Digital Transformation and Supply Chain
One of the most common topics at TARTLE is the digitization of the modern world. More and more of daily life and of business is conducted online, something that we all know has really taken off in the last year and a half. However, at some point, goods have to be physically produced and distributed. Even if we develop Star Trek level replicator technology, we are still going to need the raw material for that. That means there are and will be factories, boats, planes, trains, and automobiles that transport goods around the world and back again. And that puts us in the world of logistics and supply chain and that is the domain of one Mac Sullivan.
Mac has a staggering resume, including multiple degrees, teaching positions, living in various countries abroad and is currently the Head of Technology and Digital Promotion at NNR Global Logistics. He has also recently released his first book, The Digital Transformation of Logistics: Demystifying Impacts of the Fourth Industrial Revolution. As you might guess, Mac is focused on bringing the very physical world of logistics into the digital age.
One of the things that Mac calls attention to right out of the gate is how COVID and the resulting acceleration of the digital transformation served as a great catalyst to get even the most luddite of companies to at least explore the digital realm. A clear example is that according to Forbes, many companies report having engaged directly with customers much more than they have in the past. As you can imagine, direct engagement with customers is exactly the kind of thing we really like here at TARTLE. But I digress.
However, logistics and supply chain remains somewhat intransigent. How badly is this digital transformation needed in the world of logistics? Very. As Mac himself points out, they are still working on fully integrating the internet into their operations. Goods are still often tracked with pen and paper that might get scanned and sent via fax. Yes, a few of those machines still exist. Essentially, Mac is working on getting a lot of simple office processes automated, things that are still done by people in cubicles entering data on a keyboard. This is actually more important than just streamlining operations. It also will help reduce human error in the form of transcription errors, errors that can cost time and money down the line.
Money of course is one of the obstacles for a lot of transportation companies. They operate at very low margins and are very adverse to the costs of automating their systems. After all, they have a system in place. It might be slow but it works. Not to mention, these companies are constantly getting pressured to cut costs, not spend money on automating anything. This puts the pressure on Mac to show them the value added by spending some money on tracking and notification systems now and the money it will save down the line by correcting the issues mentioned above and simply making the process more efficient.
Another barrier is that while there is a lot of excitement about a great deal of digital technology like IoT, 3-D printers, blockchain, and smart contracts, there are few working models on the kind of scale that is needed for a global supply chain. Everything is either small scale or at the level of the theoretical.
It is possible to change all this but it will take time. As Mac says, it will have to be pushed by new people entering the field, people who are familiar with the potential of digital technologies and have the education to push logistics into the fourth industrial revolution.
What’s your supply chain worth?
The Fourth Industrial Revolution
The next industrial revolution is upon us. Already we are experiencing a major shift in how and where we work. Just a couple of years ago, working from home was something that really only applied to a select few but now it is the norm in many areas. That means companies are moving out of their office buildings and into much smaller, and easier to maintain spaces.
Instead of work teams being limited to those in a cluster of cubicles all living a few miles from each other, people now work in teams that include members from all around the world. TARTLE is a great example of that. We are physically based in New Mexico, incorporated as a public benefit corporation in Delaware and work with people everywhere from Michigan to the Philippines. We are hardly the only company that is operating in this way, nearly everyone employs freelancers or firms on an as needed basis in order to save money overall. One of the most surprising things is that there are plenty of people eager for this kind of work.
What this portends is a major ongoing shift in the way we do business around the world. Desired skill sets are changing and with all of this is coming a different kind of economy, different enough to call it a new industrial revolution. As with the previous industrial revolutions, there is a need for people with vision to lead the way adapting and making the best use of this new business and economic environment.
These visionaries will need to have more than drive, more than the desire to be on top. They need to have a deep understanding of the nature of the new economy. Gone are the days when everything can be thought of as a standalone entity. Not only do they have to see each department of a company as part of a larger dynamic whole, they need to see that each company’s actions can have a large effect on the other. Thanks to the advances in technology we’ve experienced over the last forty years, it’s become incredibly apparent that businesses exist as part of an ecosystem. This has always been true, it’s just much easier to see now.
Speaking of technology, these visionaries will also have to recognize the importance of data in the new economy. Data is what drives everything these days, making the acquisition of it and analyzing it is the most important thing any company can do for itself. In order to survive the new revolution, much less come out on top, our visionaries will need to realize that they are a data acquisition and technology company as much as they are a doll manufacturer (for example).
Of course, not even the best of visionaries can hope to navigate all these waters on their own. They will need help along the way. Just as every athlete has a coach, every bodybuilder a trainer, every visionary will need someone to support them on their journey. TARTLE understands this as the Sherpa model. Like the Sherpas who help people reach the top of Everest, TARTLE is here to team with the visionary, to carry the load and make the journey easier. We don’t seek the glory, our goal is to help others reach their goals. Sherpas can reach the peak of Everest dozens of times in their careers, and we’d love to help many more companies reach the top of their game in the digital economy.
We can help you gather and analyze the data you need in an ethical way, a way that still treats data with respect, as the product and work of individuals with rights as well as thoughts and desires. We’ll help make you not just financially successful but a champion of the digital economy.
What’s your data worth?
The Fourth Industrial Revolution
Recently, the World Economic Forum held its annual meeting in Davos, Switzerland. The group – a who’s who of global leaders in business – discussed what is being called the fourth Industrial Revolution. Consisting of developments that we are already familiar with like the Internet of Things (IoT) and others that are on the cusp of entering the mainstream like quantum computing, this latest industrial revolution is presenting some fresh challenges.
