When Analytics Fail

Nick Petri

Image provided by: ETF Prodigy

After hearing the redundancy of my title, Analyst on OpenView’s Research and Analytics team, most people naturally assume I love numbers. Often I tell them I do. Numbers boil down an infinitely complex world into a manageable format that can be manipulated, modeled, and mined for insight. Accurate numbers, properly used, can teach you a ton about how the world works, and in turn, the adjustments you make based on that analysis can affect the world in tangible and profound ways.

But numbers can’t answer everything, and if you follow them blindly, you can be badly misled.

Too many executives, whether “numbers people” or not, see statistical analysis as a necessary stamp of approval to any business decision.  But the simple truth is that there isn’t a mathematical answer to every question, and if you force one using data that doesn’t accurately describe the real world, no amount of color-coded charts, quadratic regressions, and chi-squared tests will yield an ounce of insight.

These situations are incredibly common in the business world. Unlike physicists, chemists, or biologists, business people are unable to run tightly controlled experiments. We can’t scour the earth for cool problems with clean statistical answers, like academics can. The problems come to us, and they’re usually messy and fraught with biases.

While the statistical discipline has very good tools for identifying relationships within a data set, it’s blind to the quality of the data itself. Here are three common problems that can render a statistically significant conclusion dead wrong:

  • Self-Selection: Survey or interview respondents often respond because they have good things to say about the subject. Likewise, firms prefer to disclose financial information when it’s favorable or improving. This type of problem paints a rosier picture, on average, than is really the case.
  • Missing Data: More information is almost always available on larger companies and more recent events. When there’s missing information, do you come up with a proxy, estimate the missing fields, or exclude those entries altogether? Any solution you choose will introduce a layer of noise into the equation.
  • Tenuous Proxies: Say we’re trying to measure the impact of marketing spend on customer acquisition for a particular industry. Since neither variable is public, we’ll have to use proxies and assumptions to estimate them. It’s important to remember that the ultimate conclusion isn’t measuring the actual variables, but their proxies: the strength of the conclusion relies heavily on how close the two are. Since we don’t have the actual variables, this can be very difficult to measure.

The result is a difficult balancing act: you have to tolerate moderate levels of bias within the data to reach a conclusion, but as the problems pile up, the validity of that conclusion declines no matter how statistically significant it may appear.

Still, an analyst is being paid to solve a problem, and to some, an inconclusive result is the worst kind of failure. It can be tempting to present a conclusion as a home run despite obvious flaws in the methodology. The best analysts properly communicate their level of confidence in the results, and know when to admit that the data at hand is inconclusive, even if it isn’t what their stakeholders were hoping to hear. Doing otherwise can be extremely destructive.

So do I love numbers? I’d say our relationship is rocky. I certainly respect them as a powerful tool to understand the world around me, but am realistic about their limitations. Statistical conclusions are only as good as the data that goes into them, and there isn’t good data for every problem.

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Data Analysts And Scientists More Important Than Ever For The Enterprise

Daniel Newman

The business world is now firmly in the age of data. Not that data wasn’t relevant before; it was just nowhere close to the speed and volume that’s available to us today. Businesses are buckling under the deluge of petabytes, exabytes, and zettabytes. Within these bytes lie valuable information on customer behavior, key business insights, and revenue generation. However, all that data is practically useless for businesses without the ability to identify the right data. Plus, if they don’t have the talent and resources to capture the right data, organize it, dissect it, draw actionable insights from it and, finally, deliver those insights in a meaningful way, their data initiatives will fail.

Rise of the CDO

Companies of all sizes can easily find themselves drowning in data generated from websites, landing pages, social streams, emails, text messages, and many other sources. Additionally, there is data in their own repositories. With so much data at their disposal, companies are under mounting pressure to utilize it to generate insights. These insights are critical because they can (and should) drive the overall business strategy and help companies make better business decisions. To leverage the power of data analytics, businesses need more “top-management muscle” specialized in the field of data science. This specialized field has lead to the creation of roles like Chief Data Officer (CDO).

In addition, with more companies undertaking digital transformations, there’s greater impetus for the C-suite to make data-driven decisions. The CDO helps make data-driven decisions and also develops a digital business strategy around those decisions. As data grows at an unstoppable rate, becoming an inseparable part of key business functions, we will see the CDO act as a bridge between other C-suite execs.

