Tag Archives: autonomous vehicles

Why Most Corporate Innovation Programs Fail

(And How To Make Them Succeed)

Why Most Corporate Innovation Programs Fail

GUEST POST from Greg Satell

Today, everybody needs to innovate. So it shouldn’t be surprising that corporate innovation programs have become wildly popular. There is an inherent tradeoff between innovation and the type of optimization that operational executives excel at. Creating a separate unit to address innovation just makes intuitive sense.

Yet corporate innovation programs often fail and it’s not hard to see why. Unlike other business functions, like marketing or finance, in a healthy organization everybody takes pride in their ability to innovate. Setting up a separate innovation unit can often seem like an affront to those who work hard to innovate in operational units.

Make no mistake, a corporate innovation program is no panacea. It doesn’t replace the need to innovate every day. Yet a well designed program can augment those efforts, take the business in new directions and create real value. The key to a successful innovation program is to develop a clear purpose built on a shared purpose that can solve important problems.

A Good Innovation Program Extends, It Doesn’t Replace

It’s no secret that Alphabet is one of the most powerful companies in the world. Nevertheless, it has a vulnerability that is often overlooked. Much like Xerox and Kodak decades ago, it’s highly dependent on a single revenue stream. In 2018, 86% of its revenues came from advertising, mostly from its Google search business.

It is with this in mind that the company created its X division. Because the unit was set up to pursue opportunities outside of its core search business, it didn’t encounter significant resistance. In fact, the X division is widely seen as an extension of what made Alphabet so successful in the first place.

Another important aspect is that the X division provides a platform to incubate internal projects. For example, Google Brain started out as a “20% time project.” As it progressed and needed more resources, it was moved to the X division, where it was scaled up further. Eventually, it returned to the mothership and today is an integral part of the core business.

Notice how the vision of the X division was never to replace innovation efforts in the core business, but to extend them. That’s been a big part of its success and has led to exciting new business like Waymo autonomous vehicles and the Verily healthcare division.

Focus On Commonality, Not Difference

All too often, innovation programs thrive on difference. They are designed to put together a band of mavericks and disruptors who think differently than the rest of the organization. That may be great for instilling a strong esprit de corps among those involved with the innovation program, but it’s likely to alienate others.

As I explain in Cascades, any change effort must be built on shared purpose and shared values. That’s how you build trust and form the basis for effective collaboration between the innovation program and the rest of the organization. Without those bonds of trust, any innovation effort is bound to fail.

You can see how that works in Alphabet’s X division. It is not seen as fundamentally different from the core Google business, but rather as channeling the company’s strengths in new directions. The business opportunities it pursues may be different, but the core values are the same.

The key question to ask is why you need a corporate innovation program in the first place. If the answer is that you don’t feel your organization is innovative enough, then you need to address that problem first. A well designed innovation program can’t be a band-aid for larger issues within the core business.

Executive Sponsorship Isn’t Enough

Clearly, no corporate innovation program can be successful without strong executive sponsorship. Commitment has to come from the top. Yet just as clearly, executive sponsorship isn’t enough. Unless you can build support among key stakeholders inside and outside the organization, support from the top is bound to erode.

For example, when Eric Haller started Datalabs at Experian, he designed it to be focused on customers, rather than ideas developed internally. “We regularly sit down with our clients and try and figure out what’s causing them agita,” he told me, “because we know that solving problems is what opens up enormous business opportunities for us.”

Because the Datalabs units works directly with customers to solve problems that are important to them, it has strong support from a key stakeholder group. Another important aspect at Datalabs is that once a project gets beyond the prototype stage it goes to one of the operational units within the company to be scaled up into a real business. Over the past five years businesses originated at Datalabs have added over $100 million in new revenues.

Perhaps most importantly, Haller is acutely aware how innovation programs can cause resentment, so he works hard to reduce tensions through building collaborations around the organization. Datalabs is not where “innovation happens” at Experian. Rather it serves to augment and expand capabilities that were already there.

Don’t Look For Ideas, Identify Meaningful Problems

Perhaps most importantly, an innovation program should not be seen as a place to generate ideas. The truth is that ideas can come from anywhere. So designating one particular program in which ideas are supposed to happen will not only alienate the rest of the organization, it is also likely to overlook important ideas generated elsewhere.

