Paul Hobcraft

SEPTEMBER 15, 2017

I have argued in the past that innovation management needs to radically adjust and needs to be designed differently, it needs to be highly adaptive. We need to be highly adaptive and that comes from a greater technology understanding. Digital and technology matters, in its raw innovating power and its potential business impact.

Design 232

Design Technical Review Innovation System 232

etventure

AUGUST 4, 2020

Many of the most groundbreaking technologies of our time (e.g. Deep Learning) require access to huge amounts of data to reach their full potential. Many countries globally have recognized that the handling and processing of these large data sets depend heavily on the agile innovation engines of our economies – the startups.

Data 52

Data Big Data Artificial Inteligence Technical Review 52

Paul Hobcraft

MAY 6, 2018

We also know today that innovation management itself must become “fluid” in design, in adaptation so the right approach is to be constantly ‘adaptive’ and put together what is needed to tackle the challenge that needs resolution. Horizon One – keeping the lights on, managing today. Where is innovation within this?

Design 138

Design Innovation Agile System 138

Paul Hobcraft

SEPTEMBER 27, 2017

So from what I can see so far, change is highly constrained: Evolution is slow, revolution is seemingly non-existent due to narrow vested interests. Digital connections and technology platforms. Big Data, Artificial Intelligence, Analytics and Algorithms beckon hugely. Unleashing the talent, changing the cultures.

Collaboration 138

Collaboration Artificial Inteligence Technical Review Industry 138

mjvinnovation

MAY 8, 2019

It is nothing more than the phenomenon of adopting innovative tools, resources and technological services to optimize the management of the most varied industrial aspects. the emergence of tools, resources and methods for data analysis: BI and Analytics solutions to complex management methodologies and use of Big Data; .

Industry 40

Industry Big Data Technical Review Internet of things 40

hackerearth

DECEMBER 8, 2017

According to McKinsey’s , across all dimensions, the most significant differences between top growers and their peers were in data and analytics, developing products and services, and company processes, such as agile work environments, cross-functional collaboration, and colocated teams . Manage their costs.

Marketing 40

Marketing How To Big Data Data 40

ITONICS

MAY 14, 2018

Large corporations have taken steps towards being more agile and adapting to the rapid pace of digitization by improving their oftentimes long innovation processes and giving more autonomy to employees. Often, it’s due to the speed at which they can innovate and this has a lot to do with their size. Adapt or die. Germany, and India.

Company 57

Company Technical Review Software Review Innovation 57

Integrative Innovation

JANUARY 27, 2016

Hence, I gave it some thought, starting by revisting an earlier reflection: Beginning of 2013, Tim Kastelle and I identified four key issues in innovation management for the time to come. Recently, experimentation in innovation management is particularly facilitated by intinsified use of (rapid) prototyping.

Underperforming Technical Team 40

Underperforming Technical Team Big Data Innovation Technical Review 40

Linda Bernardi

JULY 24, 2017

It is due to the confluence of six factors: 1. Mega Data 2. Culture of Agility There has never been a more exciting time for artificial intelligence in enterprises. We are past Big Data (which occurred with the advent of mobile, apps and social media), and are in the Hyper-Data stage. Compute Availability 3.

Artificial Inteligence 29

Artificial Inteligence Technical Review Agile Software Review 29

Paul Hobcraft

NOVEMBER 22, 2015

There is this sense that consultants are resolutely staying very internally driven, self-promoting, still trying to convey the story of innovation mastery, when clearly this is lacking in rapidly changing market and technology conditions and due to this staying ahead of the knowledge curve are actually failing the client.

Innovation 60

Innovation Collaboration Technical Review Leadership 60

Planview

DECEMBER 16, 2022

With the holiday season in full swing and a global recession predicted sometime in the new year, banks remain committed to investing in modernized technology through digital banking transformation efforts vs. traditional cost-cutting routes. “Retail banking customers are expecting more from their banks. The organization serves 14.4

Technical Review 59

Technical Review Case Study Agile Artificial Inteligence 59

Paul Hobcraft

DECEMBER 2, 2016

There is the shift to more open-sourcing, the profound shifts that technology and digital transformation is having upon all our worlds is allowing a very different “connecting” innovation to come into play. We have seen an amazing transformation in how we socialize through the use of technology and the smartphone.

Technical Review 100

Technical Review Innovation Collaboration Software Review 100

Paul Hobcraft

FEBRUARY 18, 2019

What are Europeans loss is the UK’s gain, in being unshackled from others, not just lagging behind in digital technology and innovation but actually blocking it for the “collective union” Europe offers incredible history, the same as Asia. Let me take my area of focus – Innovation and Digital Technology.

Innovation 178

Innovation Artificial Inteligence Technical Review Report 178

Qmarkets

JUNE 16, 2017

Over the last couple of decades, Silicon Valley has been responsible for inventing and reinventing all kinds of gadgets and technologies: the music player, the phone, the watch, the TV and the computer itself. In their view, cars are an old, inconvenient technology, destroying lives, polluting the air, and contributing to global warming.

Industry 56

Industry Technical Review Software Review Disruption 56

Corporate Innovation

JULY 4, 2015

Because of problems such as pollution, climate change and loss of productivity due to long commute times, consumer attitudes towards car ownership and use are changing. These technologies and business models are not in the automotive industry’s DNA. Companies in the automotive value chain are faced with a challenging future.

Disruption 61

Disruption Big Data Technical Review Software Review 61

Corporate Innovation

JULY 4, 2015

Because of problems such as pollution, climate change and loss of productivity due to long commute times, consumer attitudes towards car ownership and use are changing. These technologies and business models are not in the automotive industry’s DNA. Companies in the automotive value chain are faced with a challenging future.

Disruption 61

Disruption Big Data Technical Review Software Review 61

eZassi

MARCH 28, 2019

The best solutions tend to be a combination of technology and services. While we tend to think of innovation in terms of new technology, solutions can also come in the form of new types of services that offer improvements on old ways of doing things, meet previously unidentified needs or fill gaps in the market. Continued coaching.

Software Review 45

Software Review Underperforming Technical Team Software Technical Review 45

Acuvate

AUGUST 2, 2019

However, changing a company’s culture is one of the most challenging parts of any data and analytics initiative, making it difficult to create a data-driven enterprise. 69 percent of the participants also reported that they are yet to create a data-driven organization. . Develop A Data-Focused Workforce In The Organization.

Data 45

Data Leadership Culture Big Data 45

David Marks

APRIL 11, 2017

Disruptive technologies and upstarts are wrecking havoc far and wide, they warned, and (unless you hire us) you will be the next to go. They now tweet, on mobile, collect big data and learn deeply (Current technology terms have an unwittingly infantile twang) Yet there is more to it. are indeed wonderful beasts.

Disruption 40

Disruption Company Technical Review Comparison 40

Acuvate

SEPTEMBER 19, 2022

As incredible as it sounds, what defines a truly successful organization in today’s data-led world is the willingness and ability to build modern data estates, find meaning in an increasingly complex myriad of data sources and data silos, and incorporate agility, speed, and innovation into data-driven business decisions.

Data 52

Data Software Review Technical Review Artificial Inteligence 52