What’s the Number One Number Thing Today’s CEO’s Must Do? Do the OODA Loop Faster and More Innovatively

What’s the Newest Requirement for a CEO? Do the OODA Loop Faster and Better!

You would think it would to generate revenue, profits and reduce costs. Think again. It’s all about iterating and pivoting like a start-up. And who better than a former fighter pilot to teach CEO’s a thing or two about making quick. So I want you to meet John Boyd, who was among many things, a military strategist, colonel and fighter pilot whose theories are highly influential in the military, sports and business.

So why bring up Colonel Boyd in the context of CEO’s and their need to be nimble? Because investors and boards have transitioned from desiring quarterly profits (something that has driven Wall Street and corporations for many years) to searching for leaders to those who have the ability to disrupt their industry or die. What did the fighter pilot, Colonel Boyd used to make those decisions to do something out of the ordinary? He created a framework known as the OODA Loop:

  • Observe (M—ake the best use of the information and other intelligence resources available right now)
  • Orient (Quickly put the new observations into a context with the old)
  • Decide (Make quick decisions and take the “next actions” based on a combination of observations, current knowledge and intuition), and then
  • Act on those decisions to carry out the selected action(s), ideally— while the competitor is still observing your last action so you beat them to the punch!

OODA Loop

                                         Photo Source: Larry Paul

Above is a video from Ralph Mroz on the OODA Loop as applied to business if you want more information!

Observe, Orient, Decide and Act Is Known as John Boyd’s OODA Loop

As a fighter pilot, John had to make decisions in nano-seconds. With this framework of observe, orient, decide and act he way able to describe a way to iterate and pivot, very quickly, and decide if the object in front of them is friend or foe. Not doing so could mean life or death. It could also mean the end to a critical mission.  What does the OODA Loop mean to a CEO? Iterating and pivoting is also mission critical. Just ask the CEO of Ford Motor Company, Chief Executive Mark Fields. He was a 28 year old veteran of the business and was replaced by someone the business thought would be able to disrupt the automotive industry very quickly!

The Message is Simple: Do the OODA Loop Faster or Die

While Mr. Field’s did what most board’s used to expect of a CEO’s, i.e., he returned consistent profits, he did’t make enough changes fast enough. His OODA loop was too slow. But he didn’t know what he didn’t know. He, as many other CEO’s don’t realize that the winds of change are changing all around us. Like in most any industry, the car market has entered into the era of transportation.

It’s no longer just about building and selling a car. It’s about car-as-a-service. Think: ride-sharing (think Lyft, Tesla and ReachNow (by BMW.) It’s also about taking the traditional gasoline engine and transforming it’s power source to be an electric vehicle. And it doesn’t stop there. Some companies are disrupting the industry by experimenting with self-driving technology, making investments in connected cities (think BMW and Santa Monica, CA.) And at the same time Ford’s stock sank. 

How Fast Does Your CEO do The OODA Loop?

How fast do decisions get made? How fast can the ship be turned? Today, with the need to act quickly, the message is simple. We are in an age of rapid disruption by the software and tech industries. A leader of any company has to pick up the tempo and make riskier bets sooner… or die. While it was Mr. Field’s intention to set Ford on a path to be part of the new, emerging auto industry, he just didn’t do it fast enough.

Since Mr. Field’s took over three years ago, the share price of Ford is down 40%. As a CEO, as yourself, “Are you disrupting yourself, your company and your products fast enough? Are you really changing anything or are you just doing the old stuff just faster?” These are not easy questions, but ones that we all need to contend with. Consider you are one company and your are disrupting yourself faster than your competitor. What happens to the competitor?

ooda loop faster to drive innovation @drnatalie

                                                             Photo Source: Larry Paul

As a CEO, Are You On Track?

In military operations, OODA loops takes place in nano-seconds. In corporations, its decisions are often slower. In the old days, strategy was rigidly followed till next years’ planning cycle. But today, that’s no longer an acceptable mindset. And it’s critical to validate we’re on track and if not, correct it. Using a model like the OODA Loop, along with design-thinking which requires to you go and talk to your customers, your employees, customer’s of your competitors, to industries that are similar to your and industries that have nothing to do with yours.

