Management Consultant
Consumer packaged goods (CPG) are feeling tremendous pressure in 2019 as the industry continues to undergo seismic changes. Increased demand volatility and shorter lead times from retailers have become major concerns, hurting service and inventory levels. Under Pressure, CPG Companies Look to Digital.
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Uber-like on-demand fulfillment platforms for supply chain and and logistics services are rapidly emerging. For companies feeling the pressure to meet rising customer expectations while keeping costs down, uberized supply chains could bring much-needed relief.
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Computer vision is the lynchpin of the current AI/machine learning (ML) renaissance. In 2013, deep learning based vision solutions crossed a historic milestone of achieving human level accuracy.
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2013 was a watershed year for Industry 4.0, moving from the concept pages to becoming strategic pillars of investment across governments and businesses.
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While Augmented Reality (AR) is gaining significant attention as one of the Industry 4.0 technologies that will revolutionize supply chain, we believe it is important to look beyond the hype and qualify the true potential and challenges of AI/VR in supply chain.
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Demands on supply chains are ever increasing as companies vie to deliver more personalized products, with faster lead time, at a lower cost. Further, unexpected execution conditions continually disrupt operational performance.
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Even today’s most sophisticated supply chains still try to predict what will happen, then optimize performance against plan. The problem is, the world is not predictable.
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Digital transformation?? Oh, not again! Everything seems to be a digital transformation today and there’s nothing left under the sun that hasn’t been written about such disruptive change. We felt the need to demystify digital transformation and separate the truths from the misconceptions based on our hands-on experience:
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利用机器学习能力，来改善并自动化业务流程，人工智能将在不远的未来释放出巨大的潜力。 作者：Michael Hu，科尔尼全球合伙人 | 翻译校订：李健，科尔尼全球合伙人 人工智能（AI）和机器学习开始迅速地被消费者所接受，并在日常生活中随处可见。仅在过去三年里，亚马逊就售出了1000万台Echo智能音箱，而苹果新推出的iPhoneX也自带一款人工智能芯片，专门用于处理面部识别和语音命令等任务。
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While AI and machine learning has made rapid progress in consumer facing applications such as Amazon Alexa, playing Go, and making art, enterprise AI and automation deployment is still emerging and uneven. We discuss key facts and implications on enterprise AI.
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AI is the darling of the moment and the corporate meme-stream. So much so, it’s forcing some CFOs into tough discussions with executive teams that are overly anxious to gamble with current assets in hopes of gaining future competitive advantages. How can companies avoid overspending in AI?
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Artificial intelligence (AI) is a fast-moving technology with a long road ahead of it. For all its surrounding hype, AI is still in its infancy.
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I held a podcast this week with Supply Chain Management Review on the topic of AI in Planning.
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In our recent article “US E-Commerce Trends and Impact of Logistics”, we assess the current state of the last mile fulfillment market and key supply side drivers of eCommerce.
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AI progress has been uneven in the past 5 decades, with spurts of breakthrough followed by “winter-like” stagnation. Barriers like technology cost, organization capability and ineffective policies held back AI from going mainstream.
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