Data skills an emerging business necessity

So far, only large enterprises with bigger data mining and management needs maintain in-house solutions. These in-house teams and technologies handle the growing sets of diverse and dispersed data. Others work with third-party service providers to develop and execute their big data strategies.

As the amount of data grows, the need to mine it for insights becomes a key business requirement. For both large and small businesses, data-centric roles will experience endless upward mobility. These roles include data anlysts and scientists. There is going to be a huge opportunity for critical thinkers to turn their analytical skills into rapidly growing roles in the field of data science. In fact, data skills are now a prized qualification for titles like IT project managers and computer systems analysts.

Forbes cited the McKinsey Global Institute’s prediction that by 2018 there could be a massive shortage of data-skilled professionals. This indicates a disruption at the demand-supply level with the needs for data skills at an all-time high. With an increasing number of companies adopting big data strategies, salaries for data jobs are going through the roof. This is turning the position into a highly coveted one.

According to Harvard Professor Gary King, “There is a big data revolution. The big data revolution is that now we can do something with the data.” The big problem is that most enterprises don’t know what to do with data. Data professionals are helping businesses figure that out. So if you’re casting about for where to apply your skills and want to take advantage of one of the best career paths in the job market today, focus on data science.

I’m compensated by University of Phoenix for this blog. As always, all thoughts and opinions are my own.

For more insight on our increasingly connected future, see The $19 Trillion Question: Are You Undervaluing The Internet Of Things?

The post Data Analysts and Scientists More Important Than Ever For the Enterprise appeared first on Millennial CEO.

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About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies.
Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book “The Millennial CEO.” Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter.
Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5).
A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

When Good Is Good Enough: Guiding Business Users On BI Practices

Ina Felsheim

Image_part2-300x200In Part One of this blog series, I talked about changing your IT culture to better support self-service BI and data discovery. Absolutely essential. However, your work is not done!

Self-service BI and data discovery will drive the number of users using the BI solutions to rapidly expand. Yet all of these more casual users will not be well versed in BI and visualization best practices.

When your user base rapidly expands to more casual users, you need to help educate them on what is important. For example, one IT manager told me that his casual BI users were making visualizations with very difficult-to-read charts and customizing color palettes to incredible degrees.

I had a similar experience when I was a technical writer. One of our lead writers was so concerned with readability of every sentence that he was going through the 300+ page manuals (yes, they were printed then) and manually adjusting all of the line breaks and page breaks. (!) Yes, readability was incrementally improved. But now any number of changes–technical capabilities, edits, inserting larger graphics—required re-adjusting all of those manual “optimizations.” The time it took just to do the additional optimization was incredible, much less the maintenance of these optimizations! Meanwhile, the technical writing team was falling behind on new deliverables.

The same scenario applies to your new casual BI users. This new group needs guidance to help them focus on the highest value practices:

  • Customization of color and appearance of visualizations: When is this customization necessary for a management deliverable, versus indulging an OCD tendency? I too have to stop myself from obsessing about the font, line spacing, and that a certain blue is just a bit different than another shade of blue. Yes, these options do matter. But help these casual users determine when that time is well spent.
  • Proper visualizations: When is a spinning 3D pie chart necessary to grab someone’s attention? BI professionals would firmly say “NEVER!” But these casual users do not have a lot of depth on BI best practices. Give them a few simple guidelines as to when “flash” needs to subsume understanding. Consider offering a monthly one-hour Lunch and Learn that shows them how to create impactful, polished visuals. Understanding if their visualizations are going to be viewed casually on the way to a meeting, or dissected at a laptop, also helps determine how much time to spend optimizing a visualization. No, you can’t just mandate that they all read Tufte.
  • Predictive: Provide advanced analytics capabilities like forecasting and regression directly in their casual BI tools. Using these capabilities will really help them wow their audience with substance instead of flash.
  • Feature requests: Make sure you understand the motivation and business value behind some of the casual users’ requests. These casual users are less likely to understand the implications of supporting specific requests across an enterprise, so make sure you are collaborating on use cases and priorities for substantive requests.

By working with your casual BI users on the above points, you will be able to collectively understand when the absolute exact request is critical (and supports good visualization practices), and when it is an “optimization” that may impact productivity. In many cases, “good” is good enough for the fast turnaround of data discovery.

