Cathy O’Neil: Unmasking Unconscious Bias in Algorithms

In the wake of the 2008 banking crisis, Cathy O’Neil, a former Barnard College math professor turned hedge fund data scientist, realized that the algorithms she once believed would solve complex problems with pure logic were instead creating them at great speed and scale. Now O’Neil—who goes by mathbabe on her popular blog and 11,000-follower Twitter account—works at bringing to light the dark side of Big Data: mathematical models that operate without transparency, without regulation, and—worst of all—without recourse if they’re wrong. She’s the founder of the Lede Program for Data Journalism at Columbia University, and her bestselling book, Weapons of Math Destruction (Crown, 2016), was long-listed for the 2016 National Book Award.

Q. If an algorithm applies rules equally across the board, how can the results be biased?

Cathy O’Neil: Algorithms aren’t inherently fair or trustworthy just because they’re mathematical. “Garbage in, garbage out” still holds.

There are many examples: On Wall Street, the mortgage-backed security algorithms failed because they were simply a lie. A program designed to assess teacher performance based only on test results fails because it’s just bad statistics; moreover, there’s much more to learning than testing. A tailored advertising startup I worked for created a system that served ads for things users wanted, but for-profit colleges used that same infrastructure to identify and prey on low-income single mothers who could ill afford useless degrees. Models in the justice system that recommend sentences and predict recidivism tend to be based on terribly biased policing data, particularly arrest records, so their predictions are often racially skewed.

Q. Does bias have to be introduced deliberately for an algorithm to make skewed predictions?

O’Neil: No! Imagine that a company with a history of discriminating against women wants to get more women into the management pipeline and chooses to use a machine-learning algorithm to select potential hires more objectively. They train that algorithm with historical data about successful hires from the last 20 years, and they define successful hires as people they retained for 5 years and promoted at least twice.

They have great intentions. They aren’t trying to be biased; they’re trying to mitigate bias. But if they’re training the algorithm with past data from a time when they treated their female hires in ways that made it impossible for them to meet that specific definition of success, the algorithm will learn to filter women out of the current application pool, which is exactly what they didn’t want.

I’m not criticizing the concept of Big Data. I’m simply cautioning everyone to beware of oversized claims about and blind trust in mathematical models.

Q. What safety nets can business leaders set up to counter bias that might be harmful to their business?

O’Neil: They need to ask questions about, and support processes for, evaluating the algorithms they plan to deploy. As a start, they should demand evidence that an algorithm works as they want it to, and if that evidence isn’t available, they shouldn’t deploy it. Otherwise they’re just automating their problems.

Once an algorithm is in place, organizations need to test whether their data models look fair in real life. For example, the company I mentioned earlier that wants to hire more women into its management pipeline could look at the proportion of women applying for a job before and after deploying the algorithm. If applications drop from 50% women to 25% women, that simple measurement is a sign something might be wrong and requires further checking.

Very few organizations build in processes to assess and improve their algorithms. One that does is Amazon: Every single step of its checkout experience is optimized, and if it suggests a product that I and people like me don’t like, the algorithm notices and stops showing it. It’s a productive feedback loop because Amazon pays attention to whether customers are actually taking the algorithm’s suggestions.

Q. You repeatedly warn about the dangers of using machine learning to codify past mistakes, essentially, “If you do what you’ve always done, you’ll get what you’ve always gotten.” What is the greatest risk companies take when trusting their decision making to data models?

O’Neil: The greatest risk is to trust the data model itself not to expose you to risk, particularly legally actionable risk. Any time you’re considering using an algorithm under regulated conditions, like hiring, promotion, or surveillance, you absolutely must audit it for legality. This seems completely obvious; if it’s illegal to discriminate against people based on certain criteria, for example, you shouldn’t use an algorithm that does so! And yet companies often use discriminatory algorithms because it doesn’t occur to them to ask about it, or they don’t know the right questions to ask, or the vendor or developer hasn’t provided enough visibility into the algorithm for the question to be easily answered.

