How To Take AI From Tech Dream To Mainstream IT Opportunity In 2017

Savita Raina

Artificial intelligence (AI) has earned significant buzz over the last year. Across a wide range of sectors and geographies, established conglomerates, emerging startups, and everyone in between are focusing on the potential disruption looming ahead and innovating to embrace game-changing opportunity and efficiency. According to IDC, mass adoption of cognitive systems and AI will continue to boost worldwide revenues with a compound annual growth rate of 55.1% – from nearly $8 billion in 2016 to over $47 billion in 2020.

In a few short years, AI has become the “brains” behind many recent breakthroughs. From helping doctors identify disease early-on to making cars more autonomous and matching travelers to the accommodations they want, this technology is quickly changing our world. Unfortunately though, many executives still do not have a clear view of the value it offers.

CIOs inherently know the risk of waiting a few years until the C-suite gets on board. How can they invest anything in AI solutions if the boardroom doesn’t have a clear sense of what it wants to accomplish?

As more companies begin to test the technology and bring it to the masses, this indecisive stalemate warrants thought-provoking discussion about the future of the business. But instead of evangelizing the advantages of AI as a whole, it is best to break it down into two distinct forms: machine learning and deep learning.

Machine learning: The core of intelligence

Machine learning is a process that allows computers to improve take performance through increased exposure to data. Rather than using traditional programming methods, this technique requires a high degree of computational power to sift through massive volumes of information. Over time, machines can better sense, perceive, learn, and respond to their environment and their users through manual selection of relevant learning – enabling everything from better service to transforming how customers and companies engage with each other.

The opportunity: The task of machine learning is traditionally relegated to clusters of energy-guzzling computer servers equipped with specialized processors. However, as mobile devices continue to grow in computing power and perform tasks offline, the greater capacity for machine learning to become a mainstream activity that happens anytime and anywhere. For a growing remote workforce, this latest development is great news. For example, healthcare providers in isolated villages can diagnose skin conditions by analyzing digital photos without requiring connectivity access.

Deep learning: Filling in the edges with a mind of its own 

As an advanced branch of AI with predictive capabilities, deep learning mirrors the human brain’s capacity to continuously learn with higher accuracy and faster processing than traditional computing models. This approach is resistant to small changes and obstructions and can automatically make general assumptions from partial data. Fundamentally, deep learning can evaluate an object, digest the information, and adapt as conditions change.

The opportunity: Although it is not as mature as machine learning, deep learning is ripening to become a significant investment opportunity. This AI form leverages other technologies – such as in-memory computing, online presence, predictive analytics, the Internet of Things, and cloud solutions – to resolve increasingly complex problems, once thought impossible, across all types of industries. Breakthroughs in deep learning are now starting to teach machines to process natural language and interpret the information into decision and action. Innovations from startups, such as Kore, has taken this technology to a new level by making devices smarter and able to evolve with the needs of the user.

Evangelizing the C-suite on the power of AI

Even though IT budgets continue to shrink, the influencing power of the CIO shouldn’t. Line-of-business leaders will eventually invest in AI directly and search for third-party vendors to implement it quickly. By educating executives on the advantages of each form of AI, CIOs can help ensure that every dollar spent permeates value throughout the enterprise.

Learn more about how CIOs can become digital solution innovators.

 

 

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Savita Raina

About Savita Raina

Savita is the Sr. Product Marketing Manager for SAP Cloud Platform and has +10 years of direct work experience working in high tech industry. She has a diverse set of experiences that span from engineering design & product development to pre-sales, product and audience marketing functions. In prior roles at SAP she has been responsible for defining and delivering audience messaging, value proposition, and thought leadership content for the IT line-of-business. Prior to SAP, she has worked at Proofpoint, MKS Instruments and Oerlikon. She holds an MBA from Santa Clara University and MS in Electrical Engineering from New Jersey Institute of Technology.

How ‘Digital Twins’ Nurture The Customer Experience

Todd Hassell

Retailers are embracing the shift from transaction-focused interactions to a sustained customer engagement, recognizing that their buying journey neither begins when they set foot in a physical store or visit a digital storefront via browser or mobile device, nor ends when the sale is complete.

