Forecasting uncertainty at Airbnb

O'Reilly on Data

Theresa Johnson outlines the AI powering Airbnb’s metrics forecasting platform. Continue reading Forecasting uncertainty at Airbnb

How to forecast stock on hand

Phocas

Yet, without the ability to accurately forecast stock on hand, keeping optimal stock levels can be a challenge. The ability to deliver orders in full and on time (DIFOT) is essential to keeping satisfied customers.

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Stock Market Forecasting Using Time Series Analysis

KDnuggets

Time series analysis will be the best tool for forecasting the trend or even future. So let us understand this concept in great detail and use a machine learning technique to forecast stocks. 2020 Jan Tutorials, Overviews Analysis Finance Forecasting Stocks Time SeriesThe trend chart will provide adequate guidance for the investor.

Webinar: Data-Driven Approaches to Forecasting

KDnuggets

Whether it’s demand forecasting, supply chain management, or any other application, getting it right requires balancing the need for performance with the constraints of implementation and complexity. Learn more in this free webinar, Data-Driven Approaches to Forecasting, Sep 26. 2019 Sep Webcasts & Webinars Forecasting Metis

Crucial KPIs for Your Growing Company: 7 Principles & 35 Metrics Every SMB Needs

Expert advice for SMBs to help drive the right results, including: principles to making good decisions quickly, why you need leading and lagging indicators to improve your odds of success, and how to use interlocking KPIs to improve company alignment.

5 Tips for High Quality Finance Forecasting

Jedox

A high-quality business forecast delivers far more than just numbers. Finance professionals regularly try to look in their crystal ball with forecasts and enable the company to have seamless, solid planning. For this to succeed, your forecast must be of high quality.

Machine Learning Can Assist with Five Year Balance Sheet Forecasts

DataFloq

The financial forecasting process is one of the least liked aspects of business. Machine learning is making many business processes much easier.

Using Business Intelligence in Demand Forecasting

Jet Global

One of those areas is called predictive analytics, where companies extract information from existing data to determine buying patterns and forecast future trends. We’ll explain what it is, how it works, and ways to start using demand forecasting with business intelligence software.

Understanding Demand Forecasting And Then Mastering It

BizAcuity

To cater to these fast-changing market dynamics, the practice of demand forecasting began. Today, several businesses, especially those belonging to the FMCG sector, have sophisticated demand forecasting models in place, which help them stay ahead of the market.

Using Business Intelligence in Demand Forecasting

Jet Global

One of those areas is called predictive analytics, where companies extract information from existing data to determine buying patterns and forecast future trends. We’ll explain what it is, how it works, and ways to start using demand forecasting with business intelligence software.

Hey Siri, What’s My Forecasted EBITDA Look Like?

Jedox

Even though we have so much advanced technology surrounding us, we still cannot just ask, “ Hey Siri, what’s my forecasted EBITDA look like ?” Many of the algorithms used for budgeting, planning, and forecasting are already in use and were proven decades ago. The first, and probably most popular area, is time-based forecast and prediction. The post Hey Siri, What’s My Forecasted EBITDA Look Like?

Increased Sell-Through Accuracy Using Forecasting Engine

bridgei2i

Increased Sell-Through Accuracy Using Forecasting Engine. The client, a Fortune 500 global enterprise technology hardware manufacturer, was generating about 50,000 different forecasts at a monthly level from its distributor network spread across 120 countries. Using sophisticated Demand Planning software could only provide a 3-month accuracy of about 45% however, the client needed improved accuracy and a more powerful demand forecasting application. Case study.

Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective. Our team does a lot of forecasting. For high stakes, strategic forecasts, my answer is: yes!

What is ARIMA Forecasting and How Can it Be Used for Enterprise Analysis?

Smarten

This article provides a brief explanation of the ARIMA method of analytical forecasting. What is ARIMA Forecasting? ’ The ARIMA model is suggested for short term forecasting. The ARIMA forecasting technique uses three primary parameters for analysis within the model.

Age care provider finds value in forecasting and prediction

IBM Big Data Hub

When providing care for the elderly, you have a tremendous responsibility to your residents and their families.

What is ARIMAX Forecasting and How is it Used for Enterprise Analysis?

Smarten

This article looks at the ARIMAX Forecasting method of analysis and how it can be used for business analysis. What is ARIMAX Forecasting? To understand ARIMAX Forecasting, let’s look at an example of annual GDP values in India.

What is the Holt-Winters Forecasting Algorithm and How Can it be Used for Enterprise Analysis?

Smarten

This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment. What is the Holt-Winters Forecasting Algorithm? The Holt-Winters algorithm is used for forecasting and It is a time-series forecasting method.

Demand Forecasting Using Traditional and Contemporary Data Science

ScienceSoft

Dissatisfied with your demand forecasts? Instead of giving up on them completely, try reconsidering the methods you use. Here, we describe the approaches that will definitely work: traditional and contemporary data science

Automated Sales Forecasting with Predictive Analytics Making AI Real (Part 4)

Jedox

In today’s organizations, the role of financial controlling or FP&A is not only to provide financial insights so business partners can make better decisions, but it is also to lead the way towards a more mature use of analytics technology including predictive analytics for sales forecasting.

