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Civic Hacking: Evolution Of Public Policy Or Hype?

Natalie Kenny

It is the modern reality that the speed of technological change, globalisation, and economic mobility are making our world increasingly connected and diverse. The challenges that face government to put the correct precautions and safety nets in place to protect their citizens from economic and social risk require new skills and knowledge.

At the same time, governments have access to a new dimension of collaboration and consultation with citizens in solving complex civic problems. In a similar manner to opening up to the public a cold case in a criminal investigation, new leads from unexpected sources can sometimes result in new policy options. New roles have emerged in recent years that view technology as a bridge that brings together government, industry, NGOs, and citizens to transform government. They are known as civic hackers.

A short history of hacking

Propagated by the media and popular culture, the image of a “hacker” more often than not brings to mind technically skilled, nefarious individuals huddled away in dark rooms and plugged into their laptops, wreaking havoc against secure systems across the globe with malicious or greedy intent.

Indeed, the hackers we hear about in the media are generally associated with high-profile security breaches such as the devastating cyberattacks on Sony Pictures Entertainment or extramarital affairs website Ashley Madison, which saw private and confidential data such as credit card information, e-mails, home addresses, salacious photographs, and phone numbers leaked out across the Internet in droves.

These examples of hackers are contradictory to the ethos of the civic hacking movement. Their vision is altruistic and seeks work collaboratively across communities to improve the operation of government and outcomes for citizens. Civic hacking expanded out of an idea to bring highly skilled coders, programmers and developers together to improve government through technology.

Although it started with technology, the term civic hacking has evolved and is being applied to anyone who looks to improve civic outcomes in more efficient and creative ways. As Jake Levitas from the organisation Code for America notes, “These days I see just as many community leaders, architects, environmentalists, artists, and other professionals coming out to events under the purview of civic hacking as coders and designers.”

The evolution of civic hacking

In recent years, there has been a global movement in government towards information openness and transparency. Initiated by the United States, the last decade has seen over 70 countries around the world pass legislation for all non-sensitive public data collected across levels of government to be made open by default and published to the world. Globally it is estimated there are more than one million open datasets that have been made available today on digital portals across all levels of government (local, state, and federal), research institutions (CSIRO), and not-for-profit institutions (United Nations, WHO).

Whilst originally started as an action to promote greater government transparency and accountability, smart and creative technology enthusiasts recognised that they could take this information released by governments and use it to create new value for communities. These original civic hackers worked to build open source apps, create visualisation tools such a dashboards, or build new business models and products for market, and support the transformation of government service delivery and offerings.

Civic hackers were not just working to revolutionise government from the outside in. Governments began waking up to the potential value in civic hacking at the same time that technological capability made it possible to more easily share data and digitally interact with communities. Governments around the world now regularly host and sponsor hackathons, which bring together people with technical backgrounds to form teams around a civic problem or idea and collaboratively code a unique solution from scratch (GovHack, HackLondon).

New jobs have been advertised to bring technical skills formally into the public service such as the Australian Digital Transformation’s posting for an “ethical hacker” in 2015.  Formal civic hacking organisations have even been established, such as DataKind, Code for All, Rewired State, and IndianKanoon. These groups enlist coders and technology professionals to work with governments to build open-source applications, foster startup and agile-led approaches to government service delivery and promote the sharing of public data to foster transparency and innovation.

A great example of what can be achieved by the civic hacking community is their response immediately after the 2011 Haiti earthquake. Using information gathered from online social and mainstream media and satellite images, they built a detailed real-time crisis map of Haiti.

Haiti

This resource directly helped to saves lives. Humanitarian aid workers were able to use the map to navigate collapsed roads and buildings and more effectively deliver aid, resources, and emergency assistance to those in need.

Civic hacking: revolutionary or an exaggeration of value?

However, with nearly a decade of civic “hactivism” at work, numerous open government policies in place, and one million open government datasets available, the question to be asked is: Why hasn’t more been achieved?

Why has this abundance of availability not led to widespread and long lasting social, economic and political change? It seems as though despite the amount of effort put into this movement, the ideas and outcomes generated are not always sustainable and do not lead to long-lasting government transformation. This is not to say there is no place for civic hacking; rather there needs to be a new approach to hacker coordination.

There are several reasons as to why this might be the case:

1. The quality and availability of open data published by government is inconsistent

Simply releasing open data to the public is not enough. The open data that is being made available on government portals is hard to find, not well structured or described, dumped in silos and data portals across every department and level of government, and not readily published in easily linkable formats. This makes it challenging for civic hackers to search portals, identify datasets that are useful, combine them, and perform meaningful analysis on that information to help solve challenging social and civic problems.