In today’s connected world, with Alexa, Google, and Siri in our homes, cars, and with us wherever we go, the journey starts earlier – when the consumer has an unfulfilled need (recognized or not). Be it a new batch of K-cups for their Keurig machine, a portable battery pack to boost the charge for their smartphone that runs low by 4 pm, or a new outfit for a planned vacation to Hawaii in the cold of February, there are tens or hundreds of customer journeys starting for each consumer, every day.

The end of the journey has changed too. It’s no longer the point of purchase: it’s the conclusion of the vacation, being able to keep using the phone through the end of the day, or enjoying the hot cup of coffee from the Keurig machine. It’s often is accompanied by a Facebook or Instagram post or a product review. That journey’s “end” can (and should) actually be the beginning of a new cycle, a new journey of needs, ripe for retailers or consumer products companies to take advantage of it. But how?

Creating a digital twin of your customer

Industrial products companies have been creating “digital twins” of their key assets – production machinery, mining equipment, delivery vehicles, large-scale refrigerators, and industrial ovens that monitor and measure operating performance, temperatures, heat generation, and wear and tear. By mining the real-time data from their assets and applying machine-learning techniques to effectively predict (and proactively address) required maintenance and avoid unplanned downtimes, they have successfully improved productivity and profitability, in addition to creating entirely new business models.

Retailers and consumer products companies now have a similar opportunity. By combining detailed transactional data with insights from social media and consumption/usage data from IoT-enabled devices (smartphones, connected home lighting, appliances, home entertainment systems, heating and cooling, and cars, for example) it is now becoming possible to create “digital twins” of consumers.

Combining transactional data – such as the quantity and frequency of K-cup purchases – with insights to consumption, as well as non-transactional knowledge such as family size and makeup, time spent away from home on a vacation, local travel to work, etc., allows companies to establish a reliable model of individual consumers, to predict timing of and frequency purchases of products – but also to understand the point at which that unique customer is likely approaching their own personal “reorder point” – the ideal time to present them with an offer (but not necessarily a discount.)

Applying these insights with machine learning to understand customers’ behavior outside of a store’s four walls,  retailers can communicate in an effective, relevant and timely manner to let them know, for example, that their favorite coffee K-Cup is available at two or three local stores (which we happen to know are conveniently located on their route home from work), and if they want to double their order, we will include a complementary 4-pack of breakfast Danishes (which we also know would have been overstock in 36 hours) and have it all waiting for them.

Leveraging insights gained from both product consumption and how connected devices are being used (e.g. – a sudden increase in the number of low-calorie meals being prepared / cooked) present entirely new opportunities for retailers to cross-sell and up-sell.  When internal battery monitors indicate low levels in devices, you tailor offers to include extended battery-life models.  If a customer typically adds an additional 30 seconds after microwaving their dinner, flag them as a target for a higher-wattage model, or offer them a service call to check the output of the appliance.

The consumer of today demands relevancy, and applying “Digital Twin” concepts to predictively offer relevant solutions to them, not as they enter a store with their minds (and shopping lists) already made up, but rather at point in time (and location) they will be most receptive will drive additional profitable revenue and, just as important, increased loyalty.

The future of retail is insight-driven relevancy – and that future is here today.

For more insight on customer service, see What A Local Baker Taught Me About The Customer Experience..

This article originally appeared on SAP Community.

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Todd Hassell

About Todd Hassell

Todd Hassell is Senior Principal of Industry and Value Advisory at SAP America.

Guide To The Machine Learning Galaxy: Meet Tomorrow’s Rising Stars

Jessica Schubert

We’ve just begun to scratch the surface of the impact of machine learning on the enterprise. Organizations are applying machine learning algorithms to business processes to automate manual tasks and identify patterns in transactional data to drive strategic decisions. Many applications are focused on efficiency and automation, but that trend is shifting. More and more businesses are using machine learning to develop disruptive new business models.

What does this mean for your organization? Plenty, according to two experts during a recent Deloitte and ASUG Webinar, Guide to the Machine Learning Galaxy: How Your ERP Knowledge Enables Value-Driven Intelligent Processes. Leading the Webinar from Deloitte Consulting LLP were Darwin Deano, principal and chief officer for SAP Leonardo and Denise McGuigan, senior manager and Deloitte reimagine platform leader for Lights Out Finance. Darwin and Denise explained emerging trends, why enterprise resource planning (ERP) software is a hotbed for machine learning, and the potential impact on the workforce.

