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More Resources, More Problems

Danielle Beurteaux

This is the second of a two-part series on resource volatility. As noted in the first post, globalization has created an environment of resource volatility. This post, with numbers 11 through 20 on the list, describes resources that are more stable than the previous 10. However, that doesn’t mean there isn’t turmoil, whether that’s environmental concerns in Indonesia’s palm oil production industry, or community organization for water rights in Chile. And, of course, whatever China does, the markets follow.

Top resources and trends

11. Natural Gas

According to the International Energy Agency, most natural gas comes from Russia, the United States, Canada, Qatar, and Iran, and the countries that use the most are the U.S., Russia, China, and Iran. There are sufficient reserves of natural gas, again according to the IEA’s projections, that should last past the year 2040. Liquefied natural gas, which is produced mostly by Qatar, with Australia set to overtake Malaysia for second place, has had a flat market recently. There isn’t the demand to keep up with increased production, so liquefied natural gas producers are looking for new markets, like cruise lines, to grow demand.

12. Tin

Most of the world’s tin comes from China and Indonesia. The tin market tanked last year because of less demand and lots of tin, although it did rally in July and then improve earlier this year, mostly because Indonesia is exporting less and easing the flood of tin on the market.

13. Gold

It seems like everyone’s crazy for gold right now. The precious metal is often perceived as a safer investment than other asset classes, and it’s up 20% this year. Famed investor George Soros just bought $264 million worth of shares in Barrick Gold. The Toronto-based gold-mining company is the world’s largest. Gold prices bumped down a bit while the market waited on the Federal Reserve’s meeting minutes, but some are saying gold will soon recover – and then some.

14. Nickel

Russia, Canada, and New Caledonia are the largest producers of nickel. Most is used to make stainless steel. Like several other commodities we’ve examined, there is more production than demand of nickel at the moment, which has led to depressed prices. China is a big consumer of nickel for stainless steel, and the country is using less because of a slowing real estate market.

15. Beef

The global demand for beef is up, but production is down due to a variety of factors. One is Australia’s decreased production due to drought conditions, which will mean 300,000 tons less beef for export this year. As Australia is a favored trading partner of the U.S., that will affect the American beef market. A recent study from Radobank predicts that China will increase live cattle imports for domestic processing, and Brazil will enter the U.S. market as well.

16. Wheat

It’s a good year for wheat. North American wheat production is doing well, although levels are down from the previous year, with five percent less planted in the U.S. and six percent less in Canada. According to the most recent USDA World Agricultural Supply and Demand Estimates report, total U.S. wheat supplies and use are up six percent and seven percent, respectively. Globally, the report projects a two percent increase in wheat supplies, and consumption will increase, too.

17. Iron Ore

Earlier this year, the iron ore market jumped, reportedly because of the Chinese government’s moves to help along the country’s economy. Things have settled down since then, with recent trading sending the per ton price downwards 22.9% from its high in April, which seems to be due to China’s increased crude steel production and also the government’s stopping speculative trading. They’ve also committed to transportation infrastructure projects, but there is still too much iron ore compared to demand.

18. Copper

As with iron ore, China’s announcement that it would be investing in transportation infrastructure affected the price of copper recently. This is likely a welcome piece of news, as copper had been trading at the lowest levels since March 2009. Output and demand are both projected for small increases this year. Chile has the largest open pit mine and the largest global reserves of copper, but it’s been facing difficulties in recent years including lack of water, which is essential for mining, and local community resistance.

19. Palm oil

Palm oil is a global big business to the tune of $50 billion, which is projected to increase to $88 billion by 2020. It’s in almost everything these days because it’s inexpensive, stable, and can be used for many applications. (It’s not always listed on ingredient labels as palm oil).  Most is produced in Malaysia. It’s also a bête noire of environmentalists – it’s linked to deforestation, the recent massive forest fires in Indonesia which were set, it’s thought, to clear land for plantations, and lost habitat for orangutans and increased worries about their extinction.

20. Aluminum

Aluminum rose overall in 2015, but took a dive in the last few months of the year. Market-watchers are hoping that China’s announcement that it will reduce aluminum output will help energize the market once oversupply is balanced. But one of the world’s biggest producers, Alcoa, is reorganizing, which could be an indication that the company is preparing for an era of depressed prices, despite continued healthy demand.

Digital transformation is affecting different industries at different speeds and on different scales. IDC reveals how in The Internet of Things and Digital Transformation: A Tale of Four Industries.

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Live Product Innovation, Part 2: IoT, Big Data, and Smart Connected Products

John McNiff

In Part 1 of this series, we looked at how in-memory computing affects live product innovation. In Part 2, we explore the impact of the Internet of Things (IoT) and Big Data on smart connected products. In Part 3, we’ll approach the topic from the perspective of process industries.

