Navigating an Enterprise Level Digital Transformation

Digital transformation isn’t a clean and simple process. There is no one singular path when it comes to implementing digital transformation within a company. No one knows this better than Chris Hsu, who was the EVP and GM of HPE software business. He was also the Chief Operating Officer of Hewlett Packard Enterprise. After HPE sold the software business to Micro Focus, he became the Chief Operating Officer of Micro Focus. Chris joined our COO, Lalit Singh to discuss how companies can lead effective digital transformations in our latest Thought Leader Webinar Series.

Digital transformation marks a radical rethinking of how an organization needs to use  technology, people and processes to fundamentally change business performance, Chris Hsu stresses. “Frankly, in today’s day and age, I think that if you are living in old systems and processes, you will be disrupted.”

Fearful of being outflanked by more nimble competitors, companies are seeking to accelerate innovation, experimenting with new digital services and capabilities to augment existing offerings or to slide into adjacent markets. One of the first things companies should do in embarking on a digital transformation is answer this critical question: What business outcomes do you want to achieve?

“It starts with the business outcomes and the new business models you’re going after and working backwards from there,” says Chris Hsu. “There are a number of perspectives to consider including technology, data, and more than anything the people and operational side of the business.”

Companies can follow some key digital transformational tips to affect the kind of change they desire, including:

  • Focus on a clear set of objectives. Whether you’re transforming an existing model or starting from scratch, leaders must reach a consensus on the best path to pursue.
  • Adopt agile execution. Encourage risk taking, enabling even lower-level employees to make decisions, fail fast and learn.
  • Instill focus. Business leaders must recognize it  is a marathon, not a sprint. And in order to present and to be effective over a long period of time, leaders must be mentally and physically fit so they can focus.

While emerging tech and revamped processes are crucial, having the right skills on staff is essential to any digital transformation.

Software engineers, cloud computing specialists and product managers remain key roles for companies seeking to roll out new products and services. DevOps leaders galvanize software development by merging development with operations, enabling companies to continuously iterate software to speed delivery.

Data scientists and data architects are also in high demand, as companies seek to glean insights out of vast troves of data, and transformations lean increasingly on machine learning and artificial intelligence.

Companies can lag in digital transformations for several reasons, a few being poor leadership, disconnects between IT and the business, lagging employee engagement and substandard operations. But, according to Chris Hsu, “I think digital transformation, if you’re doing it correctly, should impact all parts of the organization. Digital transformation has the ability to flatten an organization, and to really start to streamline and remove those manual administrative processes that no one really loves doing, and creates the capacity for more customer-facing interactions,  for more innovation, and fundamentally more building of things.”

This is one webinar, you don’t want to miss. View it here.

How companies need to think about the cloud and digital transformation

Enterprises are at a critical juncture: adopt and adapt technology to meet the 24×7 demands of customers, employees, and partners—or risk becoming obsolete. One of the primary shifts in responding to such demands is cloud computing.

As part of our Udacity Thought Leader webinar series, our very own Lalit Singh, COO at Udacity, sat down with Rahul Tripathi, the CTO and VP of Customer Success at Nutanix to discuss the challenges facing companies looking to embrace the cloud while remaining relevant in today’s competitive market. The conversation anchored on how the cloud is the foundational enabler of digital transformation and offers the scale and speed needed for businesses to grow.

When it comes to transforming the infrastructure of a business, both modernization and automation play crucial roles. For organizations looking to bridge the digital skills gap and attract talent, it’s important to move from outdated to next-generation systems that facilitate innovation. Hear Rahul stress how technical skills and soft skills are critical for any business looking to stay competitive and transform into digital enterprises.

Watch as they discuss:

  • What a modern enterprise cloud strategy looks like
  • Why digital transformation requires the right blend of business, IT and soft skills
  • How organizations can take steps to bridge their hiring and training strategies

View webinar

SXSW: How Top Companies Create Training Data

Udacity had the unique opportunity to have two of our thought leaders on a panel discussion on training data for machine learning entitled AI-AI-Oh! during SXSW 2019. The discussion triggered an exchange of viewpoints among the expert panelists which ranged from how the data is being used in various industries, how much training data you need to apply machine learning, and practical tips for the audience to consider.

You can listen to the entirety of our panel discussion here.

The discussion started with the framing of machine learning. Machine learning (ML) is about teaching computers how to learn from data to make decisions or predictions. For true machine learning, the computer must be able to learn to identify patterns without being explicitly programmed to.