2. Coordination of civic hacking can be complex and disorderly

With the exception of formal hackathons or specific groups such as Code for All, most civic hackers work remotely from outside governments, in different locations and geographies. There can be a lack of continuity. Referencing what work has been done previously by other hackers is difficult to determine and can lead to repeated efforts and duplicated work. Hackers may work on one project or idea and then quickly move on to the next, so flaws may go unrecognised.

3. Expectations need to be realistic; innovation takes time and is iterative

Hackathons, civic coding meet-ups, and short embedded projects in government often have limited parameters, undefined governance and ownership, and work at a breakneck pace. These factors can narrow the possibility of lasting innovation. Ideas are developed and confined by the data, skills, and experiences that are made available in the room on the day or online.

Civic hackers may not always have the right contextual knowledge and expertise, so they tend to come up with ideas that are neither feasible nor realistic in the real world. Part of the challenge is that it can be difficult and time-consuming to perform meaningful market research and financial planning or identify possible risky side effects of an idea in short project timelines. After projects and hackathons are complete, research can reveal that similar projects were created in the past and had failed to find a market.

4. Solving complex problems requires an ecosystem

Ideas and solutions may also fail to deliver long-lasting change without the internal support from the departments and agencies they target or whose data they use. Even the greatest technical solution can fail rapidly if it is constrained by lack of access to data or strict policy requirements that prohibit the sharing or linking of data across programs. Finding a way to bring these skills and talents together in a combined effort that targets all levels of the problem and matches up skilled civic hackers with experienced government public servants will lead to greater outcomes for everyone.

This is not to say civic hacking and all of these engagements don’t have their value and place. The digital era has enabled the concept of civic hacking. Each of these outputs could add a piece to the greater puzzle. Moreover, they are fun, engaging, and bring together skilled and passionate people to work on creative ideas. This can be an effective way for government to source ideas from non-traditional actors in the policy making process. Civic hacking may not solve a complex problem in its own right, but it has the ability to generate new ideas, foster collaboration, and build awareness for important civic issues and challenges, which could lead to a solution.

For more blogs on civic hacking, click here.

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Natalie Kenny

About Natalie Kenny

Natalie Kenny is an Industry Value Engineer at SAP, focused on digital transformation of public sector organisations across Australia and New Zealand. She is dedicated to helping governments re-imagine future ways to interact with and deliver services to citizens. Natalie's key focus area is exploring how digital technologies can help un-tap the immense value that lies in government data to extract new value and insights and help solve challenging civic problems.

Why Corporate Social Responsibility Could Be Your Next Strategic Priority

Derek Klobucher

When organizations do the right thing, value can extend far beyond the good deed itself. Corporate social responsibility (CSR) can help drive better business outcomes, attract like-minded partners, increase employee engagement and more.

“Just like human resources years ago … CSR is going to grow into a strategic partner in the company,” John Matthews, SAP’s global vice president of HCM LoB Business Partner, Global Customer Strategy & Business Operations, said on Changing The Game with HR last week. “Doing good is also good for business.”

CSR refers to how organizations go above and beyond to evaluate and own their environmental and social impacts. But growing into strategic partnership with other, more quantifiable lines of business would require objective CSR metrics.

Quantifying good deeds

“We’re going to see the emergence of an index that captures the corporate social responsibility agenda … the responsibility with which companies act,” Chris Johnson, senior partner at New York-based human resources consulting firm Mercer, said on Changing the Game with HR. “And the index will be a key part of how the company will be accountable to its shareholders.”

If this seems farfetched, consider that shareholders are also beginning to demand sustainability. And organizations already get rated as best places to work, on work-life balance, and many other ratings; and Mercer even sponsors the Britain’s Healthiest Company index.

Johnson predicts a CSR index within the decade.

“It could be a very public account—a transparency and public accountability thing,” Johnson said. Advocacy groups “will be able to go to those companies that are low down [on] the index, and offer them a way of clamoring up the index and demonstrating their broader responsibility to society.”

“People love to work for a corporation that is paying it forward,” Bonnie J. Addario, founder of the Bonnie J. Addario Lung Cancer Foundation, said.

But CSR-minded organizations will still want a return on investment.

Paying it forward

“Corporate social responsibility also helps the bottom line, meaning that it helps you build trust with customers, employees, as well as with your suppliers,” SAP’s Matthews said. “If you give them that guidance, that direction, and you’re clear on what matters, others will come running to you—and come running with you to help solve problems.”

One of Matthews’ “problems” is a 3,400-mile bicycle ride across the U.S. to raise awareness—and funds—for lung cancer research; he’s doing so in memory of his late mother who died of the disease. Whether the issue is healthcare, education or implementing design elements that cut costs by increasing energy efficiency, corporate social responsibility can be an effective way to increase employee engagement.

“People love to work for a corporation that is paying it forward,” Bonnie J. Addario, founder of the Bonnie J. Addario Lung Cancer Foundation, said on Changing the Game with HR. “It’s not always about money … it’s about involvement—it’s about having an emotional connection.”