The truth is that innovation isn’t about ideas. It’s about solving problems. In researching my book, Mapping Innovation, I came across dozens of stories from every conceivable industry and field and it always started with someone who came across a problem they wanted to solve. Sometimes, it happened by chance, but in most cases I found that great innovators were actively looking for problems that interested them.

If you look at successful innovation programs like Alphabet’s X division and Experian’s Datalabs, the fundamental activity is exploration. X division explores domains outside of search, while Datalabs explores problems that its customers need solved. Once you identify a meaningful problem, the ideas will come.

That’s the real potential of innovation programs. They provide a space to explore areas that don’t fit with the current business, but may play an important role in its future. A good innovation program doesn’t replace capabilities in the core organization, but leverages them to create new opportunities.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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The Power of Big Data

Driving Innovation and Insights in the Digital Age

The Power of Big Data

GUEST POST from Art Inteligencia

In today’s digital age, the massive amounts of data generated every second have unparalleled potential to drive innovation and provide invaluable insights across various industries. With the advent of big data analytics, organizations can now harness this enormous volume of information to unlock new opportunities, improve decision-making processes, and foster growth. In this article, we will explore the transformative power of big data through two case studies, showcasing how businesses have leveraged it to drive innovation and gain unparalleled insights.

Case Study 1: Amazon’s Personalized Recommendations

Amazon, the world’s largest online retailer, has revolutionized the way we browse and shop by effectively utilizing big data analytics. By leveraging extensive customer data, including browsing history, purchase behavior, and product ratings, Amazon has developed an incredibly effective recommendation system that personalizes each user’s shopping experience.

Through the power of big data, Amazon’s algorithms analyze millions of data points to make predictions about a customer’s potential interests. These recommendations have significantly increased customer engagement, driving sales and loyalty. In fact, it’s estimated that approximately 35% of Amazon’s revenue comes directly from these personalized recommendations.

By leveraging big data insights, Amazon understands customer behavior patterns, which allows them to optimize their supply chain management, inventory, and product placement. This invaluable knowledge enables Amazon to forecast demand accurately, reduce costs, and optimize their operations, contributing to its position as an industry leader.

Case Study 2: Google’s Self-Driving Cars

The development of self-driving cars by Google’s parent company, Alphabet, illustrates how big data is transforming the automotive industry. Google’s autonomous vehicles rely on a multitude of sensors, including cameras, radar, and LIDAR, to collect and process vast amounts of real-time data about the vehicle’s surroundings.

Big data analytics enables these vehicles to react dynamically to changing road conditions, avoiding accidents, and providing a safe driving experience. Through machine learning algorithms, these cars continuously analyze the collected data to improve their decision-making capabilities over time.

Moreover, the data collected by these self-driving cars provides invaluable insights into traffic patterns, road conditions, and potential hazards. This knowledge can be utilized to optimize urban planning, reduce congestion, and improve infrastructure. By leveraging big data, Google has not only created a groundbreaking technology but has also paved the way for a smarter and safer future of transportation.

Conclusion

These case studies clearly demonstrate the immense power of big data in driving innovation and generating invaluable insights. From revolutionizing customer experiences to transforming entire industries, big data analytics has become an integral part of businesses across the globe. Embracing and effectively leveraging the potential of big data will not only enhance decision-making processes but also foster growth and lead to a more efficient and prosperous future in the digital age.

Image credit: Pixabay

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The Future of Transportation

Autonomous Vehicles and Beyond

The Future of Transportation: Autonomous Vehicles and Beyond

GUEST POST from Chateau G Pato

Transportation has always been an essential element of human progress and development. From horse-drawn carriages to steam locomotives and automobiles, our journey towards efficient mobility has been nothing short of remarkable. However, the next phase of transportation promises to be truly revolutionary, thanks to the advent of autonomous vehicles. In this article, we will explore the potential of self-driving cars and highlight two intriguing case studies that illustrate the trajectory of this transportation revolution.