Making room for your digital twin

Machine learning unleashes the greatest possibilities for the enterprise by amplifying the best of human capabilities. It’s not about replacing humans; it’s about coexistence. In the future, there will be greater opportunities for people who can work with machines, take the information that’s produced, and do something meaningful with it.

Consider the concept of a digital twin. The digital twin is essentially the replication of a process system. In finance, payables transactions and record-to-report tasks require a copious number of journal entries that take a lot of time to input. Those tasks could all be reduced or even eliminated by a machine learning bot.

As a digital twin takes on transactional processes, individuals who performed those tasks are then able to focus their efforts on activities that make better use of their human skills by driving actionable insights. They would need to work alongside the digital twin and activate the resulting insight and analytics.

Unleashing data-driven ERP power

Before we give too much credit to the enabling power of machine learning, keep in mind that it all starts and ends with data. Machine learning is only as good as the algorithm, the algorithm is only as good as the data, and nobody knows the data about your core business better than the people who understand your ERP. Therefore, your people play key roles in identifying opportunities and driving the value of machine learning in your enterprise.

There are emerging roles across business and IT that will be critical to the success of not only designing and implementing, but operating, sustaining, and continuously improving investments in machine learning. Two of these roles are orchestrators and guardians.

Identifying orchestrators and guardians – the new stars

Before the advent of machine learning, organizations valued individual skills with a lot of emphasis on specialization. With machine learning, that emphasis shifts to the people who can put it all together – the orchestrators. Orchestrators help realize the value of machine learning. For example, a finance manager is a classic orchestrator. Finance managers know how order-to-cash flows into the central finance operation and how each individual department interacts with finance. For any machine learning scenario in finance, this manager would help put it all together.

The guardians monitor the effectiveness of machine learning to validate that your model works and to address any uncertainty about machine-driven actions. They’ll safeguard the audit trail, assess the evolution of data, and determine what adjustments need to be made. A supply chain director is a very good guardian who can filter out extraneous noise and verify the merits of machine learning scenarios. These roles and constructs will be increasingly important going forward.

Learn more to prepare for a disruptive future

By bringing together your people, processes, and technology, you can more effectively put machine learning to work for your organization. To learn more about what it takes to build modern machine-intelligence capabilities with a solid ERP foundation, watch a replay of Guide to the Machine Learning Galaxy: How Your ERP Knowledge Enables Value-Driven Intelligent Processes. You’ll explore use cases, industry-specific challenges, and leading practices, as well as how the combination of SAP Leonardo and SAP S/4HANA provides a synergistic digital innovation capability. For more information, contact @demcguigan, @darwindeano, @DeloitteSAP, or visit www.deloitte.com/sap. For more on this topic, read “Underfit Vs. Overfit: Why Your Machine Learning Model May Be Wrong.”

Follow SAP Finance online: @SAPFinance (Twitter) | LinkedIn | FacebookYouTube

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Jessica Schubert

About Jessica Schubert

Jessica Schubert is the director of Global Partner Marketing, Deloitte Alliance Lead, at SAP. Her specialties include strategic partnerships, business alliances, go-to-market strategy, product marketing, and demand generation.

Why Strategic Plans Need Multiple Futures

By Dan Wellers, Kai Goerlich, and Stephanie Overby , Kai Goerlich and Stephanie Overby

When members of Lowe’s Innovation Labs first began talking with the home improvement retailer’s senior executives about how disruptive technologies would affect the future, the presentations were well received but nothing stuck.

“We’d give a really great presentation and everyone would say, ‘Great job,’ but nothing would really happen,” says Amanda Manna, head of narratives and partnerships for the lab.

The team realized that it needed to ditch the PowerPoints and try something radical. The team’s leader, Kyle Nel, is a behavioral scientist by training. He knows people are wired to receive new information best through stories. Sharing far-future concepts through narrative, he surmised, could unlock hidden potential to drive meaningful change.

So Nel hired science fiction writers to pen the future in comic book format, with characters and a narrative arc revealed pane by pane.

The first storyline, written several years before Oculus Rift became a household name, told the tale of a couple envisioning their kitchen renovation using virtual reality headsets. The comic might have been fun and fanciful, but its intent was deadly serious. It was a vision of a future in which Lowe’s might solve one of its long-standing struggles: the approximately US$70 billion left on the table when people are unable to start a home improvement project because they can’t envision what it will look like.