An easy example of a machine learning algorithm is an on-demand music streaming service. For the service to make a decision about which new songs or artists to recommend to a listener, machine learning algorithms associate the listener’s preferences with other listeners who have similar musical taste.

Machine learning fuels all sorts of automated tasks and spans across multiple industries, from data security firms hunting down malware to finance professionals looking out for favorable trades. They’re designed to work like virtual personal assistants, and they work quite well.

Machine learning serves a mechanical function the same way a flashlight, a car, or a television does. When something is capable of “machine learning”, it means it’s performing a function with the data given to it, and gets progressively better at that function. It’s like if you had a flashlight that turned on whenever you said “it’s dark”, so it would recognize different phrases containing the word “dark”.

In machine learning projects, we need a training data set. It is the actual data set used to train the model for performing various actions.

ML relies heavily on data; without data, it is impossible for an “AI” to learn. It is the most crucial aspect that makes algorithm training possible. The panelists discuss three different types of training data including:

Client services data – data generated from customers. “At HubSpot, we gather user-generated training data for ML that informs everything from email send time optimization to audience targeting,” stated Hector Urdiales.

User generated data – data created by users on their own without being prompted.  “We train data based on patterns,” said Rob McGrorty.

Simulated data – sensor data that self-driving cars, for example, collect in the real world. “A test vehicle’s cameras might record video of pedestrians crossing the street at night. Software developers can use that video every time they update their self-driving software, to verify that the software still detects the pedestrians correctly,” explains David Silver.

Essentially, training data is the textbook that will teach your AI to do its assigned task, and will be used over and over again to fine-tune its predictions and improve its success rate. Your AI will use training data in several different ways, all with the aim of improving the accuracy of its predictions.

Quite simply, without training data there is no AI. The cleanliness, relevance and quality of your data has a direct impact on whether your AI will achieve its goals.

Be sure to listen to this informative panel discussion and learn more about training data and practical use cases.

Educating Our Way Out of the Data Scientist Shortage

It’s no secret that employers are looking for data scientists. They have become the stars of the modern workforce – the most valuable employees.

Companies of all sizes have awoke to the fact that data science, by mining new insights from even decades of accumulated data sets, has the potential to drive efficiencies and increase productivity in ways never previously imagined. Simply put, it has the potential to transform businesses. From Zillow’s home price predictions to Amazon’s recommendation engines, applications of data science have become increasingly accurate, prevalent, and impactful on our everyday lives.

But while “data scientist” has been ranked the “No. 1 Job in America” for three years running now, according to careers website Glassdoor, there’s still a shortage of talent to fill the huge need of employers across every industry. In fact, according to a recent LinkedIn study, businesses across the nation need 151,717 more data scientists right now.

The need is nothing short of stunning.

This is why companies understand that they must increasingly invest in the education of their employees in order to compete in an ever-changing world. At the same time, employees need to recognize that traditional higher education just isn’t designed or equipped  to keep up with the breathtaking pace of technological developments and digital transformation that we see in business every single day. People may intuitively know that learning is a lifelong process. But the modern employees also needs to accept that that continually adding to their skill set is the best way they stay competitive in the job market.

Here’s the reality: Jobs are available. But organizations expect potential employees (and current ones) to have the skills to those critical jobs.

The advantage of this digital transformation is that it’s also changing how we think about education. And it truly can be the answer to solving the data scientist shortage within your company.

This ongoing process of learning can take place digitally and independently of location. E-learning can happen anywhere, anytime: at the workplace, at home, on the train, or in the coffee shop. The subject matter can even be adapted to the precise, tailored requirements of a company. This way, it has maximum added value for employees and employers. For example, last year the automobile company Audi launched its employee “data-camp” training focused on big data and artificial intelligence.

Even companies that specialize in data analysis have recognized their own crying need to create alternatives to the traditional training pathways. After all, they are on the front lines of the digital transformation, and their workers need to have cutting-edge skills.

For example, our customer Alteryx, which develops self-service data analysis software, offers a nanodegree that enables regular employees to become data specialists and to expand their own career opportunities. In this way, companies meet the need for data specialists, while employees sharpen their skill sets, receive additional qualifications and ultimately improve their career opportunities.

It becomes a win-win. Organizations benefit the improved effort of employees. The workers themselves expand their horizons.

Employees who have a background in computer science or mathematics – and interact with numbers, data and programming daily – are ideal candidates in terms of becoming data experts in the company. Udacity’s online course, with concrete sample projects and application examples, is usually enough to give employees the added education they need to take that next step within their own company.

