Harvard Business Review Webinar: From Big Data to Big Profits

Harvard Business Review Webinar: From Big Data to Big Profits

Everywhere you look there is mention of “Big Data.” But what business people care most about is turning big data into big profits. This is the focus of Russell Walker’s book From Big Data to Big Profits: Success with Data and Analytics. Walker examines the evolving nature of big data and how businesses can leverage it to create new monetization opportunities. Professor Walker looks at companies that are using big data to drive profits, including Uber, Netflix, Google, LinkedIn, Zillow, and Amazon. He explores how digital platforms, including mobile apps and social networks, are changing customer interactions and expectations. He also provides a framework for assessing big data readiness for getting the most from big data.

On March 3, in a complimentary, live and interactive Harvard Business Review webinar, Dr. Walker will share insights and case studies from his new book and discuss the following:

  • how Big Data is disrupting markets and business models
  • best strategies for Monetizing Big Data
  • how to invert and fuse Big Data to create greater value
  • how to score firms for Big Data Monetization readiness using the SIGMA framework

If your company has a wealth of data, is interested in doing more with Big Data, but is most interested in turning data into profits, join Russell Walker and HBR on March 3, 2016. REGISTER HERE

About Russell Walker, Ph.D.

Professor Russell Walker helps companies develop strategies to manage risk and harness value through analytics and Big Data. He is Clinical Associate Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management of Northwestern University.

About From Big Data to Big Profits (Oxford, 2015), Thomas H. Davenport, Distinguished Professor of IT and Management at Babson College, said, “Russell Walker’s important book is not just about Big Data, but how to monetize all your data. It’s an essential guide to competing in the data economy and developing analytics-based products and services.”

Dr. Walker is also the author of Winning with Risk Management (2013). Russell Walker consults with firms on the topics of Big Data and Analytics, Risk Management, and International Business Strategy. He holds an MBA from the Kellogg School of Management and an MS and Ph.D. from Cornell University

You can find him at @RussWalker1492 and russellwalkerphd.com

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Risk Predictions for the New Year and Interesting Business Cases in 2016

Risk Predictions for the New Year and Interesting Business Cases in 2016

Risk Predictions for the New Year and Interesting Business Cases in 2016

With 2016 just about a week old, I would like to share some risk issues that are interesting to consider in 2016.

Federal Reserve Interest Rate Increase

Although delayed many times, the Federal Reserve did finally increase the benchmark interest rate.[1] However, inflation does not seem to exist in a significant manner and some sectors, like energy and commodities are seeing deflation. There has already been discussion of the Federal Reserve slowing its rate of interest rate increases.[2] The recent move to increase interest rates is a real test and vote of confidence that job expansion and growth are happening and will continue to happen.

I think the underemployment situation is a major risk to the economy that hinders growth prospects. The U6 measure of underemployment, which accounts for those unemployed and underemployed, as tracked by the US Bureau of Labor Statistics, ticked up in November 2015 to 9.9% and remained there for December of 2015.[3][4] Although it is on a long-term downward trend from the peak in 2010, the level of 9.9% is still at levels seen in 2008 and 2002, when we had major recessionary pressures, suggesting the job market is still delicate. With many baby boomers existing the job market, the hope is that even a sluggish job growth in the economy can suffice to bring job growth.

Even with the seemingly strong job growth numbers in the recent December labor report, there is a strong concern of wage stagnation. “Wages simply did not grow, and with Wall Street expecting a 0.2% increase in average hourly wages, in December not only was there no wage growth, but in fact, average hourly earnings posted a tiny decline from $25.25 to $25.24.”[5]

Outlook and Prediction: Look for the Federal Reserve to reverse course by the third quarter of 2016, either by reducing rates or increasing liquidity through more quantitative easing. The first week of 2016 had already shown that there are many forces working against wage growth.

ISIS

Most of the world remains in shock that the seemingly disorganized militants and extremists can pull off the attacks seen recently. The reality is that they are more organized and funded than we admit in the media. With the recent San Bernardino attack, it is clear that ISIS is a growing and formidable risk for the US and all western countries.

Outlook and Prediction: ISIS will continue to dominate the US presidential election as a major concern. The ability to respond to this risk will command attention of the US voting populous. Nationalistic feelings are on the upswing in Europe and even in the US, as demonstrated with the swelling support for Trump. Actions by ISIS and the role of the US in the region will be important to voters. Continued terrorist actions by ISIS lift Trump, too. It will make for an interesting and risky election, especially for candidates that look soft on or inexperienced with terrorism.

Deflation (In Various Forms and Places)

The danger that economist all try to avoid is that of deflation. Deflation is great if you hold cash, as assets become cheaper in the future, but for economies built on consumerism and borrowing, it is really bad news and leads to default and lack of investment (See Irving Fisher for his great work on this topic). Deflation is alive in Japan.[6] Consumer prices fell in Europe in late 2015, showing signs of the deflation beast, even with the massive quantitative easing at work in Europe to ward it off.[7] Here in the US, we have seen deflationary trends, largely driven by the drop in energy prices. China has shown signs of a slowing economy, and demographic realities of an aging US, Europe, Japan (and even China) are deflationary forces that might be kicking into high gear. (See my recent posts on China’s changing Demographics and the The World in 2050). A real danger is that as deflation takes hold, firms can and will pay less for labor and with underemployment already high, the risks of salary stagnation or even salary deflation is growing in the US and globally. (Ask the people working in the energy sector or even on Wall Street. Ask what bonuses get paid out this year, too.)

