Enterra Insights

Sales & Operations Planning Must be Inclusive

Back in 2011, John Westerveld penned a two-part blog that discussed "a new way to think about S&OP." ["Thoughts from Kinexions – A new way to think about S&OP, Part 1 and Part 2," The 21st Century Supply Chain, 21 and 24 October 2011] The old way of thinking about S&OP, he explained, involved a team that used some kind of demand planning system to create forecasts which were then bounced off a traditional ERP system to see if the forecasts were doable. One of the problems with this method, he noted, was the assumption "that you will only need to evaluate a single demand plan." Anyone familiar with forecasts knows that they are seldom accurate enough to survive in the real world. Westerveld explained in Part 2 of his post that an S&OP process that could match the vagaries of the real world required six different functionalities. They are:

1. You need a system that allows you to create 'what-if' scenarios instantly, and provides the ability to collaborate with these scenarios.
2. You need to have both collaborative demand planning and complete supply planning in the same tool. The supply planning tool needs to accurately emulate the planning done by your ERP system.
3. You need to be able to drive the supply planning system from the demand plan.
4. Further, you need to be able to configure which forecast stream (or combination of streams) forms the demand plan (and therefore drives the supply planning process). This combined with #1 will allow you to evaluate and compare different demand planning scenarios.
5. You need excellent reporting tools that allow you to understand supply issues, their cause, and potential resolutions.
6. You need excellent reporting tools that allow you to present the recommended S&OP plan, the issues, and alternative resolutions to the executive team.

There are a few words in those six functions I would like to highlight; namely: collaborate, collaborative, and the repeated use of the word "supply." Although the word "supply" isn't found in "Sales & Operations Planning," the supply chain clearly plays an essential role in ensuring that any plan (or plans) can be implemented. That's why I was surprised when I read a headline declaring "The 'S' in S&OP Can Stand for Supply Chain, Too." [Becky Partida, IndustryWeek, 18 April 2013] It seemed odd to me that business executives needed to be reminded that their supply chains undergird their businesses. Partida, who is a supply chain management research specialist with APQC, notes, "Sales and operations planning (S&OP) has the potential to promote visibility within the enterprise and foster collaboration among business functions. However, the functions involved in the S&OP effort can vary from organization to organization. " Notice that the word "collaboration" is once again used when discussing S&OP. She reports that analysts at her company asked a number of organizations to tell them what functions they included in their S&OP processes. The results are shown in the following graph.

One thing struck me immediately upon viewing the chart: Some companies appear to be conducting "sales and operations" planning without involving "sales and marketing,"  manufacturing," and/or "logistics." I'm not sure how that's done. You would have thought that all those categories would have been 100%! Part of the answer may be that some companies simply don't have an S&OP process, which means nobody is involved. Malory Davies, editor of Supply Chain Standard, reports, "The concept of Sales and Operations Planning is hardly new, but a surprisingly large number of companies, 72 per cent, have only started to make use of it in the past five years, according to a survey by consultants Bearing Point." ["All going to plan?," 30 April 2013] Davies goes on to report, "The survey, which focused on process industries in western Europe, also found some significant weaknesses in how S&OP is implemented, notably the supporting IT systems and a lack of S&OP integration to risk management to the finance function as well as to supply chain partners." One of the recommendations made by Bearing Point was improving "collaboration across the company."

By now you should get the idea that S&OP processes need to be much more collaborative than they have been in the past. Peter Balbus, Managing Director of Pragmaxis, LLC, defines S&OP "as a set of integrated corporate-wide planning processes that enable senior management to strategically direct operations with the intent to achieve superior levels of performance on a sustained, long-term basis." ["How S&OP is Changing the Face of Advanced Supply Chain Management," Dustin Mattison's Blog, 5 May 2013] He went on to explain:

"It means integrating customer-focused sales plans, historic trend data and predictive analytics with supply chain management to enhance customer fulfillment capabilities, drive efficiency, improve resiliency and maintain agility to respond rapidly to changes in customer, market and supply dynamics. Successful S&OP processes align operations with the corporate business strategy. As companies have become more global and face rising complexity, volatility and uncertainty, the importance of S&OP is increasing. Especially in those industries that are well-served and where we see growth is flattening, S&OP becomes critical to competitive survival."

I appreciate the fact that Balbus mentioned corporate alignment. You simply can't align an organization if some parts of the organization are excluded from S&OP process. That's why I insist that S&OP must be inclusive. Rich Sherman, a Supply Chain Discipline Expert at Trissential, insists, "Collaboration is the key ... to unlocking the hidden wealth in supply chain operations. For that, S&OP is among the most important best practices and processes a company can implement." ["Sales & Operations Is Only the Tip of the Iceberg," SupplyChainBrain, 13 March 2013]

Balbus also reinforces a point that Davies made earlier. He told Mattison, "The overwhelming majority of companies today have ongoing S&OP initiatives, significantly fewer have fully implemented these planning processes and even fewer are reporting successful outcomes among those that have." I suppose another way of stating that would be, "Companies know S&OP is important but they don't have a clue about how to implement it." Balbus notes that one market survey indicated that "90% of companies responding believe that a strong S&OP process improves supply chain agility and efficiency. All well and good. But only 13% of these same companies report having effectively tied S&OP planning to execution activities!" Balbus concluded his interview with Mattison by sharing a few thoughts about how companies can better implement S&OP processes.

"The key to any successful S&OP initiative is the ability of the organization to align demand, supply, inventory and financial plans easily and seamlessly against the overall business strategy. This requires a technology layer to enable demand translation -- that is, the modeling of changing product mix, and the visualization of equivalent units. This technology layer then becomes the system of record tying together the multiple S&OP plans. However, this alone is not sufficient to sense and define a response to buy- and sell-side market changes. All too often, plans are built on enterprise data – and not external market data. In addition, the process definition is inside-out (where enterprise data is used to predict future market shifts) rather than outside-in (where market data used to sense and shape responses based on market shifts). The most effective S&OP processes use both buy- and sell-side market data to bi-directionally align the organization from market-to-market. As the company shifts from inside-out to outside-in, data models must to be redefined and the technologies re-architected to reflect this profound change in orientation. These are fundamentally different data models. Another common barrier to achieving S&OP excellence is that companies are not sufficiently deliberate in their statement of goals, definition of governance practices, or the definition and alignment of key performance metrics. While companies universally state that they want to improve their S&OP processes and want to be agile, they often struggle to define what this means specifically for their company to make it 'actionable'."

Supply chain analyst Lora Cecere has been touting, for some time, the notion that organizational strategies need to be more outside-in rather than inside-out. If you haven't done so, you should join her Supply Chain Insights Community. Outside-in demand visibility often involves big data. Nari Viswanathan, Vice President of Product Management at Steelwedge, reports that companies are collecting more product, supply, demand, and finance data; but, "are not actually leveraging this data in their S&OP processes, thereby leaving 'blind spots' in their decision making processes around critical supply/demand trade-offs." ["Big Data Is Becoming a Big Deal for Agile S&OP," SupplyChainBrain, 13 March 2013] The biggest blind spots of all, however, can come from within an organization if planning isn't an inclusive activity. Partida concludes:

"Because S&OP affects the entire supply chain, organizations should give serious thought to involving representatives from the supply chain functions in this process. Organizations should consider whether any additional costs incurred in the planning process would be offset by increased efficiency or costs savings generated within the procurement, manufacturing, or logistics functions. It may be that involving the supply chain in S&OP is worth the investment."

I might have put it another way, "Is excluding parts of your organization from the S&OP process worth the cost?" The simple answer is, "No."

Supply Chains: Growing Risk, Less Preparedness

In spite of the numerous supply chain disruptions that have occurred over the past several years, results from "the 2013 Aon Global Risk Management Survey points to a significant decline in risk readiness among many of the survey respondents. On average, reported readiness for the top 10 risks dropped a material 7 percent (from 66 to 59 percent) from the 2011 survey and reported loss of income increased 14 percent." ["Worrying trend emerges from 2013 Aon Global Risk Management Survey," PR Newswire, 22 April 2013] Not all industry sectors were found in retreat, "Of the 28 industries defined in the report, only three industries – pharmaceutical and biotechnology, non-aviation transportation manufacturing and agribusiness – reported the same or improved levels of readiness this year." A decline in risk readiness is a bit surprising since risk awareness has never been higher. This was underscored by the fact that the number of respondents to the 2013 survey was 47 percent higher than the number who responded to the 2011 survey.

Stephen Cross, chairman of Aon Global Risk Consulting, stated, "One possible explanation of the decline in risk readiness could be that the prolonged economic recovery has strained organizations' resources, thus hampering the abilities to mitigate many of these risks. Our survey revealed that, despite diverse geographies, companies across the globe shared surprisingly similar views on the risks we are facing today – whether or not they feel prepared." Another possible explanation for the decline in risk readiness might be the result of increased risk awareness. Executives are no longer living in blissful ignorance when it comes to risks and, therefore, their sense of readiness may have declined.

Below is the Top Ten list of risks identified by respondents.

