Corporate Innovation

JANUARY 25, 2016

In this two-part series, we will discuss the big data challenge facing the automotive industry. The pieces are the result of my work in the industry helping corporations with their innovation and big data strategies. There is much less conversation about the fifth dimension.

Big Data 58

Big Data Data System Artificial Inteligence 58

Ecosystems4Innovating

NOVEMBER 2, 2023

Why is design thinking regarded as so crucial to the future of innovation in a world of accelerating interplays between humans, technology and generative AI? What will be the changes or potential to leverage these three of Design Thinking, Technology and AI Generative Thinking for solving innovation challenges in the future?

Design Thinking 59

Design Thinking Design Technical Review Artificial Inteligence 59

Tullio Siragusa

JULY 25, 2022

Unlocking Innovation with Data, Creativity, and Automation. For some, it may be through hard work and determination, while others may find success through innovation with creativity, data, and automation. In this podcast recap blog post, we will discuss how innovation derived from creativity, data, and automation can lead to success.

Data 118

Data Creativity Technical Review Innovation 118

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. I’d like to offer some views, partly looking out to the future, partly considering what is potentially within our grasp, if we step back and rethink innovation design.

Design 232

Design Technical Review Innovation System 232

Jeffrey Phillips

MAY 31, 2019

In my last post I tried to illustrate the importance (and the challenges) of data to digital transformation. This is often a complex and difficult idea for people to understand - why is "data" so hard? We humans have this insight and understand the less overt concepts around meta-data because we have learned experience.

Data 129

Data Artificial Inteligence Innovation Big Data 129

Corporate Innovation

JANUARY 25, 2016

In this two-part series, we will discuss the big data challenge facing the automotive industry. The pieces are the result of my work in the industry helping corporations with their innovation and big data strategies. There is much less conversation about the fifth dimension.

Big Data 40

Big Data Data System Artificial Inteligence 40

Corporate Innovation

JANUARY 3, 2017

However, the challenges created from the combination of ACE vehicles and Mobility Services along with the models they enable will be impossible to overcome with the industry’s “traditional” playbook that includes mixing of new designs, financial incentives, and more advertising under the same business models.

Big Data 40

Big Data Data Industry Technology 40

Corporate Innovation

JANUARY 3, 2017

However, the challenges created from the combination of ACE vehicles and Mobility Services along with the models they enable will be impossible to overcome with the industry’s “traditional” playbook that includes mixing of new designs, financial incentives, and more advertising under the same business models.

Big Data 40

Big Data Data Industry Technology 40

Corporate Innovation

JANUARY 3, 2017

However, the challenges created from the combination of ACE vehicles and Mobility Services along with the models they enable will be impossible to overcome with the industry’s “traditional” playbook that includes mixing of new designs, financial incentives, and more advertising under the same business models.

Big Data 40

Big Data Data Industry Technology 40

Acuvate

APRIL 12, 2023

For example, changes in product design, market demands, or production volume are more difficult to accommodate in these rigid legacy solutions. With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity. Traditional automation, however, has its drawbacks.

Data 52

Data Artificial Inteligence Technical Review Big Data 52

Acuvate

APRIL 12, 2023

For example, changes in product design, market demands, or production volume are more difficult to accommodate in these rigid legacy solutions. With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity. Traditional automation, however, has its drawbacks.

Data 52

Data Artificial Inteligence Technical Review Big Data 52

Destination Innovation

DECEMBER 13, 2019

He designed a programme which created thousands of random circuit designs. Eventually the process yielded completely novel and effective designs. Since then this approach has been used successfully in various fields – particularly in engineering and component design. These were measured against desired outcomes.

Artificial Inteligence 246

Artificial Inteligence Big Data Innovation Data 246

Paul Hobcraft

MAY 9, 2023

I am working through what I think this should become in design and application, involving providing the key innovation building blocks as components of the innovation stack, using the innovation stack to guide platform development and the platform to support this innovation stack.

Artificial Inteligence 182

Artificial Inteligence Technical Review Agile Innovation 182

mjvinnovation

SEPTEMBER 3, 2020

It is no coincidence that data visualization has gained such relevance in recent years. Let’s start with what the data-driven mindset is! Data Culture goes far beyond a strategy that simply guides a company’s data. Don’t think that the data mindset is the result of infrastructure alone.