Outlook and Prediction: Hopefully, low energy prices will stimulate growth in various sectors, but it has not seemingly happened yet. Low energy prices are typically seen as an opportunity to expand, but much of the economy is driven by services that are not directly related to energy. There is some additional benefit to lower energy prices, still. Paying less for energy may allow consumers to spend more elsewhere or save more, which is generally seen as good. Currently, holding cash does not offer a large penalty now for investors, which already sounds like deflation, so stimulating saving over spending is not too helpful now. Look for firms to hold hiring increases in 2016 and for deflationary issues to weigh on salary growth.

Some interesting firms were in the news in 2016, offering lessons on the handling of risk and how they will recover from the risks seen will prove very interesting. Here are a few to consider:

Cars: Volkswagen, GM, Tesla, (Plus Gas Prices)

The cheating and deceit at VW is only surpassed by the ignition scandal at GM (See post on The Value of Trust and Leadership Failures at VW). In the case of GM, knowingly installing faulty ignition switches harmed and killed people. GM will try to get its cases resolved quickly, but a divided Congress and an election year can make it a bigger mess. Which politician will stand with GM’s position this year? Few if any, I predict. With the concurrent VW case unraveling and everyone vilifying VW, supporting the GM case just got harder for GM (or anyone else like politicians or unions). Expect expensive settlements soon. As for VW, it  has cheated customers and the environment. Its position as a progressive, labor-forward, and environmentally oriented firm is damaged for a long time. There will be fines, maybe some prison times for executives, and a period of apology. People will remember this for a long time.

Outlook and Prediction: VW will survive, but its image as the progressively minded car manufacturer is tarnished and it will take a big hit in credibility. VW has lost the halo of being the environmentally minded and labor-forward firm that can teach others how to operate. VW sold a lie. BTW, who needs diesel cars now? Gas is at early 2000 levels (See graphic below from the EIA).[8] In the absence of an environmental promise on clean diesel, what is the benefit of a diesel car? While you are trading in that diesel VW, get an electric car, like a Tesla – that is what all the uber progressives want anyhow. Tesla can’t make cars fast enough!

Chipotle

This darling of the fresh, humane, fair, and sustainable food movement has hit more than a few bumps in 2015. The shortage of carnitas (due to a lack of pork raised by humane practices) was handled very well by management. Some might even say it helped Chipotle strengthen its sense of ethos and trust with consumers. However, the recent and multiple E. coli outbreaks at Chipotles across the US have raised concerns about the firm’s handle on its supply and operations. Can these guys keep the food safe? The stock analysts thought the burritos were a bit too hot and beat the stock down. Chipotle’s stock is down big time, losing the heat a rate of nearly 30%![9]

Outlook and Prediction: The food industry is driven by fickle tastes. Is Chipotle a movement, like Starbucks and Panera Bread, or is it a fad that will be beaten back by changing tastes? The safety issues will test consumer demand for Chipotle, and lots of options exist for consumers to get their burrito fix elsewhere. I think Chipotle will bounce back. But it will require that management really gets a handle on its sourcing and operations. It will further require a strong demonstration that things are different going forward and that the risks are under control. It will be a great example to exercise the benefits of risk and supply chain management to return to its pepper hot place in the market.

NFL

There seems to be no sport that has ever enjoyed the dominance currently enjoyed by the NFL. Fans are engrossed each weak, gambling (no, um, playing games of skill) for weekly payouts. But the NFL has major issues facing its image. Last year, the high profile cases of players assaulting women made the news. This year, the release of Concussion, a movie that highlights the concussion risks in the NFL, will, in my opinion, cement in the minds of millions that football is a real health risk (and avoidable). Added to this, we have seen various health warnings on playing youth football and challenges by doctors in recommending not to play the youth sport.[10] [11] A recent survey of views of parents by NPR shows that 51% believe high school football is too risky or needs to be made safer (See graphic below).[12] It is not a good sign for the creation of the next generation of NFL players.

With the NFL owners and teams desiring more luxurious stadiums in various markets and with local municipalities all suffering economically from the downturn in tax revenues since the Great Recession, the appetite for municipally financed stadiums is on the decline. In a major twist, the stadium proposed for relocating the St. Louis Rams to LA would be financed by the owner. This is a change in course for teams and will give some cities increased leverage when teams demand municipally financed stadiums in the future.

Outlook and Prediction: The NFL has a major liability with concussions. Indeed, it has (and likely will) pay for the health damages experienced by past players. But its impact to the image of the sport and the cultivation of younger fans is a growing risk. How many kids go into boxing? The NFL can be experiencing a similar downturn.

The role of cities in funding stadiums is a potentially alienating risk, too. Although not sanctioned by the NFL, the gambling sites for the sport offer long-term risks. Will football be about the sport or the payouts in fantasy football? The answer will change the make-up of fans and what they want out of the sport. Gamblers are less likely to follow one team, I think, making the franchise model less valuable to owners. And, the growing public image of a game destroying people with concussions and municipalities supporting this with stadium subsidies will become a challenge to NFL advances on the stadium front. I think the recent movie, Concussion, will galvanize people to believe more strongly that football is dangerous and that other people should play it and other people should pay for it, but they will continue to watch the product on TV.

Happy New Year!

About Russell Walker, Ph.D.