Next week, I’ll wrap this series up with hints on getting your casual users to embrace the “we” not “me” mentality.

Read Part One of this series: Changing The IT Culture For Self-Service BI Success.

Follow me on Twitter: @InaSAP

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Tick Tock: Start Preparing for Resource Disruption

By Maurizio Cattaneo, Joerg Ferchow, Daniel Wellers, and Christopher Koch

Businesses share something important with lions. When a lion captures and consumes its prey, only about 10% to 20% of the prey’s energy is directly transferred into the lion’s metabolism. The rest evaporates away, mostly as heat loss, according to research done in the 1940s by ecologist Raymond Lindeman.

Today, businesses do only about as well as the big cats. When you consider the energy required to manage, power, and move products and services, less than 20% goes directly into the typical product or service—what economists call aggregate efficiency (the ratio of potential work to the actual useful work that gets embedded into a product or service at the expense of the energy lost in moving products and services through all of the steps of their value chains). Aggregate efficiency is a key factor in determining productivity.

After making steady gains during much of the 20th century, businesses’ aggregate energy efficiency peaked in the 1980s and then stalled. Japan, home of the world’s most energy-efficient economy, has been skating along at or near 20% ever since. The U.S. economy, meanwhile, topped out at about 13% aggregate efficiency in the 1990s, according to research.

Why does this matter? Jeremy Rifkin says he knows why. Rifkin is an economic and social theorist, author, consultant, and lecturer at the Wharton School’s Executive Education program who believes that economies experience major increases in growth and productivity only when big shifts occur in three integrated infrastructure segments around the same time: communications, energy, and transportation.

But it’s only a matter of time before information technology blows all three wide open, says Rifkin. He envisions a new economic infrastructure based on digital integration of communications, energy, and transportation, riding atop an Internet of Things (IoT) platform that incorporates Big Data, analytics, and artificial intelligence. This platform will disrupt the world economy and bring dramatic levels of efficiency and productivity to businesses that take advantage of it,
he says.

Some economists consider Rifkin’s ideas controversial. And his vision of a new economic platform may be problematic—at least globally. It will require massive investments and unusually high levels of government, community, and private sector cooperation, all of which seem to be at depressingly low levels these days.

However, Rifkin has some influential adherents to his philosophy. He has advised three presidents of the European Commission—Romano Prodi, José Manuel Barroso, and the current president, Jean-Claude Juncker—as well as the European Parliament and numerous European Union (EU) heads of state, including Angela Merkel, on the ushering in of what he calls “a smart, green Third Industrial Revolution.” Rifkin is also advising the leadership of the People’s Republic of China on the build out and scale up of the “Internet Plus” Third Industrial Revolution infrastructure to usher in a sustainable low-carbon economy.

The internet has already shaken up one of the three major economic sectors: communications. Today it takes little more than a cell phone, an internet connection, and social media to publish a book or music video for free—what Rifkin calls zero marginal cost. The result has been a hollowing out of once-mighty media empires in just over 10 years. Much of what remains of their business models and revenues has been converted from physical (remember CDs and video stores?) to digital.

But we haven’t hit the trifecta yet. Transportation and energy have changed little since the middle of the last century, says Rifkin. That’s when superhighways reached their saturation point across the developed world and the internal-combustion engine came close to the limits of its potential on the roads, in the air, and at sea. “We have all these killer new technology products, but they’re being plugged into the same old infrastructure, and it’s not creating enough new business opportunities,” he says.

All that may be about to undergo a big shake-up, however. The digitalization of information on the IoT at near-zero marginal cost generates Big Data that can be mined with analytics to create algorithms and apps enabling ubiquitous networking. This digital transformation is beginning to have a big impact on the energy and transportation sectors. If that trend continues, we could see a metamorphosis in the economy and society not unlike previous industrial revolutions in history. And given the pace of technology change today, the shift could happen much faster than ever before.

The speed of change is dictated by the increase in digitalization of these three main sectors; expensive physical assets and processes are partially replaced by low-cost virtual ones. The cost efficiencies brought on by digitalization drive disruption in existing business models toward zero marginal cost, as we’ve already seen in entertainment and publishing. According to research company Gartner, when an industry gets to the point where digital drives at least 20% of revenues, you reach the tipping point.