It’s where the kernel of the seeds of innovation are hatched, born and grown into a full idea. The results of your actions become the observations to re-orient you to make your next decision. Quickly repeating the OODA loop equals success. And as you are doing this, you want to make sure you are making real-time changes that are just changes to make changes, but change to create a “Blue Ocean Strategy.” As defined by the author’s of the book, Blue Ocean Strategy, CEO’s need to quickly create an uncontested marketplace, where the competition is irrelevant.

Who’s Slow to the OODA Loop?

According to the article by Christopher Mims of the Wall Street JournalRonald Boire of Barnes & Noble, GNC Holdings’ Mike Archbold and top executives at three of the six major Hollywood studios making changes faster is very important. Where to look for inspiration? According to Mr. Mims, unlike large corporations, startups don’t need decades to make the changes the businesses need to succeed in the new world. They are nimble, they are always iterating, pivoting, changing, trying new things, not being afraid of conflict…

What does this mean for established companies? They will need to take drastic measures to do the OODA loop faster. What kind of drastic measures? According to the article, these CEO’s must be willing to tell their stakeholders they may have to lose money and cannibalize existing products and services, while scaling up new technologies and methods. Not the same old dog chow most CEO’s having been dishing out.

How Can a CEO Get On Track?

It used to be that you could acquire the start-up that was trying to put you out of business. But in today’s market it takes more than that. Companies that are disrupting the marketplace are growing so quickly, capturing so much market share, they don’t want or need to be acquired. And they can become too valuable to buy or are unwilling to sell. So the questions for you, as a CEO, “Is do you have systems to monitor/measure what employees know, think & feel about what is going on in the business?”

They are often the ones on the front line that really know what is going on and what needs to be done, or at least what isn’t working. “Do you really know what your customers know, think & feel? Or do you have a cordial relationship where the “real deal” is not really discussed?” Honest, conscious conversation is where it all starts. Many people have made careers by learning how to manage-up well. That’s not a bad thing, except when you aren’t telling the CEO the truth about what the troops think, feel and know. But there has to be a cultural environment that always you to be able to safely say the things. That’s not always the case.

And, as a CEO, “Do you take that information that you have gathered from your employees, your customers, all kinds of sources and integrate it into your company?” One of the best ways to stay on top of the game is to monitor social and digital media. If you have a digital / social media command center, where all the top news and information is brought into one central place, you can begin to digest a new picture of the quickly changing landscape very easily. You’ll also want to keep your ear closely attuned to what is happening in the start-up world, regardless of whether it is Silicon Valley or Silicon Beach or Silicon Edge or…

The More Things Change, The More They Stay The Same

To me, all of this sounds like something very familiar to those of us who came from the voice of the customer or quality. Remember Deming, the father of Quality who was pushed out of the American Auto Industry? And then only to be invited to Japan and make their automative industry soar? What was his secret sauce? To listen to their customers and the employees. To make really changes to their products and services based on that feedback!

Start Incubating Innovation

Today, companies must incubate disruptive ideas within their own corporate cultures. And this is not easy, because often it means supporting them as they grow into something truly disruptive. The company might have to absorb their losses. For example, for its first 20 years Amazon made almost no profit. But iterating, pivoting and incubating is not enough. A CEO must maintain the existing business at the same time as they innovate. This is a new and rare skill.

So where best to learn how to think like an OODA Loop CEO? Find a group that help take you through thinking differently, through a design-thinking process where you never know what will come out of it, but it always spurs innovation. You have to cross the chasm, from how you normally do things, to how things have never been done before. That’s a lot of change, so it’s also important to develop those ideas and new innovations in the culture where change and honestly is accepted and appreciated.

@drnatalie

VP, Program Executive, in the Innovation and Transformation Center 
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Want to Know More About Machine Learning and AI?