But employees outside of traditional IT departments have opportunities to pursue what is known in the industry as  “Citizen Data Scientists.”The term describes employees who evaluate data but do not program the algorithms themselves. Instead, they use self-service tools. These tools enable the analysis and visualization of large amounts of data with preconfigured workflows. The advantage here is that employees usually know more about the context of the data and can bring that understanding directly into their own departments.

Data isn’t the future. It’s now. And it’s critical to every company in every industry.

Companies are looking everywhere for data scientists. They can be academically trained, educating through  internal further education programs, or this relatively new world of Citizen Data Scientists, It’s clear that businesses need all of them because we live in  a world where data is collected everywhere. It’s clear that companies need to invest in employee training to keep pace with digital transformation.

Faced with this dire shortage of talent, business leaders who want to make the most of data science can’t rely on half-measures and casual hiring processes. What they need is a strategic roadmap toward building data science skills internally and effectively upskilling their talented employees.

Stay tuned for new releases from Udacity Enterprise.

Answering “Yes” to Hard Questions About the SKills Gap, and The Future of Work

A recent article from the University of California’s Chief Innovation Officer, about the impact of disruptive technologies on jobs and skills, poses critical questions about how we connect learning to jobs—today, and in the future.

Future of Work

Everyone from politicians to policy makers, utopianists to university professors, innovators to investors, is talking about the future of work, the fourth industrial revolution, and the automation age. It’s hard to avoid these topics, and if you’re between the ages of, say, 16 and 80, you probably shouldn’t avoid them.

Our work lives are changing, and depending on how we manage the transition, this could either be a new golden age, or a serious shock to the system.

At Udacity, we’re engaged in helping lifelong learners across the globe empower themselves through learning, in order to build rewarding lives and careers. As such, we’re acutely aware of the looming changes—the theories around how it’s going to happen, and what it’s all going to mean.

We engage every day with innovators, educators, students, employees and thought leaders, to better understand what education needs to do, be, and represent as we move forward. We work with recruiters, hiring managers, entrepreneurs, and executives, to better forecast what skills will be needed, where the demand will be, and what career advancement will look like in the days, years, and decades to come. We collaborate with individuals, startups, and global corporations, to better understand how and where the work of the future will happen. In short, we spend a vast amount of time learning from anyone and everyone about what the future holds, and how we can best prepare our students to succeed.

We listen, we talk, we watch, we ask, and we read.

One article that recently impressed us for its ambitious scope, rich degree of insight, and clear-eyed understanding of where the world is heading, is a post by Christine Gulbranson, the Chief Innovation Officer for the University of California System. The article is entitled The Future of Work: The Impact of Disruptive Technologies on Jobs and Skills. Here is a sample of the wisdom Gulbranson shares in this provocative and timely piece:

“It’s not difficult to make some basic calculations about what skill sets will be needed in the future: automate predictable manual labor jobs and the skills demanded for such jobs decreases. More automated factories will increase the demand for hard skills in mechanical engineering, software architecture, coding, algorithms, data structures, data analysis/data science, and machine architecture/design. Increasing gene editing and robotic surgery will increase the demand for software engineers and mechanical engineers who also have medical skills. Move to IoT cities and policy makers and lawyers will need to understand coding, software architecture, economics, and more, on top of what they’re expected to know today.

Clearly with a rise of connected devices and infrastructure, machines, AI, spatial computing, blockchain, and autonomous vehicles, there comes an increase in demand for STEAM skills. However, sitting on top of hard skills is a deep and strong layer for cognitive, analytical, and soft skills. Employers won’t be looking for a degree that signifies what a candidate knows: they will be looking for someone who can learn, combine and analyze, problem-solve, create, and adjust.”

It’s that last sentence that especially resonated with us, because this echoes exactly what we hear directly from employers every single day. The pace of modern business and the rapid advance of technology have significantly altered the hiring landscape in such a way that characteristics such as agility, growth mindset, adaptability, creativity, and grit have emerged as the most important factors in predicting a successful hire.

That’s not to say that acquired skills don’t matter—they do!—but the ability to learn new skills and apply them has become just as important as the skills you already possess.

This is also not to say that educational pedigree doesn’t have a place any longer—it does—but what constitutes credible pedigree is changing rapidly. As we’ve learned in the years since first launching our Nanodegree programs, a Nanodegree credential fulfills a dual role. In addition to affirming your skills acquisition, earning a Nanodegree credential stands as evidence that you are a self-motivated problem-solver who possesses grit and determination.