“We’re going to see the emergence of an index that captures the corporate social responsibility agenda … the responsibility with which companies act,” Chris Johnson, senior partner at New York-based human resources consulting firm Mercer, said.

More than a cause

“CSR is becoming much more of a heritage asset, meaning people prefer their service efforts to leave lasting effects,” Kevin Xu, CEO of global intellectual property management company MEBO International, stated on Forbes CommunityVoice last month. “Rather than championing campaigns that make big splashes, businesses want to build and work toward causes that resonate with and get carried on by younger generations.”

These efforts can lead to new partnerships with like-minded organizations—what a wireless solutions provider’s CEO called a “return on doing good,” as opposed to a simple return on investment. And it’s a great way to build pride within the organization.

“I’ve already had 30 people from SAP from all across the world … who just heard what we were doing, and said, ‘How can I help?’” SAP’s Matthews said. “And it grows every day … so I’m very happy, fortunate, and proud to work for SAP.”

This story originally appeared on SAP’s Business TrendsClick here for a replay of this episode. And click here to learn more about Matthews’ ride. Follow Derek on Twitter@DKlobucher

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Derek Klobucher

About Derek Klobucher

Derek Klobucher is a Brand Journalist, Content Marketer and Master Digital Storyteller at SAP. His responsibilities include conceiving, developing and conducting global, company-wide employee brand journalism training; managing content, promotion and strategy for social networks and online media; and mentoring SAP employees, contractors and interns to optimize blogging and social media efforts.

Diversity Is Hard Work And Requires Rethinking

Anka Wittenberg

In the third episode of the SAP Future Factor series, I sat down with Iris Bohnet, professor of public policy and behavioral economist at the Harvard Kennedy School of Government, to talk about the positive impact of diversity in the workplace for employee engagement and the business bottom line. We also talked about what it takes for companies to create an inclusive work environment.

Hint: It does not happen overnight.

Anka: As we discussed during our SAP Future Factor episode, an increasing number of companies are paying attention to diversity in the workplace.

Iris: Yes, workplaces today are much more heterogenous. Companies recognize that this heterogeneity is an asset. There is a lot of evidence that diverse teams tend to outperform homogenous teams in terms of creativity, innovation, and group processes.

Anka: There is also a strong business case for diversity and inclusion, which are linked to employee engagement. At SAP, we tracked an increase of 48 million euros on operational profit per year by increasing employee engagement by one percent alone. And, to your point, we see a huge benefit for innovation. Research has consistently shown that the more diverse your teams are, the more innovative you are. To tap into that innovative potential, we use a “design thinking” approach to the way we work at SAP, which means that we work with diverse teams to evaluate an issue from different angles and come up with out-of-the-box ideas.

Furthermore, diversity is important for a company to be able to relate to their customers – the diversity of customers needs to be reflected in the diversity of employees. However, diversity is also increasing complexity – which brings up its own set of challenges.

Iris: Certainly. Diversity is hard work. It is hard work for the exact reason that makes it an asset – bringing together a diversity of perspectives. This helps us consider issues from different angles, but can also be a trigger for debate, argument, disagreement. However, we can’t afford to forget that if we all have the same perspective, we will only move in one direction.

Many companies are implementing diversity training. Diversity training itself may not solve the problem, but it can open doors, and we can integrate technology to help us begin “redesigning” the way we work and even how we learn. From your perspective, what are some of the technologies that will have a positive impact in terms of making companies more diverse and inclusive?

Anka: Technology can be helpful in discovering and eliminating unconscious bias across the HR lifecycle. For example, software can identify biased language in job postings and suggest alternatives, so that companies can source talent more broadly. Machine learning is used to put together diverse teams. I truly believe that technology is a catalyst for change that helps us become aware of unconscious biases and create a more inclusive environment.

However, it’s important to recognize that each company faces its own unique set of challenges. The same company may even experience different challenges in different geographic regions. For example, recruitment might be an issue in one region, but in another, it may be the retention of talent. Given that, it’s critical to identify where the blind spots are, and then put clear action items behind it.

Iris: Precisely. Unfortunately, many companies and governments continue to throw money at the problem without diagnosing what is broken. It’s important to understand what the challenge is and then intervene strategically. For example, I worked with a tech company that found out that it was much less biased based on gender and race than it thought, but on the flipside, had a much bigger disciplinary bias. Blind evaluation, as we discuss in the Future Factor episode, can be helpful in terms of eliminating implicit bias in hiring.

Anka: Adopting an inclusive mindset and embracing diversity go beyond recruitment. As you mentioned earlier, we have a much more heterogeneous workforce today. For example, at SAP, we have a workforce that spans five generations. We have programs in place, such as “Autism at Work,” to recruit differently abled individuals who excel at certain tasks but may have a different way of working. This means that we need to change the norms around work to integrate individuals with different backgrounds, expectations, and working styles.