When the lab presented leaders with the first comic, “it was like a light bulb went on,” says Manna. “Not only did they immediately understand the value of the concept, they were convinced that if we didn’t build it, someone else would.”

Today, Lowe’s customers in select stores can use the HoloRoom How To virtual reality tool to learn basic DIY skills in an interactive and immersive environment.

Other comics followed and were greeted with similar enthusiasm—and investment, where possible. One tells the story of robots that help customers navigate stores. That comic spawned the LoweBot, which roamed the aisles of several Lowe’s stores during a pilot program in California and is being evaluated to determine next steps.

And the comic about tools that can be 3D-printed in space? Last year, Lowe’s partnered with Made in Space, which specializes in making 3D printers that can operate in zero gravity, to install the first commercial 3D printer in the International Space Station, where it was used to make tools and parts for astronauts.

The comics are the result of sending writers out on an open-ended assignment, armed with trends, market research, and other input, to envision what home improvement planning might look like in the future or what the experience of shopping will be in 10 years. The writers come back with several potential story ideas in a given area and work collaboratively with lab team members to refine it over time.

The process of working with writers and business partners to develop the comics helps the future strategy team at Lowe’s, working under chief development officer Richard D. Maltsbarger, to inhabit that future. They can imagine how it might play out, what obstacles might surface, and what steps the company would need to take to bring that future to life.

Once the final vision hits the page, the lab team can clearly envision how to work backward to enable the innovation. Importantly, the narrative is shared not only within the company but also out in the world. It serves as a kind of “bat signal” to potential technology partners with capabilities that might be required to make it happen, says Manna. “It’s all part of our strategy for staking a claim in the future.”

Planning must become completely oriented toward—and sourced from—the future.

Companies like Lowe’s are realizing that standard ways of planning for the future won’t get them where they need to go. The problem with traditional strategic planning is that the approach, which dates back to the 1950s and has remained largely unchanged since then, is based on the company’s existing mission, resources, core competencies, and competitors.

Yet the future rarely looks like the past. What’s more, digital technology is now driving change at exponential rates. Companies must be able to analyze and assess the potential impacts of the many variables at play, determine the possible futures they want to pursue, and develop the agility to pivot as conditions change along the way.

This is why planning must become completely oriented toward—and sourced from—the future, rather than from the past or the present. “Every winning strategy is based on a compelling insight, but most strategic planning originates in today’s marketplace, which means the resulting plans are constrained to incremental innovation,” says Bob Johansen, distinguished fellow at the Institute for the Future. “Most corporate strategists and CEOs are just inching their way to the future.” (Read more from Bob Johansen in the Thinkers story, “Fear Factor.”)

Inching forward won’t cut it anymore. Half of the S&P 500 organizations will be replaced over the next decade, according to research company Innosight. The reason? They can’t see the portfolio of possible futures, they can’t act on them, or both. Indeed, when SAP conducts future planning workshops with clients, we find that they usually struggle to look beyond current models and assumptions and lack clear ideas about how to work toward radically different futures.

Companies that want to increase their chances of long-term survival are incorporating three steps: envisioning, planning for, and executing on possible futures. And doing so all while the actual future is unfolding in expected and unexpected ways.

Those that pull it off are rewarded. A 2017 benchmarking report from the Strategic Foresight Research Network (SFRN) revealed that vigilant companies (those with the most mature processes for identifying, interpreting, and responding to factors that induce change) achieved 200% greater market capitalization growth and 33% higher profitability than the average, while the least mature companies experienced negative market-cap growth and had 44% lower profitability.

Looking Outside the Margins

“Most organizations lack sufficient capacity to detect, interpret, and act on the critically important but weak and ambiguous signals of fresh threats or new opportunities that emerge on the periphery of their usual business environment,” write George S. Day and Paul J. H. Schoemaker in their book Peripheral Vision.

But that’s exactly where effective future planning begins: examining what is happening outside the margins of day-to-day business as usual in order to peer into the future.

Business leaders who take this approach understand that despite the uncertainties of the future there are drivers of change that can be identified and studied and actions that can be taken to better prepare for—and influence—how events unfold.

