Gone are the days when getting something done by IT means banging on their door or tying up the phones. A business that truly optimizes its IT department will have ongoing projects that are more important than repeatedly removing viruses from the same employee’s system. If your IT department is tied up in small tasks and struggling to remember specific requests, then cut out the unofficial favors as the main way of doing business and consider how improving ticket management can help.
Ticket management delivers deeper trend discovery
The best way to manage an IT department that services an entire business is with a tracking system that follows not only the machine but also the specific problems, solutions, and people making the requests.
Not all technical problems are the same, but there are similarities and trends that can be tracked to find the big picture. Running into the same common tech problems may be blamed on a system or a person if there’s no tracking. However, if you compare enough tickets, you may discover that the problem is a specific piece of software needed by a certain employee that may require changes to the machine at a less-than-obvious level.
On the opposite side of common issues are those unique, truly wondrous problems that no one would believe if they weren’t documented. Some situations are worthy of Tales from Tech Support, and many are important enough to send to a vendor with detailed information demanding a solution in its next software or hardware version.
That is where the true power of ticket systems emerges. It’s certainly important to keep an eye on troubled systems and problematic employees, but you’re more likely to see small bugs and flaws that are constantly encountered by a specific user related to his or her mindset.
Training can help, but having a ticket to refer to can make the explanation and future fixes more enlightening for everyone. A non-technical user will learn and be more productive if they have some insight into the problem, while the simple blame game can result in resistance and unwillingness to improve.
Along with linking trends in ticket requests, a good ticketing system can make ordering new systems a lot easier. If there are specific problems that your systems have, such as major flaws or merely being too complex for your users, these tickets can help pinpoint traits of new systems that would better fit business requirements in ways that system requirements would only briefly cover.
Required ticket policies cut travel time
There will always be a person or group of people who wants to get around the system. They may be high-ranking members of your business or employees who either don’t respect boundaries or aren’t capable of understanding boundaries.
Stopping a technician in the hallway for a quick fix or demanding a repair off the books is a problem that must be limited as much as possible. Times have changed, and there’s no reason for a technician to perform a repair that isn’t in the system. Modern ticketing systems use enterprise cloud computing, which means they are available to everyone, anyplace, anytime.
Your business can be a lot more efficient if company culture pushes employees to file tickets before seeking anyone out. This doesn’t mean that an in-person request isn’t impossible to make with a ticket system. A technician or engineer could file the ticket manually when they’re done, but it takes time away from their own work.
A business that optimizes its IT department won’t have time to pull its technicians away from a major project simply to install a new program or show a user how to do a specific task at any random time. With tickets built into all parts of the business culture, time management can be monitored and improved while giving technicians a chance to consult others before reaching the repair site.
Ticketing captures details and saves time
Because it’s possible to forget certain details about a user’s complaint, the requesting employee should be responsible for initiating a ticket. A technician can fill in technical information after the employee filing the ticket explains the situation in their own words.
If necessary, a technician can help users create trouble tickets. Some employees are simply not technical, but in an age when every employed person with an eye on advancement should know how to use a smartphone or desktop computer, a statement of “it’s broken” simply isn’t enough.
To make it simpler for employees to enter tickets., the user-facing part of the helpdesk ticket system should allow employees to select through a dropdown menu of common problems. A selection for “other” with an area to describe the issue should be provided for unusual problems and to force employees to enter some information.
With training that covers both non-IT and IT sides of the system, a helpdesk ticketing system can change company culture, improve troubleshooting, and support better communication.
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About Andre Smith
An Internet, Marketing and E-Commerce specialist with several years of experience in the industry. He has watched as the world of online business has grown and adapted to new technologies, and he has made it his mission to help keep businesses informed and up to date.
In a recent Q&A with SAP, “The Value of Data and Analytics in Digital Transformation,” Dan Vesset at IDC makes an interesting observation. Deep into the exchange, he points out that today, “there is significantly greater acceptance by IT that it shouldn’t control all things analytics.”
The reasons why are intriguing. IT control, of course, is a long-standing issue when it comes to enterprise technology in general – and models have swung from one extreme to the other. In the interest of security, some IT groups wield considerable control over who uses what technology. In the interest of flexibility, others are quite open – allowing almost anyone to access anything with minimal controls.
Ideally, you want to find the sweet spot that balances these two extremes so that your company can minimize risk on the one hand while enabling the flexibility to innovate and serve customers more effectively on the other. This, I think, is fairly obvious. But the dichotomy between security and flexibility is not really what Dan has in mind.
Complexity and control
What he has in mind is complexity. The fact is, many IT organizations exert control over enterprise technology due to its complexity. Let’s call it “control by necessity.” A classic case is analytics, which until recently has almost always been no more than a step away from the complexities of data management. Analytical tools were complex – because using them required a fair amount of data management expertise.
In the past, analytics involved data warehouses stored on disk where experts ran batch jobs on data subsets and generated reports that were then delivered to the business. Dashboards were a nice advance, but IT had to build them, and they quickly lost relevance. IT controlled analytics because they needed to.
The new face of analytics
Today, things have shifted. Today, businesses are using new technologies in new ways to bring analytics directly to the consumer. Dan runs through a few examples:
Advances in user interface design: Today’s state-of-the-art UIs take a cue from the mobile world, where data can be accessed and manipulated with touch-screen simplicity. Not only are interfaces increasingly designed with the user in mind; they’re designed by the user to meet individual needs and preferences.
In-memory databases: Rather than storing transactional data and analytical data in separate silos, companies can now store both kinds of data in active memory, where it is easier to work with. This is helping companies sense and respond to developments faster and more effectively.
