How to Monetize Your Data 01-22

These days, most companies are awash in data. But figuring out how to derive a profit from the data deluge can help distinguish your company in the marketplace. 

Image credit : Shyam's Imagination Library

The possession of rich amounts of data is hardly unique in today’s world. Indeed, data itself is increasingly a commodity. But the ability to monetize data effectively — and not simply hoard it — can be a source of competitive advantage in the digital economy.

Companies can take three approaches to monetizing their data: (1) improving internal business processes and decisions, (2) wrapping information around core products and services, and (3) selling information offerings to new and existing markets. These approaches differ significantly in the types of capabilities and commitments they require, but each represents an important opportunity for a company to distinguish itself in the marketplace.

Theoretically, companies can pursue more than one approach to data monetization at the same time. In practice, adopting each approach requires management commitment to specific organizational changes and targeted technology and data management upgrades. Thus, it’s best to identify your most promising opportunity and start there. In doing so, you will enhance your data in ways that will accelerate subsequent efforts related to the other approaches. More importantly, you’ll build your company’s capacity for monetizing its data.

Improving Internal Processes

Using data to improve operational processes and boost decision-making quality may not be the most glamorous path to monetizing data, but it is the most immediate. Executives often underestimate the financial returns that can be generated by using data to create operational efficiencies. Companies see positive results when they put data and analytics in the hands of employees who are positioned to make decisions, such as those who interact with customers, oversee product development, or run production processes. With data-based insights and clear decision rules, people can deliver more meaningful services, better assess and address customer demands, and optimize production.

When Satya Nadella became CEO of Microsoft Corp. in February 2014, he urged employees to find ways to improve the company’s processes with data. Within sales, executives believed that, with the right tools and systems, they could improve the productivity of their salespeople by 30%. To do so, Microsoft’s sales leaders sought to deploy tools that would help salespeople spend more of their time engaging with customers — and in more effective ways — by arming them with key computed insights such as how likely a sale is to close and when.

To deliver actionable insights, sales executives first had to define shared concepts (for example, what is meant by “a lead”). They then needed to locate data sources that could be used to calculate performance. They quickly learned that sales data was located in too many different systems to easily create a comprehensive snapshot of a salesperson’s business. Within a year, they created a new, integrated customer system that could produce 360-degree views of Microsoft’s relationships with corporate customers, including what those customers bought, what issues they encountered, and how the company engaged with them.

The new system saved 10 to 15 minutes per sales opportunity by eliminating the need for Microsoft salespeople to manually search for and prepare data. The system also helped sales executives more accurately manage their pipelines; it used predictive analytics and machine learning to compute the likelihood of a successful sales engagement based on data that the salesperson provided about an opportunity. For example, buying and deploying enterprise software is complex and often requires a partner’s involvement, so the system may calculate a higher likelihood for success when customers already have partners involved. Information about an opportunity’s likelihood of success, along with suggestions on how to advance engagements along the sales pipeline, helped salespeople prioritize their leads and act in ways most likely to achieve their goals. Over time, Microsoft salespeople learned how to forecast more accurately (for example, the accuracy of forecasts regarding global accounts has risen from 55% to 70%), which has led to better sales-pipeline data and, in turn, improved pipeline management.

Wrapping Information Around Products

Most companies have opportunities — often quite significant ones — to enrich their products, services, and customer experiences using data and analytics, a phenomenon that we call “wrapping.” Companies are wrapping their offerings with data to escape commoditization and satisfy increasingly hard-to-please customers — with the goals of generating sales increases, higher prices, and deeper customer loyalty. FedEx Corp. was an early exemplar of wrapping when it introduced online package tracking as a free service in the 1990s. Now examples abound as companies bundle reporting, alerts, and other information to add value to products ranging from credit cards to health monitors.

Wrapping is a creative exercise in which companies identify what problems their customers have and then find ways to solve those problems using data and analytics. For example, Capital One Financial Corp., a diversified bank based in McLean, Virginia, learned that many of its credit card holders are concerned about fraudulent transactions but find the task of examining every charge to be tedious. So the company helps customers identify fraud more easily and more quickly by displaying merchant logos and maps with each transaction in online statements. The visual cues jog cardholders’ memories about whether they made a purchase or not. As a result, customers are more satisfied with the credit card and more likely to use it more often.