Iris: I couldn’t agree more. Previously when we talked about flexibility, it was pretty much associated with women. But now, we have a whole new generation of people with different needs, including requiring more flexible work arrangements for various reasons such as child care or elder care or simply because they want to pursue interests outside of work. It is a surprise for many companies that employees are no longer defining themselves with work.

Anka: Thank you, Iris, for being part of the SAP Future Factor series and for your support and guidance in helping SAP achieve its goal of 25% women in leadership. As you know, it was a journey over many years, but we built a strategy around the goal and now have an environment that is inclusive of the thoughts and opinions of men and women in management. This allows us to better serve an increasingly diverse customer base, attract and retain talent, and compete in the global economy.

Before we conclude, I want to congratulate you on the publication of the German edition of your book, What Works: Gender Equality by Design. It is an excellent resource for understanding organizational dynamics and design in relation to diversity and inclusion.

To watch the entire discussion between SAP chief diversity officer Anka Wittenberg and Prof. Iris Bohnet, click here

For more on digitization, work, and HR, visit Episode 1 and Episode 2 of the SAP Future Factor Web Salon, in which HR executives and thought leaders from science/academia discuss the digitization of work.

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Anka Wittenberg

About Anka Wittenberg

Anka Wittenberg is the Chief Diversity & Inclusion Officer at SAP. She is responsible for the development and implementation of SAP’s Diversity and Inclusion strategy globally, ensuring sustainable business success.

Primed: Prompting Customers to Buy

Volker Hildebrand, Sam Yen, and Fawn Fitter

When it comes to buying things—even big-ticket items—the way we make decisions makes no sense. One person makes an impulsive offer on a house because of the way the light comes in through the kitchen windows. Another gleefully drives a high-end sports car off the lot even though it will probably never approach the limits it was designed to push.

We can (and usually do) rationalize these decisions after the fact by talking about needing more closet space or wanting to out-accelerate an 18-wheeler as we merge onto the highway, but years of study have arrived at a clear conclusion:

When it comes to the customer experience, human beings are fundamentally irrational.

In the brick-and-mortar past, companies could leverage that irrationality in time-tested ways. They relied heavily on physical context, such as an inviting retail space, to make products and services as psychologically appealing as possible. They used well-trained salespeople and employees to maximize positive interactions and rescue negative ones. They carefully sequenced customer experiences, such as having a captain’s dinner on the final night of a cruise, to play on our hard-wired craving to end experiences on a high note.

Today, though, customer interactions are increasingly moving online. Fortune reports that on 2016’s Black Friday, the day after Thanksgiving that is so crucial to holiday retail results, 108.5 million Americans shopped online, while only 99.1 million visited brick-and-mortar stores. The 9.4% gap between the two was a dramatic change from just one year prior, when on- and offline Black Friday shopping were more or less equal.

When people browse in a store for a few minutes, an astute salesperson can read the telltale signs that they’re losing interest and heading for the exit. The salesperson can then intervene, answering questions and closing the sale.

Replicating that in a digital environment isn’t as easy, however. Despite all the investments companies have made to counteract e-shopping cart abandonment, they lack the data that would let them anticipate when a shopper is on the verge of opting out of a transaction, and the actions they take to lure someone back afterwards can easily come across as less helpful than intrusive.

In a digital environment, companies need to figure out how to use Big Data analysis and digital design to compensate for the absence of persuasive human communication and physical sights, sounds, and sensations. What’s more, a 2014 Gartner survey found that 89% of marketers expected customer experience to be their primary differentiator by 2016, and we’re already well into 2017.

As transactions continue to shift toward the digital and omnichannel, companies need to figure out new ways to gently push customers along the customer journey—and to do so without frustrating, offending, or otherwise alienating them.

The quest to understand online customers better in order to influence them more effectively is built on a decades-old foundation: behavioral psychology, the study of the connections between what people believe and what they actually do. All of marketing and advertising is based on changing people’s thoughts in order to influence their actions. However, it wasn’t until 2001 that a now-famous article in the Harvard Business Review formally introduced the idea of applying behavioral psychology to customer service in particular.

The article’s authors, Richard B. Chase and Sriram Dasu, respectively a professor and assistant professor at the University of Southern California’s Marshall School of Business, describe how companies could apply fundamental tenets of behavioral psychology research to “optimize those extraordinarily important moments when the company touches its customers—for better and for worse.” Their five main points were simple but have proven effective across multiple industries:

  1. Finish strong. People evaluate experiences after the fact based on their high points and their endings, so the way a transaction ends is more important than how it begins.
  2. Front-load the negatives. To ensure a strong positive finish, get bad experiences out of the way early.
  3. Spread out the positives. Break up the pleasurable experiences into segments so they seem to last longer.
  4. Provide choices. People don’t like to be shoved toward an outcome; they prefer to feel in control. Giving them options within the boundaries of your ability to deliver builds their commitment.
  5. Be consistent. People like routine and predictability.