Live engineering? Live product innovation? Live R&D?

To some people, these concepts sound implausible. When you talk about individualized product launches with lifecycles of days or weeks, people in industries like aerospace and defense (A&D) look askance.

But today, most industries—not just consumer-driven ones—need timely insights and the ability to respond quickly. Even A&D manufacturers want to understand the impact of changes before they continue with designs that could be difficult to make at the right quantity or prone to problems in the field.

The Internet of Everything?

Internet of Things (IoT) technologies promise to give manufacturers these insights. But there’s still a lot of confusion around IoT. Some people think it is about connected appliances; others think it’s just a rebranded “shop floor to top floor.”

The better way to think about IoT is from the perspective of data: We want to get data from the connected “thing.” If you’re the manufacturer, that thing is a product. If you buy the product and sell it to an end customer, that thing is an asset. If you’re the end customer, that thing is a fleet. Each stakeholder wants different data in different volumes for different reasons.

It’s also important to remember that the Internet has existed for far longer than IoT.

There’s a huge amount of non-IoT data that can offer useful insights. Point-of-sale data, news feeds, and market insights from social channels are all valuable. And think about how much infrastructure is now connected in “smart” cities. So in addition to products, assets, and fleets, there are also people, markets, and infrastructure. Big Data is everywhere, and it should influence what you release and when.

New data, new processes

It has been said that data in the 21st century is like oil in the 18th century: an immense, valuable, yet untapped asset. But if data is the new oil, then do we need a new refinery? The answer is yes.

On top of business data, we now have a plethora of information sources outside our company walls. Ownership of, and access to, this data is becoming complex. Manufacturers collecting data about equipment at customer sites, for example, may want to sell that data to customers as an add-on service. But those customers are likely using equipment from multiple manufacturers, and they likely have their own unique uses for the information.

So the new information refinery needs to capture information from everywhere and turn it into something that has meaning for the end user. It needs to leverage data science and machine learning to remove the noise and add insight and intelligence. It also needs to be an open platform to gather information from all six sources (products, assets, fleets, people, markets, infrastructure).

And wouldn’t it be great if the data refinery ran on the same platform as your business processes, so that you could sense, respond, and act to achieve your business goals?

Digital product innovation platform

If you start with the concept of a smart connected product, the data refinery — the digital product innovation platform — has five requirements:

  1. Systems design — Manufacturers need to design across disciplines in a systems approach. Mechanical, mechatronic, electrical, electronics, and software all need to be supported, with modeling capabilities that cover physical, functional, and logical structures.
  1. Requirements-linked platform design — Designers need to think about where and how to embed sensors and intelligence to match functional requirements. This will need to be forward-thinking to cover unforeseen methods of machine-to-machine interactions. In a world of performance-based contracts, it will be important to minimize the impact of design changes as innovation opportunities grow.
  1. Instant impact and insight environment — The platform must support fully traceable requirements throughout the lifecycle, from design concept to asset performance.
  1. Product-based enterprise processes — The platform needs to share model-based product data visually — through electrical CAD, electronic CAD, 3D, and software functions — to the people who need it. This isn’t new, but what’s different is that the platform can’t wait for complex integrations between systems. Think about software-enabled innovation or virtual inventory made possible by on-demand 3D printing. Production is almost real time, so design will have to be as well.
  1. Product and thing network — A complex, cross-domain design process involves a growing number of partners. That calls for a product network to allow for secure collaboration across functions and outside the company walls. Instead of every partner having its own portal for product data, the product network would store digital twins and allow instant sharing of asset intelligence.

If the network is connected to the digital product innovation platform, you can control the lifecycle both internally and externally — and take the product right into the service and maintenance domain. You can then provide field information directly from the assets back to design to inform what to update, and when. Add over-the-air software compatibility checks and updates, and discrete manufacturers can achieve a true live engineering environment.

Sound like a dream? It’s coming sooner than you think.

Learn more about supply chain innovations at SAP.com or follow us on @SCMatSAP for the latest news.

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John McNiff

About John McNiff

John McNiff is the Vice President of Solution Management for the R&D/Engineering line-of-business business unit at SAP. John has held a number of sales and business development roles at SAP, focused on the manufacturing and engineering topics.

Leveraging Contract Manufacturing Organizations In Life Sciences

Joseph Miles

The 21st century has been a remarkable and volatile time in the life sciences industry.

The onset of the patent cliff in the pharmaceutical and biotechnology sectors set forth a variety of strategies that have quite literally changed the face of the industry. Organizations, in an attempt to recoup the lost revenue and margin from patent expirations on blockbuster products, began acquiring companies at a pace that has never been seen before. What has emerged is a new and more focused industry. Non-strategic divisions where sold off in divestitures and focus areas were expanded with acquisitions that grew their pipeline, markets, and revenues.

