DataRobot

AUGUST 5, 2021

After Banjo CEO Damien Patton was exposed as a member of the Ku Klux Klan, including involvement in an anti-Semitic drive-by shooting, the state put the contract on hold and called in the state auditor to check for algorithmic bias and privacy risks in the software. The good news was the software posed less risk to privacy than suspected.

Uncertainty 98

Uncertainty Sales Risk Statistics 98

CIO Business Intelligence

JUNE 23, 2023

It helps reduce risk, increase efficiency, optimize resources, and improve both the customer and employee experience. When asked what keeps them up at night, IT leaders noted the need to improve overall IT performance (60%), followed by data security (50%), process risk and compliance (46%), and the need to improve agility (41%).

IT 97

IT Risk Management Risk Optimization 97

Cloudera

DECEMBER 3, 2021

Surely there are ways to comb through the data to minimise the risks from spiralling out of control. This involves identifying, quantifying and being able to measure ethical considerations while balancing these with performance objectives. Systems should be designed with bias, causality and uncertainty in mind. Model Drift.

Uncertainty 99

Uncertainty Measurement Metrics Risk 99

CIO Business Intelligence

MARCH 14, 2022

In How to Measure Anything , Douglas Hubbard offers an alternative definition of “measurement” to the Oxford English Dictionary’s “the size, length, or amount of something.” Hubbard defines measurement as: “A quantitatively expressed reduction of uncertainty based on one or more observations.”.

Uncertainty 94

Uncertainty Measurement Cost-Benefit Optimization 94

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. Hollywood is a $10 billion-a-year industry, and movies range from huge hits to box office bombs.

Risk 67

Risk ROI Modeling Metrics 67

IBM Big Data Hub

FEBRUARY 20, 2024

These proactive measures are made possible by evolving technologies designed to help people adapt to the effects of climate change today. Climate models provide answers Human activities precipitated changes to the Earth’s climate in the 20th century and will largely determine the future climate.

Modeling 123

Modeling Forecasting Reporting Risk 123

CIO Business Intelligence

DECEMBER 18, 2023

A primary fear is that employees, partners, and organizational stakeholders might share everything from private data to source code into public large language models (LLMs), expose proprietary information and intellectual property, or reveal vulnerabilities to exploit. So, simply blocking LLM access is not the right answer.

Enterprise 115

Enterprise Management Risk Uncertainty 115

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. Machine learning adds uncertainty. Models also become stale and outdated over time.

Management 332

Management Machine Learning Experimentation Metrics 332

DataKitchen

SEPTEMBER 21, 2023

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. Given this, it’s crucial to have in Place meticulous testing protocols for the results of models, visualizations, data delivery mechanisms, and overall data utilization.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

CIO Business Intelligence

MAY 9, 2023

Like most CIOs you’ve no doubt leaned on ROI, TCO and KPIs to measure the business value of your IT investments. Those Three Big Acronyms are still important for fine-tuning your IT operations, but success today is increasingly measured in business outcomes. Maybe you’ve even surpassed expectations in each of these yardsticks.

ROI 120

ROI Cost-Benefit KPI Uncertainty 120

CIO Business Intelligence

JULY 23, 2023

EY recently found that in current economic and financial uncertainty, 94% of tech executives plan to increase their IT investment over the next year. Optimization also rose to the top of IT leaders’ lists: 67% measure success within their IT organization by better optimizing resources.

Optimization 78

Optimization IT Digital Transformation Uncertainty 78

O'Reilly on Data

SEPTEMBER 15, 2020

In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Technical sophistication: Sophistication measures a team’s ability to use advanced tools and techniques (e.g., Technical competence results in reduced risk and uncertainty.

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

Jedox

SEPTEMBER 3, 2020

The new normal introduced new risks from employee health and safety, supply chain stress and government mandates – all with working capital implications. The unprecedented uncertainty forced companies to make critical decisions within compressed time frames. This placed an acute spotlight on planning agility. Conclusion.

Uncertainty 81

Uncertainty Forecasting Digital Transformation Risk 81

CIO Business Intelligence

OCTOBER 18, 2023

If anything, 2023 has proved to be a year of reckoning for businesses, and IT leaders in particular, as they attempt to come to grips with the disruptive potential of this technology — just as debates over the best path forward for AI have accelerated and regulatory uncertainty has cast a longer shadow over its outlook in the wake of these events.

Risk 138

Risk Manufacturing Enterprise Technology 138

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” How can identifying gaps or discrepancies in the training data help you build a more trustworthy model? Dimensions of Trust. How large is the data set?

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

CIO Business Intelligence

SEPTEMBER 20, 2023

They are afraid of failure and the uncertainty of knowledge work, and so that’s stressful. Agile is an amazing risk management tool for managing uncertainty, but that’s not always obvious.” The key is recognizing that planning must be an agile discipline, not a standalone activity performed independently of agile teams.

Digital Transformation 131

Digital Transformation Uncertainty Metrics Business Objectives 131

DataRobot

JUNE 1, 2021

Before you put a model into production, you may first need to clear compliance hurdles. You should first identify potential compliance risks, with each additional step again tested against risks. Typically, these areas require the most attention: model development, implementation, and use. Knowing When to Trust a Model.

Uncertainty 52

Uncertainty Machine Learning Advertising Risk 52

Cloudera

DECEMBER 11, 2020

Insurance and finance are two industries that rely on measuring risk with historical data models. To facilitate risk modeling in this new normal, agility and flexibility is required. Data Variety. This will only become more important as we move into 2021 and a post-pandemic new normal.

