Equalizing: Ensure Comparability within Business Dynamics

There are common changes that can influence the truthfulness of data:

• Data vendor/provider changed (e.g. Nielsen vs. IPSOS vs. SimilarWeb)
• Methodology changed (e.g. POS vs. Survey Data collection)
• Definition changed (e.g. New retailers are added to the competitive set)
• Reporting hierarchy changed (e.g. Category moving from one portfolio to another)
• … and more

Typically, changes in metrics or data result in a noticeable shift in the trend, rendering new data points incomparable to older ones. This disparity leads to another form of data chaos – lack of comparability.

Many may question – “Does this mean I need to trash all the historical data?” Discarding historical data is wasteful and it prevents meaningful comparisons that reveal true performance over time (e.g., comparing this year’s results to last year’s to assess improvement). Thus, Equalizing metric and data is essential to ensure full comparability, regardless of the scale or frequency of data changes.

The Challenge of Data Changes

Reporting hierarchy adjustments are perhaps the most common casus of data disruption across companies. Examples include:

• Retail: Moving Baby Formula products from Health & Wellness division to Baby Goods division
• Food & Beverages: Moving Croissants category from Pastry division to Bread division
• Banking: Moving Home equity lines from Mortgage division to Line of Credit division

Tracking these changes can indeed be quite challenging. It is common to find situations where some metrics and data sources accurately reflect the changes, while others are not updated due to oversight or lack of communication. This can lead to incomparability, resulting in artificial step changes or false signals in data trends.

This challenge is amplified when dealing with numerous reporting hierarchy adjustments, alongside multiple metrics and data sources.

Fusion’s Equalize Insights AI Engine focuses on:

• Central Mapping: When everything is mapped directly to reporting hierarchy but reporting hierarchy is often changing, this means everything needs to be remapped every time there is a change. Thus, what we need to do is map all metrics and data sources to a middle layer that remains stable – a central map. Therefore, updates only need to be made to between reporting hierarchy and the central mapping, ensuring consistency across the metrics and data sources without the need for extensive remapping.
• Realign to the Right Base Values: With vendor, methodology or definition improvements, these can change the metric/data values for the better. Using AI modelling, Fusion’s engine processes these changes through Filtering, Unifying, and Synchronizing steps to evaluate whether the new values offer better quality. This assessment empowers data users to decide whether to adopt the new values or maintain the existing base values based on their specific needs and objectives.

Example of Equalize metric with methodology change:

Benefit’s of Fusion’s Equalizing AI Engine

• Reliable Performance Tracking: Ensure all metrics and data trends remain consistently comparable for executives and data users, facilitating confident decision-making with trusted performance measurements.
• Continuous Improvement: Enhance metrics and data quality seamlessly without disrupting reporting. Once improvements are validated, integrate them into the ecosystem smoothly, providing executives and data users with reliable insights free from artificial step changes.
• Eliminate Distractions: Gain confidence in trend movements by eliminating false signals, reducing uncertainties and debates during decision-making based on metrics and data.

The Power of Visualizing Decision-Led Metrics

Raw Data Lakes need to be transformed into Decision-Led Metrics through Filtering out data noise, Unifying One Version of the Truth, Synchronizing all the pieces into a decision-driven framework, and Equalizing dynamic insights to maintain comparability at all time. Once F.U.S.E., Visualizing metrics through a Decision-Led dashboard empowers faster decision-making, as everything you need will be at your fingertips.

If you’re tired of battling unreliable data and its negative consequences, Fusion Analytics is here to assist. Let’s collaborate and uncover meaningful insights that foster confident decision-marking.

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