Wondering whether you should invest in AI and Machine Learning? That’s a question that the most innovative companies are considering. Why consider it? One good reason is because your competitors have already started. If that doesn’t give you some reason to get motivated, I hope you get started before you are put out of business. To make sure that doesn’t happen, there are  a few things to consider to help you start to explore an investment in machine learning.

It’s the Data, Stupid

Of course, as with any business initiative, you’ll want to create value. And this can be done using machine learning systems. But for those systems to provide value, companies will need to begin by evaluating their organization’s data maturity, but more importantly their readiness to accomplish its data-driven goals. Company’s need to start with an audit of their data warehousing, data scientific research capabilities, data governance and data hygiene. In addition, it’s important to look at the sources, uses, volume, and veracity of all your date, meaning your first-, second-, and third-party data.

Garbage in, Garbage Out

Why is making sure your data so clean? Machine learning is basically taking a computer and making it smart enough to learn from the data it’s fed. We are essentially programming machines to learn. The goal is that after a certain point of time, the computer is able to predict further data. How so? Let’s pretend you want to make your computer predict the weather. So to begin, you might feed the computer weather reports of every hour of every over the past year. What you might end up with is– because the temperature (z) depends on day of the year (x) as well as the time of the day (y), more than two-dimensional curve. In fact, weather is random, so the equation generated by the computer won’t just have 3 variables (x, y, z), it may also have higher powers. So depending on the number of factors in a prediction and the randomness of the outcome, the complexity of the curve can increasingly get more complicated.

So back to the data… And I know you know the story about data: garbage in, garbage out. So hopefully, now you see can why good, clean data is so important to prediction. As the computer is taking the data you feed it to make future predictions, those predictions dependent on the data you are feeding it. So you want the very best data possible. And it takes super computers which are capable of handling large volumes of data, as well as the ability to learn fast and to make fast decisions based on the learning it under goes.

AI and ML Are Not The Same

Often times Artificial Intelligence (AI) and Machine Learning (ML) are used interchangeably. But they are actually different. Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart.” Machine Learning is the application of AI based on the idea that we should be able to give machines access to data and let them learn for themselves. Artificial Intelligence devices (devices designed to act intelligently), are often classified into one of two groups: 1) applied and 2) general.

Applied AI is far more common. Applied AI is about systems designed to intelligently trade stocks and shares or drive an autonomous vehicle. Generalized AI is may up of systems or devices that, in theory, can handle any task. And are less common. However, this is where some of the most exciting advancements are happening today.

Deep Learning is A New Area of Machine Learning Research

It was introduced with the objective of moving Machine Learning closer to one of its original goals: that of being Artificial Intelligence. So essentially Deep Learning is a subfield of machine learning concerned with the algorithms inspired by the structure and function of the brain called artificial neural networks. Deep learning has worked it’s way into business language via Artificial Intelligence (AI), Big Data and analytics. Deep learning is an approach to AI which shows great promise when it comes to developing the autonomous, self-teaching systems which are revolutionizing many industries.

The Two Big Ideas: It May Be Possible To Teach Computers to Learn and The Internet is a Source of a Ton of Data

Arthur Samuel, in 1959 is credited as the one who came up with the big idea that it might be possible to teach computers to learn for themselves. That would be in contrast to teaching computers everything they need to know about the world and how to carry out tasks. The second big idea was that the Internet, with huge increase in the amount of digital information being generated, stored and could be used for analysis. So the scientists and engineers realized it would be far more efficient to code computers to think like human beings, and then plug them into the internet to give them access to all of the information in the world.

Neural Networks Are Algorithms

Neural networks are a set of algorithms, modeled loosely after the human brain and designed to recognize patterns. The development of neural networks has been key to teaching computers to think and understand the world in the way we do, in addition to the innate advantages they hold over people such as speed, accuracy and lack of bias. So a Neural Network is a computer system that classifies information in the same way a human brain does. It can be taught to recognize, for example, images, and classify them according to elements they contain. It works on a system of probability – which means that based on data it’s fed, it is able to make statements, decisions or predictions with a degree of certainty. The addition of a feedback loop enables “learning” – by sensing or being told whether its decisions are right or wrong and then can modify the approach it takes in the future.