Before we get to that though, we should probably take a brief look at the other three Industrial Revolutions. After all, we usually only really talk about one. That one that we are so used to talking about began with the introduction of steam power. That brought us trains and boats, both things that made transportation of large amounts of materials over a long distance possible. The second was focused on electric power, giving people the ability to get much more work done with the flip of a switch and to literally keep the lights on all night long. The third industrial revolution came about with the advent of automation. Now we no longer have to rely strictly on people to get all the work done. Machines are literally making machines now, though still under human direction. This began in the 1960s with the introduction of the transistor and has driven much of our world from the tangible tactile world of the past, a world that is fairly simple to grasp, to the modern digital world in which many things are happening strictly electronically with processes that we can’t and may never be able to see. This is a world that is much more difficult to wrap our heads around. So it only makes sense that this new Industrial Revolution will be even harder to understand and adapt to.
Strangely, as this latest stage in technological development gains traction, the gap between the non-technological and the technological is shrinking. Even in the business world, every company is a tech company on some level. This is just as true of small businesses run out of someone’s garage as it is of a multi-billion dollar corporation. That’s how you can buy a highly customized quilt from a company operating out of a pole barn in Michigan while you are sitting in a coffee shop in Seattle. They’ve understood the importance of data to their business and learned how to apply it to their situation.
So what are some of the problems and concerns brought about by the fourth industrial revolution? One of them is the fact that so many have a difficult time learning how to understand not just how to analyze data but how important it is in the first place. While some small businesses have done a great job learning how to use data to their advantage a massive number of others, even larger businesses are still a full industrial revolution behind the curve. They may realize they need to adapt but have no idea how.
There are also concerns about how the latest round of development will hurt people and their ability to make a living. This is a legitimate concern. After all, once the car became viable on a large scale, there was little use for people who made wagons. Suddenly, there were whole groups of people who had to learn how to do something new. However, there were lots of new things to do. The move to cars actually created lots of new jobs that no one saw coming. Even now that a lot of those assembly lines are automated, there are still jobs repairing, designing, and installing the machines that build the cars. In short, while the concern is valid, especially in the short term, a standard feature of each industrial revolution has been the creation of jobs that no one could predict.
Another, more important problem is that as things become more digital, it will be harder to keep people at the center of everything. While the world’s economic and technological growth becomes less tangible it will be ever easier to make decisions in the abstract, to think only in terms of numbers and increasing the bottom line without concern for whether or not people are being helped or hurt by those decisions.
That is TARTLE’s concern, to keep reminding people that while we don’t have to be afraid of the next Industrial Revolution, we do need to remember that it doesn’t happen without people and it should happen not for the benefit of a wealthy few but for the benefit of all.
What’s your data worth?
Data Analytics: The Good and the Bad
It’s no surprise that we are TARTLE are big on data and using it to improve lives all over the world. By collecting and analyzing quality first party data processes can be refined and better decisions made.
One famous example of this is Domino’s Pizza. Years ago, the Michigan-based pizza giant was on the ropes. Once the leading name in pizza delivery, they were losing market share to others and getting bad reviews on their pizza and their delivery times. They went from the king of the mountain to sliding fast towards the valley.
What did they do? They realized they had to take a hard look at all of their processes and possibly make some very hard choices. To do this, they developed their pizza tracker program, tracking the whole process for each pizza from order to delivery. Looking at the data gained from that software, Dominos identified a number of inefficiencies, inefficiencies that they had to fix to get back on top. Altering their mentality to treat the pizza making process like a manufacturing process, the company completely revamped its business. The process was more efficient and they were able to deliver better, fresher pizzas faster than ever before. As a result, Domino’s is once again climbing the mountain and rebuilding its reputation.
That success story unfortunately isn’t every story. The other side of the coin is represented by an incident featuring America’s biggest big box store, Wal-Mart. Sam Walton’s company has been big on using data to optimize its profits for years. Because of this, they noticed that Vlassic pickles were selling remarkably well. What’s more, they figured that they would sell even better if they could get them down to a lower price point.
They contacted Vlassic to ask if it was possible and after the supplier crunched all their numbers based on their down data, they got close enough to make the bean counters at Wal-Mart happy and the order was placed. Everyone wins and we have another success story about the power of data analytics, right? Wrong. Instead of a raging success, this seemingly smart move was a disaster. Pickles indeed flew off the shelves, until they weren’t on the shelves anymore. What happened? The farmers that grow the cucumbers in the first place simply couldn’t keep up with the demand that was getting placed on them. With no pickles to put on the shelves the orders were cancelled or significantly reduced. That compounded problems for the farmers, especially those who would have bought new equipment and altered their own processes in order to meet the sudden increase in demand. Then all of a sudden that demand fell through the floor again, meaning that the farmers wouldn’t be able to recoup all those costs.
So what went wrong? Why did a reliance on data and the in depth analysis of it lead to success for one company and a major loss for another? It was a difference in approach. Domino’s didn’t just go over their procedures or have a couple teams demonstrate their process for the board. They went into many of their stores, working with the employees and analyzing how their pizzas were made. They also paid attention to their customers so they knew what it was they had to focus on improving. In short, they listened to everyone that mattered most in the process and worked with them to find the best possible solutions to everyone’s concerns.
Wal-Mart seemingly did the same thing. They knew what their customers wanted, knew they would be even happier with a lower price and worked with Vlassic to order more pickles at a lower price. But they forgot to talk to the real suppliers, the farmers that are pulling the product out of the ground in the first place. Granted, this need not always be a concern. A single store isn’t going to strain the system. However, given the number of stores Wal-Mart has and the volume of product they move, talking to the farmers is a necessary step.
What these two examples demonstrate is the necessity of remembering that even the most scientific data analysis has to be about people first and foremost. Keeping that in mind means you not only achieve financial success for yourself, you will improve the lives of others in the process. Forget that and you will do harm you never intended.
What’s your data worth?