Risk Description	Risk rank - 2013	Risk rank  - projected 2016
Economic slowdown/slow recovery	1	1
Regulatory/legislative changes	2	2
Increasing competition	3	3
Damage to reputation/brand	4	8
Failure to attract or retain top talent	5	5
Failure to innovate/meet customer needs	6	4
Business interruption	7	11
Commodity price risk	8	7
Cash flow/liquidity risk	9	10
Political risk/uncertainties	10	6

Judging from the top three risks (which aren't predicted to change over the next few years), respondents seem convinced that economic recovery is going to be sluggish even as competition increases. Kenneth Rapoza notes that those risks "are largely uninsurable," which may account for their high priority. ["What Keeps Business Leaders Up At Night?" Forbes, 23 April 2013] Cross told Rapoza, "The [insurance] industry globally should wake up and think that these are the risks and concerns their clients worry about most." Thinking about it and being able to do something about it are two different things. As Rapoza asserts, "It's one thing to insure an oil spill or lost cargo deep in the Pacific Ocean. But how does a German nuclear power company insure against legislative risk?"

The press release notes, "Political risk/uncertainties broke into the top 10 risks for the first time in 2013. Due to the increasing civil wars and social and political conflicts around the world, this risk is projected to move up to number six in the 2016 survey." For more on that topic, read my post entitled Geopolitics and Supply Chain Risk. In what was the biggest surprise to me, weather/natural disasters did not make the Top Ten list for 2013. It ranked number 16 (although it is "projected to jump into the top 10 list at number nine" by 2016). Most of the significant supply chain disruptions that have occurred over the past five years have been related to weather or natural disasters. Aon Global Risk Consulting analysts don't anticipate this will change "given the unusual climate patterns worldwide and an unprecedented increase in natural disasters and weather events." Rowan Douglas, Chairman of the Willis Research Network (WRN), asserts, "[The] breadth and impact of natural disasters in recent years, coupled with growing concern about the emerging effects of climate change on assets and business operations, have driven resilience to natural hazards high up the corporate risk agenda." ["Willis Report Warns of Growing Risks from Natural Catastrophe Exposures," Insurance Journal, 23 April 2013]

The next 10 risks on the survey list were:

11. Exchange rate risk
12. Technological failure
13. Third party liability
14. Supply chain failure
15. Corporate credit risk
16. Natural disasters
17. Property damage
18. Cybercrime
19. Compliance
20. Counterparty credit risk

A list of the Top 50 risks can be found by clicking on the following link. The Aon Global Risk Consulting analysts "uncovered several significant risks to watch, as these are perceived to be underrated risks." Those risks include: Computer crimes/hacking/viruses/malicious codes; Counter party credit risk; Loss of intellectual property/data; Social media; and Pension scheme funding. Norman Marks, who was a chief audit executive and chief risk officer at major global corporations for more than 20 years, believes there are other "massive risks that are faced ... by a majority of organizations and, even if they are recognized, are often accepted instead of corrected." ["The Important Risks That Are Overlooked but Should Come First," Marks on Governance, 23 April 2013] His list includes:

• The board and top management setting organizational objectives and monitoring performance without sufficient information. ...
• A failure to consider risks when establishing strategies and objectives. ...
• Executives making business decisions without adequate, current, timely, and reliable information. ...
• A failure to consider risk when making day-to-day business decisions. ...
• An inability to monitor risk as it changes, which is very often at least daily. ...
• A failure to communicate and explain the personal relevancy of organizational strategies to every manager and decision-maker. ...
• Putting cost considerations ahead of the quality of the management team and the workforce in general. ...
• Processes and systems that cannot move and adapt – a lack of agility. ...
• A board that is unable to provide effective oversight. ...
• A conflict between the personal interests of the executive team (short-term results, bonuses, stock appreciation) and the long-term interests of the organization as a whole. ...

Javier Gimeno, a professor in international risk and strategic management at INSEAD, agrees with Marks that corporate boards need to be more involved in risk management. "As part of the board's responsibility to endorse and monitor strategy," he states in the press release, "directors should gain an intimate understanding of the major strategic risks, possible scenarios and how the appropriate strategy allows the exploration of uncertainties and mitigation of strategic risks."

One thing that most analysts seem to agree upon is that because the world is more connected it is more difficult for companies to isolate themselves from catastrophes. Cross told Rapoza, "There's an inter-connectivity of global risk. What happens overseas can impact you anywhere." Phil Ellis, CEO of Willis Global Solutions Consulting Group, agrees, "Major catastrophes – so called 'black swans' – are not the rare risks they once seemed. Population density, urbanization, globalization and climate change make the world increasingly interconnected. A catastrophe in a far-off locale is no longer a remote risk; it could have an immediate impact on a company's operations. Risk modeling can help companies understand, quantify and articulate threats to the bottom line, which in turn helps them plan and prepare for these scenarios."

The Strategic Sourceror concludes, "Organizations that understand risk management is not just part of the business but a means to improve the organization can drive their bottom line. ... Early risk identification can be a method for minimizing the impacts of changes to a supply chain." ["Companies are less prepared for risk," 23 April 2013] A good place to start identifying potential risks to your business is the list generated in the 2013 Aon Global Risk Management Survey.

Big and Small Data

Dr. Rufus Pollock, Founder and co-Director of the Open Knowledge Foundation, insists that the real revolution that will take place in the Big Data era will involve "small data." ["Forget Big Data, Small Data is the Real Revolution," Open Knowledge Foundation Blog, 22 April 2013] Pollock asserts, "The real opportunity is not big data, but small data. Not centralized 'big iron', but decentralized data wrangling. Not 'one ring to rule them all' but 'small pieces loosely joined." He explains:

"The real revolution ... is the mass democratisation of the means of access, storage and processing of data. This story isn't about large organisations running parallel software on tens of thousand of servers, but about more people than ever being able to collaborate effectively around a distributed ecosystem of information, an ecosystem of small data. Just as we now find it ludicrous to talk of 'big software' – as if size in itself were a measure of value – we should, and will one day, find it equally odd to talk of 'big data'. Size in itself doesn't matter – what matters is having the data, of whatever size, that helps us solve a problem or address the question we have."

Although I agree with Pollock that what really matters "is having the data ... that helps solve a problem or address a question," for many of those problems and questions, size does matter. Outliers in small data sets can significantly skew results. Pollock himself admits that even though "for many problems and questions, small data in itself is enough," there are times when you need to "scale up." He believes, however, that "when we want to scale up the way to do that is through componentized small data: by creating and integrating small data 'packages' not building big data monoliths, by partitioning problems in a way that works across people and organizations, not through creating massive centralized silos."

Big data initiatives generally involve integrating data not creating "massive centralized silos." Nevertheless, Pollock is not alone in the belief that small data will play a role in the big data era. Bruno Aziza, Vice President of Marketing at SiSense, believes that one of the surprises that has emerged is that "Big Data isn’t about “Big”. [Forbes, 22 April 2013] By that he means that the term "big" is subjective. What is considered big today might be considered normal a few years from now. In other words, like Pollock, he believes that size is irrelevant as a descriptor of data sets. Aziza also agrees with Pollock that most problems don't require petabytes of data to solve. "Sometimes," he writes, "what can be perceived as 'Small Data' can go a long way." That's true as long as it's the right data. Regardless of the size of the data set, what really matters according to Aziza is the analytics applied to it.

The big data era began, he claims, as the result of a revolution in storage capability. He calculates that a terabyte of disk storage would have cost upwards of $14 million (adjusted) in 1980 but can be bought today for $30. When it comes to analytics, however, he asserts that what has occurred has been more evolutionary than revolutionary. Eric Schwartzman, founder and CEO of Comply Socially, underscores the importance of analytics. He writes:

"An avalanche of information is not necessarily a good thing. More often than not, it's a path to obfuscation rather than enlightenment, where speculation inflicts irrevocable harm and sensationalism travels farther and faster than tolerance. If you're a business, the takeaway is that sharing without analytics is essentially useless, that engagement is not as valuable as insight, and that seeing things in context is more important than being popular." ["Without Analytics, Big Data is Just Noise," Brian Solis blog, 24 April 2013]

Jake Sorofman, a research director at Gartner, believes that big data is still a big deal, because "big data [is] the intelligence behind microtargeting." He also agrees with Pollock and Aziza, however, that relevant smaller data sets will remain important in the big data era because "the precision of your aim doesn't matter if the customer experience falls short." He believes these relevant smaller data sets will be created from larger data sets to create "Big Content" and claims that they will be created through content curation. ["Forget Big Data—Here Comes Big Content," Gartner, 12 April 2013] He believes that curated content is especially important in the marketing sector because "content is the grist for the social marketing mill." He continues, "The rhythm and tempo of social marketing puts extraordinary pressure on marketing organizations that are more accustomed to publishing horizons measured in weeks and months than those measured in minutes and hours." As a result, "The expectation for content quality and authenticity has changed dramatically."

Steve Olenski agrees that in the marketing arena less is often more when it comes to the data involved. ["When It Comes To Big Data Is Less More?," Forbes, 22 April 2013] His take on why "less is more" is a bit different than the pundits discussed above. Olenski focuses on the fact that some of the sensitive data that is collected isn't necessary to achieve desired goals. He writes:

"Two esteemed professors at an Ivy League school say that while those in the marketing world continue to struggle with how to handle all the data they are accumulating, they may in fact be wasting their time and more than likely need to go on what they refer to as a 'data diet.' ... According to the aforementioned professors, all the talk about Big Data and privacy may be, as they put it, 'a tempest in a teapot.'"