What Can Machine Learning Applications Do?

Machine Learning applications can read text and work out whether the person who wrote it is making a complaint or offering congratulations. They can also listen to a piece of music, decide whether it is likely to make someone happy or sad, and find other pieces of music to match the mood. They can even compose their own music expressing the same themes, or which they know is likely to be appreciated by the admirers of the original piece.

These are all possibilities offered by systems based around ML and neural networks. The idea is that we should be able to communicate and interact with electronic devices and digital information, as naturally as we would with another human being. And another field of AI – Natural Language Processing (NLP) – has become an exciting area of innovation in recent years, and one which is heavily reliant on machine learning. (And yes, my initials just happen to be NLP, but that doesn’t really mean anything… just a happy coincidence…)

Where is Used?

Take Google for instance. Google is using it in its voice and image recognition algorithms. It is also used by Netflix and Amazon to decide what you want to watch or buy next. And it is also being by researchers at MIT to predict the future.  While Machine Learning is often described as a sub-discipline of AI, we might look at Machine Learning as the state-of-the-art of AI. Why? Perhaps because it is showing the greatest promise to provide tools that industry and society can use to drive change.

More on the practical uses of AI and ML in the future. For now, noodle on that!

@drnatalie

VP, Program Executive, Innovation and Transformation Center

 

 

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Innovation & Disruption In Delivery: Could Your Next Amazon Delivery Be By a Drone?

Ever Had a Package Delivered Late, Not at All Or To the Wrong Address?

One of the most irritating issues with ordering online is whether the package gets delivered and to the right address and on time. I know I’ve experienced this a number of times and what’s interesting is that, as customer’s we don’t always think about the delivery service as the issue, but rather it reflects poorly on the company we by the product from. How to fix this customer experience issue? One option is to deliver packages to consumers’ homes using drones. Could this allow companies to bypass the challenges with that last step of the delivery? It might be for delivery to people’s homes. It might not work at apartments, though, because the drone can’t get into the apartment building. Or can it?

What customers may not know is that the last leg of the delivery is the most expensive and inefficient part of parcel delivery. Customers don’t often think about that the product has to go from a store or warehouse, to the shipper’s delivery center and then from there, be deployed to the customer’s address. It is often not the place you bought the product from that is having the issue. It maybe who their delivery service or services are. It could be the individual who works for the delivery service. I know I personally had package delivered to an address that was similar to mine, but not mine. The individual was new to the delivery route and got mixed up. I had to run after the delivery truck, stop them and tell them they delivered to the wrong building. (I had gotten a text my package was delivered, but it was not on my doorstep or at the post office boxes for my building.) And since this happened more than once, I knew what had happened.

What’s the Solution To Better Customer Experience Delivery?

E-commerce companies, like Amazon, are using drones to speed up the this last part of the delivery process, while cutting costs. The result? Improving the customer experience, customer satisfaction and loyalty. And what’s interesting is even legacy retailers could take advantage of a similar process to grow online sales.

So What’s the Hold Up?

While there are many obstacles to overcome for instance, drone regulations, the development of autonomous flight and traffic control systems for drones, as well as consumer acceptance, there are companies actively trying to figure this all out. For instance, Amazon is working on drone delivery, depending on when and where they have the regulatory support needed to safely delivery packages. They want to use drones to deliver packages to customers around the world in 30 minutes or less. In fact, they have Prime Air development centers in the United States, the United Kingdom, Austria, France and Israel.

Amazon Prime @drnatalie

Photo Source: Amazon

They believe the airspace is safest when small drones are separated from most manned aircraft traffic, and where airspace access is determined by capabilities. To learn more, you can look at Amazon’s airspace proposals here: Best-Served Model for Small Unmanned Aircraft Systems and Revising the Airspace Model for the Safe Integration of Small Unmanned Aircraft Systems.

