Supply Chain Management
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Author Archives: Teddy Nee
To Woo Apple, Foxconn Bets $3.5 Billion on Sharp
The Apple iPhone transformed the technology industry by popularizing the smartphone and blazing a path to a mobile future. But to do it, the company needed an important ally: a penny-pinching Taiwan-based factory operator named Foxconn.
Employing hundreds of thousands of workers at vast facilities in mainland China, Foxconn figured out a way to assemble the iPhone at a cost low enough that middle-class Americans could afford it. The business offered low profit margins, but the work buffed Foxconn’s financial results and cemented its status as the world’s largest maker of hardware for companies like Apple and Sony.
Those relationships are now shifting — and Foxconn is betting heavily to keep up.
On Wednesday, Foxconn said it had struck a deal to acquire control of the Japanese screen maker Sharp for $3.5 billion, after weeks of negotiations and high-profile setbacks.
The deal, for a 66 percent stake in Sharp, is intended to make Foxconn a more attractive partner for Apple. The American technology company uses Sharp screens, which could give Foxconn added leverage in dealings between the two.
The screen is an especially lucrative piece of the smartphone, costing as much as $54 each, according to estimates by the research firm IHS. Sharp provides roughly 25 percent of the iPhone displays, IHS said.
Still, the Sharp purchase will saddle Foxconn with an ailing business that will take considerable money and effort to turn around, some analysts say. Reflecting those problems, the purchase price is $2 billion lower than a deal the two sides struck just last month, after Sharp disclosed the potential for costly problems — nearly $3 billion in potential liabilities — down the road.
But Apple has been diversifying its supply chain, giving some production contracts to other assemblers and component makers. And Foxconn is grappling with China’s rising labor costs and a slowdown in the global smartphone market.
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How to Use Big Data to Enhance Employee Performance
Big Data has been one of the most significant and influential aspects of the Information Age as it relates to the enterprise world. Essentially, Big Data is the massive collection, indexing, mining, and implementation of information that emanates from just about any activity that can be monitored and managed electronically. Some of the uses of Big Data include: marketing intelligence, sales automation, strategizing, productivity improvement, and efficient management.
Enhancement of the workforce is one of the exciting and meaningful benefits of Big Data for the business sphere. Recently, human resource managers and analysts have been researching the implementation of Big Data as it relates to employees, and the following trends have emerged:
Employee Intelligence
For many decades, companies and organizations have tried various methods to gain knowledge about what their employees are really like. The productivity that workers can contribute to their employers is based on personal needs as they are balanced against the performance of their duties. With Big Data solutions, both personal needs and performance can be diluted into metrics for efficient analysis.
Modern workplace analytics originates from tracking employee records as well as metrics on their performance, interactions and collaboration. The idea is to focus on the right metrics to create a climate of positive engagement.
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Big (and Smart) Data for Digital Globalization
Data is all around us whether we use it or we are part of it. More than another trend, data is the way to move with agility and make every step and achievement tangible for those who do not see or believe it. One of the most transformational and accelerating factors of digitization is precisely how data is considered, leveraged, valued, and distilled. As data mining is not new it has become more than just a back office type of activity. It is all about turning facts into more than facts, figures into more than figures, and content into more than content.
For digital globalization practitioners and leaders, data shines like a glittering prize. That is why they face similar challenges to all business leaders when it comes to making the most of data. With the world to conquer and a number of diverse audiences to engage, they have to transform big data into smart data to focus on what enables making–and avoids breaking–the digital experiences local customers require. Specifically they must pin down the right data at the right time in the content supply chain to convert it into reliable indicators and valuable assets in the long run. In addition, due diligence is required to cover the cost and efforts of funneling, acquiring, and maintaining data. While the amount, the nature, and the scope of data depend on digital globalization targets and priorities, several categories may help establish a good base line to identify smart data and agree on a starting point for global expansion.
- Customer understanding data-Ranging from general (e.g. census) to segmentation data these data enable you to bear in mind what customers do at all times as prospects, decisions, buyers, or users.