For example, McKinsey cites a major health insurance company that experimented with this framework in 2009 as part of its health management program. A test group of patients received regular coaching phone calls from nurses to help them meet health goals.

The front-loaded negative was inherent: the patients knew they had health problems that needed ongoing intervention, such as weight control or consistent use of medication. Nurses called each patient on a frequent, regular schedule to check their progress (consistency and spread-out positives), suggested next steps to keep them on track (choices), and cheered on their improvements (a strong finish).

McKinsey reports the patients in the test group were more satisfied with the health management program by seven percentage points, more satisfied with the insurance company by eight percentage points, and more likely to say the program motivated them to change their behavior by five percentage points.

The nurses who worked with the test group also reported increased job satisfaction. And these improvements all appeared in the first two weeks of the pilot program, without significantly affecting the company’s costs or tweaking key metrics, like the number and length of the calls.

Indeed, an ongoing body of research shows that positive reinforcements and indirect suggestions influence our decisions better and more subtly than blatant demands. This concept hit popular culture in 2008 with the bestselling book Nudge.

Written by University of Chicago economics professor Richard H. Thaler and Harvard Law School professor Cass R. Sunstein, Nudge first explains this principle, then explores it as a way to help people make decisions in their best interests, such as encouraging people to eat healthier by displaying fruits and vegetables at eye level or combatting credit card debt by placing a prominent notice on every credit card statement informing cardholders how much more they’ll spend over a year if they make only the minimum payment.

Whether they’re altruistic or commercial, nudges work because our decision-making is irrational in a predictable way. The question is how to apply that awareness to the digital economy.

In its early days, digital marketing assumed that online shopping would be purely rational, a tool that customers would use to help them zero in on the best product at the best price. The assumption was logical, but customer behavior remained irrational.

Our society is overloaded with information and short on time, says Brad Berens, Senior Fellow at the Center for the Digital Future at the University of Southern California, Annenberg, so it’s no surprise that the speed of the digital economy exacerbates our desire to make a fast decision rather than a perfect one, as well as increasing our tendency to make choices based on impulse rather than logic.

Buyers want what they want, but they don’t necessarily understand or care why they want it. They just want to get it and move on, with minimal friction, to the next thing. “Most of our decisions aren’t very important, and we only have so much time to interrogate and analyze them,” Berens points out.

But limited time and mental capacity for decision-making is only half the issue. The other half is that while our brains are both logical and emotional, the emotional side—also known as the limbic system or, more casually, the primitive lizard brain—is far older and more developed. It’s strong enough to override logic and drive our decisions, leaving rational thought to, well, rationalize our choices after the fact.

This is as true in the B2B realm as it is for consumers. The business purchasing process, governed as it is by requests for proposals, structured procurement processes, and permission gating, is designed to ensure that the people with spending authority make the most sensible deals possible. However, research shows that even in this supposedly rational process, the relationship with the seller is still more influential than product quality in driving customer commitment and loyalty.

Baba Shiv, a professor of marketing at Stanford University’s Graduate School of Business, studies how the emotional brain shapes decisions and experiences. In a popular TED Talk, he says that people in the process of making decisions fall into one of two mindsets: Type 1, which is stressed and wants to feel comforted and safe, and Type 2, which is bored or eager and wants to explore and take action.

People can move between these two mindsets, he says, but in both cases, the emotional brain is in control. Influencing it means first delivering a message that soothes or motivates, depending on the mindset the person happens to be in at the moment and only then presenting the logical argument to help rationalize the action.

In the digital economy, working with those tendencies means designing digital experiences with the full awareness that people will not evaluate them objectively, says Ravi Dhar, director of the Center for Customer Insights at the Yale School of Management. Since any experience’s greatest subjective impact in retrospect depends on what happens at the beginning, the end, and the peaks in between, companies need to design digital experiences to optimize those moments—to rationally design experiences for limited rationality.

This often involves making multiple small changes in the way options are presented well before the final nudge into making a purchase. A paper that Dhar co-authored for McKinsey offers the example of a media company that puts most of its content behind a paywall but offers free access to a limited number of articles a month as an incentive to drive subscriptions.

Many nonsubscribers reached their limit of free articles in the morning, but they were least likely to respond to a subscription offer generated by the paywall at that hour, because they were reading just before rushing out the door for the day. When the company delayed offers until later in the day, when readers were less distracted, successful subscription conversions increased.

Pre-selecting default options for necessary choices is another way companies can design digital experiences to follow customers’ preference for the path of least resistance. “We know from a decade of research that…defaults are a de facto nudge,” Dhar says.

