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Max Just is accompanied by a special guest on this episode of Future of Work. Julie Seitz is an expert on all things workspace, which makes her the perfect partner for the topic of—you guessed it—the future of workspaces. While she notes that an enterprise can’t necessarily futureproof themselves in this regard, she encourages them to get out of their insular spaces for the sake of spotting trends in how people are working in universities, airports, etc. Flexibility and simplicity in a workspace make more practical investments than technological ones that will become outdated. Julie also reflects on the evolution of the public school classroom and how examining that process helps illustrate how different generations work differently. Max jumps in with the ah-hah moments he had while working with Julie, including the importance of providing collaborative workspaces for collaborative work. Ultimately, Max and Julie agree: workspaces matter.

NASA’s Pam Wolfe joins us to discuss their RPA journey, which started over two years ago in their Shared Services Center. Establishing RPA governance across NASA has taken time, strategy, and strong support across the agency. In many ways, NASA’s move to RPA is very similar to the typical enterprise, but let’s not forget—NASA sends people to space. In fact, a recent decision was made to send astronauts to the moon and Mars by 2024. In order to reach their goals, NASA went through a cultural and digital transformation shift that received a high level of support from the top—which Pam defines as a necessity. Naturally, governance and security is of the utmost importance during this transformation. Pam shares some astonishing numbers in regard to their progress while laying out a path for the lay-enterprise, if you will, to accomplish similar workflow evolutions.

In this episode, IEEE’s Lee Coulter discusses the notion that the future of every successful company will depend on its transformation into a technology services business—even the local pizza joint. This far-reaching conversation covers the entirety of the current “data chasm.” Lee kicks the discussion off by justifying his aversion to the term RPA. He notes that organizations start with task automation before moving onto intelligent automation, a process that gets lost in the blanket term RPA. Lee says, “Where we are today and what's now happening is that the tool makers and the advanced practitioners are beginning to interact with unstructured data and expanding the use case to now include unstructured data. There's several different specific scenarios in which that occurs. Service initiation almost always begins with unstructured requests, like to a call center or chatbot.”

Kenneth Farrugia is the chief business development officer with the Bank of Valletta. Kenneth starts this conversation off with a bang, making the case that if banks don’t stay on top of the technological revolution, they run the risk of becoming irrelevant. Next, Kenneth, perhaps counterintuitively, labels legacy financial operations who’ve jumped on board with Industry 4.0 as FinTechs, while the up-and-comers are TechFins. Of course data and security is a big part of the conversation as well. Balancing the convenience of turning over one’s data with the risk of data breaches and/or privacy concerns is on the forefront of every financial institution’s mind. Kenneth discusses additional pain points to the future of banking, both for the client and corporation, and potential solutions for those pain points.

Juan Araya discusses structuring for scale from the eyes of the disruptor and disruptee—both of which Juan knows well. Juan reminds us that before making any actionable change, an end goal must be set. Next, Juan discusses the role speed plays in structuring for scale. Some industries need to move faster than others, which affects their decision making. In the case of Uber, Juan understood that transformative technology supported the speed of change Uber strived for, even more than the other scaling components: people and process. On the flipside, scaling legacy organizations quickly and through technology-first means isn’t conducive to success. His new role with Stryker moves slower and with an enterprise-wide intention different than Uber’s, which Juan details well. Finally, Juan paints a metaphor between scaling and art.

Robert Welborn joins us again for the second part of autonomous vehicle myths. During this discussion, Robert compares the vast and critical differences between the capabilities of today’s math and the necessity of developing tomorrow’s math before fully autonomous vehicles are a safe, mainstream option. He parses out the weakness in today’s autonomous vehicles. For example, converting visual information into digital information and then trying to extract features from that before making a decision off of those inputs. As one could imagine, and as Robert so vividly depicts, there are issues—namely safety—in expecting a computing system to respond quickly and correctly to the infinite numbers of inputs it may receive. Robert closes the discussion with a few viable ways of progressing the technology.