- Usage data-As typical performance data this remains crucial in any proper mix of smart data for digital globalization.
- Content effectiveness data-Capturing and measuring the real impact of content on experiences is tricky and must reflect the nature and ecosystem of the content.
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Walmart and Target are refusing to surrender to Amazon
While many public companies focus their attention on embellishing their quarterly results, Amazon has always taken the long view.
The online retailer leader has invested heavily in infrastructure including a nationwide network of warehouses, robots which help ship orders, and even predictive technology that helps the company know what a customer plans to buy before he or she orders it.
Amazon even has a pioneering deal with the United States Postal Service which allows for Sunday delivery in some markets.
All of this has not come cheap, and it has hurt Amazon’s short-term profitability in some quarters, but it has helped the company build a strong competitive advantage over its chief rivals Wal-Mart and Target.
Those two physical retailers are struggling to change their supply chains to meet the needs of individual digital customers rather than stores. That’s a radical switch that requires major changes to how both brick-and-mortar chains operate.
But if either Wal-Mart or Target can hope to compete with Amazon, they have to recreate the digital leader’s ability to ship millions of products in a two-day window efficiently. Both companies seem to at least understand the problem and are taking steps to catch up.
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Managing risk in the digital supply chain
You may be aware of risks and problems in your own business, but increasingly it’s possible to be exposed to issues by other organizations that you deal with, particularly if you’re buying in IT services.
How can enterprises deal with these threats and ensure that their data and that of their customers is kept safe at all stages of the supply chain? We spoke to Dean Coleman, head of service delivery at service management and support specialist Sunrise Software, to find out.
BN: How difficult is it for larger organizations to manage problems that might occur further down the supply chain?
DC: It can be quite difficult, historically most organizations have a handle on risk in terms of what’s going on in the business, financial targets and so on. But when it comes to IT risks and the supply chain providing IT they don’t have the same visibility. These days IT is everywhere and businesses depend on it so IT problems have a larger impact. The understanding of risk needs to be something that key decision makers are more aware of.
BN: Is this a particular problem when dealing with smaller companies who might not have resources in house?
DC: Yes, from the supplier side of the fence we see that smaller organizations often don’t have the skills in house to deal with security, infrastructure, and so on. They rely heavily on these services but don’t see them as a core part of their business. Because they don’t have the skills and resources they will often turn to third parties to manage these things for them. However, in some cases the third parties also don’t do a very good job, they’ll be providing reactive services rather than the proactive ones that are really needed to predict problems based on risk.
Read more at Managing risk in the digital supply chain [Q&A]
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Instagram and Pinterest are killing Gap, Abercrombie, & J. Crew
Traditional mall retailers like Gap, J. Crew, and Abercrombie & Fitch have faced declining sales in recent years.
And the problem might be signaling something even more troublesome than dowdy apparel. Instead, it is a total shift in how teen consumers think.
Young people want to purchase experiences rather than actual stuff, and when they do buy clothing or shoes they want to be able to showcase purchases on social media.
“Their entire life, if it’s not shareable, it didn’t happen,” Marcie Merriman, Generation Z expert and executive director of growth strategy and retail innovation at Ernst & Young, said to Business of Fashion. “Experiences define them much more than the products that they buy.”
The only apparel young people want is clothing that can translate into an experience on Instagram or Snapchat.
Given their limited budgets and frugal tendencies, they’re more likely to purchase lots of clothes at fast fashion retailers, like cutting-edge Zara or cheap Forever 21, so that they have ample images to share.
Read more at Instagram and Pinterest are killing Gap, Abercrombie, & J. Crew
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One step ahead: How data science and supply chain management are driving the predictive enterprise
DHL, the world’s leading logistics company, today launched its latest white paper highlighting the untapped power of data-driven insight for the supply chain. The white paper has revealed that most companies are sitting upon a goldmine of untapped supply chain data that has the ability to give organizations a competitive edge. While this wealth of supply chain data already runs the day-to-day flow of goods around the world, the white paper has revealed a small group of trailblazing companies are utilizing this data as a predictive tool for accurate forecasting.