Professor Russell Walker helps companies develop strategies to manage risk and harness value through analytics and Big Data. He is Clinical Associate Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management of Northwestern University.

His most recent book, From Big Data to Big Profits: Success with Data and Analytics is published by Oxford University Press (2015), which explores how firms can best monetize Big Data. He is the author of the text Winning with Risk Management (World Scientific Publishing, 2013), which examines the principles and practice of risk management through business case studies.

You can find him at @RussWalker1492 and russellwalkerphd.com

[1] Fed Raises Rates after Seven Years Near Zero, WSJ, Dec. 16, 2015.

[2] Fed Raised Rates Even as Inflation Debate Continued, Reuters, Jan. 6, 2016.

[3] U6 Unemployment Rates (2000-2015)

[4] The True Unemployment Rate, U6 vs U3.

[5] December Jobs Soar by 292k, Smash Expectations, but Average Wages Post First Drop Since 2014.

[6] Japan Falls Back into Deflation for First Time Since 2013. Financial Times, Fall, 2015.

[7] Eurozone Faces Renewed Deflation Threat as Consumer Prices Fall. WSJ, Sept. 30, 2015.

[8] US Historical Gasoline Prices from EIA.

[9] Chipotle Stock price for 2015, CNN Money

[10] Noted Surgeon, Dr. James Andrews wants your young athlete to stay healthy by playing less.

[11] America’s Most Dangerous Football is in the Pee-Wee Leagues, Not the NFL. The Atlantic. Aug. 2013.

[12] NPR Poll on High School Football Safety, Feb, 2014.

Lessons on Big Data, Risk, and the Vertical Integration of Wearables and Startups

Lessons on Big Data, Risk, and the Vertical Integration of Wearables and Startups

Lessons on Big Data, Risk, and the Vertical Integration of Wearables and Startups

It is amazing how quickly the world of health sensors and wearables has developed. In just a few years, we have seen the wearable market explode with Fitbit, Jawbone, and Apple commanding healthy shares of the overall market that delivered some 70 million devices to users this past year alone and will deliver more next year [1]. Still, many scores of other wearable devices are available. With such growth and product availability, it forces us to wonder, where is this market headed? I think its future will be driven by the creation and use of Big Data. It is a lesson for startups in the data space, too.

Clearly, wearables bring a new level of measurement to our bodies and health that was not possible previously. The data created by a wearable device is becoming more and more valuable to insurers, doctors, health researchers, employers, and the users themselves. But who can access and control that data is currently limited by law and ownership. It stands to reason that the user will and should have access to his or her own data. That is part of the point. Use a wearable and participate in your health tracking. However, the digital platforms or systems created by leaders like Jawbone, Fitbit, and Apple, however, raise competitive questions around the use and economic value of that data.

Users of wearables are not likely to see the performance of the whole population of users, but the owner of the digital platform does see this. That is to say, you can see your data (only), but not that of the aggregate of the population. The algorithms that score users on performance, health, prescription costs, risk, and even morbidity are also highly unlikely to be shared with the users. Expect proprietary models to be developed here. Such data is where a tremendous economic value is created for insurers, employers, hospitals, and pharmaceutical firms.

Key Point: Wearable devices create valuable data when aggregated and are of economic importance to various firms in the health industry. Users don’t even get to see that data, yet they participate in its creation. Privacy and data use issues will become more poignant as wearables advance in adoption.

If you are a large insurer and you convince, reward, or require all of your customers to use a wearable to track health and report that information back to your analytics team, you will have a huge benefit in being able to better manage and price risk and understand the costs of insuring your customers. The novel data coming from wearables becomes a critical component to your risk management process. As the insurer, you would likely have your analytics team look at that data and develop customized algorithms for the measurement of health, costs, and treatment options. The Big Data coming from wearables, its transformation through analytics, and use in the firm in managing risk is a competitive advantage. It stands to reason that an insurer does not have incentive in sharing that data with other insurers (or many other constituents for that matter). In fact, insurance firms that get better results by leveraging wearable data to better manage risk, preemptively treat customers, and control costs are economic rewarded for the creation and management of the data coming from wearables. It suggests a need for insurers to control the use and creation of the data from the wearables.

This suggests to me that the future of wearables involves vertical integration with the health industry and in particular insurers. It a small way, this has already happened. John Hancock launched a new program, Vitality, in which policy holders get reduced rates for using a wearable. [2] In particular, John Hancock provides a Fitbit device to policy holders in this program. John Hancock provides policy holders a discount on premiums and Fitbit sends that data to John Hancock. This is a form of vertical integration, with integration evolving along the availability of the data created by the device. Fast forward some years, and one might ask, should John Hancock allow Fitbit to partner with other insurers? Maybe Fitbit finds the business offer from John Hancock so compelling that they are open to an exclusive partnership, too.

Key Point: Big Data and its use to create value is a competitive advantage for firms. Expect companies to grow and diversity along lines of data. Firms that are better able to control, create, and use such Big Data will want to form unique and exclusive partnerships to strengthen the creation of the Big Data going forward.

Exclusivity is a feature of vertical integration that becomes most desired when the value of the partnership is high. Insurers are far better capitalized than the wearable startups (with Apple being the notable exception – more on that later) and have many more customers, meaning vertical integration is likely to include insurers as initiators. John Hancock could press for or require exclusivity in its partnership with Fitbit. It could do this by becoming a greater customer for Fitbit, an investor, or owner. In essence, John Hancock already pays Fitbit for the data (by buying Fitbit units). Expect more vertical integration in the wearables market with buyers and partners wanting access to the user data.