Gulbranson’s article concludes on a sobering note of caution:

“Finally, as we already know today, if education can’t keep up with changing industry, then the skills gap will hinder technological advancement and adoption.”

She goes on to ask some powerful questions, such as:

  • Are students learning how to learn, handle high complexity, and be flexible?
  • Are they learning how to make the invisible visible, and how to make good decisions using data and analysis?
  • Are there solutions that don’t cost an arm and a leg and last four years when the industry needs a software engineer who is also a psychologist to create a product that detects the mood of drivers and auto-shuts off the car appropriately?

We’re proud to be part of a new generation of learning providers offering opportunities that represent a “yes” answer to all the above, and we’re grateful to innovators like Christine Gulbranson who are out there asking the hard questions, and providing the right answers.

Through your commitment to lifelong learning at your organization, you are helping build rewarding careers for employees, while creating an environment for innovation.

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Visit udacity.com/enterprise to discover how we can help your organization successfully navigate workforce transformation!

Future Focused: Udacity and AT&T Join Forces to Train Workers for the Jobs of Tomorrow

AT&T is in the midst of one of the most significant transformations in its more than 140-year-old history, and their work with Udacity enables both the upskilling of its existing workforce, and the development of vital new talent pipelines.

 

Across every sector of the global economy, we are seeing profound signs of transformation as the pace of technological innovation continues to accelerate. From tiny startups to massive corporations, organizations are rethinking the future of work, and what it will require in the way of new approaches to learning, training and hiring.

The Future of Work

As a provider of learning experiences designed explicitly to support career advancement in the digital economy, Udacity sits at the critical junction where employer needs meet employee aspirations. We connect learning to jobs in new and vital ways. Our ongoing collaboration with AT&T offers a powerful example of what is possible when industry and education come together to support digital transformation.

New Skills for a New Century

AT&T is in the midst of one of the most significant transformations in its more than 140-year old history. Theirs is an industry with constantly changing expectations, and customers that demand progress and innovation. The key to success in this environment is employee commitment to continuous learning, powering the company to succeed.

To keep pace, we worked to create a culture of continuous learning. We expect that in the future, the job market will increasingly place a premium on ongoing worker knowledge and training. Accordingly, the demand for us all to be lifelong learners will only intensify. On-demand, mobile, swift, specific skills-based learning is the future.” —John G. Palmer, Senior Vice President, Human Resources, AT&T

AT&T recognized they needed a workforce with more than just relevant hard skills—they needed continuous learners that were focused, curious, and driven to master the very latest tools and technologies. They also realized their transformation efforts would require a two-pronged approach: they would need to upskill their existing workforce, while simultaneously developing new talent pipelines that would deliver exceptional candidates. To help accomplish this, AT&T joined with Udacity in 2014 to co-create our first Nanodegree programs, which was ultimately integral to our by-industry, for-industry approach to education and training.

Today, AT&T spends upwards of $200 million a year on their flagship internal training curriculum, known as T University. This effort enables their existing employees to take hands-on courses in subjects like data science and machine learning. The company also provides more than $24 million in tuition aid annually to enable their employees to engage in learning outside the company. More than 2,000 AT&T employees have completed Nanodegree programs.

Internship opportunities and new talent pipelines

Parallel to these internal upskilling and reskilling initiatives, a number of Udacity graduates from outside the company have been recruited and hired through AT&T’s Technology Development Program (TDP), which was developed to bring software development interns into the organization, and provide them the opportunity to learn, work, and earn full-time roles.

“We’ve put Udacity graduates in many different roles such as full-stack development, front-end, back-end, & iOS development; they’ve succeeded in all of these places … Whether those Nanodegree graduates have formal STEM education or not, Udacity has prepared them for their internship, and our colleagues in other parts of the business have been pleased with the results.” —Teresa Ostapower, Senior Vice President, Technology Transformation, AT&T

Swati Lingaraj Kamtar is an Associate Applications Developer at AT&T. She was hired through the TDP internship program, after having completed Udacity’s Front-End Web Developer Nanodegree program. She’s a perfect example of how genuinely committed to their employees—and to continuous learning—AT&T really is; she’s already enrolled in a new Nanodegree program, with the full support and encouragement of her supervisor at AT&T.