Disruption to Delivery Logistic Firms

As e-commerce providers like Amazon look for solutions within their own company, many logistics providers are experimenting with drone delivery. These firms also seek to cut costs as well as ward off competition, whether it’s from startups, technology companies or e-commerce companies. In fact, FedEx is betting on automation to Fend off contenders like Uber and Amazon. The shipping giant is investing in autonomous trucks and is interested in delivery robots, drones and an Alexa app. And while there are attempts to get this right, those of us in the innovation space know that #failfast – iterating and pivoting is the key. In my book, it’s ok to fail. You can’t learn what you don’t know, you don’t know unless you try. Trying means you learn something each time. Though the concept of failfast is very popular today, if we look back at Edison, it took him 9,999 times to get the filament for the lightbulb to work on the 10,000th time. What if he gave up? We’d all be in the dark!

How Is Amazon’s Prime Air Trial Drone Deliver Program Progressing?

Amazon have started with a private customer trial, to gather data to continue improve the safety and reliability of their systems and operations. As they gather data, this will bring them closer to realizing this how to use this innovation for all their customers. Does weather affect the delivery? Currently, Amazon is permitted to operate during daylight hours when there are low winds and good visibility. However, they are not using it when it rains, snows or in icy conditions. They feel they need to gather more data to improve the safety and reliability of their systems and operations to expand the offering. They are working with regulators and policymakers in various countries in order to make Prime Air a reality for customers around the world.

Video Source: Amazon

Where Can you Find more Information On the Disruption and Innovation Drone Delivery Can Provide?

In a new report, BI Intelligence examines the benefits drone delivery can provide as an e-commerce fulfillment method. In the report, they look at the different approaches companies are taking to experiment with the new technology and processes involved in this new delivery process. In addition, they look at the key players working in the drone delivery space. And have researched the challenges drone delivery faces in reaching mainstream adoption.

Will Your Industry Be Disrupted? Every Industry Should Be Thinking It Will Be Disrupted!

As I was giving a talk on disruption and innovation, I had many questions from what would be considered very standard legacy firms. What they need to be careful of is being aware of the fact that somewhere, in someone’s basement or garage, someone is probably working on a project that will disruption their industry. It’s customary to do the ostrich: stick you head in the sand. But doing so will only make you a dinosaur, (extinct) if you are not careful.

Disruption and innovation are all around us. Just look at what happened to the taxi industry. Not only did Lyft and Uber transform how customers’ order, receive and pay for rides, but they disrupted an age old industry that had not changed for years. And take GM for instance. They make cars. But they decided to look at cars as a service and invest $500M in Lyft to be part of the cars-as-a-service industry.

Disrupt Yourself or Die

Instead of being one of those industries or companies that waits until an upstart disrupts their revenue model and takes marketshare, why not start innovating within your own company. Too many companies are complacent or don’t have the skills to think outside the box. If you don’t, it may want to seek out a firm that can you help you think through this new and confusing new frontier of design-thinking, innovation and disrupting yourself — as a company and as a person. No one wants to be the company that had the leg up on IBM and caused it’s own demise: i.e, nobody wants their story to go down like Digital Equipment Corporation: DEC.

“Digital Equipment Corporation achieved sales of over $14 billion, reached the Fortune 50, and was second only to IBM as a computer manufacturer. Though responsible for the invention of speech recognition, the minicomputer, and local area networking, DEC ultimately failed as a business and was sold to Compaq Corporation in 1998. The  fascinating modern Greek tragedy in book form by Ed Schein, a high-level consultant to DEC for 40 years, shows how DEC’s unique corporate culture contributed both to its early successes and later to an organizational rigidity that caused its ultimate downfall.” Don’t do a DEC.

@drnatalie

Natalie Petouhoff

VP, Program Executive, Innovation and Transformation Center | Salesforce.com

 

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