Johnson & Johnson has discovered the value of providing pattern identification to users of its health-monitoring products, including those for diabetics. The company offers its OneTouch Verio Sync Meter customers historical reporting on their blood glucose levels along with tools to help them understand patterns of changes. The reporting is intended to help customers identify the possible causes for the glucose level variations and thus identify behavioral changes that can result in healthier living.

Wrapping activities are best viewed as extensions of a company’s product management processes. This means offering data and analytics to customers at the same level of quality as the core product. Doing so requires comparable levels of scrutiny and control. Most companies don’t manage and cannot deliver data and analytics in this way. In fact, exposing data to customers could reveal quality problems and a lack of analytical sophistication. Thus, in most cases, wrapping requires companies to “up their game” in their information capabilities so that wrapping doesn’t damage their reputation or undermine their value proposition. This effort may entail heavy investment in data-quality programs, advanced computing platforms (for instance, Hadoop), or data-science talent.

Selling Data

Many executives are eager to sell their company’s data, convinced that it has inherent value and can generate important new revenues for the company. We caution that selling represents the hardest way to monetize data, mainly because it requires a unique business model that most companies are not set up to execute. Yet it can be done to potentially great effect under the right circumstances.
State Street Corp. is a Boston, Massachusetts–based financial services company that reported $10.4 billion in 2015 revenue. It provides products and services to institutional investors such as mutual funds, corporate and public retirement plans, and insurance companies.

In 2013, State Street announced a new information-business division called State Street Global Exchange that would combine existing State Street data and analytics capabilities with new research to develop information-based solutions that clients would be willing to buy independently of the company’s core services. State Street established a new division for the information business in recognition of its unique business model needs — something the company had not done in 30 years.

Even though it started out as a discrete unit, State Street Global Exchange focused on developing products that were tightly associated with State Street’s core business. For example, State Street is one of the largest administrators of private equity assets, which means that it collects data about the financial capital that is not noted on a public exchange; this kind of data is of great value to markets that require an accurate representation of the private equity industry. State Street Global Exchange appreciated that the data was not automatically monetizable. Executives secured permission from 3,000 private equity clients to aggregate and anonymize that data — and then created an index that conveyed the financial performance of the private equity industry.

State Street leaders realized that they would need an entirely new operating model to support the information business. For one, sales processes had to change because, although State Street Global Exchange often sold to State Street clients, a buyer of Global Exchange products was frequently a different person or cost center than the kind of buyer traditional State Street products attract. In addition, the information business required salespeople with different selling experience and skills in selling stand-alone data and analytics-based products.

State Street understood that establishing an information business is hard and takes time. State Street Global Exchange had to learn to achieve balance between maintaining key ties with State Street (to create benefits from being a part of the larger organization) and responding quickly to new markets and new needs. Executives believe that State Street Global Exchange is gaining significant traction with its clients — and that their commitment will pay off. But we caution that such a model is not easy to replicate. Other companies should think carefully about the operational capabilities, investment, and commitment required to successfully sell data.

The Importance of Accountability

Chances are you have two major obstacles to monetizing your data. The first is the accessibility and quality of your data. Our research has found that only about a quarter of companies offer employees and customers easy access to the data they most need. You can’t monetize data no one can use.
The second obstacle is lack of accountability. All three approaches to data monetization require committed leaders who can redirect the behaviors of employees to deliver an important new value proposition.

Your inclination may be to solve the data quality issue first with big investments in new infrastructure. We propose that addressing the second issue of accountability will create urgency and commitment to addressing data quality issues — and so we recommend starting there.
Data monetization through process improvement requires strong process leaders. These leaders systematically use data to analyze the outcomes of existing processes and test hypotheses about proposed improvements. At Microsoft, for example, sales managers designated specific people to reshape and institutionalize new ways of selling. Process leaders are ultimately responsible for the design of best practices, the capture of the right data, the availability of tools, and the training of all staff regarding how to use data to do their jobs.

Data monetization through wrapping requires strong product leaders. These leaders treat the data that accompanies a core product or service much like any other product innovation — they hold it to the same quality standards. At Capital One, product leaders know the value of adding a data or analytics feature to a credit card because they predict — and then track — the lift in revenue from the information as well as the cost of providing it. Product leaders assemble teams to design experiments and methodologies that help analyze the impacts of information features and make appropriate adjustments.

