Disrupting Rocket Science
The National Aeronautics and Space Administration (NASA) was created in 1958 in response to Russia’s 1957 Sputnik launch, throughout most of its history NASA’s main competition came from Russia’s space program. Developing space programs is a massively complex and expensive effort requiring big government investments, the total cost of NASA’s space shuttle program that ended in 2011 is estimated at $200 billion. The term “it’s not rocket science” has been used since the 80’s highlighting the complexity of this work and how other tasks are much simpler by comparison. Today NASA is working on its new Orion spacecraft with plans to take humans back to the moon and eventually Mars in the coming decades. Similar government backed space programs are in the works in Russia, China, India and Japan. However today space exploration is not limited to government backed ventures, it now includes private companies backed by entrepreneurs starting with Blue Origin in 2000. These private companies and entrepreneurs are not only participating in space exploration programs but actually helping to advance the field of “rocket science”. These companies have developed spacecraft in a shorter time and at lower costs than NASA or other major aerospace companies, have the ability to simultaneously and smoothly land the flight-tested (aka reused) boosters back on earth, can do dual launches from opposite sides of the country in as many days, and of course, even put a Tesla roadster in orbit.

Today NASA depends on these companies for cargo transport to the international space station with more collaborations being planned for the future. When government backed rocket science and space exploration, arguably considered some of the more demanding human enterprises, can be disrupted by new comers in a relatively short time then is any company safe from disruption?

A Fast Moving Technology Target
Technological advancement has been a great driver of disruption. An important area that has gone through very rapid growth in recent years, with no expectations for a slowdown, is data analytics. While data analytics has been around for a very long time, the recent growth in capabilities and impact is astounding. Our greatly increasing ability to collect data and our advances in data processing, storage and analysis have provided new and unprecedented opportunities to grow knowledge, disrupt incumbents and impact society. But the speed of development has also made it very difficult for companies to keep up. One can get a sense of how fast these developments have taken place by looking at the analytics space. It wasn’t that long ago that D.J. Patil then at LinkedIn and Jeff Hammerbacher then at Facebook sat down to discuss how they were building their data and analytics teams to handle their growing needs and settled on the term Data Science to describe their team’s special skills, a term that has since become not just a buzzword but a highly recognized in-demand discipline. This was 2008, a time when other leading technology companies like Google and Microsoft were grappling with similar issues as they were building and expanding their data analytics efforts and teams. The developments in this space were led mainly by technology and finance companies, other industry sectors were not yet broadly engaged. By 2011 a McKinsey report was calling out the use of big data as a key basis of competition and growth for individual firms and that data analytics had become a necessity and differentiator in all sectors of the economy. It further estimated that by 2018 there could be a shortage of 140 – 190K people with deep analytical expertise. At this time there were less than 10 Master’s Degree programs in analytics and data science offered in the US which meant that the supply of data scientists would not be growing very quickly, that number has since grown to around 220 as universities rush to meet the demand. Then in 2012 Harvard Business Review published an article – Data Scientist: The Sexiest Job of the 21st Century, and by 2015 The U.S. government had hired its first Chief Data Scientist. In 2017, LinkedIn listed Machine Learning and Data Science as the top two emerging positions. As other companies began to look into big data and the increasing value of analytics, they found that the corporate roadmap had not yet been written for how to approach the move to big data and analytics and that hiring data scientists was virtually impossible. Understandably many of these companies have been struggling to get up to speed with data analytics, but while they are working to get started the field continues its feverish advance going from mostly classical statistical analysis of big data in its early days to heavy use of machine learning, artificial intelligence and deep learning, image and voice recognition. Creating an even bigger challenge for companies still trying to get started. I have lived through these developments and led many of the changes at Microsoft, even so I am still amazed by the speed at which change has and is taking place.

The developments in analytics have been accompanied and enabled by corresponding developments in data processing and storage including the evolution from relational data bases to NoSQL, growth of the Hadoop/MapReduce platform and application framework, expanding from data warehousing to data lakes, migration from in-house data centers to storage as a service on the Cloud, together with our growing ability to collect and process data through IoT, edge technologies and upcoming quantum computing.