“The predictive enterprise: Where data science meets supply chain” is a white paper by Lisa Harrington, President of the lharrington group LLC that was commissioned by DHL to identify the opportunities available to companies to anticipate and even predict the future. It encourages companies to get ahead of their business and direct their global operations accordingly.
Data mining, pattern recognition, business analytics, business intelligence and other tools are coalescing into an emerging field of supply chain data science. These new intelligent analytic capabilities are changing supply chains – from reactive operations, to proactive and ultimately predictive operating models. The implications extend far beyond just reinventing the supply chain. They will help map the blueprint for the next-generation global company – the insight-driven enterprise.
Jesse Laver, Vice President, Global Sector Development, Technology, DHL Supply Chain, said, “At DHL, we’re helping our customers get ahead of the competition by working with them to harness the wealth of data information from across their businesses, allowing us to develop smarter supply chain solutions that factor in their wider business operations. For our technology customers, we use data analytics to predict what’s going on in the supply chain, such as what products are in high demand, so we can tailor our solutions accordingly.”
While supply chain analytics technologies and tools have come a long way in the last few years, integrating them into the enterprise is still far from easy. Companies typically progress through several stages of maturity as they adopt these technologies. The descriptive supply chain stage uses information and analytics systems to capture and present data in a way that helps managers understand what is happening.
Read more at One step ahead: How data science and supply chain management are driving the predictive enterprise
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How data science and supply chain management are driving the predictive enterprise
DHL, the world’s leading logistics company, today launched its latest white paper highlighting the untapped power of data-driven insight for the supply chain. The white paper has revealed that most companies are sitting upon a goldmine of untapped supply chain data that has the ability to give organizations a competitive edge. While this wealth of supply chain data already runs the day-to-day flow of goods around the world, the white paper has revealed a small group of trailblazing companies are utilizing this data as a predictive tool for accurate forecasting.
“The predictive enterprise: Where data science meets supply chain” is a white paper by Lisa Harrington, President of the lharrington group LLC that was commissioned by DHL to identify the opportunities available to companies to anticipate and even predict the future. It encourages companies to get ahead of their business and direct their global operations accordingly.
Data mining, pattern recognition, business analytics, business intelligence and other tools are coalescing into an emerging field of supply chain data science. These new intelligent analytic capabilities are changing supply chains – from reactive operations, to proactive and ultimately predictive operating models. The implications extend far beyond just reinventing the supply chain. They will help map the blueprint for the next-generation global company – the insight-driven enterprise.
Jesse Laver, Vice President, Global Sector Development, Technology, DHL Supply Chain, said, “At DHL, we’re helping our customers get ahead of the competition by working with them to harness the wealth of data information from across their businesses, allowing us to develop smarter supply chain solutions that factor in their wider business operations. For our technology customers, we use data analytics to predict what’s going on in the supply chain, such as what products are in high demand, so we can tailor our solutions accordingly.”
Read more at One step ahead: How data science and supply chain management are driving the predictive enterprise
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How to Better Manage Supply Chain Climate Risks
Supply chains are responsible for up to four times the greenhouse gas emissions of a company’s direct operations and yet half of major companies’ key suppliers don’t provide requested climate data to their corporate customers, according to a study produced by CDP and written in partnership with BSR.
The report also gives examples of ways companies can encourage supplier performance. It says L’Oréal works with CDP to create supplier climate scorecards that can be easily understood in the purchasing department.
Additionally, Coca-Cola and Lego Group are both experimenting with incentives and training for suppliers that aim to improve climate performance. Coca-Cola, for example, encourages suppliers to implement sustainable agricultural practices, reduce material used in packaging, and reduce the carbon footprint of vending machines. Lego Group LEGO Group is hosting “innovation camps” that the report says not only identify projects to reduce CO2 emissions, they also strengthen partnerships with suppliers.
Read more at How to Better Manage Supply Chain Climate Risks
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