Also, there will be a shakeout in the wearable industry. The many scores of manufactures of watches, bands, and clothing items will not all survive. Remember the many PDAs and many TV manufacturers of old. Technology rewards the makers that are efficient and able to evolve quickly. Gaining large market share quickly is immensely important, too. Vertical integration, in part or whole, will anoint winners in the wearable industry. With the backing of a major insurer, any such wearable maker would achieve massive market share and push competitors out of business, by controlling customer demand. With the wearable market already dominated by a few major players, it appears that many of the smaller wearable firms are not financial viable now and are surviving on investor funding. Patents, technology, data, and analytics can be sold to interested parties, like insurers, allowing for a new form of vertical integration. A major insurer might just buy a small and poorly funded wearable firm (with solid technology) and distribute the devices to thousands or millions of users, making it a major player in the space quickly. Devices might be given out for free (like John Hancock currently does) making it hard if not impossible for other wearable firms to charge for devices. With devices being free, the wearable market will coalesce around those firms that offer users the best economic trade for their data. Insurers are best positioned to offer that economic trade, as they are best positioned to gain from the data. It is a bet that some venture capitalists might be making – sell a wearable firm to an insurer. Expect insurers and possibly major hospital networks to become more than customers and partners of such wearables, expect them to want to own and control wearable devices, too.

I expect some leading insurers to even acquire wearable devices. In a recent study by PwC, 70% of consumers said that they would exchange their wearable data with employers and or insurers for price discounts and majority of prospective wearable users would prefer that their employer or insurer provide and pay for the wearable (bands and smart watches in particular).[3]

Key Point: Consumers already see insurers and employers as major beneficiaries of the data collected from wearables. They want those beneficiaries to also become benefactors. Consumers want to be paid for their data. Insurers are in a position to pay.

Big Data is the new advantage that is revolutionizing business partnerships and will drive how firms grow and expand. As for Apple and its dominance as a brand and hardware producer, it makes me wonder if its wearables could lead Apple into new enterprises like insurance. Users of Apple wearables might be offered life insurance policies at special rates for sharing data collected from the Apple Watch. It would be an amazing opportunity to capture the interest of the millennial generation in life insurance. And if Apple does not see new business entry along the lines of data valuable, it could (and should) form exclusive partnerships with insurers and be paid for providing that data to the insurers.

Key Point: Look at the novel data created in your firm or startup to identify growth strategies. Opportunities to grow along data lines are compelling, especially if you can control and create that data.

More on strategies for leveraging Big Data and Analytics for growth and innovation are discussed in my recent book, From Big Data to Big Profits: Success with Data and Analytics.

About Russell Walker, Ph.D.

Professor Russell Walker helps companies develop strategies to manage risk and harness value through analytics and Big Data. He is Clinical Associate Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management of Northwestern University.

His most recent book, From Big Data to Big Profits: Success with Data and Analytics is published by Oxford University Press (2015), which explores how firms can best monetize Big Data. He is the author of the text Winning with Risk Management (World Scientific Publishing, 2013), which examines the principles and practice of risk management through business case studies.

You can find him at @RussWalker1492 and russellwalkerphd.com

References:

[1] Gartner Report on Wearable Device Forecasts.

[2] John Hanncock Vitality at https://www.jhrewardslife.com/

[3] PwC Report: The Wearable Future.

 

Learning from Hurricanes: Big Data Analytics, Risk, & Data Visualization

Learning from Hurricanes: Big Data Analytics, Risk, & Data Visualization

Learning from Hurricanes: Big Data Analytics, Risk, & Data Visualization

This year, Florida has experienced its 10th consecutive year without a hurricane. It is the longest period without a hurricane strike in modern times and one more remarkable considering that Florida’s more then 1200 miles of coastline account for about 40% of the US landed hurricanes recorded in modern history.

Exploring this long stretch without hurricanes is worthy of some examination, as it offers us many lessons in Big Data Analytics, Risk, and Data Visualization. First, the obvious: how frequent are hurricanes and are hurricanes regular in their arrival? The below graphic from the WSJ of last year nicely shows this.[1]

Indeed, the graph shows that in some decades such as the 1910s, 1920s and 1940s, hurricanes were quite frequent in Florida (nearly annual!). Interestingly, the frequency of hurricanes is less in recent decades, except for a major spat of hurricanes in 2004 and 2005. All of this raises questions that are of great interest to climatologists, disaster recovery planners, risk managers, insurers, and re-insurers. Is the irregular arrival of hurricanes just a manifestation of randomness?

It might be a product of climate change, global warming, or simply a level of variation in the natural cycle not seen before. Indeed, hurricane patterns are complex, and we are rapidly learning more about their formation and occurrence, thanks to improved data collection and analytics. In recent years, climatologists have been able to zero in on factors that are more predictive of high hurricane activity years. The below graphic from NOAA communicates some of the most important factors in a high hurricane occurrence year.[2]

A large number of hurricanes are expected when there is high pressure in Northwest Africa, warm temperature in the Atlantic, and favorable trade winds. That is a complex interaction of variables. And, El Niño is generally shown to result in less of these conditions and less therefore hurricanes. Such insight is valuable to a risk manager and risk insurer. From a risk management perspective, knowing about this beforehand allows for more appropriate risk taking, preparation, and investment. Indeed, owning hurricane insurance risk in Florida over the past few years turned out to be a rather nice investment.