Monetizing data by selling it requires a strong business-unit leader. That leader, in turn, must assemble a team that can launch and grow what is for most companies a new line of business. The head of that business will start by ensuring the value of the data and related services to potential customers. But the business head and his or her team must also design data, analytics, and dashboards to monitor the business and enable rapid response to new business opportunities.
Each of the data-monetization strategies requires new processes, new skills, and new cultures to generate maximum returns. Companies with data-monetization experience have learned that it is insufficient to simply put data and tools into the hands of employees. Microsoft refined goals, cleaned up data, honed reports and algorithms, grew talent, and changed habits. Capital One and Johnson & Johnson reshaped product-management talent, platforms, and capabilities. State Street redesigned its organization and created a new profit formula that would generate stand-alone revenues from information.

Impressive results from data monetization do not transpire from single “aha” moments. Instead, they stem from a clear data-monetization strategy, combined with investment and commitment.

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A Data-Driven Approach to Customer Relationships A Case Study of Nedbank’s Data Practices in South Africa 10-19

South Africa’s Nedbank is a leader in its market — but to stay in that position, it needed to identify new ways to serve its existing business clientele as well as attract new customers. Its solution: Use the extensive transaction data the bank collects to help customers improve their service.

Introduction

In 2015, store managers at BUCO, a hardware retailer with 46 locations across South Africa, had an intuitive feel for whether men or women were their most frequent customers, which locations had the most loyal customers, and from what suburbs the most valuable customers to a given store were coming. That all changed shortly after Judy Gounden, a group marketing executive at BUCO’s parent company, Iliad Africa Ltd., began using Market Edge, a commercial data service provided by Nedbank Group Ltd., South Africa’s fourth-largest bank by market value.

According to Gounden, Market Edge — which packages credit and debit card information with geolocation, demographic, and other transactional data — enabled new insights into customers’ behaviors that would have been difficult to identify without the new tool. These insights in turn have changed the way the company operates, says Gounden:

We can now look at card transaction data and say, “On a Wednesday at 9:00 a.m., we had the most card transactions versus any other day in the week, and most of these people are 50 and 60 years old.” That’s our pensioner day. In some geographical regions, we’ve got very high loyalty, and in others, we get new customers constantly, so the tool helps us think about how we market in each region. What’s more, when I told a store manager who believed that most of his business was derived from local residents that, in fact, half of his business was coming from residents that lived in a town 10 kilometers away, his eyes went wide and he said, “How do you know that?” So we shared the data with him. At BUCO’s location in Nelspruit, which is on the Crocodile River in the northeast near Kruger National Park, we learned through the data that a large portion of our clientele was female, so we introduced a Saturday craft workshop featuring chalk paint. It’s the latest craze in do-it-yourself painting. The workshop was a huge hit; it just accelerated the craft area of that business. After that, department sales just skyrocketed. Many stores have replicated this example.

Chris Wood, head of emerging payments, strategy, and regulation at Nedbank, counts Iliad Africa and BUCO as one of the many success stories for Market Edge since its public launch in July 2015. Wood’s team sold or gave away the tool to 1,500 of Nedbank’s merchant locations. Several large companies, such as Burger King and McDonald’s, were either involved in co-creating the product with Nedbank as part of the pilot or had purchased the tool, demonstrating that it could make a significant business contribution to the bank’s credit and debit card line of business as well as to retail and business banking (RBB), the largest business division within Nedbank Group. The value of Market Edge to Nedbank may derive less from sales of the tool — the typical price is a flat fee of 500 rand per location a month (about $35) — and more from expanding relationships with existing merchant clients and acquiring new customers. (See “Market Edge: Use Cases.”) 

Nedbank’s Market Edge clients, like Burger King and BUCO, use the tool to analyze potential store locations and drive business into their stores.

A year after its launch, Wood was convinced that he could build a team to place Market Edge in 90,000 merchants. But there was one big challenge: The current sales force in the card and payments line of business was not yet effective at selling Market Edge, despite concerted training efforts. Nedbank had plans to expand the sales force, but there were many competing priorities and it was unclear whether the bank would support a sales force dedicated to Market Edge.