Q. What are the ramifications for businesses if they persist in believing that data is neutral?

O’Neil: As more evidence comes out that poorly designed algorithms cause problems, I think that people who use them are going to be held accountable for bad outcomes. The era of plausible deniability for the results of using Big Data—that ability to say they were generated without your knowledge—is coming to an end. Right now, algorithm-based decision making is a few miles ahead of lawyers and regulations, but I don’t think that’s going to last. Regulators are already taking steps toward auditing algorithms for illegal properties.

Whenever you use an automated system, it generates a history of its use. If you use an algorithm that’s illegally biased, the evidence will be there in the form of an audit trail. This is a permanent record, and we need to think about our responsibility to ensure it’s working well. D!

Ever since discovering the fledgling Internet in the early 1990s, Fawn Fitter has been fascinated by the places where business and technology intersect. She’s spent 15 years in San Francisco, watching the ebbs and flows of the digital economy and writing for magazines, including Entrepreneur and Fortune Small Business.

The Power Of Digital In The Utilities Industry

The utilities industry touches every person, every household, and every business. It provides generation, transmission, distribution, and metering of all forms of energy and water, as well as waste disposal and recycling. It is considered the foundation for modern life. It is also considered by many to be an industry at risk, as the way consumers perceive and consume resources is changing. It is also an industry that stands much to gain from current and emerging digital technologies.

There are three macro forces shaping the industry today: decentralization, deregulation, and decarbonization. Decentralization involves a shift in how and where energy is consumed. No longer the exclusive domain of power companies, energy is now being produced at an increasing rate by both businesses and households leveraging solar, wind, and battery technologies. Most customers that produce their own energy are still connected to the power grid. In fact, many of them sell surplus energy back to the local power utility. This has resulted in a market dynamic where customers have now become suppliers. As a benefit, this allows utility companies to better manage supply and demand, particularly during peak periods. But it also adds significantly to the complexity of the supply chain.

Deregulation is another force shaping the industry. As regulatory bodies have opened the door to new competition, energy resellers (using utility company transmission systems) have become an alternative to the traditional electric or gas company. Deregulation is also allowing non-utility companies into the home, as seen in the rapid rise of on-premises monitoring and control products and companies. These firms, such as Amazon (Nest), offer new ways for consumers to manage their energy usage. In the process, they also have the ability to take control of the customer relationship, often positioning the utility company as a commodity item, while they provide the value-add today’s consumer seeks.

Decarbonization is also changing the utility landscape, as the strong customer-driven push for carbon energy alternatives (e.g., solar, wind, hydro) has resulted in higher demand for energy saving and the use of renewable resources.

The challenges of being a utility

Combined, these three forces are placing a number of challenges on utilities, which are increasingly asking:

• How can they support and even encourage consumers to smartly generate power, all while retaining control of the relationship (or partnership)?
• How can they drive the use of smart in-home control and metering devices that add value to both the consumer (lower energy utilization) and the utility (improved load management)?
• How can they offer clean energy and cost-savings programs through the use of smart sensors and intelligent assets?
• How can they evolve their businesses, services, and operational processes to survive in a world where the consumer is asking for improved energy consumption at a lower price point than before?

Utility providers are also asking how they can attract and retain the talent necessary to address these problems.

Enter the digital solution

The answers to these questions can be found through the right application of digital technologies, a willingness to rethink business operations and revenue models, and the appropriate tools necessary to capture, analyze, and act on the massive amount of data that is available to utilities today.

With the right digital core, the cloud can become a secure and ubiquitous platform for storing data and a common system of record for the company, its partners, and its customers. Internet of Things (IoT) sensors can be used to gather data from operational infrastructure, supply chain partners, employees, and customers to better understand and manage the generation, distribution, and consumers of its offerings. Predictive analytics and machine learning can offer insights into improved operations and maintenance. Even emerging technologies such as blockchain can play a role, helping record and track supply chain and customer equipment transactions.

The bottom line is digital offers the ability to foster innovation, develop new revenue opportunities, and address the challenges faced by today’s utilities industry.

Learn how to innovate at scale by incorporating individual innovations back to the core business to drive tangible business value by reading Accelerating Digital Transformation in Utilities.