That starts with developing foresight, typically a decade out. Ten years, most future planners agree, is the sweet spot. “It is far enough out that it gives you a bit more latitude to come up with a broader way to the future, allowing for disruption and innovation,” says Brian David Johnson, former chief futurist for Intel and current futurist in residence at Arizona State University’s Center for Science and the Imagination. “But you can still see the light from it.”

The process involves gathering information about the factors and forces—technological, business, sociological, and industry or ecosystem trends—that are effecting change to envision a range of potential impacts.

Seeing New Worlds

Intel, for example, looks beyond its own industry boundaries to envision possible future developments in adjacent businesses in the larger ecosystem it operates in. In 2008, the Intel Labs team, led by anthropologist Genevieve Bell, determined that the introduction of flexible glass displays would open up a whole new category of foldable consumer electronic devices.

To take advantage of that advance, Intel would need to be able to make silicon small enough to fit into some imagined device of the future. By the time glass manufacturer Corning unveiled its ultra-slim, flexible glass surface for mobile devices, laptops, televisions, and other displays of the future in 2012, Intel had already created design prototypes and kicked its development into higher gear. “Because we had done the future casting, we were already imagining how people might use flexible glass to create consumer devices,” says Johnson.

Because future planning relies so heavily on the quality of the input it receives, bringing in experts can elevate the practice. They can come from inside an organization, but the most influential insight may come from the outside and span a wide range of disciplines, says Steve Brown, a futurist, consultant, and CEO of BaldFuturist.com who worked for Intel Labs from 2007 to 2016.

Companies may look to sociologists or behaviorists who have insight into the needs and wants of people and how that influences their actions. Some organizations bring in an applied futurist, skilled at scanning many different forces and factors likely to coalesce in important ways (see Do You Need a Futurist?).

Do You Need a Futurist?

Most organizations need an outsider to help envision their future. Futurists are good at looking beyond the big picture to the biggest picture.

Business leaders who want to be better prepared for an uncertain and disruptive future will build future planning as a strategic capability into their organizations and create an organizational culture that embraces the approach. But working with credible futurists, at least in the beginning, can jump-start the process.

“The present can be so noisy and business leaders are so close to it that it’s helpful to provide a fresh outside-in point of view,” says veteran futurist Bob Johansen.

To put it simply, futurists like Johansen are good at connecting dots—lots of them. They look beyond the boundaries of a single company or even an industry, incorporating into their work social science, technical research, cultural movements, economic data, trends, and the input of other experts.

They can also factor in the cultural history of the specific company with whom they’re working, says Brian David Johnson, futurist in residence at Arizona State University’s Center for Science and the Imagination. “These large corporations have processes and procedures in place—typically for good reasons,” Johnson explains. “But all of those reasons have everything to do with the past and nothing to do with the future. Looking at that is important so you can understand the inertia that you need to overcome.”

One thing the best futurists will say they can’t do: predict the future. That’s not the point. “The future punishes certainty,” Johansen says, “but it rewards clarity.” The methods futurists employ are designed to trigger discussions and considerations of possibilities corporate leaders might not otherwise consider.

You don’t even necessarily have to buy into all the foresight that results, says Johansen. Many leaders don’t. “Every forecast is debatable,” Johansen says. “Foresight is a way to provoke insight, even if you don’t believe it. The value is in letting yourself be provoked.”

External expert input serves several purposes. It brings everyone up to a common level of knowledge. It can stimulate and shift the thinking of participants by introducing them to new information or ideas. And it can challenge the status quo by illustrating how people and organizations in different sectors are harnessing emerging trends.

The goal is not to come up with one definitive future but multiple possibilities—positive and negative—along with a list of the likely obstacles or accelerants that could surface on the road ahead. The result: increased clarity—rather than certainty—in the face of the unknown that enables business decision makers to execute and refine business plans and strategy over time.

Plotting the Steps Along the Way

Coming up with potential trends is an important first step in futuring, but even more critical is figuring out what steps need to be taken along the way: eight years from now, four years from now, two years from now, and now. Considerations include technologies to develop, infrastructure to deploy, talent to hire, partnerships to forge, and acquisitions to make. Without this vital step, says Brown, everybody goes back to their day jobs and the new thinking generated by future planning is wasted. To work, the future steps must be tangible, concrete, and actionable.

