Harvard Business Review

JUNE 7, 2023

An entirely new “management paradigm” for data is needed. As used here, a “management paradigm” embodies a common language, a holistic vision of the ways data should contribute, a clearly defined organizational structure showing how data integrates across the organization, along with clear roles and responsibilities for all involved.

Data 135

Data Strategy Strategy Policies 135

Acuvate

MAY 22, 2020

10 Key Challenges Data Scientists Face in Machine Learning projects AI-driven, powered by AI, transforming with AI/ML, etc., Everyone is chasing after the promised land of machine learning but so few fully understand it. The post Key Challenges Data Scientists Face in Machine Learning projects appeared first on Acuvate.

Artificial Inteligence 95

Artificial Inteligence Data Project Learning 95

Harvard Business Review

JANUARY 26, 2024

There are three immediate challenges for companies that want to train fine-tuned AI models: 1) they require extensive, high-quality data — a scarce resource for many enterprises, 2) third-party AI models can include problematic biases, and 3) training fine-tuned models with users’ personal data may result in privacy violations.

Data 127

Data Collaboration Company Training 127

InnovationManagement

FEBRUARY 16, 2022

Many people have said that 2021 was 2020 Part II, but IdeaScale looked at some of our system data (as we do every year) to see what we could learn, and there are a few key trends we think are different from 2020, and that we think bode well for a creative 2022. appeared first on InnovationManagement.

Trends 97

Trends Data Innovation Management Learning 97

Harvard Business Review

JANUARY 15, 2024

Although cultural change generally requires human intervention, it appears that new technology — especially a new technology like generative AI that captures human imaginations — can play a role in catalyzing a data-oriented culture.

Survey 109

Survey Data Generative AI ChatGPT 109

Jeffrey Phillips

FEBRUARY 13, 2020

In his or her place is emerging a new kind of miner - a data miner, a process miner, a bitcoin miner. People who are expert at exploiting a new, but somewhat unnatural resource: all the data that we create. We are in the very beginning of one now - a gold rush to find, mine and refine data and turn the insights into value.

Data 157

Data Learning Artificial Inteligence Technical Review 157

Harvard Business Review

SEPTEMBER 13, 2023

Despite the rapidly increasing prominence of data and analytics functions, the majority of chief data officers (CDOs) fail to value and price the business outcomes created by their data and analytics capabilities. It comes as no surprise then that many CDOs fall behind expectations and have short tenures.

Data 116

Data Strategy Strategy Artificial Inteligence 116

Harvard Business Review

SEPTEMBER 8, 2023

As reliance on data and analytics continues to expand across industries from agriculture to manufacturing, health care to financial services, it stands to reason that the next generation of data leaders will have far-reaching roles that impact strategy, decision-making, operations, and countless other functions.

Data 141

Data Industry Strategy Strategy 141

Harvard Business Review

JUNE 20, 2023

With the explosion of generative AI and other powerful new data tools, chief data and artificial intelligence officers (CDAIOs) are more important than ever as companies navigate this new landscape.

Data 133

Data Artificial Inteligence Generative AI Technical Review 133

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

IdeaScale

MAY 18, 2017

The keys to innovation from failure are to have a culture around dealing with and accepting failures, failing fast, and learning from the failure. So how do we go about learning from failure? The culture to deal with and accept failures creates a feedback loop of learning. It’s only failing if you learned nothing.

Learning 214

Learning Innovation Culture Data 214

Brunner

JULY 12, 2023

Only a few short years ago, the general public learned companies were collecting and selling data with every click consumers made. In 2018, Facebook CEO Mark Zuckerberg was called to address Congress about a data-sharing scandal with Cambridge Analytica, a company that bought data from Facebook to target political advertising.

Data 94

Data Marketing Policies Strategy 94

InnovationTraining.org

SEPTEMBER 23, 2022

Learn the basics of data storytelling and find training resources, articles, videos, and more. Data is all around us – from our schools, to our workplaces, and internet habits. Data storytelling recognizes that data on its own is often not enough to move people to action. What is data storytelling?

Training 70

Training Data Underperforming Technical Team Video 70

Tullio Siragusa

AUGUST 1, 2022

The Hyper-personalization Data and Privacy Debate?-?Solved. Data is what we share with the websites we visit. In this podcast recap blog post, we will discuss how websites store data, what goes on with the data that we share, and how we can have an option to control our data to have personalized experiences.

Data 118

Data Technical Review Marketing Design Thinking 118

Jeffrey Phillips

FEBRUARY 12, 2018

Lately, with the advent of "big data", machine learning and other factors associated with data and more intelligent processes, the argument has been made that these capabilities will solve the innovation gap. To date, there's been some improvement but the innovation gap still remains. Humans are omnivorous connectors.