In spite of all the M&A activity, the industry continues to explore new ways of improving their operating margins.   Outsourcing of operational processes has continued to increase in importance across the industry as organizations look for ways of reducing operational overhead.

Long used in the medical device and equipment sector, pharmaceutical and biotechnology companies have traditionally had more of an insource approach to manufacturing but that continued to change. Drug companies are not only leveraging contract manufacturing organizations (CMO) for less complex small molecule and active pharmaceutical ingredient production (API) but are now leveraging CMOs for more complex, large molecule products in spite of that manufacturing complexity.

This strategy is not without risk as organizations understand that you can outsource the process but you cannot outsource the accountability for that process. This dramatic transformation of business models, processes, and work strategies are focused on returning to the levels of profitability that had been accomplished earlier in their history.

If that isn’t complicated enough, the industry continues to see the emergence of global regulations that make manufacturing a complicated process to outsource. Global serialization, outlined in my previous blog, “The Rapidly Changing World of Serialization in Life Sciences,” now requires drug manufacturers to include a unique serial number on every vial of product produced. That serial number coordination with the CMO is challenging and is further complicated as the drug manufacturer is required to submit the information to global regulatory agencies who want to track the serial numbers to ensure the integrity of the product and, ultimately, the safety of the patient.

My team is very passionate about our ability to help global pharmaceutical, biotechnology, and medical device companies during these very challenging times. Life sciences companies should consider leveraging a cloud-based approach to direct materials that supports all aspects of direct material procurement. This should include processes to support supplier audits, approved vendor lists, purchase order releases, and blanket purchase orders. The cloud helps organizations reduce their capital expenses while also simplifying the IT support to enable the process.

Life sciences companies should also consider aggressively leveraging CMOs for the manufacturing of their products, even in this highly regulated industry. This would include the medical device and equipment segments that have leveraged CMO strategies for many decades but also drug companies inclusive of the serialized information.

Organizations are not only able to provide the CMO with all of the work orders, manufacturing instructions, routings, and standard operating procedures for regulated manufacturing, but they also have the ability to manage and generate all serial number information that would be applied to every vial of pharmaceutical and/or biotechnology product during the manufacturing process. This information can be delivered through a network that further simplifies the process and improves operational efficiencies, ultimately reducing the total cost of ownership to support the process.

Life sciences companies should not just be content with leveraging the cloud to enable the direct material and contract manufacturing processes for small and large molecule compounds, including serial number support, to meet global regulations. The network can be exploited further in the area of operational quality and production tracking. Manufacturing data, batch reports, quality information, and operational KPIs can be shared across the network to ensure the manufacturers have full visibility and transparency around the outsourced processes. This is highly strategic and reflects the underlying complexity of enabling outsourced manufacturing across all segments of the life sciences industry.

For more on digitalization in the life sciences industry, see Special Compliance Aspects And Quick Wins In The Life Sciences Industry.

 

 

 

 

 

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Joseph Miles

About Joseph Miles

Joseph Miles is Global Vice President pf Life Sciences at SAP. He is passionate about helping organizations improve outcomes for their patients and enable innovation across the health sciences value chain.

How Emotionally Aware Computing Can Bring Happiness to Your Organization

Christopher Koch


Do you feel me?

Just as once-novel voice recognition technology is now a ubiquitous part of human–machine relationships, so too could mood recognition technology (aka “affective computing”) soon pervade digital interactions.

Through the application of machine learning, Big Data inputs, image recognition, sensors, and in some cases robotics, artificially intelligent systems hunt for affective clues: widened eyes, quickened speech, and crossed arms, as well as heart rate or skin changes.




Emotions are big business

The global affective computing market is estimated to grow from just over US$9.3 billion a year in 2015 to more than $42.5 billion by 2020.

Source: “Affective Computing Market 2015 – Technology, Software, Hardware, Vertical, & Regional Forecasts to 2020 for the $42 Billion Industry” (Research and Markets, 2015)

Customer experience is the sweet spot

Forrester found that emotion was the number-one factor in determining customer loyalty in 17 out of the 18 industries it surveyed – far more important than the ease or effectiveness of customers’ interactions with a company.


Source: “You Can’t Afford to Overlook Your Customers’ Emotional Experience” (Forrester, 2015)


Humana gets an emotional clue

Source: “Artificial Intelligence Helps Humana Avoid Call Center Meltdowns” (The Wall Street Journal, October 27, 2016)

Insurer Humana uses artificial intelligence software that can detect conversational cues to guide call-center workers through difficult customer calls. The system recognizes that a steady rise in the pitch of a customer’s voice or instances of agent and customer talking over one another are causes for concern.