Case Study 1: Waymo’s Self-Driving Taxis in Phoenix

A prominent player in the field of autonomous vehicles is Waymo, a subsidiary of Alphabet Inc. (Google’s parent company). Waymo has been steadily forging ahead with its self-driving taxi service in Phoenix, Arizona since December 2018. This ambitious project aims to replace traditional ride-sharing services by providing fully autonomous transport to residents in the Phoenix metropolitan area.

Waymo’s test fleet consists of various autonomous vehicles equipped with an array of sensors, Lidar, radar, and computer vision systems. These technologies enable the cars to perceive their surroundings, navigate complex traffic situations, and interact with pedestrians and other road users safely. As of 2021, Waymo’s taxis have successfully completed over 20 million miles on public roads in autonomous mode, honing their capabilities through machine learning algorithms.

The Phoenix case study showcases the potential of autonomous vehicles to revolutionize daily commuting. By removing the need for human drivers, self-driving taxis can significantly reduce traffic congestion, carbon emissions, and the costs associated with car ownership. Moreover, they offer improved accessibility to transportation for those who are unable to drive, such as the elderly or individuals with disabilities. Waymo’s ongoing success in Phoenix hints at a future where autonomous transportation becomes the primary mode of urban mobility.

Case Study 2: Tesla’s Autopilot and Full Self-Driving Capability

While Waymo focuses on ride-sharing, Tesla, the electric vehicle pioneer, has been at the forefront of enabling autonomous driving for personal vehicles. Tesla’s Autopilot system, a suite of advanced driver-assistance features, has been available in their vehicles since 2014. Over the years, Tesla has continuously refined and expanded its Autopilot capabilities, aiming to eventually achieve full self-driving (FSD) capability.

Tesla’s approach to autonomy revolves around utilizing an ever-increasing fleet of vehicles to collect vast amounts of data. Those data are then used to train machine learning algorithms, which inform the development of autonomous driving software. Through regular over-the-air updates, Tesla’s global fleet’s driving experiences continuously contribute to the improvement of their autonomous technology.

This case study demonstrates the power of leveraging data and machine learning to achieve greater levels of autonomy. Tesla’s wide-reaching network of vehicles, each acting as a data-gathering entity, allows for rapid advancements in autonomous driving capabilities. As Tesla’s FSD technology matures, it has the potential to transform personal transportation, offering individuals the freedom to relax or be more productive during their journeys.

Looking Beyond Autonomous Vehicles

While autonomous vehicles are undoubtedly the future of transportation, the revolution extends beyond cars. Other transportation modes, such as trucks, buses, and drones, are also ripe for autonomous disruption. Self-driving trucks, for instance, have the potential to revolutionize logistics and freight transportation by maximizing efficiency and minimizing the risk of human error. Furthermore, autonomous drones could soon revolutionize last-mile deliveries, bringing packages directly to our doorsteps more efficiently and at lower costs.

Conclusion

The future of transportation lies in autonomous vehicles and beyond. The case studies of Waymo and Tesla illustrate the significant progress being made towards this future, where fully autonomous transportation becomes the norm. As we ride this wave of technological innovation, it is crucial to embrace the opportunities and challenges that autonomous vehicles present. By doing so, we can shape a future of transportation that is safer, more efficient, and more sustainable for us all.

Bottom line: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Pexels

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The Impact of Autonomous Vehicles on Society

The Impact of Autonomous Vehicles on Society

GUEST POST from Chateau G Pato

With the emergence of autonomous vehicles (AVs), society is now at a crossroads, on the cusp of a whole new reality in transportation and mobility. AVs offer many benefits, including improved safety, reduced emissions, and increased efficiency. They also come with some risks, including a disruption of infrastructure and labor, as well as the potential for increased privacy concerns. As AVs become increasingly integrated into our society, it is important to consider both the benefits and risks of this new technology so that we can maximize its potential and minimize its drawbacks.

The potential benefits of AVs are immense. In terms of safety, human error is the leading cause of automotive fatalities, accounting for 90 percent of fatal accidents. AVs are equipped with advanced sensory systems that can enable them to be significantly safer drivers than their human counterparts. They can sense potential hazards on the road better than a human driver, and their reaction times are significantly faster. Furthermore, due to their automation, the risk of fatigue among drivers is eliminated, which can reduce the risk of accidents.