Nevertheless, the tool has shown Nedbank the promise of data and analytics as a commercial offering. It is also just one of several ways that the RBB business cluster is using data and analytics to build an edge in its market. “The strategic challenges that we’ve set for ourselves highlight the need to ramp up all of that [data] capability,” says Ciko Thomas, group managing executive of RBB. “We have momentum, but we need to build institutional and organizational capability.”



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From Data to Decisions — Moving Past the Hype 04-09

From Data to Decisions — Moving Past the Hype


The 2016 Data & Analytics Report by MIT Sloan Management Review and SAS finds that analytics is now a mainstream idea, but not a mainstream practice. Few companies have a strategic plan for analytics or are executing a strategy for what they hope to achieve with analytics. Organizations achieving the greatest benefits from analytics ensure the right data is being captured, and blend information and experience in making decisions.

The hype around data and analytics has reached a fever pitch. From baseball to biomedical advances, the media highlights one money-making or money-saving corporate experience with analytics after another. Stories abound about data scientists applying their wizardlike talents to find untapped markets, make millions, or save lives. Pundits have been talking up the promise of data in grand terms for several years now: Data has been described as the new oil, the new soil, the next big thing, and the force behind a new management revolution.

Despite the hype, the reality is that many companies still struggle to figure out how to use analytics to take advantage of their data. The experience of managers grappling, sometimes unsuccessfully, with ever-increasing amounts of data and sophisticated analytics is often more the rule than the exception. In many respects, the hype surrounding the promise of analytics glosses over the hard work necessary to fulfill that promise. It is hard work to understand what data a company has, to monitor the many processes necessary to make data sufficient (accurate, timely, complete, accessible, reliable, consistent, relevant, and detailed), and to improve managers’ ability to use data. This unsexy side of analytics is where companies need to excel in order to maximize the value of their analytics initiatives, but it is also where many such efforts stall.

Moving past the hype takes a measure of resolve that few companies demonstrate. A 2015 survey of more than 2,000 managers conducted by MIT Sloan Management Review and SAS Institute — as well as more than a dozen interviews with executives at global companies — reveals insights about the unglamorous but necessary actions required to improve decision making with analytics.
Five key findings came from this research:

• Competitive advantage with analytics is waning. The percentage of companies that report obtaining a competitive advantage with analytics has declined significantly over the past two years. Increased market adoption of analytics levels the playing field and makes it more difficult for companies to keep their edge. In addition, many organizations are in the early stage of their analytics initiative.

Many managers in organizations that have difficulty obtaining a competitive advantage are still experimenting with what they can do with data, and have yet to capitalize on data use across the enterprise. The transition from pilots to organization-wide deployments can be difficult given costs, effort required, and broader questions about whether the analytics will be used consistently by decision makers. Silicon Valley Bank is one company that’s making the transition. “We’ve gone from experimenting with some analytics tools to deploying one visualization tool across the entire enterprise,” says Allan. “Every person has access to data reports and the ability to look at the data from the exact viewpoint they would like. If you had told me two years ago I was going to shift that tool out from a small group of people to all 1,400 employees, I would have said, ‘I highly doubt it.’”

• Optimism about the potential of analytics remains strong, despite the decline in competitive advantage. Most managers are still quite positive about the potential of analytics. They’ve seen increased interest in analytics over the past few years, and they expect its use to continue to grow in their organizations. In addition, use of analytics for innovation remains steady.

• Achieving competitive advantage with analytics requires resolve and a sustained commitment to changing the role of data in decision making. This commitment touches many aspects of organizational behavior, from revamping information management to adapting cultural norms.

• Companies that are successful with analytics are much more likely to have a strategic plan for analytics, and this plan is usually aligned with the organization’s overall corporate strategy. These companies use analytics more broadly across the organization, and they are able to measure the results of their analytical efforts.

• Most companies are not prepared for the robust investment and cultural change that are required to achieve sustained success with analytics, including expanding the skill set of managers who use data, broadening the types of decisions influenced by data, and cultivating decision making that blends analytical insights with intuition.

