DataRobot Blog

OCTOBER 4, 2022

This has prompted AI/ML model owners to retrain their legacy models using data from the post-COVID era, while adapting to continually fluctuating market trends and thinking creatively about forecasting. In the last few years, businesses have experienced disruptions and uncertainty on an unprecedented scale.

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Jet Global

APRIL 8, 2021

Many organizations already consider the potential short-term challenges to their tax positions when building forecasts. How prepared are they, though, for the different sets of risks and opportunities associated with long-term uncertainties? Instead, they should already be incorporating these considerations into their tax forecasts.

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CIO Business Intelligence

MAY 20, 2024

By our estimates , at least 50% if not around 70% of organizations have yet to fully automate their testing and build pipelines. Practices like test-driven development, refactoring, and pair programming give you the exact recipe to start with. How to do agile development right Speeding up release cycles can be surprisingly quick.

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CIO Business Intelligence

NOVEMBER 14, 2022

A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another. Forecasting models. These models are used for “what-if” analysis. Optimization analysis models.

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Jedox

SEPTEMBER 3, 2020

The unprecedented uncertainty forced companies to make critical decisions within compressed time frames. The room for poor assumptions and missed forecasts shrank. Using these drivers as an overlay to stress-test models add robustness to forecasting and can identify exposure and risks to long-term stability. Conclusion.

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CIO Business Intelligence

DECEMBER 13, 2023

Certinia is using predictive AI to deliver more precise forecasts of cash flow and days to pay, based on analyses of trends in customer payments, and to forecast how many days it will take to staff resource requests, help enterprises keep projects on schedule, or to manage their customers’ expectations when things fall behind. “We

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Jet Global

OCTOBER 21, 2020

Companies use forecasting to make critical investments, plan for covenant compliance, and even decide on future mergers and acquisitions (M&A) strategies. Furthermore, obtaining organisational consensus on a forecast can be as difficult as getting the organisation to contribute to the planning process in the first place.

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CIO Business Intelligence

APRIL 28, 2024

However, new energy is restricted by weather and climate, which means extreme weather conditions and unpredictable external environments bring an element of uncertainty to new energy sources. Carbon neutrality and carbon peak strategies are driving the adoption of new energy worldwide. We need to build grid-based sources, loads and networks.

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BI-Survey

FEBRUARY 14, 2022

Overnight, the impact of uncertainty, dynamics and complexity on markets could no longer be ignored. Local events in an increasingly interconnected economy and uncertainties such as the climate crisis will continue to create high volatility and even chaos. The COVID-19 pandemic caught most companies unprepared.

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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.

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DataRobot Blog

JUNE 21, 2022

The last few years have been plagued with uncertainty, making it difficult to navigate everyday life, let alone plan and make thoughtful decisions for a business. Forecasting for the Real World, Not the Ideal World. By allowing users to build and explore scenarios by adjusting these features, they can test out various outcomes.

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The Unofficial Google Data Science Blog

APRIL 19, 2021

To explain, let’s borrow a quote from Nate Silver’s The Signal and the Noise : One of the most important tests of a forecast — I would argue that it is the single most important one — is called calibration. If, over the long run, it really did rain about 40 percent of the time, that means your forecasts were well calibrated.

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CIO Business Intelligence

FEBRUARY 28, 2023

The year ahead is likely to be characterised by recessionary pressures in key global economies, increasing borrowing costs, unpredictable supply chains, oil price uncertainty, and volatile demand. of all ICT investments made that year.

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Jet Global

APRIL 2, 2020

Unless you operate in a few privileged industries, you will likely contend with declining revenues this quarter and next, making it incumbent on the accounting team to adjust plans and forecasts accordingly. Having access to up-to-date data to understand the depth of those declines and their enterprise-wide impact will be crucial.

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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. Forward-looking enterprises that are achieving better outcomes have already quickly reworked forecasts on supply chains, materials, and costs. Navigating Your Transition to xP&A.

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DataRobot

JUNE 1, 2021

You should first identify potential compliance risks, with each additional step again tested against risks. Recognizing and admitting uncertainty is a major step in establishing trust. Like a weather forecast, AI predictions are inherently probabilistic. Interventions to manage uncertainty in predictions vary widely.

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bridgei2i

JUNE 11, 2020

If nothing else, this anecdote offers valuable insight into the impact that uncertainty of any kind has on consumer behaviour; it triggers volatility. The immediate factor guiding consumer demand behaviour in CPG is Fear— fear of uncertainty, fear of losing incomes, fear of falling sick, fear of running out of essentials etc.

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Digital Transformation Sales Uncertainty Forecasting 52

Andrew White

MARCH 6, 2021

The real problem is its inability to forecast the inflation rate at all, and its use of the levers that impact it. We have hypothesis and we test them. How do we frame our short-term decisions given all these uncertainties? The problem with that view is not that the Fed has undershot its target – for so long. We guess.

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Juice Analytics

APRIL 17, 2020

He goes on to clarify by saying that some estimate that 80% of the cases don’t get tested, so we don’t actually know the real number of cases, but it’s likely very much higher. Forecasts are not Predictions (But they’re still useful.) And forecast modelers know how not only to create those, but also how to interpret them.

Forecasting 101

Forecasting Snapshot Dashboards Uncertainty 101

Insight

FEBRUARY 19, 2020

Photo by Roberto Nickson on Unsplash Much effort has been spent understanding and forecasting the success of movies (e.g., I held out 20% of this as a test set and used the remainder for training and validation. Below is the result of a single XGBoost model trained on 80% of the data and tested on the unseen held-out 20%.

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Jet Global

SEPTEMBER 27, 2023

But now more than ever, challenges from both outside and inside organizations are testing your resiliency. Inflation, economic uncertainty, and swiftly-changing regulations significantly impact finance professionals. Finance teams are no strangers to pressure.

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Jet Global

DECEMBER 14, 2020

But the emergence of COVID-19 layered even more complexity on their ability to predict ETRs and to support their organizations with accurate forecasts. Read how scenario planning for tax forecasts should work in 2021. Read how top tax teams are responding to the latest global disruptions. So, what lies ahead of us in 2021?

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O'Reilly on Data

JUNE 16, 2020

But when making a decision under uncertainty about the future, two things dictate the outcome: (1) the quality of the decision and (2) chance. This essay is about how to take a more principled approach to making decisions under uncertainty and aims to provide certain conceptual and cognitive tools for how to do so, not what decisions to make.

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