“A clear pattern has emerged,” says Peter Sondergaard, executive vice president and head of research and advisory for Gartner. “Once digital revenues for a sector hit 20% of total revenue, the digital bloodbath begins,” he told the audience at Gartner’s annual 2017 IT Symposium/ITxpo, according to The Wall Street Journal. “No matter what industry you are in, 20% will be the point of no return.”

Communications is already there, and energy and transportation are heading down that path. If they hit the magic 20% mark, the impact will be felt not just within those industries but across all industries. After all, who doesn’t rely on energy and transportation to power their value chains?

The eye of the technology disruption hurricane has moved beyond communications and is heading toward … the rest of the economy.

That’s why businesses need to factor potentially massive business model disruptions into their plans for digital transformation today if they want to remain competitive with organizations in early adopter countries like China and Germany. China, for example, is already halfway through an US$88 billion upgrade to its state electricity grid that will enable renewable energy transmission around the country—all managed and moved digitally, according to an article in The Economist magazine. And it is competing with the United States for leadership in self-driving vehicles, which will shift the transportation process and revenue streams heavily to digital, according to an article in Wired magazine.

Once China’s and Germany’s renewables and driverless infrastructures are in place, the only additional costs are management and maintenance. That could bring businesses in these countries dramatic cost savings over those that still rely on fossil fuels and nuclear energy to power their supply chains and logistics. “Once you pay the fixed costs of renewables, the marginal costs are near zero,” says Rifkin. “The sun and wind haven’t sent us invoices yet.”

In other words, zero marginal cost has become a zero-sum game.

To understand why that is, consider the major industrial revolutions in history, writes Rifkin in his books, The Zero Marginal Cost Society and The Third Industrial Revolution. The first major shift occurred in the 19th century when cheap, abundant coal provided an efficient new source of power (steam) for manufacturing and enabled the creation of a vast railway transportation network. Meanwhile, the telegraph gave the world near-instant communication over a globally connected network.

The second big change occurred at the beginning of the 20th century, when inexpensive oil began to displace coal and gave rise to a much more flexible new transportation network of cars and trucks. Telephones, radios, and televisions had a similar impact on communications.

Breaking Down the Walls Between Sectors

Now, according to Rifkin, we’re poised for the third big shift. The eye of the technology disruption hurricane has moved beyond communications and is heading toward—or as publishing and entertainment executives might warn, coming for—the rest of the economy. With its assemblage of global internet and cellular network connectivity and ever-smaller and more powerful sensors, the IoT, along with Big Data analytics and artificial intelligence, is breaking down the economic walls that have protected the energy and transportation sectors for the past 50 years.

Daimler is now among the first movers in transitioning into a digitalized mobility internet. The company has equipped nearly 400,000 of its trucks with external sensors, transforming the vehicles into mobile Big Data centers. The sensors are picking up real-time Big Data on weather conditions, traffic flows, and warehouse availability. Daimler plans to establish collaborations with thousands of companies, providing them with Big Data and analytics that can help dramatically increase their aggregate efficiency and productivity in shipping goods across their value chains. The Daimler trucks are autonomous and capable of establishing platoons of multiple trucks driving across highways.

It won’t be long before vehicles that navigate the more complex transportation infrastructures around the world begin to think for themselves. Autonomous vehicles will bring massive economic disruption to transportation and logistics thanks to new aggregate efficiencies. Without the cost of having a human at the wheel, autonomous cars could achieve a shared cost per mile below that of owned vehicles by as early as 2030, according to research from financial services company Morgan Stanley.

The transition is getting a push from governments pledging to give up their addiction to cars powered by combustion engines. Great Britain, France, India, and Norway are seeking to go all electric as early as 2025 and by 2040 at the latest.

The Final Piece of the Transition

Considering that automobiles account for 47% of petroleum consumption in the United States alone—more than twice the amount used for generators and heating for homes and businesses, according to the U.S. Energy Information Administration—Rifkin argues that the shift to autonomous electric vehicles could provide the momentum needed to upend the final pillar of the economic platform: energy. Though energy has gone through three major disruptions over the past 150 years, from coal to oil to natural gas—each causing massive teardowns and rebuilds of infrastructure—the underlying economic model has remained constant: highly concentrated and easily accessible fossil fuels and highly centralized, vertically integrated, and enormous (and enormously powerful) energy and utility companies.