Cloud computing: Modern analytics, Dan says, is architected for the cloud. New data platforms that run in the cloud – or at least deliver analytics for consumption via the cloud – are helping companies meet demand for data by business users with greater flexibility at lower costs.
Machine learning: Companies can now use intelligent algorithms to analyze process data, identify issues, and take action to improve processes – often without human intervention. This only makes things easier for consumers of analytics, who can now spend more time on higher-value tasks.
Bring analytics to the masses – but start small
Surely other technologies and trends have played a role in simplifying analytics for the business consumer. And we can expect more technologies to emerge over time. But whatever specific technologies a company chooses to adopt, Dan warns against big-bang digital transformation projects that are implemented enterprise-wide for ill-defined reasons.
Most companies are better off with targeted projects that fulfill defined needs or answer specific questions. Fortunately, today’s leading-edge cloud analytics platforms are designed for rapid expansion. The best approach is to get comfortable first, expand as needed, and then evaluate if cloud analytics is something that could help enterprise-wide.
For more on the issues covered in Dan’s interview, get the full text here. It’s worth a read.
Although many companies are still determining their overall cloud strategy, the question for many is not whether to implement a cloud solution, but when and how it will be carried out. Sid Nag, research director at Gartner, has cited numerous reasons for this uptick in cloud services, noting that many companies are now realizing the benefits of cloud solutions. These include greater agility and scalability, lower costs, and more opportunities for innovation—all of which are factors that fuel business growth and enable companies to keep pace within their industries.
Case in point: Intrigo Systems
One such company benefiting from the cloud is Intrigo Systems, a systems integrator and technology service provider that specializes in implementing extended supply chain solutions for its customers. Started in 2009, the company has undergone tremendous growth within the last eight years. This has resulted in a customer base of nearly 200 organizations, with revenues ranging from US$300 million to $60 billion, which are served by Intrigo’s network of more than 250 consultants worldwide.
While most of its operations are based in North America, Intrigo has been expanding its business. The company has gone from having offices in Fremont, Calif., Houston, and Dallas to establishing a presence worldwide. Today, Intrigo boasts offices not only in multiple United States cities, but in Chennai, Bangalore, Frankfurt, and Heidelberg.
Designing for the future
Intrigo’s remarkable success and growth since its formation led the company to a crossroads. Like many in its position, it needed to start looking ahead and considering what tools would be required to create a foundation that could support its aggressive global scale-up.
“We realized the only way we could do this was to bring automation and the digital transformation to our enterprise,” said Kanth Krishnan, chief customer officer of Intrigo Systems. “Another important consideration for us was how we could accomplish this efficiently, while still providing our customers and network of consultants with top-notch service and resources.”
Intrigo began drilling down into its business processes, identifying the need to eliminate redundancies and enhance its resource management capabilities. By implementing an integrated business solution, the company has been able to better manage its assets. This has improved its ability to oversee its network of consultants and satisfy the various needs of its wide-ranging customer base.
Following this, the company turned to another trouble spot: travel and expenses. As the business grew, Intrigo’s consultants began to expand their reach, traveling worldwide to deliver its services and expertise to customers, many of which operate on an international scale. Intrigo knew it was critical to establish a more organized and scalable means of tracking these items. To accomplish this, it turned to an automated expense-reporting tool, which has helped the organization better manage these processes. While these solutions have helped address specific areas of the business, there was still the issue of how best to manage the company’s operations holistically.
“We felt as if we had hit a wall,” said Krishnan. “We’d grown to such a degree that we felt limited by many of our other systems, which couldn’t deliver the services we needed from a multinational standpoint. We thought about implementing local solutions in each country, but that didn’t really make sense to us. We realized we needed a more inclusive solution and couldn’t think of any company better suited to provide it than SAP.”
Intrigo wanted to create a single platform on which it could operate as a cohesive, global entity. It also wanted the ability to manage its resources and projects more efficiently. The company hoped that a more intuitive and comprehensive system would allow it to gain better visibility into its projects, from where money and resources were spent to how different initiatives translated into outcomes for customers.
Understanding how its projects were operating was just one aspect the company’s journey. Intrigo knew it needed to put in place a system that could not only supply valuable data on how its money and employees were being allocated, but also provide insight that would help the company make proactive changes to improve its operations and lower expenses.
To accomplish these goals, Intrigo implemented a solution equipped with an advanced in-memory platform, which brings contextual analytics, digital assistance capabilities, machine learning, and a well-designed user interface to the public cloud. The solution enables companies to benefit from the latest and most innovative advances in ERP without sizeable up-front capital expenditures or extensive infrastructure changes.
The solution includes a personal assistant, which streamlines many of the tedious tasks associated with enterprise maintenance and offers insights and guidance to drive efficient collaboration and better business decisions.
A new, intelligent ERP core
In just eight weeks, the solution became the intelligent core of Intrigo’s ERP platform. The rapid, fit-to-standard implementation ensured that the company could smoothly transition its operations without any lapse in service or functions. It also integrated tightly with existing solutions to serve as a scalable, long-term platform capable of growing and changing with the company, and help it remain responsive and competitive within its market.
As a result, Intrigo has gained greater visibility into its operations, enhanced its resource management capabilities, reduced revenue leakage, built robust controls and compliance processes, and instituted an intuitive, unified platform to better oversee global business operations from end to end. This is bringing increased transparency and efficiency to every aspect of the business, from billing and timesheets to customer engagement and employee satisfaction.
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:
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.
Front-load the negatives. To ensure a strong positive finish, get bad experiences out of the way early.
Spread out the positives. Break up the pleasurable experiences into segments so they seem to last longer.
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.
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!
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.
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.
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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.