Henry Bailey is global vice president of Utilities Industry Business Unit for SAP. He leads a team of customer focused professionals creating end-2-end solutions across the 5 key market categories; Core Applications, Cloud Computing, Mobile Platforms, Business Intelligence and Database Technologies with HANA.

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Ordering a gift online takes seconds, setting in motion a highly complex dance among manufacturer, shipping company, banks, and regulatory authorities to deliver that item to the consumer’s front door.

In this video interview at SAP TechEd Barcelona, Stefan Foerster, product manager for SAP Transportation Management, showcased an intriguing example of how blockchain could make international trade more efficient and secure.

Huge cost-cutting potential

Buyers and sellers alike are looking at blockchain to lower costs by digitizing paper-based processes, streamlining collaboration to speed up payments for goods shipped and delivered.

“We’re talking with shippers who are interested in blockchain because right now it’s costly and time-consuming relying on paper-based processes,” said Foerster. “If you have 20,000 containers, you’re dealing with pages of bills of lading, and exchanging numerous emails, PDF and other documents with many parties including banks, regulatory authorities, and other transportation companies. Blockchain saves valuable time automatically and securely obtaining required stamps, signatures, and other documentation from various places.”

He added that blockchain’s transparency could give banks fact-based visibility into risk as they issue credit on goods: “It’s not unusual for banks to finance the same cargo twice because various employees are working on the same shipments but may not be communicating with each other.”

Fighting fraud

Stolen freight is a major problem at many ports of destination with manipulated documents supporting fraudulent container pick-ups. Foerster said blockchain could address this problem.

“Blockchain authenticates every document and transaction throughout the route,” said Foerster. “Our [proof of concept] actually uses the truck driver’s mobile phone to validate the operator and goods to be picked up in real-time.”

Smart contracts

Future capabilities include using smart contracts on blockchain-enabled networks that automatically trigger activities. Companies could build in a lower prices and bonuses for early or ontime shipments, while late deliveries incur penalties. Adding in sensor-based IoT technology that tracks cargo temperatures and/or travel routes provides further incentives and controls.

“The digitalized contract with code on a blockchain would motivate sellers to streamline shipments while adhering to agreed-upon safe handling and other policies,” said Foerster. “Banks and insurance companies could better measure risk, and incent shippers to minimize it by following safety procedures or making decisions such as steering routes away from known high-pirate areas.”

The Blockchain Solution

In 2013, several UK supermarket chains discovered that products they were selling as beef were actually made at least partly—and in some cases, entirely—from horsemeat. The resulting uproar led to a series of product recalls, prompted stricter food testing, and spurred the European food industry to take a closer look at how unlabeled or mislabeled ingredients were finding their way into the food chain.

By 2020, a scandal like this will be eminently preventable.

The separation between bovine and equine will become immutable with Internet of Things (IoT) sensors, which will track the provenance and identity of every animal from stall to store, adding the data to a blockchain that anyone can check but no one can alter.

Food processing companies will be able to use that blockchain to confirm and label the contents of their products accordingly—down to the specific farms and animals represented in every individual package. That level of detail may be too much information for shoppers, but they will at least be able to trust that their meatballs come from the appropriate species.

The Spine of Digitalization

Keeping food safer and more traceable is just the beginning, however. Improvements in the supply chain, which have been incremental for decades despite billions of dollars of technology investments, are about to go exponential. Emerging technologies are converging to transform the supply chain from tactical to strategic, from an easily replicable commodity to a new source of competitive differentiation.

You may already be thinking about how to take advantage of blockchain technology, which makes data and transactions immutable, transparent, and verifiable (see “What Is Blockchain and How Does It Work?”). That will be a powerful tool to boost supply chain speed and efficiency—always a worthy goal, but hardly a disruptive one.

However, if you think of blockchain as the spine of digitalization and technologies such as AI, the IoT, 3D printing, autonomous vehicles, and drones as the limbs, you have a powerful supply chain body that can leapfrog ahead of its competition.

What Is Blockchain and How Does It Work?

Here’s why blockchain technology is critical to transforming the supply chain.