For example, many online retailers set a default shipping option because customers have to choose a way to receive their packages and are more likely to passively allow the default option than actively choose another one. Similarly, he says, customers are more likely to enroll in a program when the default choice is set to accept it rather than to opt out.

Another intriguing possibility lies in the way customers react differently to on-screen information based on how that information is presented. Even minor tweaks can have a disproportionate impact on the choices people make, as explained in depth by University of California, Los Angeles, behavioral economist Shlomo Benartzi in his 2015 book, The Smarter Screen.

A few of the conclusions Benartzi reached: items at the center of a laptop screen draw more attention than those at the edges. Those on the upper left of a screen split into quadrants attract more attention than those on the lower left. And intriguingly, demographics are important variables.

Benartzi cites research showing that people over 40 prefer more visually complicated, text-heavy screens than younger people, who are drawn to saturated colors and large images. Women like screens that use a lot of different colors, including pastels, while men prefer primary colors on a grey or white background. People in Malaysia like lots of color; people in Germany don’t.

This suggests companies need to design their online experiences very differently for middle-aged women than they do for teenage boys. And, as Benartzi writes, “it’s easy to imagine a future in which each Internet user has his or her own ‘aesthetic algorithm,’ customizing the appearance of every site they see.”

Applying behavioral psychology to the digital experience in more sophisticated ways will require additional formal research into recommendation algorithms, predictions, and other applications of customer data science, says Jim Guszcza, PhD, chief U.S. data scientist for Deloitte Consulting.

In fact, given customers’ tendency to make the fastest decisions, Guszcza believes that in some cases, companies may want to consider making choice environments more difficult to navigate— a process he calls “disfluencing”—in high-stakes situations, like making an important medical decision or an irreversible big-ticket purchase. Choosing a harder-to-read font and a layout that requires more time to navigate forces customers to work harder to process the information, sending a subtle signal that it deserves their close attention.

That said, a company can’t apply behavioral psychology to deliver a digital experience if customers don’t engage with its site or mobile app in the first place. Addressing this often means making the process as convenient as possible, itself a behavioral nudge.

A digital solution that’s easy to use and search, offers a variety of choices pre-screened for relevance, and provides a friction-free transaction process is the equivalent of putting a product at eye level—and that applies far beyond retail. Consider the Global Entry program, which streamlines border crossings into the U.S. for pre-approved international travelers. Members can skip long passport control lines in favor of scanning their passports and answering a few questions at a touchscreen kiosk. To date, 1.8 million people have decided this convenience far outweighs the slow pace of approvals.

The basics of influencing irrational customers are essentially the same whether they’re taking place in a store or on a screen. A business still needs to know who its customers are, understand their needs and motivations, and give them a reason to buy.

And despite the accelerating shift to digital commerce, we still live in a physical world. “There’s no divide between old-style analog retail and new-style digital retail,” Berens says. “Increasingly, the two are overlapping. One of the things we’ve seen for years is that people go into a store with their phones, shop for a better price, and buy online. Or vice versa: they shop online and then go to a store to negotiate for a better deal.”

Still, digital increases the number of touchpoints from which the business can gather, cluster, and filter more types of data to make great suggestions that delight and surprise customers. That’s why the hottest word in marketing today is omnichannel. Bringing behavioral psychology to bear on the right person in the right place in the right way at the right time requires companies to design customer experiences that bridge multiple channels, on- and offline.

Amazon, for example, is known for its friction-free online purchasing. The company’s pilot store in Seattle has no lines or checkout counters, extending the brand experience into the physical world in a way that aligns with what customers already expect of it, Dhar says.

Omnichannel helps counter some people’s tendency to believe their purchasing decision isn’t truly well informed unless they can see, touch, hear, and in some cases taste and smell a product. Until we have ubiquitous access to virtual reality systems with full haptic feedback, the best way to address these concerns is by providing personalized, timely, relevant information and feedback in the moment through whatever channel is appropriate. That could be an automated call center that answers frequently asked questions, a video that shows a product from every angle, or a demonstration wizard built into the product. Any of these channels could also suggest the customer visit the nearest store to receive help from a human.

The omnichannel approach gives businesses plenty of opportunities to apply subtle nudges across physical and digital channels. For example, a supermarket chain could use store-club card data to push personalized offers to customers’ smartphones while they shop. “If the data tells them that your goal is to feed a family while balancing nutrition and cost, they could send you an e-coupon offering a discount on a brand of breakfast cereal that tastes like what you usually buy but contains half the sugar,” Guszcza says.

Similarly, a car insurance company could provide periodic feedback to policyholders through an app or even the digital screens in their cars, he suggests. “Getting a warning that you’re more aggressive than 90% of comparable drivers and three tips to avoid risk and lower your rates would not only incentivize the driver to be more careful for financial reasons but reduce claims and make the road safer for everyone.”

