Fraud Attacks Often Come From Unexpected Places – Can Predictive Analytics Help?

Jerome Pugnet

Looking at companies’ experiences, of various sizes and across all industries, I think we would all agree that fraud attacks often don’t come from where one would expect! Companies still rely too much on guesswork and empiric methods while investigating potentially fraudulent transactions.

And to make things worse, fraud patterns evolve quickly and constantly. Thus, as companies put in place measures to prevent fraud, perpetrators quickly adapt and find ways to circumvent them. There’s clearly a need for better processes and tools to enhance their fraud detection and investigation.

Investigators’ experience isn’t sufficient anymore

To analyse and understand how and where fraud happens, one can’t just rely on the experience and intuitions of even the best investigators, or the analysis of standard fraud reports and basic metrics. Also, the more common analytical tools appear ineffective to scan very high and fast-growing volumes of data – where critical information to understand fraud patterns and hidden paths is buried.

Moreover, the range of data to examine to properly identify fraud trends is increasingly diverse – structured and unstructured. More than ever, fraud detection is a Big Data problem!

Fast-developing predictive technologies offer great potential for improvement

On the other hand, predictive analysis technologies are fast developing, becoming more widely available and easier to use, yet more powerful. They can help companies get deep insights into how and where fraudulent transactions originate, and analyze changing fraud patterns, in order to enhance their fraud detection strategies and adapt faster to new types of attacks.

So the combination of traditional fraud management solutions complemented by predictive analytics not only enhances capabilities to detect fraud, but also contributes to better prevention of potential future fraud. It enables a deeper, more forensic approach against fraud, helping users to improve the effectiveness of their investigations by better focusing on new types of fraud risks, and continuously updating and refining their fraud detection strategies using the data from predictive analyses.

Today’s best fraud management and predictive analytics solutions have many benefits. They:

  • Identify fraud patterns and trends more precisely: where fraud comes from, how it happens, who is involved, what areas of the business it impacts, and so on.
  • Enable going after the less known and more complex patterns and networks, and detecting earlier to minimize the damage of cleverly hidden suspicious transactions.
  • Provide the needed capabilities to analyze a wide variety and very high volume of data very fast, leveraging in-memory computing technology.
  • Help fraud investigators by reducing false alerts resulting from inadequate fraud detection mechanisms— a critical issue today for many fraud investigators as they’re faced with an excessive workload of potential alerts to analyse, and wasted efforts as many turn out to be false positives.

Can predictive analytics benefit a wider audience?

The innovation brought by predictive analytics touches many other areas of the business, and in areas such as governance, risk and compliance (GRC), its use will develop to enable better predictability of risk, increased insight in areas of control weakness, support for internal audit programs, and so on.

These multiple applications create a high demand for experts such as data analysts and specialized business analysts, but the scarcity and high cost of these resources pushes for better usability of the tools. In the area of fraud in particular, invaluable expertise resides within fraud investigation teams who don’t have these skills as their primary asset.

For them, and others, it’s important that new predictive technologies become approachable for the non-experts, and more readily consumable by their most interested audience—which is just what the latest generations of predictive technologies enable.

For more on security strategies, see Cybersecurity: Is It Time To Change Our Mindset?

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Jerome Pugnet

About Jerome Pugnet

Jérôme Pugnet is a senior director of GRC Product Marketing at SAP SE, based in London, and has over 12 years of experience in risk and compliance management, business process control, IT governance, fraud and audit management domains, in particular in the financial services industry. He has over 16 years of previous experience on financial software and ERP, in implementation engagements and pre-sales advisory roles.

How Artificial Intelligence And Machine Learning Will Transform The Wholesale Industry

Karen Lynch

Artificial intelligence and machine learning technologies are quickly becoming “the new normal.” Despite alarmist sci-fi predictions about AI from Elon Musk and Stephen Hawking, these innovations are set to transform the way wholesale distributors do business.

A new level of insight

Machines, computer software, and algorithms can now understand written and spoken words at a deep level. Some are refined enough to determine the meaning of images and video media. They can even extrapolate possible futures. Analytics and data intelligence are enhancing business processes and facilitating more intuitive customer service practices.

Artificial intelligence and machine learning technologies have enabled computers to compete with and, in many cases, surpass human ability. They are making their way into many domains that were previously reserved for humans, and this frees up human resources for more value-added tasks.

In addition to automating mundane tasks, machines are taking over increasingly complex functions in all lines of business. Machines with the ability to take on more intricate work tasks enable a new level of automation across all areas of business. These innovations are particularly valuable for wholesale distributors.

Automation frees up assets for strategic advances

Just as in the retail space, clients in the wholesale distribution industry have higher expectations as well as heightened influence. Increased efficiency, being easy to do business with and reducing errors is paramount.

Wholesale distributors are now able to create smarter, more intuitive and more efficient processes than ever before. With the supply chain process streamlined, resources are freed up for more strategic activities.

Digital transformation embodies making full use of machine learning as well as the internet of things, data intelligence, more refined analytics, big data, block chain, the cloud, design thinking and related innovative technologies.

Wholesalers of all sizes can benefit

The IoT (Internet of Things) is a dynamic “network of networks” connecting components and endpoints in the business world. This facilitates communication without the need for human interaction. This advance is foundational to the efficacy of artificial intelligence and machine learning in business.

Wholesalers operate almost exclusively in a B2B environment. While there is a bit less urgency for transformation in this realm than in the consumer space, IoT adoption is still robust. The digital revolution has already transformed the wholesale business in the past decade, and machine learning and artificial intelligence are set to take the industry into new realms altogether.

