you to the people who build and maintain these algorithms. As someone who has worked in the tech industry since the mid ’90s, I realize how incredibly hard they work on incredibly complex problems. It is awe inspiring sometimes.
Also, I would like to note, that a theme I think I see in Paul’s writings is that the alliance between computer science and marketing is in its infancy. We have barely scratched the surface. This is actually pretty exciting because there are incredible opportunities.
Fortunately, we have people here like Paul and Matt who can help move forward.
Neil, you are right that when coupled with computational power algorithms help simplify and improve the customer experience. The Economist article shows example after example of different industry applications for algorithms.
Your final point about how marketing and computer science are aligning is also spot on. I’m no forecaster but I can say that technology will bring some drastic changes to how we serve customers in the next five years.
This is just the beginning.
Absolutely, we are at the beginning but I think the trend is going to be a steep upward curve.
Neil, it will be an s-curve for sure for exponential growth, and a upward hill to climb in change management.
Yes, to refer back to Lewis’s post, I hate to agree 100%, but I really have no choice.
Well,The information provided by you is very interesting.I do agree that as data is going on increasing like population one should definitely have to take care to control and manage the data.In the present era as technology is ncreasing so we have to co-relate both technology.
with data so as to ensure betterment of the organisation.Thanks for the information
provided by you on customer satisfaction with growing data.
Though the growth of data itself is an important issue I believe it is a slightly separate topic.
Paul’s s-curve refers, I think, to the stage of the alliance between computer science/math and marketing.