Digital channels can also show shoppers what similar people or organizations are buying, let them solicit feedback from colleagues or friends, and read reviews from other people who have made the same purchases. This leverages one of the most familiar forms of behavioral psychology—reinforcement from peers—and reassures buyers with Shiv’s Type 1 mindset that they’re making a choice that meets their needs or encourages those with the Type 2 mindset to move forward with the purchase. The rational mind only has to ask at the end of the process “Am I getting the best deal?” And as Guszcza points out, “If you can create solutions that use behavioral design and digital technology to turn my personal data into insight to reach my goals, you’ve increased the value of your engagement with me so much that I might even be willing to pay you more.”

Many transactions take place through corporate procurement systems that allow a company to leverage not just its own purchasing patterns but all the data in a marketplace specifically designed to facilitate enterprise purchasing. Machine learning can leverage this vast database of information to provide the necessary nudge to optimize purchasing patterns, when to buy, how best to negotiate, and more. To some extent, this is an attempt to eliminate psychology and make choices more rational.

B2B spending is tied into financial systems and processes, logistics systems, transportation systems, and other operational requirements in a way no consumer spending can be. A B2B decision is less about making a purchase that satisfies a desire than it is about making a purchase that keeps the company functioning.

That said, the decision still isn’t entirely rational, Berens says. When organizations have to choose among vendors offering relatively similar products and services, they generally opt for the vendor whose salespeople they like the best.

This means B2B companies have to make sure they meet or exceed parity with competitors on product quality, pricing, and time to delivery to satisfy all the rational requirements of the decision process. Only then can they bring behavioral psychology to bear by delivering consistently superior customer service, starting as soon as the customer hits their app or website and spreading out positive interactions all the way through post-purchase support. Finishing strong with a satisfied customer reinforces the relationship with a business customer just as much as it does with a consumer.

The best nudges make the customer relationship easy and enjoyable by providing experiences that are effortless and fun to choose, on- or offline, Dhar says. What sets the digital nudge apart in accommodating irrational customers is its ability to turn data about them and their journey into more effective, personalized persuasion even in the absence of the human touch.

Yet the subtle art of influencing customers isn’t just about making a sale, and it certainly shouldn’t be about persuading people to act against their own best interests, as Nudge co-author Thaler reminds audiences by exhorting them to “nudge for good.”

Guszcza, who talks about influencing people to make the choices they would make if only they had unlimited rationality, says companies that leverage behavioral psychology in their digital experiences should do so with an eye to creating positive impact for the customer, the company, and, where appropriate, the society.

In keeping with that ethos, any customer experience designed along behavioral lines has to include the option of letting the customer make a different choice, such as presenting a confirmation screen at the end of the purchase process with the cold, hard numbers and letting them opt out of the transaction altogether.

“A nudge is directing people in a certain direction,” Dhar says. “But for an ethical vendor, the only right direction to nudge is the right direction as judged by the customers themselves.” D!

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


About the Authors:

Volker Hildebrand is Global Vice President for SAP Hybris solutions.

Sam Yen is Chief Design Officer and Managing Director at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

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Artificial Intelligence: The Future Of Oil And Gas

Anoop Srivastava

Oil prices have fallen dramatically over last few years, forcing some major oil companies to take drastic actions such as layoffs, cutting investments and budgets, and more. Shell, for example, shelved its plan to invest in Qatar, Aramco put on hold its deep-water exploration in the Red Sea, Schlumberger fired a few thousand employees, and the list goes on…

In view of falling oil prices and the resulting squeeze on cash flows, the oil and gas industry has been challenged to adapt and optimize its performance to remain profitable while maintaining a long-term investment and operating outlook. Currently, oil and gas companies find it difficult to maintain the same level of investment in exploration and production as when crude prices were at their peak. Operations in the oil and gas industry today means balancing a dizzying array of trade-offs in the drive for competitive advantage while maximizing return on investment.

The result is a dire need to optimize performance and optimize the cost of production per barrel. Companies have many optimization opportunities once they start using the massive data being generated by oil fields. Oil and gas companies can turn this crisis into an opportunity by leveraging technological innovations like artificial intelligence to build a foundation for long-term success. If volatility in oil prices is the new norm, the push for “value over volume” is the key to success going forward.

Using AI tools, upstream oil and gas companies can shift their approach from production at all costs to producing in context. They will need to do profit and loss management at the well level to optimize the production cost per barrel. To do this, they must integrate all aspects of production management, collect the data for analysis and forecasting, and leverage artificial intelligence to optimize operations.

When remote sensors are connected to wireless networks, data can be collected and centrally analyzed from any location. According to the consulting firm McKinsey, the oil and gas supply chain stands to gain $50 billion in savings and increased profit by adopting AI. As an example, using AI algorithms to more accurately sift through signals and noise in seismic data can decrease dry wellhead development by 10 percent.