Since many analysts believe that privacy issues are going to create a big storm rather than a tempest in a teapot, Olenski reached out to Eric Bradlow and Peter Fader, Professors of Marketing and Co-Directors of the Wharton Customer Analytics Initiative. Olenski indicates that the two professors "have studied the problem of data-privacy from an empirical perspective." He continues:

"Their research shows that brands and companies who are on a 'data diet' don't necessarily lose that much customer insights because limited customer data in conjunction with aggregate information (less privacy sensitive) can still provide precise insights. And when it comes to personal data, Fader says bluntly that 'most sensitive data is worthless and firms are often making mistakes to try to use it (or even collect it).' And adds that 'when you build a really good model, there isn't a whole lot to be gained by bringing in personal data."

That should be good news for marketers and consumers alike. Olenski reports that Bradlow and Fader believe "brands should keep the data they need to stay competitive and ditch everything else." That's the essence of a data diet. Bradlow told Olenski, "I think there is a fear and paranoia among companies that … if they don't keep every little piece of information on a customer, they can't function. Companies continue to squirrel away data for a rainy day. We're not saying throw data away meaninglessly, but use what you need for forecasting and get rid of the rest."

I'm not so sure that it's "fear and paranoia" that motivates companies to collect data as much as the unknown. Since we are at the beginning of the big data era, we really don't know what data is going to useful in the years ahead as analytics and the questions they address change. We are just beginning to appreciate exactly how valuable analyzed data can become. So at least for the next few years, discovering which data is most relevant and then concentrating on analyzing it should be a priority for most businesses. As companies get more comfortable in the world of big data, we are likely to read more about curated data sets and big data diets.

A Thought Probe Series on Tomorrow's Population, Big Data, and Personalized Predictive Analytics: Part 4, What Lies Ahead?

To get a glimpse of what lies ahead for smart cities, one need only to look to Singapore. As Mark Fischetti reported last year, "LIVE Singapore uses real-time data recorded by myriad communications devices, microcontrollers and sensors to analyze the pulse of the city, telling residents how they can reach their homes fastest, reduce their neighborhood’s energy consumption and find a taxi when a rainstorm hits." ["The Smartest Cities Will Use People as Their Sensors," Scientific American, 17 April 2011] The following short video, created by MIT's SENSEable City lab, gives you a glimpse of the future.

Looking to the future, Jemima Kiss, writes, "From transport to entertainment, work to education, our lives are already being transformed by high-speed internet that will help create the fully wired city. Within 10 years, faster, comprehensive, wired and wireless networks will not only become the norm, they will become free, says Gerd Leonhard, chief executive of the business thinktank The Futures Agency. The reason? The enormous benefits to government and education." ["City design: A digital revolution," The Guardian, 2012] While I agree that networks will continue to grow in importance, especially in urban environments, I'm not as sanguine as Kiss that ubiquitous connectivity will be free a decade from now. As connectivity increases, concerns over privacy issues will also rise, but Leonhard told Kiss, "While the debate about appropriate use of our personal data will continue, consensual services could be to our benefit." Among the benefits referred to by Leonhard is targeted marketing. "You'll walk past a department store and the window will show a personalised display with your size and preferences," says Leonhard.

Most smart city initiatives are not primarily focused on shopping experiences. Carlo Ratti and Anthony Townsend report that a number of countries are trying to create utopian urban environments. The furthest along is "Masdar in the United Arab Emirates, a walled community intended for 50,000 residents in the desert outside of Abu Dhabi, in which every building, streetlight and personal electric 'pod' vehicle has been preplanned and preloaded with high-tech gear, largely to maximize energy efficiency." ["Harnessing Residents' Electronic Devices Will Yield Truly Smart Cities," Scientific American, 17 April 2011] To learn a bit more about Masdar, read my posts entitled Abu Dhabi's Masdar Plan and Update on Masdar City. Ratti and Townsend continue:

"At Masdar, as well as New Songdo City in South Korea and PlanIT Valley in Portugal, real estate developers, global information-technology companies and governments are attempting to build urban centers from scratch that are filled with technologically enhanced infrastructure and services. The designers say their grand conceptions will determine how future cities will be built. But as models, these top-down projects pale in comparison to the emergent form of intelligence that is bubbling up from millions of newly cyber-connected residents. Truly smart—and real—cities are not like an army regiment marching in lockstep to the commander's orders; they are more like a shifting flock of birds or school of fish, in which individuals respond to subtle social and behavioral cues from their neighbors about which way to move forward."

Ratti and Townsend claim that this bottom-up view of smart city evolution represents "an immensely powerful, democratic and organic alternative vision of the smart city." They explain:

"Rather than focusing on the installation and control of network hardware, city governments, technology companies and their urban-planning advisers can exploit a more ground-up approach to creating even smarter cities in which people become the agents of change. With proper technical-support structures, the populace can tackle problems such as energy use, traffic congestion, health care and education more effectively than centralized dictates. And residents of wired cities can use their distributed intelligence to fashion new community activities, as well as a new kind of citizen activism."

Ratti and Townsend call this effort "going beyond urban efficiency." They note that "over the past decade digital technologies have begun to blanket our cities, forming the backbone of a large, intelligent infrastructure." They believe that this backbone holds the key to the future for all cities, not just planned developments like Masdar. They explain:

"Broadband fiber-optic and wireless telecommunications grids are supporting mobile phones, smartphones and tablets that are increasingly affordable. At the same time, open databases—especially from the government—that people can read and add to are revealing all kinds of information, and public kiosks and displays are helping literate and illiterate people access it. Add to this foundation a relentlessly growing network of sensors and digital-control technologies, all tied together by cheap, powerful computers, and our cities are quickly becoming like 'computers in open air.'"

Rather than embedding sensors in infrastructure, for many daily activities, Ratti and Townsend believe that mobile devices and cooperative owners will drive smart applications. They write:

"An ideal beginning is to leverage the growing array of smart personal devices we all wield and recruit people as the sensors of a city rather than relying only on formal systems embedded into infrastructure. The traffic function on Google Maps is a good example. Instead of building a costly network of dedicated vehicle sensors along roadways, Google constantly polls a large network of anonymous volunteers whose mobile devices report their up-to-the-minute status, which reveals where traffic is flowing, slowed or stopped. The information is delivered to drivers via mobile mapping applications in various ways—as colored overlays indicating traffic speeds, as estimated driving times that account for delays or as a factor in determining alternative routes. ... Bottom-up approaches to sensing can also provide rapid, cheap deployment of new kinds of sensors that measure and record data about people's activities, movements, surroundings and health."

Michael Durham claims that "Smart cities have always existed in people's heads." ["City design innovation," The Guardian, 2012] He asserts, that from the time that Plato wrote his Republic, "people have dreamed of the perfect community, where citizens live in harmony, life is good, technology is harnessed and everything works. Today, big ideas about improving city life continue to pour forth from futurologists, academics and thinktanks." Terry Kirby provides his own view of a future smart city. He writes:

"Imagine life for the citizen of the smart city: you awake in your sustainably built home, and take your morning shower in recycled industrial waste water, cost-efficiently heated overnight. Eating breakfast, you scan the flat screen, fed by maximum bandwidth internet, where the special, easy click local neighbourhood menu allows you to compare your daily energy use with other houses in the area, confirm your webcam appointment with your doctor, top up the balance of your all-purpose travelcard, order your groceries and leave messages for your child's teacher. You can even watch television on it. Outside, your electric car is waiting. On the edge of the central congestion zone, you park in a charging area and, paying with your travelcard, get into a three-wheeled utility vehicle which, via a network of special lanes and sensor-controlled pedestrianised areas, delivers you to another parking dock at your workplace." ["City design: Transforming tomorrow," The Guardian, 2012]

To me that sounds a bit like something out of The Jetsons cartoon show; but Kirby claims that "this is not some Dan Dare meets Minority Report fantasy of life in the future, where we all walk around in metallic jumpsuits. Smart thinking is here already." The problem, of course, is that cities aren't going to start over. London, for example, has had the same basic street layout (and some of the same buildings) for hundreds of years. We need to make sure that smart city initiatives help real people, living in existing dwellings, and carrying on with normal daily activities. Fortunately, Kirby is correct that smart thinking is already here and thinking about those challenges as well. He admits that smart city initiatives are "not simply about integrated transport or sustainable housing." He writes:

"The accumulation of electronic data online, digitally accessible and searchable, creates other opportunities for the consumer to know more about their neighbourhoods and the wider world we live in, and to use that information on a daily basis. It also allows local government, architects, transport bodies and utility companies to work together in partnerships to make the most of these technologies."

Simply accumulating and accessing data doesn't provide the answers or insights needed to make smart city initiatives successful. Big data analytics and other cognitive reasoning technologies are required to make sense of mountains of data being generated every minute of every day. Michael Durham claims, "In 40 years' time cities will not just be smart, they will be so brainy it hurts." ["Forty years from now ...," The Guardian, 2012] Most of that brainpower will be supplied by artificial intelligence. Among the smart people contemplating how to create smart cities are scientists at the Massachusetts Institute of Technology. MIT's City Science website notes:

"The world is experiencing a period of extreme urbanization. In China alone, 300 million rural inhabitants will move to urban areas over the next 15 years. This will require building an infrastructure equivalent to the one housing the entire population of the United States in a matter of a few decades. In the future, cities will account for nearly 90% of global population growth, 80% of wealth creation, and 60% of total energy consumption. Developing better strategies for the creation of new cities, is therefore, a global imperative. Our need to improve our understanding of cities, however, is pressed not only by the social relevance of urban environments, but also by the availability of new strategies for city-scale interventions that are enabled by emerging technologies. Leveraging advances in data analysis, sensor technologies, and urban experiments, City Science will provide new insights into creating a data-driven approach to urban design and planning. To build the cities that the world needs, we need a scientific understanding of cities that considers our built environments and the people who inhabit them. Our future cities will desperately need such understanding."