The system has led to hard results: Humana says it has seen an 28% improvement in customer satisfaction, a 63% improvement in agent engagement, and a 6% improvement in first-contact resolution.


Spread happiness across the organization

Source: “Happiness and Productivity” (University of Warwick, February 10, 2014)

Employers could monitor employee moods to make organizational adjustments that increase productivity, effectiveness, and satisfaction. Happy employees are around 12% more productive.




Walking on emotional eggshells

Whether customers and employees will be comfortable having their emotions logged and broadcast by companies is an open question. Customers may find some uses of affective computing creepy or, worse, predatory. Be sure to get their permission.


Other limiting factors

The availability of the data required to infer a person’s emotional state is still limited. Further, it can be difficult to capture all the physical cues that may be relevant to an interaction, such as facial expression, tone of voice, or posture.



Get a head start


Discover the data

Companies should determine what inferences about mental states they want the system to make and how accurately those inferences can be made using the inputs available.


Work with IT

Involve IT and engineering groups to figure out the challenges of integrating with existing systems for collecting, assimilating, and analyzing large volumes of emotional data.


Consider the complexity

Some emotions may be more difficult to discern or respond to. Context is also key. An emotionally aware machine would need to respond differently to frustration in a user in an educational setting than to frustration in a user in a vehicle.

 


 

download arrowTo learn more about how affective computing can help your organization, read the feature story Empathy: The Killer App for Artificial Intelligence.


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About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

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In An Agile Environment, Revenue Models Are Flexible Too

Todd Wasserman

In 2012, Dollar Shave Club burst on the scene with a cheeky viral video that won praise for its creativity and marketing acumen. Less heralded at the time was the startup’s pricing model, which swapped traditional retail for subscriptions.

For as low as $1 a month (for five two-bladed cartridges), consumers got a package in the mail that saved them a trip to the pharmacy or grocery store. Dollar Shave Club received the ultimate vindication for the idea in 2016 when Unilever purchased the company for $1 billion.

As that example shows, new technology creates the possibility for new pricing models that can disrupt existing industries. The same phenomenon has occurred in software, in which the cloud and Web-based interfaces have ushered in Software as a Service (SaaS), which charges users on a monthly basis, like a utility, instead of the typical purchase-and-later-upgrade model.

Pricing, in other words, is a variable that can be used to disrupt industries. Other options include usage-based pricing and freemium.

Products as services, services as products

There are basically two ways that businesses can use pricing to disrupt the status quo: Turn products into services and turn services into products. Dollar Shave Club and SaaS are two examples of turning products into services.

Others include Amazon’s Dash, a bare-bones Internet of Things device that lets consumers reorder items ranging from Campbell’s Soup to Play-Doh. Another example is Rent the Runway, which rents high-end fashion items for a weekend rather than selling the items. Trunk Club offers a twist on this by sending items picked out by a stylist to users every month. Users pay for what they want and send back the rest.

The other option is productizing a service. Restaurant franchising is based on this model. While the restaurant offers food service to consumers, for entrepreneurs the franchise offers guidance and brand equity that can be condensed into a product format. For instance, a global HR firm called Littler has productized its offerings with Littler CaseSmart-Charges, which is designed for in-house attorneys and features software, project management tools, and access to flextime attorneys.

As that example shows, technology offers opportunities to try new revenue models. Another example is APIs, which have become a large source of revenue for companies. The monetization of APIs is often viewed as a side business that encompasses a wholly different pricing model that’s often engineered to create huge user bases with volume discounts.

Not a new idea

Though technology has opened up new vistas for businesses seeking alternate pricing models, Rajkumar Venkatesan, a marketing professor at University of Virginia’s Darden School of Business, points out that this isn’t necessarily a new idea. For instance, King Gillette made his fortune in the early part of the 20th Century by realizing that a cheap shaving device would pave the way for a recurring revenue stream via replacement razor blades.

“The new variation was the Keurig,” said Venkatesan, referring to the coffee machine that relies on replaceable cartridges. “It has started becoming more prevalent in the last 10 years, but the fundamental model has been there.” For businesses, this can be an attractive model not only for the recurring revenue but also for the ability to cross-sell new goods to existing customers, Venkatesan said.

Another benefit to a subscription model is that it can also supply first-party data that companies can use to better understand and market to their customers. Some believe that Dollar Shave Club’s close relationship with its young male user base was one reason for Unilever’s purchase, for instance. In such a cut-throat market, such relationships can fetch a high price.

To learn more about how you can monetize disruption, watch this video overview of the new SAP Hybris Revenue Cloud.

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