Now, according to Rifkin, the “Third Industrial Revolution Internet of Things infrastructure” is on course to disrupt all of it. It’s neither centralized nor vertically integrated; instead, it’s distributed and networked. And that fits perfectly with the commercial evolution of two energy sources that, until the efficiencies of the IoT came along, made no sense for large-scale energy production: the sun and the wind.

But the IoT gives power utilities the means to harness these batches together and to account for variable energy flows. Sensors on solar panels and wind turbines, along with intelligent meters and a smart grid based on the internet, manage a new, two-way flow of energy to and from the grid.

Today, fossil fuel–based power plants need to kick in extra energy if insufficient energy is collected from the sun and wind. But industrial-strength batteries and hydrogen fuel cells are beginning to take their place by storing large reservoirs of reserve power for rainy or windless days. In addition, electric vehicles will be able to send some of their stored energy to the digitalized energy internet during peak use. Demand for ever-more efficient cell phone and vehicle batteries is helping push the evolution of batteries along, but batteries will need to get a lot better if renewables are to completely replace fossil fuel energy generation.

Meanwhile, silicon-based solar cells have not yet approached their limits of efficiency. They have their own version of computing’s Moore’s Law called Swanson’s Law. According to data from research company Bloomberg New Energy Finance (BNEF), Swanson’s Law means that for each doubling of global solar panel manufacturing capacity, the price falls by 28%, from $76 per watt in 1977 to $0.41 in 2016. (Wind power is on a similar plunging exponential cost curve, according to data from the U.S. Department of Energy.)

Thanks to the plummeting solar price, by 2028, the cost of building and operating new sun-based generation capacity will drop below the cost of running existing fossil power plants, according to BNEF. “One of the surprising things in this year’s forecast,” says Seb Henbest, lead author of BNEF’s annual long-term forecast, the New Energy Outlook, “is that the crossover points in the economics of new and old technologies are happening much sooner than we thought last year … and those were all happening a bit sooner than we thought the year before. There’s this sense that it’s not some distant risk or distant opportunity. A lot of these realities are rushing toward us.”

The conclusion, he says, is irrefutable. “We can see the data and when we map that forward with conservative assumptions, these technologies just get cheaper than everything else.”

The smart money, then—72% of total new power generation capacity investment worldwide by 2040—will go to renewable energy, according to BNEF. The firm’s research also suggests that there’s more room in Swanson’s Law along the way, with solar prices expected to drop another 66% by 2040.

Another factor could push the economic shift to renewables even faster. Just as computers transitioned from being strictly corporate infrastructure to becoming consumer products with the invention of the PC in the 1980s, ultimately causing a dramatic increase in corporate IT investments, energy generation has also made the transition to the consumer side.

Thanks to future tech media star Elon Musk, consumers can go to his Tesla Energy company website and order tempered glass solar panels that look like chic, designer versions of old-fashioned roof shingles. Models that look like slate or a curved, terracotta-colored, ceramic-style glass that will make roofs look like those of Tuscan country villas, are promised soon. Consumers can also buy a sleek-looking battery called a Powerwall to store energy from the roof.

The combination of solar panels, batteries, and smart meters transforms homeowners from passive consumers of energy into active producers and traders who can choose to take energy from the grid during off-peak hours, when some utilities offer discounts, and sell energy back to the grid during periods when prices are higher. And new blockchain applications promise to accelerate the shift to an energy market that is laterally integrated rather than vertically integrated as it is now. Consumers like their newfound sense of control, according to Henbest. “Energy’s never been an interesting consumer decision before and suddenly it is,” he says.

As the price of solar equipment continues to drop, homes, offices, and factories will become like nodes on a computer network. And if promising new solar cell technologies, such as organic polymers, small molecules, and inorganic compounds, supplant silicon, which is not nearly as efficient with sunlight as it is with ones and zeroes, solar receivers could become embedded into windows and building compounds. Solar production could move off the roof and become integrated into the external facades of homes and office buildings, making nearly every edifice in town a node.

