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April 5, 2024

o9 Demand Planning - Analysis Cockpit

Unlock the power of autonomous forecasting with Part 2 of our 4-part series on mastering demand planning using the o9 platform. This video delves into the crucial role of the Analysis Cockpit in automating and enhancing forecast accuracy, a key to achieving autonomous forecasting that traditional solutions struggle with. Discover how the o9 platform identifies forecast goodness and reasonability, automatically highlighting violations against historical trends, seasonality, levels, or patterns, and how it facilitates quick identification of areas for improvement.

In this installment, we cover:
- The significance of the Analysis Cockpit in transitioning forecasting from a reactive to a proactive process.
- Examples showcasing how demand analysts are alerted to suboptimal forecasts through trend, seasonality, level, and range violations.
- Insights into the o9 algorithm insights cockpit, designed to help planners fine-tune or eliminate underperforming algorithms, enhancing overall forecast effectiveness.

Through this video, gain insights into how the Analysis Cockpit streamlines the forecasting process, enabling you to efficiently address forecast exceptions and benchmark performance. This tool is instrumental in moving from data to actionable knowledge, promoting efficiency, transparency, and accuracy in demand planning.

Why is analysis cockpit important?

Autonomous forecasting is a primary business objective that will deliver efficiency and accuracy but achieving this with traditional solutions is challenging. Firstly, it requires experienced planners with many years of product insight who can react to fix poor best fit selection or manually review all intersections to check forecast reasonability.

Secondly, this activity is reactive.

Planers compare forecast against history rather than identifying the goodness of the forecast when it is created. o9 will automatically evaluate the goodness and reasonability of the outputs of the system generated forecasts. It will highlight certain violations when the output seems off when compared with the trend, seasonality, level or pattern of the past history data. This will help planners find the areas of improvement quickly. How to use analysis cockpit in the o9 platform? Here, we can see an example of a trend violation.

The past historical data is trending up, but the forecast is actually trending down.

Demand analysts can get alerts when o9 identifies suboptimal statistical results, and they can then sort or filter which intersections are affected.

In this example, we can see two violations in one, as both seasonality and straight line violations are activated.

In this other example, there is a level violation.

The forecast is too low, and arranged violation, the size of the forecast spikes and dips are not appropriate.

o9 also provides an algorithm insights cockpit. This helps planners identify algorithms that are consistently not selected as the best fit and exhibit a number of violations.

The parameters of these algorithms can then be adjusted, or these algorithms can be removed. o9 analysis cockpit forecast exception management and performance benchmarks.

Help you to be more efficient, driving transparency, and improving accuracy, progress through analysis, from data to knowledge to decisions.

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Want to learn more about Demand Planning?

View our collection of white papers regarding Demand Planning, tailored to your industry.

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