How oil and gas can leverage artificial intelligence

1. Planning and forecasting

On a macro scale, deep machine learning can help increase awareness of macroeconomic trends to drive investment decisions in exploration and production. Economic conditions and even weather patterns can be considered to determine where investments should take place as well as intensity of production.

2. Eliminate costly risks in drilling

Drilling is an expensive and risky investment, and applying AI in the operational planning and execution stages can significantly improve well planning, real-time drilling optimization, frictional drag estimation, and well cleaning predictions. Additionally, geoscientists can better assess variables such as the rate of penetration (ROP) improvement, well integrity, operational troubleshooting, drilling equipment condition recognition, real-time drilling risk recognition, and operational decision-making.

When drilling, machine-learning software takes into consideration a plethora of factors, such as seismic vibrations, thermal gradients, and strata permeability, along with more traditional data such as pressure differentials. AI can help optimize drilling operations by driving decisions such as direction and speed in real time, and it can predict failure of equipment such as semi-submersible pumps (ESPs) to reduce unplanned downtime and equipment costs.

3. Well reservoir facility management

Wells, reservoirs, and facility management includes integration of multiple disciplines: reservoir engineering, geology, production technology, petro physics, operations, and seismic interpretation. AI can help to create tools that allow asset teams to build professional understanding and identify opportunities to improve operational performance.

AI techniques can also be applied in other activities such as reservoir characterization, modeling and     field surveillance. Fuzzy logic, artificial neural networks and expert systems are used extensively across the industry to accurately characterize reservoirs in order to attain optimum production level.

Today, AI systems form the backbone of digital oil field (DOF) concepts and implementations. However, there is still great potential for new ways to optimize field development and production costs, prolong field life, and increase the recovery factor.

4. Predictive maintenance

Today, artificial intelligence is taking the industry by storm. AI-powered software and sensor hardware enables us to use very large amounts of data to gain real-time responses on the best future course of action. With predictive analytics and cognitive security, for example, oil and gas companies can operate equipment safely and securely while receiving recommendations on how to avoid future equipment failure or mediate potential security breaches.

5. Oil and gas well surveying and inspections

Drones have been part of the oil and gas industry since 2013, when ConocoPhillips used the Boeing ScanEagle drone in trials in the Chukchi Sea.  In June 2014, the Federal Aviation Administration (FAA) issued the first commercial permit for drone use over United States soil to BP, allowing the company to survey pipelines, roads, and equipment in Prudhoe Bay, Alaska. In January, Sky-Futures completed the first drone inspection in the Gulf of Mexico.

While drones are primarily used in the midstream sector, they can be applied to almost every aspect of the industry, including land surveying and mapping, well and pipeline inspections, and security. Technology is being developed to enable drones to detect early methane leaks. In addition, one day, drones could be used to find oil and gas reservoirs underlying remote uninhabited regions, from the comfort of a warm office.

6. Remote logistics

As logistics to offshore locations is always a challenge, AI-enhanced drones can be used to deliver materials to remote offshore locations.

Current adoption of AI

Chevron is currently using AI to identify new well locations and simulation candidates in California. By using AI software to analyze the company’s large collection of historical well performance data, the company is drilling in better locations and has seen production rise 30% over conventional methods. Chevron is also using predictive models to analyze the performance of thousands of pieces of rotating equipment to detect failures before they occur. By addressing problems before they become critical, Chevron has avoided unplanned shutdowns and lowered repair expenses. Increased production and lower costs have translated to more profit per well.

Future journey

Today’s oil and gas industry has been transformed by two industry downturns in one decade. Although adoption of new hard technology such as directional drilling and hydraulic fracturing (fracking) has helped, the oil and gas industry needs to continue to innovate in today’s low-price market to survive. AI has the potential to differentiate companies that thrive and those that are left behind.

The promise of AI is already being realized in the oil and gas industry. Early adopters are taking advantage of their position  to get a head start on the competition and protect their assets. The industry has always leveraged technology to adapt to change, and early adopters have always benefited the most. As competition in the oil and gas industry continues to heat up, companies cannot afford to be left behind. For those that understand and seize the opportunities inherent in adopting cognitive technologies, the future looks bright.

For more insight on advanced technology in the energy sector, see How Digital Transformation Is Refueling The Energy Industry.

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Anoop Srivastava

About Anoop Srivastava

Anoop Srivastava is Senior Director of the Energy and Natural Resources Industries at SAP Value Engineering in Middle East and North Africa. He advises clients on their digital transformation strategies and helps them align their business strategy with IT strategy leveraging digital technology innovations such as the Internet of Things, Big Data, Advanced Analytics, Cloud etc. He has 21+ years of work experience spanning across Oil& Gas Industry, Business Consulting, Industry Value Advisory and Digital Transformation.