Organizations must build a roadmap for the desired future state that anticipates both developments and detours, complete with signals that will let them know if they’re headed in the right direction. Brown works with corporate leaders to set indicator flags to look out for on the way to the anticipated future. “If we see these flagged events occurring in the ecosystem, they help to confirm the strength of our hypothesis that a particular imagined future is likely to occur,” he explains.

For example, one of Brown’s clients envisioned two potential futures: one in which gestural interfaces took hold and another in which voice control dominated. The team set a flag to look out for early examples of the interfaces that emerged in areas such as home appliances and automobiles. “Once you saw not just Amazon Echo but also Google Home and other copycat speakers, it would increase your confidence that you were moving more towards a voice-first era rather than a gesture-first era,” Brown says. “It doesn’t mean that gesture won’t happen, but it’s less likely to be the predominant modality for communication.”

How to Keep Experiments from Being Stifled

Once organizations have a vision for the future, making it a reality requires testing ideas in the marketplace and then scaling them across the enterprise. “There’s a huge change piece involved,”
says Frank Diana, futurist and global consultant with Tata Consultancy Services, “and that’s the place where most
businesses will fall down.”

Many large firms have forgotten what it’s like to experiment in several new markets on a small scale to determine what will stick and what won’t, says René Rohrbeck, professor of strategy at the Aarhus School of Business and Social Sciences. Companies must be able to fail quickly, bring the lessons learned back in, adapt, and try again.

Lowe’s increases its chances of success by creating master narratives across a number of different areas at once, such as robotics, mixed-reality tools, on-demand manufacturing, sustainability, and startup acceleration. The lab maps components of each by expected timelines: short, medium, and long term. “From there, we’ll try to build as many of them as quickly as we can,” says Manna. “And we’re always looking for that next suite of things that we should be working on.” Along the way certain innovations, like the HoloRoom How-To, become developed enough to integrate into the larger business as part of the core strategy.

One way Lowe’s accelerates the process of deciding what is ready to scale is by being open about its nascent plans with the world. “In the past, Lowe’s would never talk about projects that weren’t at scale,” says Manna. Now the company is sharing its future plans with the media and, as a result, attracting partners that can jump-start their realization.

Seeing a Lowe’s comic about employee exoskeletons, for example, led Virginia Tech engineering professor Alan Asbeck to the retailer. He helped develop a prototype for a three-month pilot with stock employees at a Christiansburg, Virginia, store.

The high-tech suit makes it easier to move heavy objects. Employees trying out the suits are also fitted with an EEG headset that the lab incorporates into all its pilots to gauge unstated, subconscious reactions. That direct feedback on the user experience helps the company refine its innovations over time.

Make the Future Part of the Culture

Regardless of whether all the elements of its master narratives come to pass, Lowe’s has already accomplished something important: It has embedded future thinking into the culture of the company.

Companies like Lowe’s constantly scan the environment for meaningful economic, technology, and cultural changes that could impact its future assessments and plans. “They can regularly draw on future planning to answer challenges,” says Rohrbeck. “This intensive, ongoing, agile strategizing is only possible because they’ve done their homework up front and they keep it updated.”

It’s impossible to predict what’s going to happen in the future, but companies can help to shape it, says Manna of Lowe’s. “It’s really about painting a picture of a preferred future state that we can try to achieve while being flexible and capable of change as we learn things along the way.” D!


About the Authors

Dan Wellers is Global Lead, Digital Futures, at SAP.

Kai Goerlich is Chief Futurist at SAP’s Innovation Center Network.

Stephanie Overby is a Boston-based business and technology journalist.


Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.

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Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation. Share your thoughts with Kai on Twitter @KaiGoe.heif Futu

About Stephanie Overby

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Human Is The Next Big Thing

Traci Maddox

One of my favorite movies of 2016 was Hidden Figures. The main character, Katherine Johnson, and her team of colleagues had an interesting job title: Computer. Here’s what Katherine said about her job: “On any given day, I analyze the binomial levels of air displacement, friction, and velocity. And compute over 10 thousand calculations by cosine, square root, and lately analytic geometry. By hand.”

That was the 1960s. It was amazing work, but work that took hours to complete – and something an in-memory computer could do in a fraction of a second today.