Dmitri Popov, global service management lead for Mann + Hummel Group, joins us today to discuss scaling RPA. Dmitri himself admits that such a process is painful, in part because of the few successful enterprise examples for which to model after. Dmitri points to IBM as a company who has done it well. Next, Dmitri discusses how to leverage shared services in the most efficient way, exemplifying R&D and certain purchasing aspects. One of the most difficult components of implementing RPA across the workflow is acceptance and adherence. Dmitri doesn’t mince words when it comes to what it takes in a person—not just an enterprise—to accept change, no matter how positive that change may ultimately be.

Rida Moustafa is an experienced data scientist with a demonstrated history of working in the retail industry. Rida covers a lot of ground in this concise, informative conversation. He shares his story with us, beginning in 1995 with the big data mining movement. Walking us through the way data mining has evolved, Rida hits on neural networks, deep learning, and expert systems. Today, however, AI technology has evolved enough to render some of these old processes moot. Of course, new obstacles present themselves, such as AI’s black box and its influence over regulatory decisions and prediction models. The last half of the conversation is reserved for Rida’s involvement with Walmart and the work he is doing with AI to automate processes and generally improve Walmart’s workflow and profits.

Robert Welborn discusses common myths surrounding autonomous vehicles. He starts with three TV shows that have skewed perception around AVs. Next, he sets expectations around the maturity model of AVs by describing the stages as childhood, adolescence, and adulthood. Today’s data presents itself in three-dimensional forms, and Robert is realistic about the struggles and opportunities within this new model of data. It is the engineers behind AVs who are tasked with making things work, and Robert spends some time pulling back the curtain on their trials and tribulations. Finally, Robert recognizes that the elasticity and compatibility of all of the elements at play in autonomous vehicles have a tendency to be overestimated. 

Deepak Subbarao joins us again, this time, to discuss unstructured data.  The recent explosion in technology inputs has raised the bar for customer expectations. They want more, and they want it now. Requests are coming via phone calls, social media, emails, etc. The product of this feedback is unstructured data. Deepak goes in depth on three actionable steps to take in order to leverage the power of unstructured data: know your data, know the sources of your data, and prepare your data. Next, Deepak discusses the importance of defining outcomes for your data, as opposed to cramming data into an algorithm and receiving an output that has no use case. As Deepak reiterates throughout the conversation, context is key.

Roland Haefs, with Henkel, discusses enterprise evolution and the shift from having purely transactional relationships to becoming a true business solutions provider. It takes strong leadership and an entrepreneurial spirit to pull off such a transformation, which Roland details. In order to demonstrate his point, Roland lays out Henkel’s approach to the shared services process of master data management. Next, the conversation turns to RPA and AI more specifically, including its role in shared services and how to make sure it is being deployed effectively. Further, Roland discusses Henkel’s four business priorities: fund growth, drive growth, excel at digitalization, and increase agility.

David Orban, founder of Network Society Ventures, discusses the rapid acceleration of technology and its consequences. How we live, work, organize, and grow a business has changed. Decentralization is now a common path forward. David gives examples, including solar energy, digital manufacturing, personalized health, and peer-to-peer learning. Next, David discusses the volatility of Bitcoin and why that’s to be expected: we don’t yet fully understand its potential. David exemplifies the past while offering solutions for the future. The rest of the conversation focuses on blockchain more generally, including future applications and implications. David’s technologically futuristic views don’t seem all that outlandish after this conversation. In fact, his optimism is contagious.

Molecule is an open market based platform that incentivizes the development and co-creation of pharmaceutical IP. Molecule’s CEO, Devon Krantz, discusses the dire state of pharmacological R&D and its cost—literally and figuratively—to patients. Molecule, on the other hand, encourages a patient-centric approach to pharma. How? Devon puts it this way: “We are focusing more on bio-techs, on smaller research labs, on academia. [What we] want to incentivize is for researchers, scientists, and academics to take their IP and put it onto the Blockchain, into an open market, which then enables other people to buy into the market and freely grow that market. We’re democratizing access to cures.” Devon elaborates on the innovative and complex ‘why & how’ during the rest of the conversation.