The following video discusses some of the interesting and exciting things that are being developed at MIT.

Achieving the objectives of smart city initiatives won't be easy (and probably won't be cheap). That is why public/private partnerships will be required. Smart city initiatives begin with people because their goal is to make cities more livable for people. If smart people fail to get the fundamentals right, technologies and processes that support smart city initiatives won't be able to overcome that shortfall.

Intelligence from Chaos

Alexander Wissner-Gross, a physicist at Harvard University and a fellow at the Massachusetts Institute of Technology Media Lab, and his colleague Cameron Freer, a post-doctoral fellow at MIT's Computer Science and Artificial Intelligence Laboratory, have been conducting experiments on how intelligence can develop out of chaos. Apparently what motivated them to research this area was the scientific notion that the cosmological systems with the greatest entropy also have the greatest probability of producing intelligent life. Entropy is most often thought of in negative terms. One of the definitions for entropy found in the online version of the Merriam-Webster dictionary is: "the degradation of the matter and energy in the universe to an ultimate state of inert uniformity." In commenting on the work of Wissner-Gross and Freer, Anthony Wing Kosner begins his article with a quotation from a William Butler Yeats' poem entitled "The Second Coming." Yeats wrote, "Things fall apart; the centre cannot hold; Mere anarchy is loosed upon the world." That stanza reminds us that things age, rust, corrode, and disintegrate; or, as the common funereal lament states, all things go from "ashes to ashes, dust to dust."

So how does one go from disorder to order? That is the question Wissner-Gross and Freer are attempting to answer. In a paper entitled "Causal Entropic Forces," Wissner-Gross and Freer "claim to have begun to formalize a mathematical framework capturing a fundamental relationship between intelligence and entropy maximization." ["Maximum Causal Entropy – Adaptive Systems and Intelligence," Compute 2020, 27 April 2013] In the introduction to their research paper, Wissner-Gross and Freer write:

"Recent advances in fields ranging from cosmology to computer science have hinted at a possible deep connection between intelligence and entropy maximization. In cosmology, the causal entropic principle for anthropic selection has used the maximization of entropy production in causally connected space-time regions as a thermodynamic proxy for intelligent observer concentrations in the prediction of cosmological parameters. In geoscience, entropy production maximization has been proposed as a unifying principle for nonequilibrium processes underlying planetary development and the emergence of life. In computer science, maximum entropy methods have been used for inference in situations with dynamically revealed information, and strategy algorithms have even started to beat human opponents for the first time at historically challenging high look-ahead depth and branching factor games like Go by maximizing accessible future game states. However, despite these insights, no formal physical relationship between intelligence and entropy maximization has yet been established."

Kosner helps us decipher the scientific lingo. He writes, "[Wissner-Gross'] idea is really very simple, but he has the mathematics ... and visualizations (see video below) to back it up. In short, everything in nature (our minds included) seeks to keep its options open. Instead of seeing entropy as a form of destruction (things falling apart) Wissner-Gross shows it to be a state of active play." ["From Atoms To Bits, Physics Shows Entropy As The Root Of Intelligence, Forbes, 21 April 2013]" The video to which Kosner refers is very interesting and takes about three minutes to watch.

Chris Gorski, an editor for Inside Science News Service, summarizes the results of Wissner-Gross' and Freer's work this way, "The researchers suggest that intelligent behavior stems from the impulse to seize control of future events in the environment. This is the exact opposite of the classic science-fiction scenario in which computers or robots become intelligent, then set their sights on taking over the world." ["Physicist Proposes New Way To Think About Intelligence," Physics Central, 26 April 2013] That interpretation sounds awfully sinister. Don Monroe offers a less ominous description of the research results. He writes, "The researchers interpreted ... behaviors as indications of a rudimentary adaptive intelligence, in that the systems moved toward configurations that maximized their ability to respond to further changes. Wissner-Gross acknowledges that 'there's no widely agreed-upon definition of what intelligence actually is,' but he says that social scientists have speculated that certain skills prospered during evolution because they allowed humans to exploit ecological opportunities."

The Compute 2020 post notes, "The paper suggests that complex adaptive behaviors can generally emerge as an agent or system attempts to maximize its accessibility to diverse future histories." It calls this "a startling generalization" that, if true, "may have impacts across a wide spectrum of fields of inquiry including the emergence of life, origins of gravity, roots of intelligent behaviors and driving forces of evolution." In the video Wissner-Gross claims it could also impact robotics, assistive technologies, manufacturing, agriculture, economic planning, gaming, social media, healthcare, energy, intelligence, defense, logistics, transportation, finance, and insurance.

As the video indicates, the software developed by Wissner-Gross and Freer is called Entropica, which they label "Sapient Software." You can access more information about the software by clicking this link. Entropica isn't the Holy Grail of artificial intelligence. Monroe concludes that "the new formulation is not meant to be a literal model of the development of intelligence." He does report, however, that Wissner-Gross believes that the model points toward a "general thermodynamic picture of what intelligent behavior is." Max Tegmark of MIT told Monroe that "the paper provides an 'intriguing new insight into the physics of intelligence. ... It's impressive to see such sophisticated behavior spontaneously emerge from such a simple physical process.'"

Simon DeDeo, a research fellow at the Santa Fe Institute, told Gorski, "It's a provocative paper. It's not science as usual." Jeff Clune, a computer scientist at the University of Wyoming, however, "expressed some reservations about the new research" to Gorski. Although Clune admitted that he "would be very interested to learn more and better understand the mechanism by which they're achieving some impressive results, because it could potentially help our quest for artificial intelligence." Clune suggested to Gorski that his reservations "could be due to a difference in jargon used in different fields." Although Wissner-Gross admits "there is room for improvement," he told Gorski, "We basically view this as a grand unified theory of intelligence. And I know that sounds perhaps impossibly ambitious, but it really does unify so many threads across a variety of fields, ranging from cosmology to computer science, animal behavior, and ties them all together in a beautiful thermodynamic picture."

Even if Wissner-Gross' and Freer's research doesn't result in "a grand unified theory of intelligence," it will nevertheless provide an important building block for the future. As Kosner concludes, "I think this approach is tremendously important for people who design interaction systems. Using the laws of physics instead of explicit goals is remarkably efficient and flexible." Kosner ended his article with this thought:

"To return to Yeats' poem, it begins with the lines, 'Turning and turning in the widening gyre / The falcon cannot hear the falconer.' ... If both the falcon and the falconer are governed by the laws of thermodynamics, they need not hear each other to be bound by the 'macrostate' of the widening gyre. Think of this gyre as a cone of possible futures emanating from the point of present moment, and the falcon as the entropic explorer of these 'future histories.'"

Whatever "future history" we end up pursuing, work like that being done by Wissner-Gross and Freer will make it all the more interesting.

Innovation: Horseless Carriages and New Perspectives

"Do you ever wonder why cars aren't called 'horseless carriages' anymore?" asks Ian Gonsher and Deb Mills-Scofield. "Today's cars are just as horseless as they were a century ago. Horselessness is standard equipment on most new and late models, both foreign and domestic." ["Great Innovators Think Laterally," HBR Blog Network, 23 April 2013] The anachronism "horseless carriage" is, of course, as outdated as "wireless radio" and "icebox." Yet each of those descriptors at one time literally and accurately described the object. Descendants of those products still exist, but the names haven't survived. That's the point that Gonsher and Mills-Scofield are trying to make. They write:

"Framing the question this way may seem a bit absurd; yet, it's a playful reminder that innovation does not emerge out of nothing. New innovations evolve from historical, iterative processes. The automobile developed out of, and in opposition to, concepts associated with the horse and carriage. This was the familiar frame of reference when the automobile first emerged. Early automobiles extended and adapted the accustomed 19th century understanding of locomotion."

In an earlier post entitled Analogies and Innovation, I pointed out that analogies are often used to explain innovative products by comparing them to other similar, but older, products. Eventually the analogies are no longer required and the once-innovative product becomes the analogy for next-generation innovations. Gonsher and Mills-Scofield note that the automobile, in some ways, remains a metaphor of horse and buggy days. "Consider the form of a car's design," they write. "You can see how four legs evolved into four wheels and headlights into the eyes of our metal beasts of burden. The vestiges of formative features still affect how we make sense of the built environment and our material culture, even if the original antecedent has long been forgotten." Although I believe the car more resembles the buggy than the horse, they make an interesting point. In the case of the automobile and the radio, their first descriptors (i.e., horseless and wireless) indicated they were opposite of things that relied on horses on wires. Gonsher and Mills-Scofield report, "Often, when searching for a new way to understand a familiar idea, we look for its opposite. By doing this, we create a spectrum of possibilities between what it is and what it is not."