Just as in-memory computing transformed calculating by hand (and made jobs like Katherine’s much easier), digital technologies are transforming the way we work today – and making our day-to-day activities more efficient.

What’s the real impact of technology in today’s workplace?

We are surrounded by technology, both at home and at work. Machine learning and robotics are making their way into everyday life and are affecting the way we expect to engage with technology at work. That has a big impact on organizations: If a machine can do a job safely and more efficiently, a company, nonprofit, or government – and its employees – will benefit. Digital technologies are becoming increasingly more feasible, affordable, and desirable. The challenge for organizations now is effectively merging human talent and digital business to harness new capabilities.

How will jobs change?

What does this mean for humans in the workplace? In a previous blog, Kerry Brown showed that as enterprises continue to learn, human/machine collaboration increases. People will direct technology and hand over work that can be done more efficiently by machine. Does that mean people will go away? No – but they will need to leverage different skills than they have today.

Although we don’t know exactly how jobs will change, one thing is for sure: Becoming more digitally proficient will help every employee stay relevant (and prepare them to move forward in their careers). Today’s workforce demographic complicates how people embrace technology – with up to five generations in the workforce, there is a wide variety in digital fluency (i.e., the ability to understand which technology is available and what tools will best achieve desired outcomes).

What is digital fluency and how can organizations embrace it?

Digital fluency is the combination of several capabilities related to technology:

  • Foundation skills: The ability to use technology tools that enhance your productivity and effectiveness
  • Information skills: The ability to research and develop your own perspective on topics using technology
  • Collaboration skills: The ability to share knowledge and collaborate with others using technology
  • Transformation skills: The ability to assess your own skills and take action toward building your digital fluency

No matter how proficient you are today, you can continue to build your digital IQ by building new habits and skills. This is something that both the organization and employee will have to own to be successful.

So, what skills are needed?

In a Technical University of Munich study released in July 2017, 64% of respondents said they do not have the skills necessary for digital transformation.

Today's workplace reality

These skills will be applied not only to the jobs of today, but also to the top jobs of the future, which haven’t been imagined yet! A recent article in Fast Company mentions a few, which include Digital Death Manager, Corporate Disorganizer, and 3D Printing Handyman.

And today’s skills will be used differently in 2025, as reported by another Fast Company article:

  • Tech skills, especially analytical skills, will increase in importance. Demand for software developers, market analysts, and computer analysts will increase significantly between now and 2025.
  • Retail and sales skills, or any job related to soft skills that are hard for computers to learn, will continue to grow. Customer service representatives, marketing specialists, and sales reps must continue to collaborate and understand how to use social media effectively to communicate worldwide.
  • Lifelong learning will be necessary to keep up with the changes in technology and adapt to our fast-moving lives. Teachers and trainers will continue to be hot jobs in the future, but the style of teaching will change to adapt to a “sound bite” world.
  • Contract workers who understand how businesses and projects work will thrive in the “gig economy.” Management analysts and auditors will continue to be in high demand.

What’s next?

How do companies address a shortage of digital skills and build digital fluency? Here are some steps you can take to increase your digital fluency – and that of your organization:

  • Assess where you are today. Either personally or organizationally, knowing what skills you have is the first step toward identifying where you need to go.
  • Identify one of each of the skill sets to focus on. What foundational skills do you or your organization need? How can you promote collaboration? What thought leadership can your team share – and how can they connect with the right information to stay relevant?
  • Start practicing! Choose just one thing – and use that technology every day for a month. Use it within your organization so others can practice too.

And up next for this blog series – a look at the workplace of the future!

The computer made its debut in Hidden Figures. Did it replace jobs? Yes, for some of the computer team. But members of that team did not leave quietly and continue manual calculations elsewhere. They learned how to use that new mainframe computer and became programmers. I believe humans will always be the next big thing.

If we want to retain humanity’s value in an increasingly automated world, we need to start recognizing and nurturing Human Skills for the Digital Future.

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Traci Maddox

About Traci Maddox

Traci Maddox is the Director of the North America Customer Transformation Office at SAP, where she is elevating customer success through innovation and digital transformation. Traci is also part of the Digital Workforce Taskforce, a team of SAP leaders whose mission is to help companies succeed by understanding and addressing workforce implications of digital technology.