“Our Udacity hires come from varying backgrounds and thus bring different perspectives that we appreciate. At AT&T, we value teamwork and the idea that a small group of talented people is more innovative than a single person. Adding those different life experiences and skills into our teams is valuable as we drive forward as a company.” —Teresa Ostapower

Robert Anderson has been an AT&T employee for two years now. He too came to the company via Udacity and the TDP internship program. It nearly didn’t happen for Robert. The first time he became aware of the opportunity, he didn’t apply for the internship. He didn’t believe he was qualified. He’d come to programming late in life, and only after spending years in other fields. He was barely three months into a Udacity Nanodegree program, and in his own words, he was actually “terrified.” But shortly after he graduated, he had another opportunity to apply for an internship, and this time, he took it. He not only landed an internship, he then earned a full-time role. Like Swati, he also returned to Udacity for more learning.

To hear Robert describe getting offered the full-time role, and to experience his passion for learning is to witness firsthand the true depth of AT&T’s commitment, and the true value of a Udacity education:

“I wanted to stay with AT&T, and for them to give me the opportunity; it was an amazing feeling. It was kind of like fireworks going off; like, I did it, I’m actually legitimate in the field, I actually have the skill set. It was a great moment. The more you learn, the more you get out of life. You’re increasing your awareness and your understanding of what’s going on, you’re leveling up. I can’t think of a better endeavor than to invest in yourself and to be the best you can be.”

A culture of continuous learning

Udacity was founded to offer innovative new learning experiences to individuals seeking to master the most important, the most-cutting edge, and the most valuable 21st century skills. As our work with AT&T makes clear, these learners—curious, independent and tenacious,—are earning their places in tomorrow’s workforce, today.

“AT&T has a long-standing history of innovation, and of driving technological advancements that literally change people’s lives. To do that, we have to have employees who are innovative, who are curious, and who are constantly pushing the bounds of what’s next.” —Jenifer Robertson, President – Field Operations, AT&T

The future of work is about creating a culture of continuous learning. AT&T knows this firsthand, as the success of their transformation efforts demonstrates. We are honored to be a part of these efforts, and thrilled to see our graduates joining an organization like AT&T, and making important contributions to their ongoing success.

 

To learn how Udacity for Enterprise is enabling AT&T’s digital transformation, join us for an upcoming Intro to Udacity webinar (register here) or visit us at www.udacity.com/enterprise.

Workforce Transformation: What It Means to Your Organization & Employees

Bridge the #AI skills gap

As companies continue to try to innovate, digitize and transform their operations, the demand for technology talent has never been higher. Training talent for the future and building a stronger workforce, in many cases, requires traditional businesses to think and act more like a nimble startup. Companies today need to reskill the workforce, inject new talent, and enable them a new way of working. Without skilled staff, there can be no digital transformation.

The reality is business has transformed and evident all around us including small changes in everything from how food is made and delivered, to how financial transactions are conducted, to how products are made, operated, and sold result in fundamental changes to how we live and work. Artificial intelligence (AI) and machine learning technologies are poised for a monumental impact.

The New York Times estimates that there are only 10,000 people in the world right now with “the education, experience and talent needed” to develop the AI technologies that businesses are betting on to create a host of new economic opportunities. Speculative figures indicate that there are around 300,000 AI practitioners globally, but millions more roles available for people with these qualifications.

The critical issue for companies lies in the fact that AI expertise comes at a price—meaning that only those organizations with the necessary resources and clout are able to attract machine learning talent. This is reflected in booming annual salaries and startling industry recruitment efforts. There is still a pronounced shortage of AI talent. In fact, it is getting worse as more and more enterprises form their own AI groups and make AI part of their corporate strategy,” argues Gary Kazantsev, Bloomberg’s Head of Machine Learning. It’s clear that recruiting one or two AI experts—a challenge in itself—won’t be enough to make the technology an actionable success in 2018.

While skills and training initiatives play catch-up, ballooning salaries, scarce talent, and an aggressively competitive hiring landscape means that the race is already on between those who stand to gain the most from AI through the ability to adopt early on, and those who will be trailing behind in their dust. This is what the AI skills gap looks like—and right now, it’s a gap that is only widening. The growing disparity between the hiring power of companies and the present scarcity of AI talent has big implications, not only for determining the winners and losers of the AI revolution, but for the future of the workforce itself. This is no longer a ‘simple’ question of technology, but of skills, personnel, and strategy. As AI technologies become a reality, companies and their workforce must keep up—and they must do so quickly.

Read our whitepaper and find out how your company can bridge the AI talent gap. Download here.