Blockchain is essentially a sequential, distributed ledger of transactions that is constantly updated on a global network of computers. The ownership and history of a transaction is embedded in the blockchain at the transaction’s earliest stages and verified at every subsequent stage.

A blockchain network uses vast amounts of computing power to encrypt the ledger as it’s being written. This makes it possible for every computer in the network to verify the transactions safely and transparently. The more organizations that participate in the ledger, the more complex and secure the encryption becomes, making it increasingly tamperproof.

Why does blockchain matter for the supply chain?

• It enables the safe exchange of value without a central verifying partner, which makes transactions faster and less expensive.
• It dramatically simplifies recordkeeping by establishing a single, authoritative view of the truth across all parties.
• It builds a secure, immutable history and chain of custody as different parties handle the items being shipped, and it updates the relevant documentation.
• By doing these things, blockchain allows companies to create smart contracts based on programmable business logic, which can execute themselves autonomously and thereby save time and money by reducing friction and intermediaries.

Hints of the Future

In the mid-1990s, when the World Wide Web was in its infancy, we had no idea that the internet would become so large and pervasive, nor that we’d find a way to carry it all in our pockets on small slabs of glass.

But we could tell that it had vast potential.

Today, with the combination of emerging technologies that promise to turbocharge digital transformation, we’re just beginning to see how we might turn the supply chain into a source of competitive advantage (see “What’s the Magic Combination?”).

What’s the Magic Combination?

Those who focus on blockchain in isolation will miss out on a much bigger supply chain opportunity.

Many experts believe emerging technologies will work with blockchain to digitalize the supply chain and create new business models:

• Blockchain will provide the foundation of automated trust for all parties in the supply chain.
• The IoT will link objects—from tiny devices to large machines—and generate data about status, locations, and transactions that will be recorded on the blockchain.
• 3D printing will extend the supply chain to the customer’s doorstep with hyperlocal manufacturing of parts and products with IoT sensors built into the items and/or their packaging. Every manufactured object will be smart, connected, and able to communicate so that it can be tracked and traced as needed.
• Big Data management tools will process all the information streaming in around the clock from IoT sensors.
• AI and machine learning will analyze this enormous amount of data to reveal patterns and enable true predictability in every area of the supply chain.

Combining these technologies with powerful analytics tools to predict trends will make lack of visibility into the supply chain a thing of the past. Organizations will be able to examine a single machine across its entire lifecycle and identify areas where they can improve performance and increase return on investment. They’ll be able to follow and monitor every component of a product, from design through delivery and service. They’ll be able to trigger and track automated actions between and among partners and customers to provide customized transactions in real time based on real data.

After decades of talk about markets of one, companies will finally have the power to create them—at scale and profitably.

Amazon, for example, is becoming as much a logistics company as a retailer. Its ordering and delivery systems are so streamlined that its customers can launch and complete a same-day transaction with a push of a single IP-enabled button or a word to its ever-attentive AI device, Alexa. And this level of experimentation and innovation is bubbling up across industries.

Consider manufacturing, where the IoT is transforming automation inside already highly automated factories. Machine-to-machine communication is enabling robots to set up, provision, and unload equipment quickly and accurately with minimal human intervention. Meanwhile, sensors across the factory floor are already capable of gathering such information as how often each machine needs maintenance or how much raw material to order given current production trends.

Once they harvest enough data, businesses will be able to feed it through machine learning algorithms to identify trends that forecast future outcomes. At that point, the supply chain will start to become both automated and predictive. We’ll begin to see business models that include proactively scheduling maintenance, replacing parts just before they’re likely to break, and automatically ordering materials and initiating customer shipments.

Italian train operator Trenitalia, for example, has put IoT sensors on its locomotives and passenger cars and is using analytics and in-memory computing to gauge the health of its trains in real time, according to an article in Computer Weekly. “It is now possible to affordably collect huge amounts of data from hundreds of sensors in a single train, analyse that data in real time and detect problems before they actually happen,” Trenitalia’s CIO Danilo Gismondi told Computer Weekly.

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials.