Data 59

Data Culture Technical Review Company 59

Michael Roberto

NOVEMBER 20, 2018

Bryant University Professor Lori Coakley and I have published a new article in the American Management Association Quarterly (Fall 2018 issue) titled, "The Human Center of Design Thinking." In this short essay, we argue that many firms stumble because they focus on a technology in search of a problem.

Design Thinking 22

Design Thinking Big Data Design Data 22

Paul Hobcraft

MAY 6, 2018

I recently applied the three horizons thinking to ‘frame’ a new innovation design. So the thinking intent of searching for a new innovation design had some framing assumptions that can leverage where we are to move towards a new future. This is a useful way to think about the initial 3H outcome.

Design 138

Design Innovation Agile System 138

mjvinnovation

OCTOBER 18, 2019

Data Science is a multidisciplinary mix of data inference, algorithm development, and technology to solve analytically complex problems. What is Data Science and why is it so urgent to invest? The main advantage of Data Science in an organization is the empowerment and facilitation of decision making. Check it out!

Data 40

Data Artificial Inteligence Big Data Internet of things 40

mjvinnovation

JANUARY 17, 2020

It is also about generating value for businesses by using their data creatively. The purpose of this article is to demystify Data Science. To understand in detail why we should utilize this science into our businesses and how to start doing so: Why invest in Data Science. How to start building a Data Science strategy.

Data 52

Data How To Big Data Analysis 52

mjvinnovation

NOVEMBER 30, 2020

As long as everyone is looking and breathing artificial intelligence, data is no longer a differential and becomes part of the mainstream. Data Science becomes another step in the process – a new normal. Analytical Culture: data as a driving force. Data Science + Marketing: the new funnel. Check it out!

Data 52

Data Marketing Artificial Inteligence Design Thinking 52

Tullio Siragusa

JANUARY 11, 2021

Can Innovation in Design Thinking Help Solve Today’s Problems? The problems that artists, designers, business owners, engineers and civic leaders of today face are on a whole new level. To solve the new problems of today, we need new kind of innovation in design thinking.”. “To Problems We Can Tackle with Design Thinking.

Design Thinking 83

Design Thinking Design Innovation Big Data 83

The BMI Lab Blog

NOVEMBER 23, 2022

The experience of recent years shows that companies often overestimate the value of their own data and their own ability to generate revenue from it. In practice, very few companies can establish a sustainable business model based on data. To start, we need to detail what a data-driven business model actually is.

Data 52

Data Technical Review How To Big Data 52

mjvinnovation

JULY 21, 2020

Data Science is about mining large amounts of structured and unstructured data to identify patterns that can help an organization control costs, increase efficiency, recognize new market opportunities, and increase the organization’s competitive advantage. Here are our seven steps to implement Data Science in your business: 1.

Data 52

Data Artificial Inteligence Company Analysis 52

mjvinnovation

DECEMBER 1, 2020

Let’s start with a strong statement: Data is inevitable. We woke up, and suddenly everything was generating data, and the race for advanced analysis had started well before that. The reason, or rather the facilitator of all this, is data! Here’s a spoiler: dashboards are the framework for data culture.

Data 45

Data Analysis Big Data Tips 45

Jeffrey Phillips

APRIL 8, 2019

I think there is great potential for digital transformation, especially big data and predictive analytics, to create new insights that lead to new innovations, but that seems to be still a few years away. Increasingly the focus within innovation is around design, human centered design and customer experience.

Artificial Inteligence 179

Artificial Inteligence Learning Technical Review Big Data 179

IdeaScale

FEBRUARY 19, 2020

Read more about how to design your innovation strategies taking globalization into consideration. Crowdsourcing is a great way to assemble data for product innovation. It gathers relevant data through educated opinions that can be used to formulate ideas that guide product development. Is Your Office Design Stifling Creativity?