Machine learning-based Sell-In Forecasting for Consumer Electronics

bridgei2i

Machine learning-based Sell-In Forecasting for Consumer Electronics. With over 2000 products and a channel-focused Supply Chain planning approach, our Client wanted accurate Supply Chain Forecast for optimal product-availability within 8-week lead-times. With a target of a 10% Accuracy Value-Add, it was imperative to explore new-age forecasting methods based on Machine Learning. Our Forecasting Engine is a Proven Tool to Improve Visibility. Case study.

Blending Art and Science: Using Data to Forecast and Manage Your Sales Pipeline

Sisense

Analytics and sales should partner to forecast new business revenue and manage pipeline, because sales teams that have an analyst dedicated to their data and trends, drive insights that optimize workflows and decision making. Nowadays, sales is both science and art.

Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

by ERIC TASSONE, FARZAN ROHANI We were part of a team of data scientists in Search Infrastructure at Google that took on the task of developing robust and automatic large-scale time series forecasting for our organization. So what did "forecasting" not mean to us?

Predictive Analytics Use Cases: Envision Success with Comprehensive Planning and Forecasting!

Smarten

When it comes to using Predictive Analytics and a self-serve augmented analytics environment, businesses often want to sell the management team on these tools by suggesting real-world use cases that reflect the needs of the organization and illustrate how advanced analytics can help business users and the organization at large with accurate, efficient insight into the planning and forecasting process, and the ability to identify trends and patterns, understand target custom buying behavior, predict fraud and loan default, combine internal and external data analytics, manage quality, improve demand planning and marketing processes and manage human resource attrition. These are just some of the examples of use cases that effectively illustrate how your business can benefit from predictive analytics in real-world scenarios. Whether you need to anticipate and plan for equipment maintenance, target online customers, control customer churn, or identify ways to cross-sell and upsell customers on existing and new products and services, these predictive analytics tools can help you to optimize your marketing budget and your resources and mitigate risk and market missteps. The benefits of advanced analytics and assisted predictive modeling are too numerous to provide a complete list here. Whether you are using these tools for day-to-day or strategic planning, self-serve augmented analytics provides easy-to-use tools for business users and analysts alike and these tools can be used to achieve a competitive advantage and make better, more educated business decisions. Gain insight into customers, competition, resource allocation, investments, new product and service offerings, supply chain and production issues and more. Learn More: Augmented Analytics Use Cases. Explore these use cases and discover how predictive analysis, and self-serve, advanced analytics tools can help you achieve your goals. Customer Targeting. Product and Service Cross-Sell and Upsell. Customer Churn. Fraud Mitigation. Quality Control. Demand Planning. Human Resource Attrition. Maintenance Management. Loan Approval. Marketing Optimization. Online Target Marketing. Predictive Analytics Using External Data. Learn more about Augmented Analytics, its uses, techniques and applications. Contact Us today to find out how you can create your own success story with assisted predictive modeling and augmented analytics. Smarten Advanced Data Discovery Advanced Analytics Use Cases Augmented Analytics Use Cases Data Analytics Predictive Analysis Use Cases Predictive Analytics Use Cases

Sales Bookings Forecasting Engine for a Global Cloud and Virtualization Major

bridgei2i

Sales Bookings Forecasting Engine for a Global Cloud and Virtualization Major. Our client, a global cloud and virtualization major, was looking to achieve a B2B revenue forecast from disparate sources—several tiers of the organization, a dynamic competitor landscape and varying density of data and mix of products at different life stages. The sophisticated sales hierarchy necessitated multiple revenue forecasts at different levels. Case study.

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The Importance of Planning and Forecasting in BI

Paris Technologies

The budgeting and forecasting process for most organizations is long and tedious and occurs on an annual basis, at least. Companies try to do it more often to improve accuracy and aim to ultimately implement a procedure for continuous planning or rolling forecasts. Unlike any other business process, budgeting and forecasting is unique because it is […].

Oracle Planning: Driver-based Rolling Forecast at #Kscope18

Perficient Data & Analytics

Rolling forecasts in healthcare are challenging because Key Performance Indicators (KPIs) are unique to each organization and market conditions are ever changing. The new rolling forecast model delivers several advantages: Flexible, driver based calculations. Several versions of the forecast can be saved. KSCOPE18 Session: Case Study: Implementing one of its kind driver based rolling forecast model at MD Anderson Cancer Center using Hyperion Planning with ASO integration.

Are spreadsheets really the best tools for financial planning and forecasting?

IBM Big Data Hub

Learn more in this webinar how predictive technologies can improve the accuracy of your own planning and forecasting Still using spreadsheets for financial planning?

Cloud Data Science 8

Data Science 101

Amazon Forecast now uses public Holidays from 30 Countries Forecast, which is a time-series forecasting tool, supports holidays from many countries now. This will greatly improve the forecast accuracy as holidays can play a large part in forecasting.