The project, which is scheduled to be completed in 2018, will change Trenitalia’s business model, allowing it to schedule more trips and make each one more profitable. The railway company will be able to better plan parts inventories and determine which lines are consistently performing poorly and need upgrades. The new system will save €100 million a year, according to ARC Advisory Group.

New business models continue to evolve as 3D printers become more sophisticated and affordable, making it possible to move the end of the supply chain closer to the customer. Companies can design parts and products in materials ranging from carbon fiber to chocolate and then print those items in their warehouse, at a conveniently located third-party vendor, or even on the client’s premises.

In addition to minimizing their shipping expenses and reducing fulfillment time, companies will be able to offer more personalized or customized items affordably in small quantities. For example, clothing retailer Ministry of Supply recently installed a 3D printer at its Boston store that enables it to make an article of clothing to a customer’s specifications in under 90 minutes, according to an article in Forbes.

This kind of highly distributed manufacturing has potential across many industries. It could even create a market for secure manufacturing for highly regulated sectors, allowing a manufacturer to transmit encrypted templates to printers in tightly protected locations, for example.

Meanwhile, organizations are investigating ways of using blockchain technology to authenticate, track and trace, automate, and otherwise manage transactions and interactions, both internally and within their vendor and customer networks. The ability to collect data, record it on the blockchain for immediate verification, and make that trustworthy data available for any application delivers indisputable value in any business context. The supply chain will be no exception.

Blockchain Is the Change Driver

The supply chain is configured as we know it today because it’s impossible to create a contract that accounts for every possible contingency. Consider cross-border financial transfers, which are so complex and must meet so many regulations that they require a tremendous number of intermediaries to plug the gaps: lawyers, accountants, customer service reps, warehouse operators, bankers, and more. By reducing that complexity, blockchain technology makes intermediaries less necessary—a transformation that is revolutionary even when measured only in cost savings.

“If you’re selling 100 items a minute, 24 hours a day, reducing the cost of the supply chain by just \$1 per item saves you more than \$52.5 million a year,” notes Dirk Lonser, SAP go-to-market leader at DXC Technology, an IT services company. “By replacing manual processes and multiple peer-to-peer connections through fax or e-mail with a single medium where everyone can exchange verified information instantaneously, blockchain will boost profit margins exponentially without raising prices or even increasing individual productivity.”

But the potential for blockchain extends far beyond cost cutting and streamlining, says Irfan Khan, CEO of supply chain management consulting and systems integration firm Bristlecone, a Mahindra Group company. It will give companies ways to differentiate.

“Blockchain will let enterprises more accurately trace faulty parts or products from end users back to factories for recalls,” Khan says. “It will streamline supplier onboarding, contracting, and management by creating an integrated platform that the company’s entire network can access in real time. It will give vendors secure, transparent visibility into inventory 24×7. And at a time when counterfeiting is a real concern in multiple industries, it will make it easy for both retailers and customers to check product authenticity.”

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials. Although the key parts of the process remain the same as in today’s analog supply chain, performing them electronically with blockchain technology shortens each stage from hours or days to seconds while eliminating reams of wasteful paperwork. With goods moving that quickly, companies have ample room for designing new business models around manufacturing, service, and delivery.

Challenges on the Path to Adoption

For all this to work, however, the data on the blockchain must be correct from the beginning. The pills, produce, or parts on the delivery truck need to be the same as the items listed on the manifest at the loading dock. Every use case assumes that the data is accurate—and that will only happen when everything that’s manufactured is smart, connected, and able to self-verify automatically with the help of machine learning tuned to detect errors and potential fraud.

Companies are already seeing the possibilities of applying this bundle of emerging technologies to the supply chain. IDC projects that by 2021, at least 25% of Forbes Global 2000 (G2000) companies will use blockchain services as a foundation for digital trust at scale; 30% of top global manufacturers and retailers will do so by 2020. IDC also predicts that by 2020, up to 10% of pilot and production blockchain-distributed ledgers will incorporate data from IoT sensors.

Despite IDC’s optimism, though, the biggest barrier to adoption is the early stage level of enterprise use cases, particularly around blockchain. Currently, the sole significant enterprise blockchain production system is the virtual currency Bitcoin, which has unfortunately been tainted by its associations with speculation, dubious financial transactions, and the so-called dark web.