Our research suggests that companies more advanced in their application of analytics view the collection, management, and use of valuable data in terms of strategic ends, not merely operational goals. These analytically advanced companies pursue their hard-won success with leadership and execution, not by leadership fiat or simply by hiring new analytics talent. Companies that have not been able to use analytics for competitive advantage — or those that have lost their analytical edge due to rapid advances in the marketplace — need to understand the level of commitment and hard work required to execute and sustain a successful analytics strategy. At the conclusion of this report, we identify four key organizational issues that managers need to address when planning for success with analytics.

Competitive Advantage From Analytics Is Down

For the past six years, MIT Sloan Management Review has asked managers to what degree analytics creates competitive advantage for their companies. For the first few years, the percent of managers reporting a competitive advantage from their use of analytics increased dramatically. In 2013, the steep incline flattened, and in the last two years, there has been a significant decline. Down from a high in 2012 of 66%, just 51% of survey respondents in 2015 indicated that analytics creates competitive advantage for their organizations. (See “Competitive Advantage From Analytics Is Declining.”) This decline is taking place across all industries, with energy and health care reporting the steepest declines, and manufacturing reporting the lowest decline.

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Figure 1: Competitive Advantage From Analytics Is Declining

The percentage of organizations gaining competitive advantage from analytics declined significantly in 2015



This decrease in the percentage of organizations reporting a competitive advantage from analytics might suggest that analytics is losing its luster. After all, the original hype around analytics was that it helped organizations compete more effectively. In addition, now there is more data, better technology to capitalize on it, and increased focus on analytical skills. So what’s behind this dramatic drop-off?
One factor in this downward trend is the increase in adoption of analytics across the corporate landscape. As more companies develop analytic capabilities, it is becoming harder for some companies to gain an edge with analytics. “Analytics used to be a competitive advantage, but now it’s becoming table stakes,” says Steve Allan, head of analytics for Silicon Valley Bank. Surprisingly, many managers report that they are innovating with analytics at about the same rate as managers in previous surveys — suggesting that companies are using analytics to stay competitive, but are having difficulty pulling away from competitors.

Beyond the increased use of analytics among companies, there is no single source of the decline that might suggest a simple fix. Among companies not obtaining a competitive advantage from analytics, the reasons varied. (See “Difficulties Gaining an Edge With Analytics.”)

Figure 2: Difficulties Gaining an Edge With Analytics

Many organizations not gaining a competitive advantage from analytics are just beginning to apply analytics and need more experience.

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Figure 2: Difficulties Gaining an Edge With Analytics

Many organizations not gaining a competitive advantage from analytics are just beginning to apply analytics and need more experience.

Many managers in organizations that have difficulty obtaining a competitive advantage are still experimenting with what they can do with data, and have yet to capitalize on data use across the enterprise. The transition from pilots to organization-wide deployments can be difficult given costs, effort required, and broader questions about whether the analytics will be used consistently by decision makers. Silicon Valley Bank is one company that’s making the transition. “We’ve gone from experimenting with some analytics tools to deploying one visualization tool across the entire enterprise,” says Allan. “Every person has access to data reports and the ability to look at the data from the exact viewpoint they would like. If you had told me two years ago I was going to shift that tool out from a small group of people to all 1,400 employees, I would have said, ‘I highly doubt it.’”

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Kiddovation: 6 Cool Inventions from High-Schoolers at MIT’s Eureka Fest 06-25

Innovation

Kiddovation: 6 Cool Inventions from High-Schoolers at MIT’s EurekaFest

Checking in on the next generation of innovators -- high-schoolers from around the country showcase their ideas at MIT's EurekaFest invention fair.

By Doug Aamot

DOUG AAMOTH / TIME.COM

Young inventors, their advisers, members of the media and more gather at MIT's 2013 EurekaFest invention fair.

The Lemelson-MIT Program wasestablished in 1994 at the Massachusetts Institute of Technology to “honor both established and rising inventors for their ingenuity, creativity and contribution to invention and innovation.”

Several grants are given out every year, including many to “InvenTeams” made up of high school students that have ideas about how to solve certain problems in their communities or around the world.

Every year, EurekaFest showcases the InvenTeams’ inventions. Many are still in the early stages of development and some may never make it to market, but here’s a glimpse at the inventions from this year’s program.

Automated robotic vehicular independence system — Beaver Country Day School (Chestnut Hill, Mass.)

