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Recognizing the Building Blocks of Innovation

Paul Hobcraft

I think of the Gartner Hype Cycle here as we have gone through each of the stages of recognition of the application and the learning from this; we have the innovation triggers first, then a peak or inflated expectations, followed by troughs of disillusionment and finally by the slope of enlightenment, to give a new plateau of productivity.

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We are facing growing complexity and more formidable challenges- time to think about Business Ecosystems

Ecosystems4Innovating

Solutions required are becoming highly dependent on a more dependent type of complementary innovation: open, collaborative, sharing, and exchanging collectively around a given concept to take it to market. Businesses need to find new competitive battle zones as they exhaust the traditional ones.

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Parkinson’s Law and the Peter Principle – are they relevant to innovation?

Idea to Value

In a competitive context, incompetence does not allow the mediocre to stay afloat for long and meritocracy is valuable and fair. There are assessments for nearly everything and big data will probably provide more on the less tangible things like creativity and likeability.

Report 148
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Top 5 Myths About Data Analytics You Should Stop Believing

Acuvate

Data Analytics in Business. According to Stastia , the global big data market is forecasted to grow to 103 billion U.S. While data analytics helps companies make informed decisions and gain a competitive edge, misconceptions surrounding it can hamper its impact. But you cannot be further from the truth.

Data 80
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Smart Factory 101 A Data, AI, Cloud and Workforce Revolution in the Making

Acuvate

With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity. Combined with machine learning and advanced analytics, AI allows smart factories to evaluate data, forecast outcomes and failures, control downtimes and maximize output.

Data 52
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Smart Factory 101 A Data, AI, Cloud and Workforce Revolution in the Making

Acuvate

With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity. Combined with machine learning and advanced analytics, AI allows smart factories to evaluate data, forecast outcomes and failures, control downtimes and maximize output.

Data 52
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Barriers to innovation, the cause and effect.

Paul Hobcraft

The need to respond to unexpected business attacks, changing competitive positions, and the inability to ramp up fast enough to take advantage of consumers’ rising expectations risks a real-time-to-market issue. Here I provide six root cause-and-effect barriers that stifle innovation that need addressing. The pressure of pace and time.