Having grown up in Tampa, Florida, I was acutely aware of the dangers and damages from hurricanes – at least I had heard about hurricanes from my grandparents. In some 22 years in Tampa, I saw only one hurricane come by Tampa in 1985. The interesting phenomenon was that the west coast of Florida had seen many hurricanes in the 1910s and 1920s and then a scrap with a category 5 hurricane in 1960. This irregularity in hurricane arrivals perplexed me. I can recall fishing in the inter-coastal way and seeing passes and breaks formed by hurricanes from the past. Why were there less hurricanes in the 1970s and 1980s than in previous decades? Or why were there more in the past? Did something change?

Risk Management Lessons

This phenomenon interested me so much that I explored it as part of my PhD Dissertation at Cornell University.[4] At the time, we did not have the big data tools of today. In particular, I examined if hurricanes and other large flood events were indeed irregular in their arrival. I found that for the southeastern US, large annual flood events are statistically “clustered in time.” That is to stay that some periods of time show many large annual floods and then there are extended periods of time (many decades) with little to no large floods at all. It is a major finding that challenges the principle assumptions of catastrophic risk analysis. It suggests that risk is dynamic and the underlying assumptions subject to changing conditions.

If the 100-year flood comes on average once every 100 years and it has been seen two times in the last 10 years, it also might mean that a long period of tranquility is ahead. That can potentially be exploited by insurers in issuing insurance during low risk periods. The recent Florida hurricane data suggest that such changes are indeed part of the climate.

Key Point: Risk models are simplifications of the real world. With more data, we can explore, understand, and account for relationships across many variables. Big data analytics is changing how we examine risk, not just in climate, but in finance and healthcare, for instance. Deploy Big Data analytics to leverage large scale and multi-variable data sets to understand risk more precisely.

Data Visualization Lessons: Risk is Dynamic and Complex

I came across a great graphic made by John Nelson of IDVSolutions. [3]

It graphs hurricanes and tropical storms since 1851 and uses colors (more green is more severe) to show the severity of hurricanes and the progression of the hurricanes along their tracks. With little explanation or climatic training, you can easily see some interesting things about hurricanes in the Gulf of Mexico and Western Atlantic Ocean. At least for me, I see a rather suspicious blank space in west Florida – an indication of less or at less severe hurricanes than other parts of the state and the Gulf Coast. One explanation is good luck; another is more physical in that hurricanes lose strength over land. It is hard to hit the west coast of Florida without hitting some land first. So, the west coast of Florida, may, in particular, be more protected. It might be useful in selecting risks. Buy hurricane risk on the west cost of Florida over the Miami area.

The next observation of this impressive data visualization by IDV Solutions is that the strongest hurricanes do in fact avoid land in their formation, riding through the Florida Straits, skirting south of Cuba, and otherwise strengthening in the Gulf of Mexico. And if you ever thought that New Orleans and the Louisiana Gulf Coast gets more strong hurricanes that elsewhere, this graphic would support your hypothesis. This is a great example of a data visualization that allows for the communication of hurricane tracks, relative strength, and geographic occurrence. It would have been great to have this when we looked at hurricane and flood data some years ago.[4] It is a great example of how data visualization is changing analysis. In a few minutes, complex relationship between location, direction, intensity, and reporting can be understood. It is also a great example of why we need data visualization as part of our analytical and risk toolbox.

We, as humans, cannot easily process complexity in numbers. However, we (or some of us in particular) are quite good at addressing and processing complexity expressed in shapes, colors, and graphics. This strength and weakness of our cognitive skills requires that we be mindful of how to use data visualization as part of an analytical strategy. It makes sense and I am reminded of this every time I park on the purple level of the parking garage at Northwestern University. I can’t as easily recall the number of the level at the garage, but the colors of each level are crystal clear to me in memory, and yet I use the garage nearly everyday. Numbers although necessary for analytics, are not the best form for our cognitive processing. Relative comparison and rate changes are more easily understood through graphics.

Key point: Leverage data visualization to understand and explore complex relationships across many variables in data. Leverage the human mind to look for patterns and ask interesting questions of the graphics. It leverages the best of graphics and our cognitive skills.

About Russell Walker, Ph.D.

Professor Russell Walker helps companies develop strategies to manage risk and harness value through analytics and Big Data. He is Clinical Associate Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management of Northwestern University.

His most recent book, From Big Data to Big Profits: Success with Data and Analytics is published by Oxford University Press (2015), which explores how firms can best monetize Big Data. He is the author of the text Winning with Risk Management (World Scientific Publishing, 2013), which examines the principles and practice of risk management through business case studies.

You can find him at @RussWalker1492 and russellwalkerphd.com

References:

[1] Jakab, Spencer. “Florida’s Hurricane Dry Spell Lasts.” The Wall Street Journal. November 28, 2014.

[2] Klotzbatch, Phil. “Forecast groups nailed the 2015 hurricane season, thanks to El Niño.” Washington Post. November 25, 2015.

[3] Nelson, John, IDVSolutions.com. Hurricane Data Visualization, Accessed November 27, 2015.

[4] Walker, Russell. “Risk and Statistical Analysis of Hydrologic and Environmental Data.” Ph.D. Dissertation, Cornell University Library, August 1999.

