Data-Generated Performance

In today’s life, we are all aware of the great sports stories, with GOATs like Serena Williams, Tom Brady, Michael Jordan and Cristiano Ronaldo, among many others. We also hear or read about companies like Google, Amazon, Apple, Netflix and Meta, formerly Facebook, rising in value every day based on ideas that will change the world as we know it, or even by creating new worlds in a metaverse.

Most of us know what those success stories are about but only a few keep digging into how and why they are successful. As Morpheus told Neo (in the 1999 film The Matrix): “There’s a difference between knowing the path and walking the path.” So, let’s make some assumptions and say that, in addition to discipline, talent, great coaching and funding, these athletes and companies use technology in their favor. But it’s not only technology itself; it’s  a means to get something that helps them to go in the right direction, be more efficient, do things better and make the most of the aforementioned assumed advantages. Let’s call that something data and doing things better as performance.

Carly Fiorina, former executive, president, and chair of Hewlett-Packard Co., mentioned that “the goal is to turn data into information, and information into insight.” I guess that insight could be turned into better performance and revenues. The sales and logistics processes of thousands of businesses trading goods and delivering them to their final customers and the details of what, when, how long and which topics are the films and shows millions of users watch; what keywords do billions of people look for on the internet maybe have something in common with how a football team’s defensive formation is used to avoid a touchdown; what racket stroke does a player use and under which circumstances in a tennis court; from which side of the court does a basketball player likes to shoot and how often she/he scores; or to which side does a certain goalkeeper use to block a penalty shot. There are trillions of data right there helping these athletes and companies to perform better each day. And they are certainly using them.

How about the logistics to transport passengers and cargo by sea and air in the offshore oil fields? Are there any useful data in all those long and complex processes? Yes, there are! Are ship/helicopter owners and operators or their customers using that data? No, they are not!

First, ship logs are handwritten; when they reach the shore base (weeks or even months after they are created), their destination is a file cabinet where they will stay for eternity. Maybe some will find their way into an excel sheet at the port authority, and maybe that excel sheet will become a report with around 5 percent of the data the ship’s log originally had, otherwise they will exist for eternity in a computer hard or virtual drive. Second, all documents created and processed during all the steps of this logistics process (contracts, estimates, load bills, passenger and cargo manifests, etc.) are also handwritten. In the event they are entered into an electronic device, they will mostly find their way to the same hard or virtual drive as the ship’s logs mentioned above. If you ask any ops manager from any shipowner or the logistics manager of any of their customers, you will get the same reply to questions like, how many passengers did your ship transport the last two weeks? What is the average cost per transported passenger or ton of cargo in your logistics process? Is it more cost-efficient to hire a ship/helicopter by the hour, by the day or for longer terms? The answer is, “I don’t know” (and some of them “I don’t care”). The basic KPI’s of any logistics process are always a mystery for everyone inside and outside those companies.

Geoffrey Moore said that “without (big) data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” Offshore oil and gas, maritime and air logistics players in Mexico are senseless.

PEMEX alone, between 2011 and 2020, spent more than US$300 million to charter crew transport vessels, with an average of 26 boats hired annually. It also spent more than US$1.43 billion on an annual average of 42 helicopters hired in the same period. These activities moved around 25 million tons and 8 million passengers by sea. Those boats and helicopters, jointly, required more than US$40 million of fuel. These numbers could be interesting and useful for almost any player in this industry, but it also depends on how and when they can have access to the data. Getting the data one or nine years later may not be as useful as having access to it one month or one week after it is generated; or even in real time.

As Mike Schmoker told us, “Things get done only if the data we gather can inform and inspire those in a position to make (a) difference.” Undoubtedly, Serena Williams, Tom Brady, Michael Jordan and Cristiano Ronaldo, as well as the relevant executives at Amazon, Facebook, Netflix, Apple and Google are actually making a difference and the data they collect transforms into revenues. I hope it’s just a matter of time before ship/helicopter owners/operators and their customers realize the value of the data their own operations generate, but they must begin looking at how they should start structuring their companies to ensure better data-generated performance. Perhaps they can use a digital platform to achieve that? Ask me and I will tell you about the right one.