This four-wheeled robot has been designed to replace wheelchair backpacks and tethered wheelchair trailers, following its owner around wirelessly and carrying up to 50 pounds on its platform. The team mentioned grocery shopping as a possible use-case. This alpha prototype cost $2,500 to put together.

Emotive aid for combating autism — Thomas Jefferson High School for Science and Technology (Alexandria, Va.)

This project consists of a watch-like device with an LCD screen meant to be worn by someone with autism. The device sports a microphone that analyzes others’ speech patterns, at which point a computer algorithm guesses (with 60% accuracy) whether whoever’s talking is happy, sad, angry or disgusted before relaying the appropriate icon to the watch’s screen. This prototype cost $150 to build.

Pedestrian alert system — Newton North High School (Newton, Mass.)

Ethiopia has some of the worst traffic fatality rates in the world, so Newton North High School paired with its sister school in Addis Ababa to create this pedestrian alert system. The system gauges the speed of oncoming cars and alerts pedestrians further down the road whether it’s safe to cross or not. Each system would cost $3,700 but costs could be driven down by using recycled parts.

Solar egg incubator — Henry M. Gunn High School (Palo Alto, Calif.)

Meant for developing countries, this system consists of a solar collector, incubator, and an automatic egg turner controlled by an Arduino microcontroller. Nicknamed the Cluck Bucket, the system can incubate a dozen eggs at a time and features a hatching detection system that alerts its owner about three days before the chickens are ready to emerge. All the parts cost roughly $300.

Drowning prevention device — Girls Leadership Academy of Arizona (Phoenix, Ariz.)

The adorably-named “Wata Wescue” is a high-tech, yet lightweight water safety shirt for small children designed to address the problem of child drownings in family pools. If a child wearing the shirt falls into the pool, the shirt inflates itself and sounds a wireless alert to a base station inside the house.

Ice search and rescue ROV — Natick High School (Natick, Mass.)

This remotely-operated vehicle (ROV) uses an underwater camera system to help search-and-rescue teams identify people or objects trapped under ice before deploying human divers. The total cost for all the finished parts comes to around $4,000.

Aside from the six inventions shown above, there were 10 other teams showing off their ideas as well. Here’s a list of those teams, with links to more information about each project:

ACTS Home Education Cooperative (Charlottesville, Va.): Wind turbine for highway airflow capture

Ann Richards School for Young Women Leaders (Austin, Texas): Non-electric pressurized cooler

Colfax High School (Colfax, Calif.): Construction layout tool

Ella T. Grasso Southeastern Technical High School (Groton, Conn.): Compost water heating system

John P. Stevens High School (Edison, N.J.): Life jacket for prolonged search and rescue

LEARN Science and Math Club (Kansas City, Mo.): Life-saving, drug-tracking system

Los Alamitos High School (Los Alamitos, Calif.): High efficiency ozone water purification system

Nashua High School North (Nashua, N.H.): Bacteria powered battery

St. Ursula Academy (Toledo, Ohio): Pill dispensing organizational system

Sturgis West Charter Public School (Hyannis, Mass.): Marine mammal rescue transporter

And here’s more information about the Lemelson-MIT InvenTeam initiative.

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Surprising turns in magnetic thin films could lead to better data storage 06-24

Surprising turns in magnetic thin films could lead to better data storage

MIT researchers discover efficient control of magnetism in chiral ferromagnets.

A magnetic phenomenon newly discovered by MIT researchers could lead to much faster, denser and more energy-efficient chips for memory and computation.

The findings, reported in the journal Nature Materials, could reduce the energy needed to store and retrieve one bit of data by a factor of 10,000, says the paper’s senior author, Geoffrey Beach, an assistant professor of materials science and engineering at MIT. The paper’s co-authors are graduate students Satoru Emori and Uwe Bauer, postdoc Sung-Min Ahn, and Eduardo Martinez of the University of Salamanca in Spain.

Beach says that hints of the new phenomenon have been reported for several years, but these had remained unexplained until now. The new results could overcome “a lot of what had seemed like fundamental limitations” in the control and use of magnetic materials, he says, adding: “It’s a whole new approach to the design of magnetic materials.”

It turns out the key to this phenomenon lies not in the magnetic materials themselves, but in what’s next to them: In this case, the team used very thin films of a ferromagnetic material, deposited on a metal base, and with a layer of an oxide material on top — a sort of ferromagnet sandwich. The behavior of the ferromagnetic layer, it turns out, depends on the metal that layer rests upon.