Another way of thinking about creating "a spectrum of possibilities" is by looking at a challenge from a number of different perspectives. Looking from the opposite side is just one possible perspective. Like most creativity gurus, John G. Agno believes that changing perspective is an essential part of the innovation process. The reason, Agno states, is because changing perspectives helps us break free of ingrained beliefs and assumptions. "Our assumptions/beliefs are the elements we use to construct new ideas in our imagination," he writes, "and they constrain us to what we readily accept and believe is possible." ["Shift Perspective to Get Innovation Right," Coaching Tip: The Leadership Blog, 19 April 2013] He continues:

"Shifting perspective is essential if you are going to get innovation right according to Seth Kahan, author of 'Getting Innovation Right.' Shifting perspective should put you in a new relationship to everything you thought you knew. From this new perspective, you'll find it easier to innovate successfully. You must try to work your way around to seeing your business from 'outside' perspectives. Seeing your enterprise as your clients and partners view it means understanding why they do business or join forces with you. If you do not know the why of their participation, you are severely handicapped when it comes to expanding the value they have come to rely on you to deliver. However, when you know what your clients and partners believe is most valuable, your innovation program is more effective. When you see your operations from varying viewpoints, you sometimes spot opportunities to parlay what you are doing today into a new field altogether. Viewing your world from a different angle requires getting out of your own way, questioning the assumptions that likely have aided your success up to this point. It is not an easy task, but it is a skill all leaders must master if they want to innovate and reach levels beyond their current success."

If changing perspectives was easy, there wouldn't be so much written about it. Creativity coaches often offer exercises that can be used to force you to think from a different perspective. These exercises can involve things like asking the right questions, putting on "different hats," using forced metaphors, and so forth. Gonsher and Mills-Scofield label the ability to change perspectives "lateral thinking." They write, "Lateral thinking, the ability to move horizontally across different categories of thought, [and it] often manifests itself as a synthesis between seemingly incongruent ideas."

Another (and probably better) way to get new perspectives is to involve people from different disciplines in the innovation process. This creates what Frans Johansson calls the "the Medici Effect" in his book of the same name. [The Medici Effect: Breakthrough Insights at the Intersection of Ideas, Concepts, and Cultures] Johansson talks about the value of creating a space in which people from diverse fields of expertise can get together to exchange ideas. The Medici's, of course, were a wealthy and powerful Italian family who played an important role in the Renaissance. The family's wealth permitted it to support artists, philosophers, theologians, and scientists, whose combined intellect helped burst the historical pall known as the Dark Ages.

Gonsher and Mills-Scofield make it clear that creativity isn't about getting a good idea (i.e., experiencing the so-called "Eureka" moment), but realizing that the future is built upon the past when creating something entirely new. They conclude:

"The creative process is just that: a process. Recognizing value that others have missed doesn't require preternatural clairvoyance. A well-honed creative process enables us to intuitively recognize patterns and use those insights to make inductive predictions about divergent ideas, both vertically within categories, and horizontally across categories. By understanding the genealogy of innovation within a given category, we can imagine what might come next. We need to break out of thinking that is solely based on what we know, what we assume, and what we've experienced. Many of us are so entrenched in our industries that we don't know how to think laterally or horizontally. We usually go a mile deep but only an inch wide. We haven't given our people and ourselves the time and opportunities to explore other industries, cultures designs, ways of being and doing, and other 'adjacent possibilities.' If you want to take your 'car' far beyond horses, even to the moon perhaps, you and your team need to understand the genealogy of innovation, of how you got to where you are, and look outside of that familiar world to see where you can go."

Neil Goldberg expresses a similar thought this way:

"Shifting perspective produces new states of awareness. New awareness affords dramatic changes in the outcomes of actions taken. At the heart of design thinking is a awareness of the integrity between the object of innovation (a new experience, product, organization, policy, etc.) and the context in which it exists, including the user, use environment, technologies, delivery mechanisms, etc." ["Perspective, once changed, can never go back," Innovationship, 20 February 2013]

I like (and agree with) the title of Goldberg's post. Once you've experienced the almost magical results that emerge from applying a number of perspectives against a particular challenge, you will never go back to applying a single perspective when challenges are again confronted.

Campbell Soup Company Gets Innovative and Personal

Recently Campbell Soup Company CEO Denise Morrison took part in Boston's annual Front End of Innovation conference. ["Campbell Soup CEO Denise Morrison talks corporate innovation in Boston," by Scott Kirsner, Boston Globe, 8 May 2013] Kirsner points out "innovation" probably isn't the first thought that comes to mind when you think of Campbell's. He writes the first thing that probably comes to mind is "the tomato soup behemoth that inspired Andy Warhol." There's certainly nothing wrong with that -- I love their tomato soup. But, as Kirsner points out, if that is all you think about, "you haven't been paying attention."

Besides it famous soups, Campbell's international portfolio contains a number of other food products and brands. They include: Bolthouse Farms^® beverages, carrot products and dressings; North America Foodservice; Pace^® sauces; Pepperidge Farm^® products; Prego^® Italian sauces; Swanson^® products; V8^® products; Arnott's^® biscuits and crackers; Blå Band^® soups; DevosLemmens^® sauces; Erasco^® soups; Lacroix^® soups and sauces; Liebig^® soups; Royco^® soups; and Touch of Taste^® bouillon. That kind of diversity offers Campbell's a unique ability to mix and match products to create something new. To help the company stay fresh and creative, it named a vice president of innovation earlier this year.

During her presentation, Morrison indicated that she "is an advocate of 'fail fast, fail often, fail cheap,' when it comes to developing new product ideas." Kirsner reports, "Her ambitious goal at the company is to double the rate of innovation, while halving the cost and time spent cultivating new product ideas." It might strike you odd that a CEO -- upon whose shoulders rests the success of a company -- would be advocating failure. Of course, that's not her point. She's simply stressing the fact that, in order to be innovative, you have to take risks and, if you take risks, you are bound to suffer failures. Her "fail fast, fail often, fail cheap" mantra also implies that she understands that you can learn a lot from failure. To learn more about that topic, read my posts entitled Dealing with Failure often Precedes Achieving Success and Innovation: Learning from both Successes and Failures.

Another point Morrison made was, "Not every great idea needs to be Campbell-generated. It's clear that partners and vendors and other external sources will generate innovative ideas for us." The "not invented here" philosophy use to be pervasive in the business world. Collaboration was eschewed and proprietary systems were the norm. The information age played a major role in breaking down that paradigm and encouraging more collaboration. Former Procter & Gamble CEO A.G. Lafley, for example, once set a goal of going outside the company to find half of all innovations. The goal of "outside-in innovation" is to tap into the talents of others at a reasonable cost with good results.

Although the article doesn't mention sustainability, a company can't gain a reputation for sustainability excellence if it doesn't collaborate. Campbell's was the only U.S. food and beverage company to be "named to the Global 100 Most Sustainable Corporations in the World in a ranking by Corporate Knights, a media and investment research company." ["Campbell Soup Company Named to the Global 100 Most Sustainable Corporations in the World," Campbell's news release, 23 January 2013] Among the factors that won it this recognition were:

• Sustainability investments across Campbell’s plant network over the past four years that have yielded savings of more than $42.5 million.
• A reduction in water use by more than 3 billion gallons, and energy savings resulting in the elimination of more than 280,000 metric tonnes of greenhouse gas emissions, since 2009, resulting in ongoing annual savings of more than $2.5 million.
• The construction of a 60 acre, 10 mega-watt solar field at Campbell’s largest manufacturing site where 24,000 sun-tracking panels generate 15 percent of the electricity to operate the plant, and a partnership to create a biogas power plant at the same site to generate renewable electricity from waste generated from product production.
• The redesign of plastic product packaging that saved more than 1.2 million pounds of plastic in fiscal 2012.
• The distribution of more than $40 million in product donations globally and sales of $3.9 billion of products with improved nutrient profiles.
• The start of a 10 year, $10 million Campbell Healthy Communities program to reduce the rate of childhood obesity and hunger, and the donation of more than 23,000 volunteer hours in the U.S. and Canada to support local Campbell communities.

At the Boston conference, Morrison went on to discuss how companies are taking a more personalized approach to reaching out to customers. Kirsner explains:

"In thinking about how consumers will shop, cook, and eat in the future, Morrison says Campbell's is trying to understand emerging trends like 'quantified lives,' or 'managing our bodies and diets through personal data and feedback loops.' She cited Blippar as an example of how shoppers might use an 'augmented reality overlay' on top of product packages to view multimedia, recipe ideas, or coupon offers. Coca-Cola's Freestyle drink machine, offering more than 100 different flavors of soda, is an example of 'more distributed and personalized approaches to creating, sharing, and eating food'."

The Coca-Cola drink machine has been so popular that PepsiCo recently announced its own version. ["PepsiCo Bows Beverage Fountain That Lets Consumers Mix-n-Match Flavors," by Natalie Zmuda,  Advertising Age, 10 May 2013] Personalization and product customization are two characteristics that are likely to define the future business landscape. One thing that Campbell's Pepperidge Farm brand already offers is customized Goldfish crackers. Morrison is smart to be thinking along these lines. My company, Enterra Solutions, is pursuing a number of initiatives that will help companies use big data to better understand their customers and, as a result, allow them to tailor product offerings to customer tastes and preferences. This is particularly important for food companies since flavor preferences can change from neighborhood to neighborhood; especially in large urban areas. With the world becoming more urbanized, this kind of street-to-street insight will become increasingly important.