The technology is still in a sufficiently early stage that there’s significant uncertainty about its ability to handle the massive amounts of data a global enterprise supply chain generates daily. Never mind that it’s completely unregulated, with no global standard. There’s also a critical global shortage of experts who can explain emerging technologies like blockchain, the IoT, and machine learning to nontechnology industries and educate organizations in how the technologies can improve their supply chain processes. Finally, there is concern about how blockchain’s complex algorithms gobble computing power—and electricity (see “Blockchain Blackouts”).

Blockchain Blackouts

Blockchain is a power glutton. Can technology mediate the issue?

A major concern today is the enormous carbon footprint of the networks creating and solving the algorithmic problems that keep blockchains secure. Although virtual currency enthusiasts claim the problem is overstated, Michael Reed, head of blockchain technology for Intel, has been widely quoted as saying that the energy demands of blockchains are a significant drain on the world’s electricity resources.

Indeed, Wired magazine has estimated that by July 2019, the Bitcoin network alone will require more energy than the entire United States currently uses and that by February 2020 it will use as much electricity as the entire world does today.

Still, computing power is becoming more energy efficient by the day and sticking with paperwork will become too slow, so experts—Intel’s Reed among them—consider this a solvable problem.

“We don’t know yet what the market will adopt. In a decade, it might be status quo or best practice, or it could be the next Betamax, a great technology for which there was no demand,” Lonser says. “Even highly regulated industries that need greater transparency in the entire supply chain are moving fairly slowly.”

Blockchain will require acceptance by a critical mass of companies, governments, and other organizations before it displaces paper documentation. It’s a chicken-and-egg issue: multiple companies need to adopt these technologies at the same time so they can build a blockchain to exchange information, yet getting multiple companies to do anything simultaneously is a challenge. Some early initiatives are already underway, though:

• A London-based startup called Everledger is using blockchain and IoT technology to track the provenance, ownership, and lifecycles of valuable assets. The company began by tracking diamonds from mine to jewelry using roughly 200 different characteristics, with a goal of stopping both the demand for and the supply of “conflict diamonds”—diamonds mined in war zones and sold to finance insurgencies. It has since expanded to cover wine, artwork, and other high-value items to prevent fraud and verify authenticity.
• In September 2017, SAP announced the creation of its SAP Leonardo Blockchain Co-Innovation program, a group of 27 enterprise customers interested in co-innovating around blockchain and creating business buy-in. The diverse group of participants includes management and technology services companies Capgemini and Deloitte, cosmetics company Natura Cosméticos S.A., and Moog Inc., a manufacturer of precision motion control systems.
• Two of Europe’s largest shipping ports—Rotterdam and Antwerp—are working on blockchain projects to streamline interaction with port customers. The Antwerp terminal authority says eliminating paperwork could cut the costs of container transport by as much as 50%.
• The Chinese online shopping behemoth Alibaba is experimenting with blockchain to verify the authenticity of food products and catch counterfeits before they endanger people’s health and lives.
• Technology and transportation executives have teamed up to create the Blockchain in Transport Alliance (BiTA), a forum for developing blockchain standards and education for the freight industry.

It’s likely that the first blockchain-based enterprise supply chain use case will emerge in the next year among companies that see it as an opportunity to bolster their legal compliance and improve business processes. Once that happens, expect others to follow.

Customers Will Expect Change

It’s only a matter of time before the supply chain becomes a competitive driver. The question for today’s enterprises is how to prepare for the shift. Customers are going to expect constant, granular visibility into their transactions and faster, more customized service every step of the way. Organizations will need to be ready to meet those expectations.

If organizations have manual business processes that could never be automated before, now is the time to see if it’s possible. Organizations that have made initial investments in emerging technologies are looking at how their pilot projects are paying off and where they might extend to the supply chain. They are starting to think creatively about how to combine technologies to offer a product, service, or business model not possible before.