Ferromagnetic materials, including the familiar bar magnets, have a north and a south pole. When such materials are used for data storage, such as on a computer’s hard disk, separate tiny “domains” on their surface can have these poles pointing either up or down, representing ones and zeros. Normally, when a ferromagnetic material is exposed to a current, these domains are pushed along the surface in the same direction as the electron flow.

But previously, in rare cases, the movement was in the opposite direction, puzzling researchers. The MIT team found that when the thin ferromagnetic film was deposited on a slab of platinum, it exhibited this backward flow — which Beach likens to being dragged upwind.

But under circumstances that were identical, except that the film was deposited on the metal tantalum, the magnetic domains flowed in the normal direction — meaning that the key was not in the ferromagnet itself, but in its next-door neighbor. Both platinum and tantalum are nonmagnetic, so they would not ordinarily be expected to affect magnetic behavior.

It turns out that in either case, an unexpected effect alters how magnetic domains switch from one orientation to the other. Normally, when the spin orientation changes from one domain to the other (say, from “up” to “down”), the direction of that change is random. But in these thin-film sandwiches, spin rotations are aligned, consistently either turning clockwise or counterclockwise. The researchers showed that because of this peculiar effect, current can push domains with much more force than in conventional materials, and the direction that the domains move can be engineered simply by selecting the nonmagnetic metal underneath the magnet.

Such asymmetrical behavior is called a chiral effect; the researchers say this is the first demonstration of chiral behavior in magnetic domains.

“There are very few systems in nature that have this preferred way to rotate,” Beach says. Among the few are the molecules that form the basis for life, such as those that assemble into DNA molecules. Additionally, a few magnetic materials have shown this property, “but only in very exotic structures,” he says: at temperatures just slightly above absolute zero, and only in a perfect single crystal.

The new phenomenon, by contrast, is seen “at room temperature and well above room temperature, and in devices that are ideally suited for integration into electronic devices,” Beach says.

In the new ferromagnetic sandwiches, the forces pushing the magnetic domains are 100 times greater than in conventional ferromagnetic storage systems. Since the power needed to move the domains varies with the square of these forces, Beach says, such a system could be 10,000 times more efficient than existing technology.

With that, “all of a sudden these go from just looking interesting to being competitive even with very entrenched technology,” Beach says. And because these structures are compatible with existing manufacturing methods, he predicts, “these things are going to be out there and making a difference very soon.”

Emori, the paper’s lead author, says that there are now several kinds of memory systems, from the ones within a computer’s internal memory to those on hard disks or solid-state USB thumb drives. Theoretically, by harnessing these new effects, he says, “all of these could be satisfied by one material.”

This is “a very important, major advance,” says Robert Buhrman, a professor of engineering and senior vice provost for research at Cornell University. The MIT research, he says, is part of “a very intense effort worldwide to efficiently control the motion of ferromagnetic domain walls in thin-film nanostructures for future very high-performance data-storage and nonvolatile logic operations.”

Buhrman adds, “This work has answered several important questions raised by earlier studies as to how a current pulse can very rapidly move domain walls in a preferred direction.” Besides providing those answers, he says, it “raises new questions for follow-on work.”

“It’s really a whole new class of magnetic materials,” Beach says. “It opens up possibilities that it would have been difficult to even speculate about a couple of years ago.”

The work was supported in part by the National Science Foundation.

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The link between circadian rhythms and aging 06-24

The link between circadian rhythms and aging

MIT study finds that a gene associated with longevity also regulates the body’s circadian clock.

Anne Trafton, MIT News Office

Human sleeping and waking patterns are largely governed by an internal circadian clock that corresponds closely with the 24-hour cycle of light and darkness. This circadian clock also controls other body functions, such as metabolism and temperature regulation.

Studies in animals have found that when that rhythm gets thrown off, health problems including obesity and metabolic disorders such as diabetes can arise. Studies of people who work night shifts have also revealed an increased susceptibility to diabetes. 