Morrison clearly understands the importance of knowing your customers. She told conference participants, "Our core consumers are baby boomers." While, for the moment, that is a good thing (because baby boomers are still active and wealthy), Morrison understands that boomers are getting older and that Campbell's must begin to appeal to new demographic groups. She indicated that Campbell's is trying to "build engagement with faster-growing consumer groups, like millennials and Hispanics." As Morrison is surely aware, this really complicates matters for both manufacturers, like Campbell's, and the retailers that sell their products. A study released by Jefferies, a global investment bank, and AlixPartners, a global business advisory firm, concluded, "The confluence of changing demographics, economic factors and customer preferences has the potential to create a long-term disruption across the food-industry value chain that transforms where and how consumers shop for groceries as well as what products they choose." ["Millennials' Grocery Consumption Patterns to Vastly Affect Food, Beverage Industry, Study Finds," SupplyChainBrain, 3 July 2012] Space on store shelves is limited and retailers want to maximize profits. This makes knowing what products are stocked, where they are located, and how often they need to be replenished important information. Big data analytics can help with those challenges as well. As Morrison told conference participants, "The top principle for disruptive and sustaining innovation is that it has to have a laser focus on customers. Innovation begins with their needs and expectations."

In her talk, Morrison also discussed the importance of knowing how current trends affect the marketplace. Kirsner writes:

"In launching its new Campbell's Go Soups, which she calls 'portable nutrition' in a microwaveable pouch, the company relied exclusively on digital and social media, including Twitter, Spotify, Facebook, and FunnyOrDie.com. The target audience was those 80 million millennials between the ages of 25 and 30."

If you were wondering how mobile communications could change the food industry, wonder no more. The company also sponsored "a hackathon designed to help home cooks everywhere answer the age-old question, 'What’s for Dinner?'" The company that developed the winning app was Pollinate Inc. Its 12-member team developed an app "fittingly titled FoodMood." Rather than create another recipe service that sorts "results based on ingredients or popularity, this app adds a different dimension to the dinner selection process, helping consumers find recipes based on their mood." ["Developer Cooks Up “What’s for Dinner?” App for Campbell Soup Company," Campbell's news release, 25 March 2013]

Morrison also used I term that was new to me and one that Kirsner writes he "really likes." That term was "drill sites." Kirsner explains:

"[Morrison] talked about identifying lucrative 'drill sites' for innovative product development. ... One example: more than 80 percent of U.S. households now own a slow-cooker (a/k/a a Crock-Pot.) But most people have a very limited repertoire of meals that they make in it. So Campbell's is developing a new line of ready-made sauces that can be combined with meat in a slow-cooker."

The slow cooker has been around for over 40 years. One wouldn't normally associate an "old technology" with a modern innovative opportunity. Obviously, however, someone did their analytic homework and, I believe, Campbell's will do well with their product line. Morrison told Kirsner that most of its product lines have associated innovation centers. While I think innovation centers are a good idea, I hope that there is a lot of cross-pollination between these centers. It would be a mistake to silo innovative ideas along product lines. Morrison told Kirsner that Campbell's is interested in both sustaining and disruptive innovations; so keep an eye on the iconic tomato soup company.

Enjoying Food: Taste, and Our Other Senses

Any true connoisseur of food understands that all of our senses (taste, smell, sight, touch, and hearing) play a role in how we experience and enjoy food. I agree with the website WeGotTaste.com, which states:

"The human body is amazing! Our body gives us a variety of different methods to interact with the world we live in. We receive information from the world via our senses. Each sense is distinct and different. ... Two people can be in the same situation but based on what they sense, they will each experience something different. Everyone relies upon their senses differently and some of the senses may be more accurate than others. ... The sense of taste teaches us flavors of food. We learn what things taste like so we can recognize what is good and bad for our body to ingest. With the variety of foods there are to eat and enjoy, it is not surprising that eating is one of our favorite things to do. Our senses all interact with each other and pass on information to our brain. Once received, our mind interprets everything and logs it away into memory. This process is what creates the individual experiences we enjoy."

Most people are aware of the close connection between the sense of smell and the sense of taste; but, they may not be aware of other sensory relationships associated with how we enjoy food. Let's begin with discussion with the basic sense of taste.

Taste

Taste is a complex subject, but let me provide you with the Cliff's Notes version of how our sense of taste works:

"The stimuli for taste are chemical substances dissolved in water or other fluids. Taste can be described as four basic sensations, sweet, sour, salty, and bitter, which can be combined in various ways to make all other taste sensations. Taste receptors (called taste buds) for these sensations are located primarily on various areas of the tongue: front, sweet; sides, sour; sides and front, salty; and back, bitter (see the attached figure). There are about 10,000 taste buds, which are situated primarily in or around the bumps (papillae) on the tongue. Each papilla contains several taste buds, from which information is sent by afferent nerves to the thalamus and, ultimately, to areas in the cortex." ["The Chemical Senses: Taste and Smell," CliffsNotes.com, 26 April 2013]

Some people now add a fifth sensation, umami, a Japanese word that can be translated "pleasant savory taste." The medical description of taste may not make food and flavors sound very exciting, but you have to admit that it is amazing that four or five basic sensations can produce the phenomenal number of tastes we experience when eating. To learn more about food flavors and how Enterra Solutions is helping McCormick & Company FlavorPrint^TM individual food preferences, read my post entitled Analytics 2.0: Big Data, Big Testing, and Big Experiences -- Part 2. As noted above, there is special relationship between the senses of taste and smell. So it's natural that we next discuss the sense of smell.

Smell and Taste

Before they started flavoring children's medicines, there were some pretty nasty tasting concoctions prescribed by doctors. Inevitably, mothers would tell their children to hold their noses while swallowing the stuff. For many children, the act of holding their nose while consuming something unpleasant was their first exposure to the relationship between taste and smell. The Cliff's Notes page says this about smell.

"The stimuli for smell are volatile chemical substances suspended in the air. These molecules stimulate the olfactory receptors, which are in the upper portions of the nasal passages. Neurons from these receptors bundle together to form the olfactory nerve, which travels to the olfactory bulb at the base of the brain. The theory of smell is not well understood (for example, how an odor of apple pie can evoke pleasant childhood memories)."

Interestingly, new research claims that the nasal passage isn't the only area in the body that contains odorant receptors. ["Odorant Receptors Found In Non-Olfactory Cells," Medical News Today, 8 April 2013] The article reports:

"In a discovery suggesting that odors may have a far more important role in life than previously believed, scientists have found that heart, blood, lung and other cells in the body have the same receptors for sensing odors that exist in the nose. It opens the door to questions about whether the heart, for instance, 'smells' that fresh-brewed cup of coffee or cinnamon bun, according to the research leader, ... Peter Schieberle, Ph.D., an international authority on food chemistry and technology."

I'll return to Dr. Schieberle's work later in this post. The next sense I'd like to discuss is sight.

Sight and Taste

Most of us are aware that food presentation is important. Debra Zellner, a professor of psychology at Montclair State University, believes that how a food looks can affect its taste. ["Professor Talk: What Attracts Us To Certain Foods?" by Mike D'Onofrio, Montclair Patch, 17 February 2013] Dr. Zellner states:

"Colored beverages are perceived to smell stronger. But when people drink it, it tastes weaker. It is what is called a contrast effect, where people are expecting something that is stronger than what they get. ... How a food is prepared on a plate can [also] have an effect on a food’s taste. We did an experiment where we used the same chicken salad but prepared one neatly on a plate, and the other unbalanced and messy. People tasted both plates said the chicken salad on the neatly prepared plate tasted better, so presentation also matters."

Terry E. Acree, Ph.D, agrees with Professor Zellner, he claims, "The eyes sometimes have it, beating out the tongue, nose and brain in the emotional and biochemical balloting that determines the taste and allure of food." ["Biochemical Balloting: 'Seeing' The Flavor Of Food," Science 2.0, 20 April 2013] "Years ago," he states, "taste was a table with two legs—taste and odor. Now we are beginning to understand that flavor depends on parts of the brain that involve taste, odor, touch and vision. The sum total of these signals, plus our emotions and past experiences, result in perception of flavors, and determine whether we like or dislike specific foods." The one sense that Acree didn't mention was hearing.

Hearing and Taste

The WeGotTaste.com page states, "Sounds affect the interpretation our mind gets, but not as much as smells and sight." We're all familiar with certain sounds associated with food, like sizzling bacon, popping corn, or percolating coffee. Nevertheless, the folks at WeGotTaste.com conclude, "Sounds do not really affect the way food tastes. Taste and sound are brought together in the mind, but do not have a whole lot of meaning together." A mother and blogger who goes by the nom de plume "mealtimehostage" isn't so sure. She writes:

"Back in January, my friend came down with a doozy of a cold, the kind that finds its way into every sinus nook and cranny. Excessive mucous accumulating in the back of her nose prevented retronasal airflow into her nasal cavity. I found it intriguing how congestion had altered her senses, and changed her preferences and perceptions of food. ... The congestion also affected my friend’s hearing, creating intermittent periods of muffled sounds, followed by periodic crackling and popping. Not uncommon with a cold, but I’m sure you're asking. What on earth do ears have to do with our sense of taste? My knowledge of ear anatomy is limited at best, but I do know the ear canals and sinus cavities are all somehow connected. Interestingly, the ear is where we find one particular nerve that has a profound effect on taste nerves and the pain fibers on the tongue."

Although mealtimehostage makes it perfectly clear that she has no scientific or medical background, she found studies that linked childhood middle ear infections and "selective eaters." The nerve she talks about is the chorda tympani. She found the following description of that nerve:

"The chorda tympani is responsible for the taste perception on the front of the tongue. If that nerve becomes damaged, tastes at the back of the tongue actually get enhanced to preserve overall 'taste constancy.' But other cues that go into our sensory experience of flavor, including texture, smells and chemical sensitivity, are also enhanced." ~ Derek Snyder, Yale University neuroscience graduate student

She discusses a couple of other studies she found of interest including one that reported "when a small sample of adult selective eaters were asked if they had middle ear issues, 27 out of 34 respondents reported they had suffered from some form of middle ear issue in early childhood." Mealtimehostage may just be on to something.