Hendrik Boehmer is the People Experience & Operations Lead for Unilever. While such a title is a few syllables longer than its counterpart, Hendrik explains that Unilever’s HR transformation involved a complete reimagination of the role. First, hand-picked roles that were once outsourced were brought back in house in order to achieve HR’s new goal: more simple, more impact, and more human. What this entails is increasing automation and the role of human talent simultaneously. While it sounds contradictive, Hendrik details the logistics and execution in full. As with any digital transformation, reskilling and security must be addressed. Unilever has a system in place for both, which Hendrik describes next. Finally, Hendrik mulls over this universal truth and what it’s meant for his career and enterprise at large: the only constant is change.

In this episode, Kai-Eberhard Lueg, Global Business Solutions expert with Siemens, discusses the future of automation. Specifically, commerce is experiencing a new type of customer expectation that involves an increase in personalization and speed. While these two concepts seem counterintuitive, digitalization and shared services make it possible. Digitization is only as effective as the foundation it was built on, however, so Mr. Lueg details the best way to move forward on firm ground. Finally, Mr. Lueg emphasizes the importance of human talent. By building a culture of curiosity and innovation, both employees and enterprise benefit from the expectation and execution of upskilling and reskilling with an emphasis on technical skills.

Dr. Timothy Renick with Georgia State joins us to talk about his implementation of predictive analytics within the university, including an AI enhanced chatbot. Since the deployment of these technologies, Georgia State is graduating 3,000 more students a year than it did seven years ago. Dr. Renick explains the university’s approach to finding solutions for problems over innovation for innovation’s sake. With a change in demographics, including a larger low-income population, the university felt it necessary to increase access to support and identify issues before students found themselves in dire straits. Dr. Renick discusses the process of finding a vendor to help them identify and build the perfect solution. It’s working, as shown by the examples he discusses during the rest of the conversation.

Sarah Aerni is a data scientist Salesforce. In this conversation, Sarah leads off by talking about what that even means. First, she gives a brief history of the expectation in customer experience and how it’s evolved with the introduction of AI. Then she describes her role in this way: “My role is to lead a team of really brilliant individuals that are focused on how to make it possible for Salesforce customers to build models, add predictions and intelligence without building out an entire data science team.” Sarah comes from a deep science background, having spent six years becoming the expert on automated labeling of C. elegans—a worm cell. How does that relate to forward-facing data science on modern platforms? Building a model is building a model, as Sarah explains. While she shirks the term “unicorn,” it is easy to understand why she’s been described that way after listening to this episode.

Martin Felder is the head process automation center at Linde Global Services. He discusses his role with Linde as well as their journey into RPA. Instead of taking the typical low-hanging-fruit approach, Martin tackled Linde's impending future when deciding where to implement RPA first. He explains the whys and hows of this, including how he got the C-suite to sign off—and fund—such a huge initiative. As Linde is a global enterprise, Michael next discusses the pain points, mistakes, and happy accidents that occurred during the pilot and roll-out of RPA solutions. Perhaps most important, Martin wraps up with his thoughts on human talent, relationships, and how to move into the future of automation by appreciating the people side of things.

Dr. Ayanna Howard is a chair of the School of Interactive computing at Georgia Tech, an academic, and a startup founder. While her talents are as vast as her pursuits, she sums up their common thread in this way: “Interactive computing is really this theme that the human is center to everything that we do when we think about computing and artificial intelligence.” Dr. Howard pursues interactive computing for the greater good, including robotics in healthcare and education. She shares some exciting, innovative uses for the robotics she's working on. She also discusses ethics in computing, including privacy and security. Finally, Dr. Howard discusses the importance of diversity in the interactive computing landscape.

Dario Izzo joins us from the World Summit AI to talk space. As the scientific coordinator the Advanced Concepts Team out of the European Space Agency, Dario is tasked with some serious undertakings. First, Dario summarizes ESA’s mission for us. He humbly describes some of his accomplishments since 2003—such as swarming missions—but, as Dario says, his goal is to stay focused on the future. Currently, energy efficiency is a major area of focus for Dario. He also discusses asteroid deflectors and cube satellites. The remainder of this sci-fi-meets-reality conversation covers AI’s contribution to space endeavors and why they’re worth our time, money, and cooperation.