Giant online wholesalers like Alibaba and Amazon are setting the stage for what’s to come. Wholesalers of all sizes will be pursuing new initiatives that make the most of the IoT and technologies like 3D printing. These additions will enable new service capabilities and product offerings for business customers.

A more intuitive way of doing business

These revolutionary changes raise the bar for all companies in the wholesale industry. Sitting on the sidelines is simply not an option; businesses are becoming accustomed to the increased innovation these changes facilitate, and they will quickly lose patience with wholesalers who are not making the most of these technologies.

Keeping track of inventory at all times is crucial to success as a wholesaler. One of the most robust aspects of this evolution for wholesale companies is the capacity for highly accurate real-time reporting.

Some of the key benefits of these innovations include:

Better customer service: Artificial intelligence and machine learning will allow wholesale distributors to anticipate and intuit future customer needs based upon past and present activity.  (Delete the word “your” before wholesale distributors)

Reduced costs: In addition to always having enough product to meet customer demand, fluctuations in demand can be better anticipated. This information will inform purchasing decisions for higher accuracy than ever before. This in turn will reduce overages and inventory surpluses that can cause a high number of “unsaleable” and wasted expenditures on these products.

Predictive maintenance: Sensors on key equipment and processes within factories and warehouses that are plugged into the IoT will allow components to be serviced and replaced before they become a problem. Remotely installed commerce assets such as vending machines, refrigerators and coolers can also be accurately monitored. This increases uptime and further enhances customer service.

Overall, a digital transformation in the wholesale industry using these technologies will help to improve internal visibility across all lines of business. This will allow exponentially better customer service while reducing both waste and overages.

A new world of innovation

As you can see, artificial intelligence and machine learning technologies will facilitate a range of innovations for the wholesale industry. Better process automation, improved customer engagement, more effective assets and even new revenue models are now possible. Real-time data will be taken to new levels with the ability of these technologies to anticipate customer needs and extrapolate futures.

Artificial intelligence, machine learning, and the digital revolution are transforming the world. Is your business ready?

Learn how to bring new technologies and services together to power digital transformation: The IoT Imperative for Consumer Industries. Explore how to bring Industry 4.0 insights into your business today: Industry 4.0: What’s Next?

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Karen Lynch

About Karen Lynch

Karen Lynch is the Vice President, Global Wholesale Distribution Industry Business Unit at SAP. She sets the vision and direction and execute the go to market plan to address the needs of Wholesale Distributors across the globe by using SAP solutions.

The Promise Of Drones And Machine Learning For Oil And Gas Industry

Ansari Nubeel

Digital transformation is no longer a fuzzy buzzword in industry, rather it is now a well understood and a credible approach to achieving business value. With increasing maturation of transformative technologies, it’s becoming a lot easier for organizations to chart their approach and digital transformation journeys.

The oil and gas industry was slow to leverage transformative technologies like the Internet of Things, machine learning, blockchain, artificial intelligence, and virtual reality. However, progressive companies have started to experiment with these new technologies to drive incremental value for their organization. These early adopters are showing how digital transformation is driving cost reduction, improving reliability, and increasing safety of people across the industry value chain and, in the process, attracting more companies and investment in these technologies.

Key challenges

The oil and gas industry faces the unique challenge of ensuring the efficient and safe operation of assets that are distributed geographically or in areas that are not easily accessible. In these cases, technologies like drones and machine learning could become very relevant. Drone-based aerial surveys of inaccessible areas can provide rich insights into the condition of the assets. Well platforms or areas above and near underground pipelines are some of the places where drone based inspection can work wonders.

How drones and machine learning can help overcome challenges

A common and simple use of a drone is to inspect inaccessible areas that would typically require scaffolding, rope, or a physical setups. By taking pictures of assets, such as flares, refinery columns, offshore platforms, or large crude oil tanks, and using them for visual inspections, oil and gas companies can prioritize detailed inspection and maintenance activities.

However, drone inspection’s true potential can be unleashed if machine learning is used to analyze the large volume of images to identify patterns and/or map the images to look for abnormalities. In this regard, a deep-learning algorithm based on a convolutional neural network (CNN) can help. In machine learning, a CNN (or ConvNet) is a class of deep, feed-forward artificial neural networks used for analyzing visual imagery. Simply put, it’s learning based on imagery.

In an oil and gas installation, a CNN-based algorithm running on a geoservice-enabled machine learning platform can be used to create a digital representation of a remote platform, a crude oil tank farm, an over-ground layout for an underground pipeline, etc., by feeding standard images (a test data set) to train the algorithm to identify an asset on the ground. This enables a CNN algorithm to understand the details in imagery. Any new photograph captured with drone-based inspection can then be evaluated based on the CNN algorithm

For example, standard images of the surface over an underground pipeline can be fed into the algorithm to train it. Afterwards, every time a visual survey is done, the new images can be analyzed based on the learning in the CNN algorithm, and any abnormality that can’t be mapped with the existing data set can be highlighted in the analysis. Human intervention can target this exception for inspection, instead of reviewing the entire information.

Summary

Drone-based aerial imagery has the potential to significantly transform maintenance and inspection processes for oil and gas installations. A geoservice-enabled machine learning platform with a CNN-based algorithm can analyze the results from aerial inspection, and recommend human intervention only if there are mismatches between the new imagery and the imagery used for training the algorithm.

For more on how technology is transforming the supply chain, see Tick Tock: Start Preparing for Resource Disruption.

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Ansari Nubeel

About Ansari Nubeel

Nubeel Ansari is the Digital Leader for Oil & Gas and Utilities industries at SAP India. He is responsible for driving SAP India's Go to Market for these industries, and engage with key customers in these industries through value management, customer co-innovation, digital transformation, and business process performance improvement programs by developing road maps, reimagining business models, and helping them reduce costs with digital technologies.

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.