[5] Walker, Russell and J. R. Stedinger. “Long-term Variability in the Arrival Rate of Flood Events as Evidenced by Flood Clustering.” EOS Transactions, American Geophysical Union 2000 Spring Meeting, 81(19), S200, May 9, 2000.

Understanding China’s One-Child Policy Shift: Big Demographic and Economic Changes Ahead

Understanding China’s One-Child Policy Shift: Big Demographic and Economic Changes Ahead

Understanding China’s One-Child Policy Shift: Big Demographic and Economic Changes Ahead

Today, China announced that it is abandoning its 35-year policy of limiting families to only one child. This policy has become a demographic experiment unmatched in the history of the world. Owing to this policy on reproduction, China is experiencing many challenges and risks that were not foreseen when the one-child policy was adopted. At its core, is a challenge to the social composition of China and its economic trajectory within the global economy.

Gender Imbalance will Pose Social Risks

The one-child policy and cultural preferences for boys over girls, has created a horrific gender imbalance. Enabled by ultrasound and gender specific infanticide, China now has more men than women. Some estimates have 116 boys being born for each 100 girls. Over many years, this imbalanced is estimated to result in some 80 million men in Asia without wives by 2040. It is an imbalance that the world has simply not seen before. Will these men demand wives from poorer countries? Probably. Will they succumb to deviant and dangerous behavior? Probably, but hopefully not. 80 million is about the population of Germany. It is about a quarter of the US. The void will be felt for years. Owing to wars, society has overcome lower numbers of men, but lower numbers of women is mostly unseen in our recent human history. It will pose social risks unseen before.

The Rise of Little Emperors

Younger people in China live a different life compared to their parents and grandparents. The one-child policy, exercised over 35 years, means that 4 grandparents, produce 2 parents, and one grandchild. It means a child grows up with 6 adults doting on him or her. It also means that child gets more of what he or she wants. This new psyche is called, “the little emperor.” And understandably, the six adults want the best and most for their only heir. In a country where eldercare has historically been handled at home, it also challenges how the Chinese will age and where they will live. We think of cultural challenges with millenials in the US, but China is dealing with the same issue, too.

Rapid Aging is in the Future for China

Below is a population pyramid of China now and in 2050. The gender imbalance is most obvious in the youngest people. The aging of China is soon upon us. It will have major economic implications to the world.

Impact of China on Global Economics

We often lose sight of the impact that China had on global prosperity. In the 1990s, trade and business with China really opened-up and expanded. It allowed US and European firms to move manufacturing to China in a big way. It provided a reduction in the cost of manufacturing to much of the world. That controlled the cost of making many things. Indirectly, it meant that inflation could be more easily controlled in developed markets. As long as some (and a growing part) of the manufacturing base could be shifted to low-paid Chinese workers, the developed markets could see expansion in product offerings and firms could expand without as much of a concern for inflation. In many ways, the success of Walmart has been tied to its ability to source from China. Walmart brought an increase in lifestyle offerings to the US middle class, built on low-cost labor in China. China has also been a boom for some US firms. Even Starbucks sees its future as tied to growth in China. The ability to add millions of new customers to a business is invaluable. China has offered that to the world market since the 1990s. Expansion in nearly every commodity over the past 40 years has been tied to the growth and increase in prosperity in China. That growth is now under examination.

Questions about China’s Growth Going Forward

Questions about the future growth in China are increasing. With economic growth recently coming in below expectations, these concerns are becoming more poignant. Trade is flat with China. Even internal consumption, like electricity use is more or less flat. The concern is that China is not growing as projected. Few people trust the economic numbers published by the Chinese government. Maybe China has reached a plateau in economic growth. The future does have some challenges for China. The one-child policy has left an aging China. Before 2050, China will be a smaller country than it is today. It is hard to believe. It will be an older country, too. Smaller and older counties have less productivity and consume less (unless then make large investments in technology to boost productivity and keep older workers working). The imminent aging of China is bad news for businesses that have grown to rely on China as a labor source or demand source.

It is interesting to think that we have spent the last 40 years in the US and developed markets defeating inflation. In many ways, China helped us control inflation, by providing a low cost labor source. China and our economic partnerships with China now pose new risks to the global market going forward. As China ages, its labor offerings will become less valuable. Might global labor costs increase – stimulating inflation? Might demand from China tail off – driving deflation? It really depends on what happens in other parts of the world For international firms, it will require pivots away from China. Here are some things to consider with the demographic shift at work in China.

China and the World will Age

The one-child policy and demographic experiment is over. China has seen the problem that is looming and is hoping to correct it, but the next 20-35 years are in the books already. China will be an older country. How does your business work with the elderly? There will be great expansion in products and services that help the elderly. Healthcare and housing will require major investments. Technology that serves the elderly will be a prerequisite.

Leverage Automation

If your business is built on low-cost labor in China, look for opportunities to further remove the labor through automation. Any expansion from more young workers in China is decades away, at best. The next few decades suggest that China will not be the workhorse that it was over the last few decades.

Look for Labor and Growth In India and Africa

The population boom is alive and well in India and Africa, however. The state of the economies in these parts of the world still involves pulling people out of abject poverty. In spite of that, fundamental investments in infrastructure, people, and products will occur. Map a path to capture this growth.