Insurance 93

Insurance Digital Transformation Unstructured Data Machine Learning 93

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

Others argue that there will still be a unique role for the data scientist to deal with ambiguous objectives, messy data, and knowing the limits of any given model. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

BizAcuity

MARCH 18, 2019

The consumer lending business is centered on the notion of managing the risk of borrower default. Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. Predictive Analytics enhances the Lending Process.

Predictive Analytics 83

Predictive Analytics Analytics Cost-Benefit Data mining 83

Sisense

MARCH 26, 2020

To effectively identify what measures need to be taken, analytics can help to summarize and predict how companies should evolve to survive in a challenging environment. Now is the time to apply the full force of business intelligence used by analytics teams to help navigate growing uncertainty. Making smarter staffing decisions.

Management 91

Management Cost-Benefit Uncertainty Digital Transformation 91

Jet Global

JULY 23, 2020

Fortunately, the level of uncertainty has fallen considerably, as many businesses are beginning to re-open, albeit with some restrictions and under capacity restrictions. F&A should be monitoring receivables closely, understanding which customers may be at risk, and taking an aggressive stance on collections. Continue to Run Lean.

Uncertainty 95

Uncertainty Finance Cost-Benefit Reporting 95

datapine

DECEMBER 28, 2021

With the rise of advanced technology and globalized operations, statistical analyses grant businesses an insight into solving the extreme uncertainties of the market. These controlling measures are essential and should be part of any experiment or survey – unfortunately, that isn’t always the case. So, can statistics be manipulated?

Statistics 363

Statistics Advertising Visualization Data mining 363

IBM Big Data Hub

OCTOBER 18, 2022

It’s more vexing than regulation, cyber risk, and even supply chain disruptions. Most admit uncertainty around ROI and nearly half struggle with adequate insights from their data. Learn how CEOs inspire new partnership models to turn sustainability goals into action.

Uncertainty 52

Uncertainty Strategy Measurement ROI 52

CIO Business Intelligence

JULY 7, 2023

As an IT management framework, ITIL can help businesses manage risk, strengthen customer relations, establish cost-effective practices, and build a stable IT environment that allows for growth, scale, and change. ITIL certification is near the top of almost every list of must-have IT certifications, and for good reason.

Cost-Benefit 98

Cost-Benefit Strategy Management Uncertainty 98

CIO Business Intelligence

SEPTEMBER 12, 2022

The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says. It requires bold bets and a willingness to persevere despite setbacks, criticism, and uncertainty,’’ wrote McKinsey senior partners Laura Furstenthal and Erik Roth in a recent blog post. “By Elixirr Consulting.

Experimentation 131

Experimentation Consulting Technology Machine Learning 131

bridgei2i

JULY 8, 2020

They discuss the impact of the pandemic on enterprises and the need to adopt parallel windows – a short term window to get an enterprise’s operational system up and running as effectively as possible, and a medium-term outlook to mitigate the supply chain shocks and risks. Can we model the impact for such structural shocks?

Digital Transformation 132

Digital Transformation Enterprise Insurance Risk 132

Domino Data Lab

JUNE 2, 2019

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

Jet Global

MAY 10, 2021

At a time of great uncertainty, the role of finance professionals has, of necessity, evolved into an ever more strategic one. The viability of new revenue models or investment opportunities. Risk and compliance issues that may impact certain actions or decisions. Improving credit risk analysis.

Finance 98

Finance Recreation/Entertainment Reporting Uncertainty 98

Jet Global

SEPTEMBER 10, 2020

Living through periods of rapid upheaval and uncertainty, like the recent pandemic, forces us to adapt quickly to new working practices. One area that often goes overlooked is the value that can be achieved from the application of consolidated KPIs to measure major indicators. Addressing Long-Lasting Changes.

Forecasting 52

Forecasting Finance Uncertainty Sales 52

bridgei2i

JUNE 3, 2020

Consumers feel threatened by the prolonged uncertainty, not having had to deal with anything like it, in their lives. Demand for minimal physical interaction/low human touch products: Due to the risk of infection, customers want to pick up products with minimal human contact.

Manufacturing 52

Manufacturing Forecasting Uncertainty Digital Transformation 52

The Unofficial Google Data Science Blog

JULY 22, 2020

One reason to do ramp-up is to mitigate the risk of never before seen arms. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. For example, imagine a fantasy football site is considering displaying advanced player statistics.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Jet Global

JUNE 28, 2022

We’re also seeing greater volatility in global events, uncertainty in global trade policies, and more. The reputational risks associated with regulatory audits and last minute scrambles to complete tax returns are too great, and the upside for truly managing the ‘data behind the numbers’ is now simply too large to ignore.

Software 52

Software Forecasting Reporting Finance 52

O'Reilly on Data

DECEMBER 9, 2019

Recall from my previous blog post that all financial models are at the mercy of the Trinity of Errors , namely: errors in model specifications, errors in model parameter estimates, and errors resulting from the failure of a model to adapt to structural changes in its environment.

Statistics 27

Statistics Uncertainty Risk Marketing 27

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This type of data is often collected through less rigid, measurable means than quantitative data. This is quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

The Unofficial Google Data Science Blog

APRIL 17, 2017

Selection and aggregation of forecasts from an ensemble of models to produce a final forecast. Quantification of forecast uncertainty via simulation-based prediction intervals. Calendaring was therefore an explicit feature of models within our framework, and we made considerable investment in maintaining detailed regional calendars.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83