Touch and Taste

Whether you've consciously thought about the relationship between touch and taste, you have subconsciously made the connection. Mushy cereal, soggy potato chips, and other not-so-appetizing foods may still be nutritionally valuable; but, because of how they feel, they become unpalatable for most of us. There is probably an evolutionary explanation for why the feel of some foods repels us. A mushy apple, for example, may indicate that it has gone rotten and could be dangerous to eat. John S. Allen, a neuroanthropologist, wrote a book entitled "The Omnivorous Mind," in which he "explores our biological equipment for taste and the ways in which each culture builds a unique cuisine upon a shared cognitive blueprint." ["An Accounting For Taste,"by Leo Coleman, Wall Street Journal, 20 May 2012] In a review of the book, Coleman writes:

"[Allen] observes ... that crispness seems to be a desirable quality of foods, whether in the crunchy crickets treated as a delicacy by some cultures or in Kentucky Fried Chicken. Such universals suggest that a deeply ingrained culinary capacity is an essential part of every human's 'biocultural' equipment, comparable to the cognitive capacities for language and empathy that indisputably marked important frontiers in human evolution."

In other words, touch may have a more profound effect on our sense of taste than we may have imagined. Earlier, I wrote that I would return to the work being done by Dr. Schieberle. I wanted to end this post discussing his work because it involves how the senses affect taste. The Medical News Today article reports, "Schieberle's group and colleagues at the Technical University of Munich work in a field termed 'sensomics,' which focuses on understanding exactly how the mouth and the nose sense key aroma, taste and texture compounds in foods, especially comfort foods like chocolate and roasted coffee." The article continues:

"For example, baked beans and beans in foods like chili provide a 'full,' rich mouth-feel. Adding the component of beans responsible for this texture to another food could give it the same sensation in the mouth, he explained. Natural components also can interact with substances in foods to create new sensations. The researchers use sensomics to better understand why foods taste, feel and smell appetizing or unappetizing. They use laboratory instruments to pick apart the chemical components. They then put those components together in different combinations and give these versions to human taste-testers who evaluate the foods. In this way, they discovered that although coffee contains 1,000 potential odor components, only 25 actually interact with an odor receptor in the nose and are smelled. 'Receptors help us sense flavors and aromas in the mouth and nose,' said Schieberle. 'These receptors are called G-protein-coupled receptors, and they were the topic of the Nobel Prize in Chemistry in 2012. They translate these sensations into a perception in the brain telling us about the qualities of a food.' Odorant receptors and the organization of the olfactory system also were the topic of the 2004 Nobel Prize in Medicine. Of the total of around 1,000 receptors in the human body, about 800 of these are G-protein-coupled receptors, he said. Half of these G-protein-coupled receptors sense and translate aromas. But only 27 taste receptors exist. And although much research in the food industry has gone into identifying food components, little effort has focused on the tying those components to flavor perceptions until now, he said."

Undoubtedly, a lot more research is going to be conducted about relationships between our senses and how they can affect our perception of flavors. I believe that process like the one that McCormick is using for FlavorPrint could be applied to other senses as well. SensoryPrinting^TM all of our senses would certainly give us a better picture of how we individually respond to the world around us.

A Thought Probe Series on Tomorrow's Population, Big Data, and Personalized Predictive Analytics: Part 3, Where Things Stand

"What makes a city?" That is a question asked on IBM's Smarter City website. The company believes that a city is "an interconnected system of systems" that rests on three pillars: infrastructure, operations, and people. The site goes on to state that a city is "a dynamic work in progress, with progress as its watchword. A tripod that relies on strong support for and among each of its pillars, to become a smarter city for all." That definition may be a bit too cheery for some because they know that for years many inner cities have not progressed but languished or deteriorated. That entropic trend must change, because the world is becoming more urbanized every day. If tomorrow's cities are not going to become vast areas of poverty and decay, we have to be smarter about how they are planned, managed, and maintained. In a special issue about smart cities, the editors of Scientific American wrote:

"Many otherwise lucid thinkers, from Tho­mas Jefferson to Frank Lloyd Wright to President Gerald Ford, tended to think of cities as centers of poverty, crime, pollution, con­gestion and poor health. In recent years, though, the thinking has shifted along with the demographics. Many experts have come to realize that people are better off when they live in a city. This is not to dismiss the problems of urban life; cities, particularly fast-growing ones in the poorer parts of Asia and Africa, can be places of great human suffering. But even a city slum has benefits that you won't find on the farm or in the village. The move from the country leads, for instance, to dramatic changes for many women. As Kavita N. Ramdas of the Global Fund for Women notes in Stewart Brand's Whole Earth Discipline (Penguin, 2010), 'In the village, all there is for a woman is to obey her husband and relatives, pound millet, and sing. If she moves to town, she can get a job, start a business, and get education for her children.' Indeed, the city has come to look less like a source of problems than as an opportunity to fix them. Investments in sanitation and water have turned many cities in the developed world from places of disease and pestilence into bastions of health. City folk are at lower risk of death from motor vehicle accidents and suicide by firearms (although they are overstressed). From the stand­point of the metropolis, climate change also seems less intractable. Because city residents rely less on cars and live in more compact dwellings than suburbanites, they tend to leave smaller carbon footprints. The challenge is to extend the efficiency of the urban center to the wider conurbation, embracing the city center, suburbs and satellite towns. Although climate is bigger than any one fix, how we build our cities, and how efficiently we live in them, is going to factor large in our response." ["Street-Savvy," 17 April 2011]

In Part 1 of this series, I discussed suggestions from experts on how to begin smart city initiatives. One of those experts, Dr. Boyd Cohen, created a model he calls the Smarter Cities Wheel. IBM has also developed a model that is reminiscent of Dr. Cohen's Wheel. The IBM model shows how it believes the three pillars of a city discussed above are interconnected.

Like most organizations involved in smart city initiatives, IBM believes that data collection and analysis is the undergirding that makes such initiatives useful. IBM's site states:

"As demands grow and budgets tighten, solutions also have to be smarter, and address the city as a whole. By collecting and analyzing the extensive data generated every second of every day, tools such as the IBM Intelligent Operations Center coordinate and share data in a single view creating the big picture for the decision makers and responders who support the smarter city."

In Part 2 of this series, I noted that participants in a study published by the Institute for the Future expressed some concern that companies like IBM are trying to establish data monopolies that could be used to hold cities hostage in the decades ahead. IBM obviously sees itself as providing a much-needed service that cities can't provide for themselves. The company offers a nifty interactive Smarter Cities experience that can be explored at your leisure. Of course, IBM isn't the only global company that sees business opportunities in helping cities operate more efficiently. Oracle has its own interactive website that highlights its solutions for smart cities. The launch page for that interactive site also shows how Oracle sees connectivity within an urban setting (with business and citizens being the focal point).

Although the site explains that "Oracle offers a complete, integrated set of solutions to meet the complex needs of local government," some people, like Greg Lindsay, believe that companies like Oracle, IBM, and Cisco are "offering 'smart city in a box' solutions" that don't take into account the nuanced complexities that make each city unique. ["The Battle for Control of Smart Cities," Fast Company, 16 December 2012] See Part 2 of this series to learn more about Lindsay's concerns. Cisco's offering is called Smart+Connected Communities. Cisco's Shane Mitchell explains, that "the main barrier to adopting [smart city] solutions is the complexity of how cities are operated, financed, regulated, and planned." ["Smart City Frameworks: A Systematic Process for Enabling Smart+Connected Communities," Cisco Blog, 10 October 2012] Rather than offering a set of solutions, Cisco begins with "a 'Smart City Framework' designed to move the Smart City debate from merely an academic or esoteric discussion to a call for action." The framework is shown below.

Mitchell explains, "The Smart City Framework ... describes a potential process that will help key stakeholders and city/community participants 1) understand how cities operate, 2) define city objectives and stakeholder roles, and 3) understand the role of ICT within physical city assets." I agree with Mitchell that all stakeholders must be involved in smart city initiatives. As I wrote in Part 2 of this series, the only way to move forward is to embrace public/private partnerships that benefit both sectors." Terry Kirby agrees with that position. He writes, "When it comes to achieving the high-tech, sustainable, and smart cities of the future, there is one word that sums up the pathway to success: partnership." ["Getting smart cities connected," The Guardian, 2012] He continues:

"Imaginative and collaborative partnerships between local authorities, utilities, universities and the private sector – whether it is bus companies or software providers – are the defining characteristics of 'smart thinking', according to leading figures in cities around UK and Europe. All agree that so-called 'smartness' – which at its most basic level is about using new technology to improve lives – is necessary to adapt to the demands of urban growth. ... These kind of partnerships can range from multi-agency infrastructure ventures aimed at transforming the lives of millions, to simple projects improving digital access for everyday users of public services. They include new ways of using mobile phones and smartcards to pay for a wide range of goods and services, to schemes designed to recycle waste water for heating."

The editors at Scientific American conclude:

"The most hopeful impact of city life may be its effect on the mind. Humans are social animals; we draw stimulation from other minds close at hand. Plato and Socrates both lived in fifth-century b.c. Athens, a city-state. Galileo and Michelangelo lived in Renaissance Florence. Steve Jobs and Steve Wozniak grew up in a western U.S. conurbation that includes Silicon Valley. The young, agile minds at work on the next Big Thing are probably tweeting—they live, as author William Gibson points out, ... in a kind of digital meta city. Chances are, they are living in a physical city, too. Technology is reshaping city life and making it more intellectually productive, but it will not soon replace the easy interchange of ideas that comes from casual proximity, the cornerstone of city life."