Some Thoughts and Observations on Growth

For companies and investors looking for growth in the world, I offer a few major trends. The world will have massive expansion in the warmest climates. Warm climates demand air conditioning, refrigeration, and such comforts go a long way in changing the satisfaction of the population. With rare exception do people ever give up such comfort. Also, the growth of these populations (especially in India) will correspond to higher per capita GDP. As people move out of the depths of poverty and into the so-called “global middle class” they adopt a richer diet that is based more on animal protein. This will require more soybean production for the raising of animals and put new pressures on sustainable animal husbandry as meat consumes not just soy beans, but large amounts of water and energy. These people will need transportation and communications. The development of low cost automobiles and the expansion of mopeds will bring these growing populations access to combustible engines and the continued environmental challenges posed by them. On the flip side, the U.S., Europe, Japan and China will need solutions for an aging population. Obviously healthcare is a focus. But these aging populations will consume services. Some of this can be met by immigration, but automation and even robots will, and already are answering the call.

Build your plan for the future. Take note; China has and does not like what it sees.

About Russell Walker, Ph.D.

Dr. Walker is Clinical Associate Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management of Northwestern University.

Professor Walker has developed and taught executive programs on Enterprise Risk, Operational Risk, Corporate Governance, Analytics and Big Data, and Global Leadership. He founded and teaches the Analytical Consulting Lab, Risk Lab, Global Lab, and Digital Lab – all very popular experiential learning classes at the Kellogg School of Management, which bring Kellogg MBA students together with corporate opportunities focused on data and strategy. He also teaches courses in risk management, analytics, and on strategies in globalization.His most recent book From Big Data to Big Profits: Success with Data and Analytics is published by Oxford University Press (2015), which explores how firms can best monetize Big Data. He is the author of the book Winning with Risk Management (World Scientific Publishing, 2013), which examines the principles and practice of risk management through business case studies. He has also authored many business cases and published multiple Kellogg case studies through Harvard Business School Publishing. His cases have been highlighted by the Harvard Business School Publishing, the Aspen Institute, PRMIA, and the Bank of England for excellence in teaching risk management.

He serves on the Scientific and Technical Council for the Menus of Change, an initiative led by the Harvard School of Public Health and the Culinary Institute of America, to develop healthier and more environmentally friendly food choices. He was formerly on the board of the Education and Technology Committee to the Morton Arboretum. He was a board member of the Virginia Hispanic Chamber of Commerce, where he developed support programs for Hispanic entrepreneurs and worked with US senators on US Latino matters.

He is at @RussWalker1492 and russellwalkerphd.com.

Risk Management Leadership Lesson: The Value of Trust in Operations

Risk Management Leadership Lesson: The Value of Trust in Operations

Risk Management Leadership Lesson: The Value of Trust in Operations

In business and life, we grow to expect certain things. Namely, our society expects companies to produce products that are safe and reliable. We go to Yelp and rail against restaurants that do not meet our expectation for service. However, large firms, when caught red-handed often have gotten by with a mere slap on the hand. When we see a firm misbehave or use a controversial advertisement, we see boycotts initiated and apologies extracted. What about more severe damages? How a firm operates is important in its success and in forming trust with its customers.

In the last few weeks, we have seen a couple of major developments in how firms have cheated and thus lost trust. Stewart Parnell, the former CEO of Peanut Corporation of America, was sentenced to 28 years in prison for knowingly selling and distributing peanut products containing salmonella. At least nine people are known to have died from these contaminated peanut products. It is a striking case, because we now have the science to keep food safe. We now have the science to find what has killed us and identify the source of that contamination. Yet, a firm and its executives decided to operate in a reckless manner. It is the first severe penalty levied on a food company for selling contaminated food. In the trial, former employees of the Peanut Corporation of America testified that the CEO and firm prioritized profits over safe operating conditions. Of course, the tragic deaths cannot be reversed with prison time or fines. The damage to the Peanut Corporation of America was self-inflicted. No competitor or market force did that to them. No surprise in the capital markets or fear of peanuts by consumers brought them harm. When firms cheat and do harm, they ultimately hurt themselves. This fraud is of course a major risk to shareholders, customers, markets, and, in this case, the health of people.

The recent EPA disclosures about how Volkswagen has more or less gamed its diesel engine systems to perform well on emissions tests (and only during tests) showcases yet another case of internal fraud. Attorneys General across the US are already calling for billions in damages from Volkswagen. The firm created an image for “clean diesel,” sold it to well-educated and wealthy Americans, who wanted an environmentally palatable vehicle, and they profited handsomely from it. Now the lies have been revealed. The fraud, again, is internal and self-inflected. No competitor, regulator, customer, or market force made Volkswagen do this. It is risk that now will harm shareholders, customers, the German economy, and the environment. And, let’s not forget about Toyota and its accelerator, GM and its ignition switches, and well… the list goes on and on. We lose trust in firms because of the harm they cause and because that is the result of internal risk taking and decision-making gone awry.

These two recent cases are largely about internal fraud. It is clear that the firms knew about their misdeeds and elected to operate in a reckless and harmful manner. We often think of internal fraud as a banker walking out of the vault with gold bars. Such fraud is far less likely to occur than that of an executive taking undue risk against the firm to meet short-term goals. With average CEO tenures on the order of 5 years, the pressure to preform is high and the window of opportunity is short. The threat of internal fraud is a risk that all firms must address.