Companies Have To “Mind The [Technology] Gap”
Although disruption and innovation have been around throughout our history, this fast paced technology driven innovation is impacting all areas of human endeavor and growing the adoption gap for those that hesitate to jump on the trends. There are many examples of the disruption happening today, even in long established and commonplace areas – those that are “not rocket science”. I highlight only a few of these for illustration starting with the once large and profitable brick and mortar retail businesses that are now fighting to remain viable while Amazon, a relatively new entrant established in 1994, has grown to account for almost 50% of all online retail sales in the US and is well on its way to become a one trillion dollar company. In contrast Sears, at one time the largest retailer in the United States, is struggling to survive. Finance is also being disrupted, long time established financial companies are being impacted by new FinTech startups, initially Mint and later others like Betterment introduced robo advisors causing established investment firms to play catchup. Investment banks and venture capital firms themselves are having to compete with Initial Coin Offerings (ICOs) that have been successfully used by many startups to bypass them and raise money directly from investors. Even Taxi service, which has been around pretty much unchanged since the 17th century, has not been immune. In 2017 Uber took over the lead in New York City daily trips from Yellow Taxi and that same year the Yellow Cab Company in Cleveland Ohio shut down after 80 years of service due to disruption from new comers Uber and Lyft, founded in 2009 and 2012 respectively. In today’s fast moving world even the technology leaders, used to dealing with rapid change, know they too can be disrupted if they don’t keep innovating. The digital ad market is an example, the leaders Alphabet and Facebook account for approximately 70% of all digital advertising in the US yet they are starting to see their share fall according eMarketer due to pressure from Amazon now commanding 49% of first product search, Snapchat and others.

Jumping On The Technology Curve May Be Hard, But Not Impossible
Not all established companies are sitting back and letting themselves be disrupted, as I previously shared, leading companies are benefitting from innovation. One company investing heavily in new technologies is Walmart, the world’s largest retailer, displacing Sears as the largest U.S. retailer in 1989. Walmart has always had a strong history of data and analytics use for its operations, now it is investing heavily in e-commerce to fight back Amazon and is expecting a 40% increase in online sales this year, it is also starting to use blockchain to reduce from six days to two seconds the time it takes to track produce. Kroger, America’s largest supermarket chain, plans to spend $9 billion over the next three years to build out its e-commerce and omnichannel businesses, and is working with a startup to provide a driverless delivery service. Monsanto is becoming a farming data and analytics company and leading the way in the digital transformation of farming through products including Climate FieldView that offers features like field-level weather and field data visualization. And Blackrock, the world’s largest money manager, has started to replace its stock pickers with robots.

“The world as we have created it is a process of our thinking. It cannot be changed without changing our thinking.” Albert Einstein

However, adjusting to the new world of technology can be very difficult for established companies causing many of them to lose out to new entrants or more nimble competitors. This is in no small measure due to the newness of the technologies and organizational skills required to implement and benefit from them, and the incredible speed with which technology is changing. But even when innovating, companies must keep in mind that there is a distinction between what Christensen calls sustaining innovation and disruptive innovation, the latter of these is the game changer but requires changing the thinking of the organization. Jumping on the technology curve to drive sustaining innovations can be challenging but can be accomplished with the right level of commitment and resources. However jumping on the technology curve to drive disruptive innovation is a much more difficult task for established firms, but the rewards of disruption can be huge as evidenced by the above examples. Working with companies, I have come across several cases where the new technology being implemented is for the purpose of “doing what we already do just faster and/or more economically”, this may be fine but in these cases they were likely missing the much bigger opportunity and in doing so risking becoming prey to disruption. Why is disruptive innovation hard? in a 1990 paper Henderson and Clark explain how the corporate structure and systems in place facilitate component-level innovations that fit well within the existing organization but makes it difficult to carry out innovations that destroy the usefulness of the existing architectural knowledge, not the least of which is the skills and competencies that have been built up and coveted in the organization over time and whose ongoing value is threatened by the new trends. Anyone having spent time in large companies or organizations has likely experienced these types of organizational dynamics when dealing with disruptive changes.

While it can be difficult for an established company to leverage the new technology for disruptive innovation, doing so on a timely manner is a must for ongoing success in today’s world.

It is much better to disrupt your own product or service through innovation than to sit back and watch others do it.