The big question, of course, is how quickly those nodes will become linked together—if, say doubters, they become linked at all. As we learned from Metcalfe’s Law, the value of a network is proportional to its number of connected users.

The Will Determines the Way

Right now, the network is limited. Wind and solar account for just 5% of global energy production today, according to Bloomberg.

But, says Rifkin, technology exists that could enable the network to grow exponentially. We are seeing the beginnings of a digital energy network, which uses a combination of the IoT, Big Data, analytics, and artificial intelligence to manage distributed energy sources, such as solar and wind power from homes and businesses.

As nodes on this network, consumers and businesses could take a more active role in energy production, management, and efficiency, according to Rifkin. Utilities, in turn, could transition from simply transmitting power and maintaining power plants and lines to managing the flow to and from many different energy nodes; selling and maintaining smart home energy management products; and monitoring and maintaining solar panels and wind turbines. By analyzing energy use in the network, utilities could create algorithms that automatically smooth the flow of renewables. Consumers and businesses, meanwhile, would not have to worry about connecting their wind and solar assets to the grid and keeping them up and running; utilities could take on those tasks more efficiently.

Already in Germany, two utility companies, E.ON and RWE, have each split their businesses into legacy fossil and nuclear fuel companies and new services companies based on distributed generation from renewables, new technologies, and digitalization.

The reason is simple: it’s about survival. As fossil fuel generation winds down, the utilities need a new business model to make up for lost revenue. Due to Germany’s population density, “the utilities realize that they won’t ever have access to enough land to scale renewables themselves,” says Rifkin. “So they are starting service companies to link together all the different communities that are building solar and wind and are managing energy flows for them and for their customers, doing their analytics, and managing their Big Data. That’s how they will make more money while selling less energy in the future.”

The digital energy internet is already starting out in pockets and at different levels of intensity around the world, depending on a combination of citizen support, utility company investments, governmental power, and economic incentives.

China and some countries within the EU, such as Germany and France, are the most likely leaders in the transition toward a renewable, energy-based infrastructure because they have been able to align the government and private sectors in long-term energy planning. In the EU for example, wind has already overtaken coal as the second largest form of power capacity behind natural gas, according to an article in The Guardian newspaper. Indeed, Rifkin has been working with China, the EU, and governments, communities, and utilities in Northern France, the Netherlands, and Luxembourg to begin building these new internets.

Hauts-de-France, a region that borders the English Channel and Belgium and has one of the highest poverty rates in France, enlisted Rifkin to develop a plan to lift it out of its downward spiral of shuttered factories and abandoned coal mines. In collaboration with a diverse group of CEOs, politicians, teachers, scientists, and others, it developed Rev3, a plan to put people to work building a renewable energy network, according to an article in Vice.

Today, more than 1,000 Rev3 projects are underway, encompassing everything from residential windmills made from local linen to a fully electric car–sharing system. Rev3 has received financial support from the European Investment Bank and a handful of private investment funds, and startups have benefited from crowdfunding mechanisms sponsored by Rev3. Today, 90% of new energy in the region is renewable and 1,500 new jobs have been created in the wind energy sector alone.

Meanwhile, thanks in part to generous government financial support, Germany is already producing 35% of its energy from renewables, according to an article in The Independent, and there is near unanimous citizen support (95%, according to a recent government poll) for its expansion.

If renewables are to move forward …, it must come from the ability to make green, not act green.

If renewable energy is to move forward in other areas of the world that don’t enjoy such strong economic and political support, however, it must come from the ability to make green, not act green.

Not everyone agrees that renewables will produce cost savings sufficient to cause widespread cost disruption anytime soon. A recent forecast by the U.S. Energy Information Administration predicts that in 2040, oil, natural gas, and coal will still be the planet’s major electricity producers, powering 77% of worldwide production, while renewables such as wind, solar, and biofuels will account for just 15%.

Skeptics also say that renewables’ complex management needs, combined with the need to store reserve power, will make them less economical than fossil fuels through at least 2035. “All advanced economies demand full-time electricity,” Benjamin Sporton, chief executive officer of the World Coal Association told Bloomberg. “Wind and solar can only generate part-time, intermittent electricity. While some renewable technologies have achieved significant cost reductions in recent years, it’s important to look at total system costs.”