The management of such risk falls under Operational Risk Management. Operational Risk and self-inflicted damages are the cause of the greatest reputational harm. Nobody forced BP, GM, Volkswagen, Toyota, or the Peanut Corporation of America to do what they did. Their executives elected to take risks (and dangerous ones). Trust requires operating successfully over many transactions and creating value for customers. Once that trust and reputation are damaged, the firm must work to change not only its image, but also its operation. The process to managing Operational Risk requires a treatment that addresses the organization, its culture, its management, and leadership. We will explore all of these topics in the upcoming course Operational Risk Master Class: Measurement, Management, and Leadership.

Join us!

About Russell Walker, Ph.D.

Professor Russell Walker helps companies develop strategies to manage risk and harness value through analytics and Big Data. He is Clinical Associate Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management of Northwestern University.

His most recent book, From Big Data to Big Profits: Success with Data and Analytics is published by Oxford University Press (2015), which explores how firms can best monetize Big Data. He is the author of the text Winning with Risk Management (World Scientific Publishing, 2013), which examines the principles and practice of risk management through business case studies.

He  has advised many leading institutions on Operational and Reputational Risk Management, including: The World Bank, SEC, Genworth, Capital One Financial, Discover Financial, PNC, The Bank of England, and the US State Department, among others.

You can find him at @RussWalker1492 and russellwalkerphd.com

Risk Management Leadership Lessons – The Importance of Focusing on Operational Risk

Risk Management Leadership Lessons – The Importance of Focusing on Operational Risk

The Volkswagen case shows us a contemporary case of what can go dramatically wrong when an enterprise does not focus on its operational risk. Worse, it shows what happens when a lack of leadership and presence of cheating overtake the virtues and values of the firm. Operational risk is a major concern for many firms and in particular for financial service firms.

It is important for risk leaders to focus on operational risk for many reasons. Let’s examine some reasons:

  1. Operational Risk is not tied to an investment with a direct upside. Unlike credit and market risk, where the downside exposure is known (or mostly known) at the time of investment, and an upside is projected, setting up an operation or taking on a new vendor introduces operational risk of an unknown and unforeseen nature. There is no upside, generally. Therefore, reducing operational risk is a direct monetary benefit to the enterprise. Removing operational risk requires knowing how and why it occurs, in the first place.
  2. Measuring Operational Risk requires acknowledging it. I once met with a CEO at a bank that told me, “We don’t have operational risk.” I remember telling him in response that until you recognize it as operational risk, you will see operational risk only as unexpected costs via project overrides, unexpected credit losses, and even lawsuits from customers. He informed me, “We have lots of that.” It is not about semantics. Operational risk is an error and unless you are looking for errors, it will simply look like your business, process, or systems have deviated from plan. Removing the error will be impossible from the investment decision to operate. If a loan process has missing data (a common operational risk) and the loans under-perform, the decision might be to shutdown the loan business entirely (not to invest) but the correct action is to fix the operational risk and process for collection of data. Not understanding and measuring operational risk will mean that business decisions are sub-optimal. Operational risk management is about removing the errors and making the business investment more precise going forward.
  3. Critical operations introduce the biggest operational risk. As in all industries, the desire to reduce costs and develop new products is with us constantly in financial services. Outsourcing and new business models have also brought new risks as costs have been removed. The pressure to move into new banking products, such as online, mobile, and RFID payments have introduced operational risks too. It is little surprise that Apple Pay experienced a fraud rate of over 6%, which is more than 60 times that of normal credit cards.[1] Today, every bank and insurance executive fears that day they see customer data breached and shared online. A repeat of the Target case is nightmare for any business leader. Storing, accessing, and transmitting critical data are now some of the most critical decisions facing a financial institution.[2]
  4. Operational Risk is at the root of reputational harm and regulatory risk. When asked, a risk leader, CEO, or board member will report that their greatest concern is harm to the reputation and customer.[3] Next, it is a great concern that a regulatory body might target the firm for behaviors (real or implied) and penalize the firm accordingly, often in response to how a customer has been harmed. The way a business operates is tied to how it treats a customer and how it fails in providing the customer what he or she expected or was promised. Customers sue banks and insurers for their practices and enforcement when something goes wrong. That is operational risk. If you want to get a head of reputational harm and regulatory risk, focus on operational risk detection and prevention. Develop a plan to measure, manage, and lead operational risk.

How a firm operates and makes decisions is tied to how it manages internal decision-making processes. The management of such risk falls under Operational Risk Management. Operational Risk and self-inflicted damages are the cause of the greatest reputational harm. Through cases and simulations, we will explore all of these topics in the upcoming course Operational Risk Master Class: Measurement, Management, and Leadership.

Join us!

About Russell Walker, Ph.D.

Professor Russell Walker helps companies develop strategies to manage risk and harness value through analytics and Big Data. He is Clinical Associate Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management of Northwestern University.

His most recent book, From Big Data to Big Profits: Success with Data and Analytics is published by Oxford University Press (2015), which explores how firms can best monetize Big Data. He is the author of the text Winning with Risk Management (World Scientific Publishing, 2013), which examines the principles and practice of risk management through business case studies.

He has advised many leading institutions on Operational and Reputational Risk Management, including: The World Bank, SEC, Genworth, Capital One Financial, Discover Financial, PNC, The Bank of England, and the US State Department, among others.

You can find him at @RussWalker1492 and russellwalkerphd.com

[1] http://blogs.wsj.com/digits/2015/03/03/fraud-comes-to-apple-pay/

[2] Deloitte, Global Risk Survey of CROs.

[3] Economist Intelligence Unit, survey of CROs.