A manufacturer will load a self-driving truck with a 3D printer capable of creating a customer’s ordered item en route to delivering it. A vendor will capture the market for a socially responsible product by allowing its customers to track the product’s production and verify that none of its subcontractors use slave labor. And a supermarket chain will win over customers by persuading them that their choice of supermarket is also a choice between being certain of what’s in their food and simply hoping that what’s on the label matches what’s inside.

At that point, a smart supply chain won’t just be a competitive edge. It will become a competitive necessity. D!

Gil Perez is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

Tom Raftery is Global Vice President, Futurist, and Internet of Things Evangelist, at SAP.

Hans Thalbauer is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

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

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

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

Four Retail Technology Trends To Take Off In 2018

Over the past few years, technology has seen a significant shift from cyclical, invention-led spending on point solutions to investments targeting customer-driven, end-to-end value. The next wave of disruption and productivity improvements is here, which means a huge opportunity for digital-focused enterprises – if you are following the right roadmap.

Technology trends have significant potential over the next few years. Establishing a digital platform will not only set the stage for business innovation to provide competitive advantage, but it will also create new business models that will change the way we do business. Technology trends in 2018 will lay the foundation for the maturity of innovative technologies like artificial intelligence and machine learning and will prepare both businesses and shoppers to be ready for their consumption.

Like any other industry, retail is being disrupted. It is no longer enough to simply stock racks with alluring products and wait for customers to rush through the door. Technological innovation is changing the way we shop. Customers can find the lowest price for any product with just a few screen touches. They can read online reviews, have products sent to their home, try them, and return anything they don’t want – all for little or nothing out of pocket. If there are problems, they can use social networks to call out brands that come up short.

Retailers are making their products accessible from websites and mobile applications, with many running effective Internet business operations rather than brick-and-mortar stores. They convey merchandise to the customer’s front entry and are set up with web-based networking media if things turn out badly.

Smart retailers are striving to fulfill changing customer needs and working to guarantee top customer service regardless of how their customer interacts with them.

2017 saw the development of some progressive technology in retail, and 2018 will be another energizing year for the retail industry. Today’s informed customers expect a more engaging shopping experience, with a consistent mix of both online and in-store recommendations. The retail experience is poised to prosper throughout next couple of years – for retailers that are prepared to embrace technology.

Here are four areas of retail technology I predict will take off in 2018:

In-store GPS-driven shopping trolleys

Supermarkets like Tesco and Sainsbury’s now enable their customers to scan and pay for products using a mobile app instead of waiting in a checkout line. The next phase of this involves intelligent shopping trolleys, or grocery store GPS: Customers use a touch screen to load shopping lists, and the system helps them find the items in the store. Customers can then check off and pay for items as they go, directly on-screen. These shopping trolleys will make their way into stores around the last quarter of 2018.

Electronic rack edge names

Electronic rack edge names are not yet broadly utilized, but this could change in 2018 as more retailers adopt this technology. Currently, retail workers must physically select and update printed labels to reflect changes in price, promotions, etc. This technology makes the process more efficient by handling such changes electronically.

Reference point technology

Despite the fact that it’s been around since 2013, reference point technology hasn’t yet been utilized to its fullest potential. In the last few years, however, it’s started to pick up in industries like retail. It’s now being used by a few retailers for area-based promotions.

Some interesting uses I’ve observed: Retailers can send messages to customers when they’re nearby a store location, and in-store mannequins can offer information about the clothing and accessories they’re wearing. I anticipate that this innovation will take off throughout 2018 and into 2019.

Machine intelligence

The technological innovations describe above will also provide retailers with new data streams. These data sources, when merged with existing customer data, online, and ERP data, will lead to new opportunities. Recently Walmart announced it would begin utilizing rack examining robots to help review its stores. The machines will check stock, prices, and even help settle lost inventory. It will also help retailers learn more about changing customer behavior in real time, which will boost engagement.

Clearly, technology and digital transformation in retail have changed the way we live and shop. 2018 will see emerging technologies like machine learning and artificial intelligence using structured and unstructured data to deliver innovation. As technology develops, it will continue to transform and enhance the retail experience.

For more insight on e-commerce, see Cognitive Commerce In The Digital World: Enhancing The Customer Journey.