On the other hand, there are many areas of the world where distributed, decentralized, renewable power generation already makes more sense than a centralized fossil fuel–powered grid. More than 20% of Indians in far flung areas of the country have no access to power today, according to an article in The Guardian. Locally owned and managed solar and wind farms are the most economical way forward. The same is true in other developing countries, such as Afghanistan, where rugged terrain, war, and tribal territorialism make a centralized grid an easy target, and mountainous Costa Rica, where strong winds and rivers have pushed the country to near 100% renewable energy, according to The Guardian.

The Light and the Darknet

Even if all the different IoT-enabled economic platforms become financially advantageous, there is another concern that could disrupt progress and potentially cause widespread disaster once the new platforms are up and running: hacking. Poorly secured IoT sensors have allowed hackers to take over everything from Wi-Fi enabled Barbie dolls to Jeep Cherokees, according to an article in Wired magazine.

Humans may be lousy drivers, but at least we can’t be hacked (yet). And while the grid may be prone to outages, it is tightly controlled, has few access points for hackers, and is physically separated from the Wild West of the internet.

If our transportation and energy networks join the fray, however, every sensor, from those in the steering system on vehicles to grid-connected toasters, becomes as vulnerable as a credit card number. Fake news and election hacking are bad enough, but what about fake drivers or fake energy? Now we’re talking dangerous disruptions and putting millions of people in harm’s way.

The only answer, according to Rifkin, is for businesses and governments to start taking the hacking threat much more seriously than they do today and to begin pouring money into research and technologies for making the internet less vulnerable. That means establishing “a fully distributed, redundant, and resilient digital infrastructure less vulnerable to the kind of disruptions experienced by Second Industrial Revolution–centralized communication systems and power grids that are increasingly subject to climate change, disasters, cybercrime, and cyberterrorism,” he says. “The ability of neighborhoods and communities to go off centralized grids during crises and re-aggregate in locally decentralized networks is the key to advancing societal security in the digital era,” he adds.

Start Looking Ahead

Until today, digital transformation has come mainly through the networking and communications efficiencies made possible by the internet. Airbnb thrives because web communications make it possible to create virtual trust markets that allow people to feel safe about swapping their most private spaces with one another.

But now these same efficiencies are coming to two other areas that have never been considered core to business strategy. That’s why businesses need to begin managing energy and transportation as key elements of their digital transformation portfolios.

Microsoft, for example, formed a senior energy team to develop an energy strategy to mitigate risk from fluctuating energy prices and increasing demands from customers to reduce carbon emissions, according to an article in Harvard Business Review. “Energy has become a C-suite issue,” Rob Bernard, Microsoft’s top environmental and sustainability executive told the magazine. “The CFO and president are now actively involved in our energy road map.”

As Daimler’s experience shows, driverless vehicles will push autonomous transportation and automated logistics up the strategic agenda within the next few years. Boston Consulting Group predicts that the driverless vehicle market will hit $42 billion by 2025. If that happens, it could have a lateral impact across many industries, from insurance to healthcare to the military.

Businesses must start planning now. “There’s always a period when businesses have to live in the new and the old worlds at the same time,” says Rifkin. “So businesses need to be considering new business models and structures now while continuing to operate their existing models.”

He worries that many businesses will be left behind if their communications, energy, and transportation infrastructures don’t evolve. Companies that still rely on fossil fuels for powering traditional transportation and logistics could be at a major competitive disadvantage to those that have moved to the new, IoT-based energy and transportation infrastructures.

Germany, for example, has set a target of 80% renewables for gross power consumption by 2050, according to The Independent. If the cost advantages of renewables bear out, German businesses, which are already the world’s third-largest exporters behind China and the United States, could have a major competitive advantage.

“How would a second industrial revolution society or country compete with one that has energy at zero marginal cost and driverless vehicles?” asks Rifkin. “It can’t be done.” D!


About the Authors

Maurizio Cattaneo is Director, Delivery Execution, Energy and Natural Resources, at SAP.

Joerg Ferchow is Senior Utilities Expert and Design Thinking Coach, Digital Transformation, at SAP.

Daniel Wellers is Digital Futures Lead, Global Marketing, at SAP.

Christopher Koch is Editorial Director, SAP Center for Business Insight, at SAP.