In terms of efficiency, AVs can help reduce traffic congestion due to their increased accuracy in predicting road conditions and their ability to plan routes more efficiently. By reducing congestion, AVs could result in improved efficiency for transportation, reducing both fuel consumption and air pollution. Additionally, by removing the need for direct human control, AVs can enable people to engage in other tasks while in transit, potentially improving productivity and reducing commute times.

While there are many potential benefits to AVs, it is important to recognize the potential risks as well. One of the most pressing concerns is the potential for AVs to displace existing workers. Truck drivers, taxi drivers, and other occupations that rely on human driving could become obsolete as self-driving vehicles become more commonplace. This could result in an increase in unemployment and social unrest. Furthermore, AVs require robust infrastructure and connectivity for them to work efficiently. This could also have a disruptive effect on existing infrastructure and require significant investment, both financially and in terms of time. Additionally, AVs raise serious concerns about the potential for surveillance and privacy, as data collected by the vehicles could be exploited by third parties.

As AVs become increasingly integrated into our society, it is important to recognize the potential benefits and risks. To illustrate this, two case studies are worth looking at.

Case Study 1 – GoMentum Station (USA)

The first is a pilot program in California called “GoMentum Station”, which was launched in 2017 by Honda to test autonomous vehicles on a closed-off track. The program has had great success and opened the door to further discussion of the potential for AVs in the public space.

Case Study 2 – Drive.ai (Singapore)

The second is a pilot program in Singapore called Drive.ai, which launched in 2018 and is testing AVs in a variety of situations, including mixed traffic roads, highways, and bad weather. These case studies provide insight into the potential for AVs to benefit society, while also highlighting the potential risks.

Conclusion

Overall, AVs have the potential to revolutionize transportation and mobility. With their increased safety features and efficiency, they could offer many benefits to society in the long run. However, it is important to consider the potential risks before introducing AVs into the public space, so that we can ensure that their benefits are maximized while their drawbacks are minimized.

Bottom line: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Pixabay

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Exploring the Impact of Autonomous Vehicles on the Future of Transportation

Exploring the Impact of Autonomous Vehicles on the Future of Transportation

GUEST POST from Art Inteligencia

Autonomous vehicles (AVs) are quickly becoming a reality, with various companies and governments actively researching and developing the technology. AVs have the potential to revolutionize transportation, as they can provide a safer, more efficient, and more affordable way for people to get around. In this article, we will explore the impact of AVs on the future of transportation.

1. Reduced Accidents: One of the major benefits of AVs is that they could drastically reduce the number of accidents on the roads. By relying on advanced sensors and algorithms, AVs can make decisions much faster than humans and can respond to potential threats in a fraction of a second. This could lead to a significant reduction in the number of traffic fatalities and injuries.

2. Improved Efficiency: AVs are also expected to improve the efficiency of transportation. By coordinating with each other, AVs can travel closely together, reducing congestion and improving traffic flow. Additionally, AVs could take over mundane tasks like driving in slow-moving traffic, freeing up time for people to do other activities.

3. Lower Costs: AVs could also reduce the cost of transportation. By relying on electric power instead of gasoline, AVs could reduce the amount of money people spend on fuel. Additionally, AVs could be shared by multiple people, reducing the cost of owning a car.

4. Increased Accessibility: AVs could also increase accessibility for people who cannot drive. By providing a safe and affordable way for people to get around, AVs could open up transportation to those who are unable to drive, such as the elderly and people with disabilities.

5. New Business Models: Finally, AVs could also lead to the emergence of new business models. Companies could offer ride-hailing services with AVs, while other companies could offer subscription services that allow people to access a pool of AVs as needed. Additionally, AVs could be used to deliver goods, which could lead to a more efficient delivery system.

The potential impacts of AVs on the future of transportation are immense. From reducing the number of accidents and increasing efficiency to reducing costs and increasing accessibility, AVs could revolutionize the way people get around. With continued research and development, AVs could soon become a reality and could pave the way for a more efficient, safer, and more affordable future of transportation.

Bottom line: Futurology and prescience are not fortune telling. Skilled futurologists and futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Pixabay

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