Big Data Forecast: Cloudy, with Increasing Chances of Success (Part 1)

Cloudera

Tune in for Part 2 of 3, coming soon… The post Big Data Forecast: Cloudy, with Increasing Chances of Success (Part 1) appeared first on Cloudera Blog. Today, public cloud is a compelling proposition for businesses and government organizations seeking to be more agile. Increasingly, self-service is seen as the most effective way to scale user access to data for analytics and operations.

DataRobot and Kx Partnership: Modernizing the Financial Markets with AI-Driven Forecasting

DataRobot

Competition throughout the financial markets is becoming more intense and top-line growth is becoming more challenging than ever to achieve.

All About Machine Learning with Oracle Analytics

Perficient Data & Analytics

Data & Analytics Oracle Augmented Analytics BI Classification clustering Data Flow Data Preparation Explain forecast machine learning ML OAC obiee oracle analytics Oracle Analytics Cloud Outlier Detection Prediction predictive sentiment analysis

Target: Process Optimization

Jedox

This means more and more requirements to extract insight and value from data will be added to the areas of planning and forecasting. In particular, the creation of future-oriented scenarios as well as the preparation of corresponding business plans and forecasts.

Predictive Model Ensembles: Pros and Cons

Perficient Data & Analytics

Data & Analytics Digital Transformation AI analytics digital transformation Forecast Modeling machine learning predictive analyticsMany recent machine learning challenges winners are predictive model ensembles. We have seen this in the news.

Predict Electricity Consumption Using Time Series Analysis

KDnuggets

Time series forecasting is a technique for the prediction of events through a sequence of time. In this post, we will be taking a small forecasting problem and try to solve it till the end learning time series forecasting alongside.

Planning in Excel: How to Make it Better

Jedox

For most finance professionals, Excel has long been the gold standard for budgeting, planning, and forecasting. In a 2018 survey , 80% of organizations reported they are still reliant on Excel for their budgeting, planning, and forecasting and almost as many reported that non-integrated systems present a challenge. Why not take advantage of solutions that integrate all data streams and cut your forecasting time dramatically?

9 Mistakes to Avoid When Predicting Business Performance

DataFloq

The “state of forecasting” in today's businesses is such that only 1% are able to achieve 90% forecasting accuracy 30 days out. Here are the nine most-common forecasting mistakes to avoid:Lack of a systematic and process-driven approach.This is the number one forecasting sin. I think we can all agree that's sub-optimal, but why is this the case?

An Open Letter To The CFO on FP&A

Jedox

Thought Leadership Budgeting and Forecasting CFO Enterprise planning Financial Performance Integrated Planning Sales PlanningDear CFO, We heard that you put FP&A on your list of top priorities to work on. We understand that you’re not satisfied with the return on investment you’re getting from the department. You told us that there is too much data, reporting, and analysis and too few real insights that change decisions for the better.

A Framework for the New FP&A Department

Jedox

The classical tasks of budgeting, forecasting and planning will remain, but a lot of it will be done by algorithms which are much more accurate at forecasting than humans. Re-forecasting and fast reactions to external events will replace obsessive budgeting. Thought Leadership Budgeting Enterprise planning Financial Performance Forecasting FP&A Performance Management

Why Transforming Your FP&A Matters

Jedox

How can you best support your FP&A team so they can improve their budgeting, forecasting, and planning? Thought Leadership Budgeting and Forecasting CFO CPM Enterprise planning Integrated Planning Performance Management Sales Planning“Transformation!” ” is the clear message from Chief Financial Officers. To do that we must address the mindset of the entire FP&A team.

How To Reinvent Your FP&A Process

Jedox

Crystal Ball: Develop an integrated budgeting and forecasting process so you can move from data gathering/reporting to insights/analysis. Take one of your processes (budgeting or forecasting would be the obvious choice). Thought Leadership Budgeting Budgeting and Forecasting Business Intelligence CPM Financial Performance Performance ManagementThere has been a lot of talk about changing FP&A processes yet little real action in this area. Budgeting?

KPI 40

How Technology Will Change FP&A Forever

Jedox

3-way predictions or forecasts typically include the Income Statement, Balance Sheets and Cash Flow Statements. These forecasts are more aligned to financial modeling, rather than analytics as they include the balance sheet positions, cash flows and profitability in an integrated manner. Thought Leadership Budgeting and Forecasting CPM Financial Performance Integrated Planning Sales Planning technology

How to Transform Your FP&A Plan

Jedox

Thought Leadership Budgeting and Forecasting Business Intelligence CFO Data Modeling Financial Performance FP&AFinance professionals generally tend to be risk averse. Transforming your FP&A plan will not be an easy task, but it must be addressed as it is a top priority for the CFO to better support delivering on the expectations from the CEO. In today’s world where technology changes are rampant and society’s expectations of new ideas and stimulation is at a rate not seen before.

9 Mistakes to Avoid When Predicting Business Performance

DataFloq

The “state of forecasting” in today's businesses is such that only 1% are able to achieve 90% forecasting accuracy 30 days out. Here are the nine most-common forecasting mistakes to avoid: 1. This is the number one forecasting sin. In the absence of a process-driven approach, or the computational power required to build forecasts at a very granular level, most staff will default to evenly distributing one high-level forecast across different.