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

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No Longer Soft Skills: Five Crucial Workplace Skills Everyone Should Learn

Carmen O'Shea

My child’s elementary school focuses on skills they believe support children in becoming changemakers. Through use of an integrated, project-based curriculum, they explicitly teach and assess “learner values” such as iteration, risk, failure, collaboration, and perspective. Their philosophy is that these attributes long considered “soft skills” have become the crucial educational priorities for this generation.

Why do they believe this? Much knowledge is now easily accessed and readily queried, such that the acquisition of specific content or know-how is far less important than how to apply that content in different situations and how to interact with others in the pursuit of goals. This holds true in the workplace as well as the academic environment. When I think about how I operate in my job at a large technology company, it’s not really what I know but what I do with what I know, and whom I engage to get things accomplished.

Watching the school teach these skills just as they do math or language has made me stop and consider what they look like for an employee. I wanted to share my thoughts on five qualities beyond relevant academic skills or professional experience that are just as important (if not more so) in predicting top work performance. These are more qualitative skills that managers should hire for, employees should develop, and organizations should optimize for.

  • Empathythe ability to see and integrate multiple perspectives and to understand the impact of how others think. Empathy can also mean advocating and showing empathy for oneself and for others. Empathy is assuming a good intention even when someone has said or done something we dislike – to stop and pause, attempt to understand, and respond compassionately in a difficult workplace situation. Empathy also extends to intuiting beyond just the professional environment to more of a personal level to truly understand what drives a colleague or employee.
  • Resiliencethe ability to take risks even when you know you may fail and then to bounce back, sometimes repeatedly, from failure. Inherent in resilience is the idea of iteration – that it is often essential to try things multiple times, in multiple ways, from multiple angles, before achieving a desired outcome. Resilience is receiving difficult yet constructive feedback from a manager or peer and resolving to act positively on it instead of wallowing or harboring a grudge. Resilience is maintaining a sense of optimism even in a down quarter at work.
  • Creativitythe ability to think differently or expansively and to approach a problem from multiple angles. Sometimes it’s called “thinking outside the box.” Creativity often includes inquiry, the act of questioning and satisfying one’s curiosity about particular topics. Torrance defined it along several parameters – number of ideas generated, number of categories of ideas, originality of ideas, and how detailed each idea is elaborated. We see it in action during brainstorming phases of projects, but it’s also possible to apply creativity on a continual basis, by pushing colleagues to expand on their thoughts, by not being satisfied with a less than stellar answer, by taking time to understand how multiple approaches to an issue could be combined, or by simply trying something new in a familiar situation.
  • Collaborationthe ability to interact and work productively with others, in all size groups. Effective collaboration requires empathy, especially when collaborators have different backgrounds, styles, or thought processes. Collaboration also requires exemplary communication skills, both oral and written, as well as reflective listening. So much of our tasks on the job require collaboration with others, whether to inform, persuade, learn, or engage, and these interactions form the bedrock for innovation. It’s tough to innovate without collaborating.
  • Flexibilitythe ability to adapt or change course if that is what the situation demands. Flexibility includes letting go of one’s idea in the interest of attaining a goal more quickly. It can also include development a comfort level with uncertainty or ambiguity, especially in times of change. Flexibility is a willingness to absorb feedback objectively and course correct as needed without personalizing the information or demonizing the provider of it. Expounding on another’s idea (not our own) in a brainstorming session demonstrates flexibility, as does remaining calm while an org change takes effect and roles are temporarily unclear.

When employees exhibit these qualities, they are better able to understand their purpose at work and to unleash their passions in the pursuit of that purpose. When teams exhibit these qualities, achievement and employee engagement are higher.  I wager that retention and innovation will improve as well. It’s heartening that as a society we’re beginning to consider how to best prepare our children educationally for the kind of work environments they will encounter after they finish their academic journey.

Do you also see these qualities as valuable in assessing employee fit? How can managers and organizations better identify, train and reward employees for living these qualities?

For more on this topic, see Your Business Needs People With Skills, Not Just Qualifications.

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Carmen O'Shea

About Carmen O'Shea

Carmen O’Shea is the Senior Vice President of HR Change & Engagement at SAP. She leads a global team supporting major transformation initiatives across the company, focused on change management, employee engagement, and creative marketing and interaction. You can follow Carmen on Twitter.