Brainstorming 173

Brainstorming Crowdsourcing Conference Product Development 173

mjvinnovation

FEBRUARY 4, 2021

To demystify the subject, we brought the Data Science steps applied in practice, and that can be incorporated into your company. The phase involves both the human side, as we seek to understand what will be relevant for end-users and the technological side, to learn about the data sources available and how they are collected.

Data 40

Data Artificial Inteligence Company Analysis 40

mjvinnovation

SEPTEMBER 22, 2020

In this article, we will explain how Design can provide a differentiated experience for your customers. In addition, we must not lose sight of the combination of online and offline data. This is the context that makes UX Design even more popular. However, we cannot forget other devices, such as browsers. New features?

Design 59

Design Artificial Inteligence Technical Review Meeting 59

mjvinnovation

APRIL 16, 2019

“Wait, but what does this have to do with Data Science?” In MJV, the infinity of the universe is represented by the amount of data we generate every day. It’s Big Data itself! So the question that remains is: how do you master this data universe and use it to your advantage?

Data 66

Data Meeting Artificial Inteligence Analysis 66

Paul Hobcraft

JUNE 3, 2019

The powerful effects of digitalization are opening up different business opportunities, the chance to design different business models and get far closer to the ultimate need, to understand the customers wishes from the products and services they are wanting to buy. We all see around us increasing disruption caused by digitalization.

Data 208

Data Innovation Design Marketing 208

The Human Factor

MARCH 11, 2021

The way businesses are using data is being analyzed by the very people it is taken from – customers. Although it’s healthy for shoppers, it’s bad for the businesses that have gotten used to the insights they glean from cultivating big data. 56% plan on sharing less in the future. Stop Being Weird! You don’t mean it.

Data 36

Data Big Data Tips Industry 36

Paul Hobcraft

OCTOBER 18, 2022

In some recent posts, I argued that we need to adopt a broader innovation ecosystem thinking and design. Still, barriers do need to be consciously built into any new thinking as ones “to be resolved” in any new solution design. They need a more fluid, highly adaptive design. Let me outline many of these here.

Software Review 162

Software Review Innovation Design Technical Review 162

mjvinnovation

JANUARY 3, 2019

The combinatorial approach to Business Intelligence with Design Thinking achieves an unprecedented level of comprehension of corporate realities, and it does so in a concrete way, incorporating the subjective factors of the human relationships involved. Big Data: data analysis is what really matters.

Design Thinking 40

Design Thinking Design Case Study Analysis 40

mjvinnovation

JANUARY 3, 2019

The combinatorial approach to Business Intelligence with Design Thinking achieves an unprecedented level of comprehension of corporate realities, and it does so in a concrete way, incorporating the subjective factors of the human relationships involved. Big Data: data analysis is what really matters.

Design Thinking 40

Design Thinking Design Case Study Analysis 40

Paul Hobcraft

MARCH 27, 2018

I have written a fair amount about the new innovation era, offering a view on its future design. One that is jumping to a fresh cycle of innovative design. We are in the middle of it, some of you may not have noticed its impact and change but it is significant on the understanding of innovation, in it’s future design.

Innovation 185

Innovation Radical Innovation Design Big Data 185

mjvinnovation

FEBRUARY 20, 2020

Design Thinking: Think of solutions, solve situations and problems, close the gaps that need filling in. It is Design Thinking that will pave the way to traveling assertively. Since you have a well-defined idea (through Design Thinking), Agile will clear a path towards your idea by removing obstacles that stand in your way.

Design Thinking 69

Design Thinking Agile Design Technical Review 69

Acuvate

NOVEMBER 28, 2019

In the coming years, the transformative trends in the CPG industry will be driven by data and technology, services that focus on customer centricity and smart supply chains. Using Big Data and Advanced Analytics. Big Data and advanced analytics opens the floodgates of opportunities for CPG companies to use data to their benefit.

Trends 72

Trends Industry Big Data Technical Review 72

Digital Tonto

OCTOBER 21, 2015

We still have yet to bridge the gap between crafting messages and designing experiences. Why Most Marketers Will Fail In The Era Of Big Data. Related posts: Simulation Marketing. Should You Be. [[ This is a content summary only. Visit my website for full links, other content, and more! ]].

Marketing 70

Marketing Big Data Data Design 70