A new study from MIT shows that a gene called SIRT1, previously shown to protect against diseases of aging, plays a key role in controlling these circadian rhythms. The researchers found that circadian function decays with aging in normal mice, and that boosting their SIRT1 levels in the brain could prevent this decay. Conversely, loss of SIRT1 function impairs circadian control in young mice, mimicking what happens in normal aging.  

Leonard Guarente is the Novartis Professor of Biology at MITPHOTO: M. SCOTT BRAUER

Since the SIRT1 protein itself was found to decline with aging in the normal mice, the findings suggest that drugs that enhance SIRT1 activity in humans could have widespread health benefits, says Leonard Guarente, the Novartis Professor of Biology at MIT and senior author of a paper describing the findings in the June 20 issue of Cell.

“If we could keep SIRT1 as active as possible as we get older, then we’d be able to retard aging in the central clock in the brain, and health benefits would radiate from that,” Guarente says.

Staying on schedule

In humans and animals, circadian patterns follow a roughly 24-hour cycle, directed by the circadian control center of the brain, called the suprachiasmatic nucleus (SCN), located in the hypothalamus.

“Just about everything that takes place physiologically is really staged along the circadian cycle,” Guarente says. “What’s now emerging is the idea that maintaining the circadian cycle is quite important in health maintenance, and if it gets broken, there’s a penalty to be paid in health and perhaps in aging.”

Last year, Guarente found that a robust circadian period correlated with longer lifespan in mice. That got him wondering what role SIRT1, which has been shown to prolong lifespan in many animals, might play in that phenomenon. SIRT1, which Guarente first linked with aging more than 15 years ago, is a master regulator of cell responses to stress, coordinating a variety of hormone networks, proteins and genes to help keep cells alive and healthy.

To investigate SIRT1’s role in circadian control, Guarente and his colleagues created genetically engineered mice that produce different amounts of SIRT1 in the brain. One group of mice had normal SIRT1 levels, another had no SIRT1, and two groups had extra SIRT1 — either twice or 10 times as much as normal.

Mice lacking SIRT1 had slightly longer circadian cycles (23.9 hours) than normal mice (23.6 hours), and mice with a 10-fold increase in SIRT1 had shorter cycles (23.1 hours). 

In mice with normal SIRT1 levels, the researchers confirmed previous findings that when the 12-hour light/dark cycle is interrupted, younger mice readjust their circadian cycles much more easily than older ones. However, they showed for the first time that mice with extra SIRT1 do not suffer the same decline in circadian control as they age. 

The researchers also found that SIRT1 exerts this control by regulating the genes BMAL and CLOCK, the two major keepers of the central circadian clock.

Enhancing circadian function

A growing body of evidence suggests that being able to respond to large or small disruptions of the light/dark cycle is important to maintaining healthy metabolic function, Guarente says.

“Essentially we experience a mini jet lag every day because the light cycle is constantly changing. The critical thing for us is to be able to adapt smoothly to these jolts,” Guarente says. “Many studies in mice say that while young mice do this perfectly well, it’s the old mice that have the problem. So that could well be true in humans.”

If so, it could be possible to treat or prevent diseases of aging by enhancing circadian function — either by delivering SIRT1 activators in the brain or developing drugs that enhance another part of the circadian control system, Guarente says.

“I think we should look at every aspect of the machinery of the circadian clock in the brain, and any intervention that can maintain that machinery with aging ought to be good,” he says. “One entry point would be SIRT1, because we’ve shown in mice that genetic maintenance of SIRT1 helps maintain circadian function.”

Some SIRT1 activators are now being tested against diabetes, inflammation and other diseases, but they are not designed to cross the blood-brain barrier and would likely not be able to reach the SCN. However, Guarente believes it could be possible to design SIRT1 activators that can get into the brain.

Roman Kondratov, an associate professor of biology at Cleveland State University, says the study raises several exciting questions regarding the potential to delay or reverse age-related changes in the brain through rejuvenation of the circadian clock with SIRT1 enhancement.

“The importance of this study is that it has both basic and potentially translational applications, taking into account the fact that pharmacological modulators of SIRT1 are currently under active study,” Kondratov says.

Researchers in Guarente’s lab are now investigating the relationship between health, circadian function and diet. They suspect that high-fat diets might throw the circadian clock out of whack, which could be counteracted by increased SIRT1 activation.

The research was funded by the National Institutes of Health and the Glenn Foundation for Medical Research.

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