While some pundits believe that smart city initiatives may drain city centers of their vitality, I agree with the editors at Scientific American that making cities more livable will actually increase the vitality of cities and make urbanization a boon rather than a bane to mankind. Gerd Leonhard, chief executive of the business thinktank The Futures Agency, agrees. He told Jemima Kiss, that "the more digitised our lives become, the more we will value real experiences. 'The landscape of the cities of the future will be a huge place to do the things that don't work in digital form – food, culture, contemplation. Digital tools drive us to want to have the actual experience much more than before.'" ["City design: A digital revolution," The Guardian, 2012] The thing I appreciate most about the smart cities movement is its optimism. There are enough Cassandras in the world warning us of impending doom. Optimists bring about progress and, as the IBM website states, progress is the watchword.

Big Data: The Beginning of an Era

"For all the change we've experienced," writes Adam Frank, "the most profound transformation of the digital era is really just getting started. Welcome to the era of Big Data." ["Big Data Is The Steam Engine Of Our Time," New Hampshire Public Radio, 13 April 2013] He continues:

"Ultimately, the promise of Big Data is the ability to understand (and control) a seemingly chaotic world on levels never before imagined. The dangers of Big Data stem from that very same promise. Its impact on society will be akin to the transformative effect of past technological revolutions."

Although I admit that the devil is in the details when it comes to Big Data, at the very highest level of abstraction, Big Data holds remarkable potential for helping to shape the world. This potential is eloquently discussed by photographer Rick Smolan in the following video.

If Smolan is correct, and we are only in the "caveman era of Big Data," you can understand why so much hype is being made about the subject. I like the description of Big Data that Marissa Mayer provided to Smolan. She said that Big Data was "the planet developing a nervous system." Just as the steam engine was the catalyst for the industrial revolution, Frank believes that Big Data (more specifically, the analysis of Big Data) is likely to spur a new data-driven revolution. He concludes:

"I believe there is something real and powerful happening in the Big Data revolution. It's more than just a fad. It's the next link in the long chain connecting culture and technology to human history. Now Big Data — seen and unseen — is hitting us in all corners of our lives, from the price of things to traffic patterns to who our social networks think we befriend. Through new fields like data science and network theory, Big Data will not only change the world we move through as individuals, it will change the world we imagine through science. Like it or not, Big Data will only get bigger (and bigger)."

Gartner analysts believe that 2013 could be the year that really launches the Big Data revolution -- at least in the business world. Earlier this year Gartner "conducted a global survey of firms and found that 42 percent of respondents had invested in big data technology, or were planning to do so within a year." ["Gartner: 2013 is the year of Big Data," by Antony Savvas, ComputerWorld, 12 March 2013] Paul Kent agrees that 2013 will likely be a watershed period in the deployment of Big Data technologies. In January, he made a five predictions about where he thought the Big Data sector was heading. ["Five big data predictions for 2013," SAS Voices, 23 January 2013] They were:

1. Streaming data from gadgets, cars and other devices will become an even bigger and more important data source.
2. Social data will be used to make important business and policy decisions, not just for marketing and sharing information with friends
3. The industry will better distinguish between big data BI and big data analytics. Neither is better than the other; but, companies will need to understand which is best suited for their business.
4. A Hadoop cluster will become considered a core element of a company’s 'analytics platform.'
5. NoSQL people will acknowledge the utility of a general purpose table-oriented query language, and SQL people will agree that relaxing some tenets of the relation model can bring huge advantages to other dimensions of data management problems.

When you talk about creating a "nervous system" for the planet, Kent's first prediction is the one that is most profound. It involves the so-called Internet of Things that will primarily involve machine-to-machine communication and networks. As I noted earlier, however, that "nervous system" will most likely take decades to develop into something truly revolutionary. In the meantime, the business world will continue to test the envelope of possibilities created by Big Data. Because we are at genesis of the Big Data era, Doug Henschen notes that "Big Data project leaders still hunger for some key technology ingredients." ["5 Big Wishes For Big Data Deployments," InformationWeek, 22 April 2013] He writes:

"If you've even experimented with building big-data applications or analyses, you're probably acutely aware that the domain has its share of missing ingredients. We've boiled it down to five top wants on the big-data wish list, starting with SQL (or at least SQL-like) analysis options and shortcuts to deployment and advanced analytics and finishing with real-time and network analysis options. The good news is that people and, in some cases, entire communities, are working on these problems. ... The whole point of gathering up and making use of big data is to come up with predictions and other advanced analytics that can trigger better-informed business decisions. But with the shortage of data-savvy talent in the world, companies are looking for an easier way to support sophisticated analyses. Machine learning is one technique that many vendors and companies are investigating because it relies on data and computer power, rather than human expertise, to spot customer behaviors and other patterns hidden in data."

The mention of machine learning is a good segue into Henschen's first wish: SQL Analysis at Big-Data Scale. He writes:

"You could compile a massive data set just by gathering all the stories and reports that have been written about the shortage of big-data talent. The most acute need is for data scientist types who know data and who also know how to write custom code, MapReduce jobs, and algorithms to gain insights from big data. But what if SQL-savvy professionals schooled in relational databases and business intelligence (BI) and analytics tools could do more of the heavy lifting? There are many more SQL professionals out there than there are data scientists, and most SQL pros would be eager to expand their career potential. There's a big push to deliver SQL-analysis capabilities on top of Hadoop, and the talent shortage is just one reason. The second reason for the trend is that Apache Hive, Hadoop's incumbent data warehousing infrastructure, offers a limited subset of SQL-like query capabilities and suffers from slow performance tied to behind-the-scenes MapReduce processing."

To learn more about the requirement for (and shortage of) data scientists, read my posts entitled Big Data Requires Big Talent, Part 1 and Part 2 and, more recently, The Search for Data Scientists. Henschen's second wish is for "simplified deployment and management." He writes:

"There's no shortage of efforts to simplify the deployment and management of big-data platforms including Hadoop and NoSQL databases. It seems each and every software update brings new management features and new built-in capabilities. ... We haven't heard a lot of complaining about the hardware-related challenges of building out Hadoop clusters. Nonetheless, EMC, IBM, Oracle and Teradata insist their released and pending Hadoop appliances make deployment faster and easier than the build-it-yourself approach. The cost of commodity hardware might be alluring, but Oracle, for one, says its appliance costs less less than build-it-yourself deployments when taking into account the price of individual components, time saved on provisioning and tuning the system, and support and upgrade efforts. Oracle's appliance includes pre-configured, ready-to-run versions of Cloudera software and Oracle's NoSQL database. The real messiness and complication of managing Hadoop usually involves the software, not hardware configuration."

Some businesses have been reluctant to jump on the Big Data bandwagon because they have been burned previously when buying expensive information technology hardware and software. With many solutions now to moving to the cloud, much of that concern can be eliminated. Nevertheless, their caution is understandable. Henschen's third wish is for "easier paths to advanced analytics." He explains:

"Developing algorithms and predictive models is work that has to be carried out by hard-to-find, expensive data scientists. Or is it? Scarcity of talent is one reason big-data, analytics and business intelligence vendors are developing machine-learning approaches. Proven in applications including optical character recognition, spam filtering and computer security threat detection, machine learning uses learning algorithms that are trained by the data itself. If you show the algorithm thousands or tens of thousands of examples of scanned text characters, unsolicited email messages, or virus bots and malware, it can reliably find more examples. The same approach can be applied to spotting customers who are ready to churn or jet engines that are about to fail. With machine learning, trained models also can continue to learn from new data."

At Enterra Solutions, we are big believers in machine learning. And our Cognitive Reasoning Platform^TM makes it easier for business executives to conduct Big Data analytics by automating human/computer interactions. Henschen's fourth wish involves "real-time analysis options." He writes:

"Another item on the big-data analytics wish list is real-time performance. Two startup vendors going after this opportunity are marketing analytics vendor Causata and real-time Hadoop-analysis vendor HStreaming. For Causata, 'real time' means making decisions in under 50 milliseconds. You need that kind of speed to change content, banner ads and marketing offers while your customers are still active on websites and mobile devices."

Although real-time performance is necessary in some situations, information latency is not a problem for all situations in which Big Data can be helpful. Henschen's final wish is for "network insight." He writes:

"Social networks are contributing to the scale and variability of big data. The social networks themselves use graph databases and analysis tools to uncover the web of user relationships by studying 'nodes' -- representing people, companies, locations and so on -- and edges, the often-complex relationships among those nodes. ... It's not the stampede of solutions you see around Hadoop, but there's clearly growing interest in graph analysis."

Even before solutions are available, companies are preparing for opportunities that are likely to emerge. Antony Savvas reports, "In anticipation of big data opportunities, said Gartner, organisations across industries are provisionally collecting and storing a burgeoning amount of operational, public, commercial and social data. In most industries combining these sources with existing underutilised 'dark data', such as emails, multimedia and other enterprise content, represents the most immediate opportunity to transform businesses." We really won't know what lies along the road down which Big Data is about to take us. Most analysts believe that the world will function better because we will have greater understanding. For sure, there will be challenges along the way; but, I believe the journey we are beginning is going to be an exciting one.