Big Data 170

Big Data Data Artificial Inteligence Innovation 170

Planview

DECEMBER 12, 2023

Historically, companies had two approaches to deriving value from data. Some companies used a grassroots approach, where individual people and teams mined their own data stores for insights as needed. Neither can handle the amount of data coming in from customers and internal operations. The problems with those approaches?

Data 72

Data Trends CTO Company 72

Harvard Business Review

JULY 11, 2023

Thanks to the increasing availability of AI, including machine learning algorithms, deliberately creating customer data feedback loops is now possible for most products and services. For some products, it is easy; for others, one needs to find more creative ways to engineer the data feedback loops.

Data 66

Data Artificial Inteligence Learning Creativity 66

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

Harvard Business Review

DECEMBER 15, 2023

But conversations aren’t just about facts and data, the grounding and structure are important as well — that is what prompt engineering is. These conversations contain a lot of knowledge that LLMs will unlock — your conversation with PowerPoint, for example, can now become an amazing presentation.

Learning 134

Learning How To Data Examples 134

Jeffrey Phillips

MARCH 20, 2020

From the formation of basic tools to assist in farming to real cultivation and shaping of the land for greater yields, humankind learned to grow food. From early sweatshops to almost fully automated factories, we've learned how to scale manufacturing and get far more productivity from fewer workers and more machinery and automation.

Data 129

Data Artificial Inteligence Tools Resources 129

Board of Innovation

DECEMBER 16, 2021

Validation is the process of gathering evidence and learning around business ideas through experimentation and user testing, in order to make faster, informed, de-risked decisions. The post Business and concept validation through qualitative and quantitative data appeared first on Board of Innovation. Here's how you can use them.

Data 145

Data Learning Innovation Design 145

Jeffrey Phillips

MAY 20, 2022

Increasingly, however, we need to invite data into this mix. As more and more data is generated, it creates new opportunities in the strategy realm and in the innovation realm. This post will consider the importance of data in strategy development and execution, as well as in innovation.

Data 144

Data Report Strategy Strategy 144

Jeffrey Phillips

OCTOBER 21, 2019

Data Driven No phrase worries me more than what I hear repeated regularly as a mantra by our customers and prospects. Everyone wants to be "data driven", which on the surface is an excellent idea. If by "data driven" they mean making decisions based on data rather than conjecture or opinion, that's good.

Data 125

Data Artificial Inteligence System Strategic Thinking 125

IdeaScale

NOVEMBER 19, 2019

Learn innovation and crowdsourcing strategy from NASA. NASA’s Center of Excellence for Collaborative Innovation — a crowdsourcing platform — unveiled their best practices for approaches to problem-solving on a recent webinar in a move to share what they’ve learned to help others. government departments. Shoot for the moon.?.

Crowdsourcing 219

Crowdsourcing Learning Data Technical Review 219

Acuvate

DECEMBER 7, 2022

Industrial IIoT, in particular, in the form of sensors, flow meters, and edge devices, are being used to collect on-field data to create situational awareness and identify leaks, sewer overflows, and faulty equipment before these require costly repairs. How are sustainable technological solutions enabling Smart Water Management (SWM)?

Data 78

Data Artificial Inteligence Management Technical Review 78

Jeffrey Phillips

JULY 15, 2019

These commentators are correct in the sense that we are entering a time where the Internet of Things (IoT) and the data generated by billions of IoT devices will create radically new opportunities for innovation. That is, they weren't connected to the internet or communication channels and did not create or publish data.

Learning 166

Learning Data Innovation Internet of things 166

Acuvate

SEPTEMBER 4, 2023

In the rapidly evolving world of finance and insurance, brimming with risks and complexities, an amalgamation of data and analytics has created a transformative approach to risk management. Predictive analytics, a highly impactful tool powered by AI and machine learning, emerges as a game-changer in the insurance underwriting domain.

Data 52

Data Artificial Inteligence Management Policies 52

Paul Hobcraft

JUNE 22, 2021

There is so much in need of disruption; we must learn not to fear it but embrace it differently. We need to utilize technology, digitalization, AI and machine learning with all the great human ingenuity. We need new imaginative thinking, which comes from listening, collaborating and learning more from each other.

Collaboration 148

Collaboration Learning Change Industry 148

IdeaScale

JUNE 12, 2019

Big data has been a foundation of innovation ever since the first suggestion box was put out. Since then, the data set has only kept growing, until now you can filter thousands or even millions of data points. How do you effectively use big data to drive innovation? Collect Only Relevant Data. Avoid Fishing.

Big Data 157

Big Data Data Strategy Strategy 157

Jeffrey Phillips

APRIL 8, 2019

But through this I've learned a bit about both innovation and digital transformation. Below I'm going to share a few things I've learned so far, and my sense of the implications. Learnings so far: Innovation and digital transformation both impact efficiency; only innovation is about creating dramatically new stuff (so far).

Artificial Inteligence 179

Artificial Inteligence Learning Technical Review Big Data 179