Taloflow
  • Introduction
  • Getting Started
  • How it Works
  • TCO 💵
    • Object Storage Assumptions
    • Cloud Usage History
  • 📝Other
    • Security
    • Authorization and Permissions
    • Status
    • Privacy Policy
    • Terms of Service
Powered by GitBook
On this page
  • How the Evaluation works
  • Product Scores
  • Product Ranking
  • Impact

Was this helpful?

How it Works

Here's an overview of the logic behind Taloflow evaluations.

PreviousGetting StartedNextObject Storage Assumptions

Last updated 1 month ago

Was this helpful?

How the Evaluation works

The Evaluation is comprised of configurable features and requirements tables, scores (and rankings) for products, and a collaborative text editor experience to help you whittle down requirements and features, and various types of blocks to show the data.

Product Scores

All products are rated on all Requirements, Dimensions, and Features.

Features are the components that make up Requirements and Dimensions. For example, a Requirement like "Must integrate with our current stack" could include Okta integration and PagerDuty integration as features, and any number of individual Features can map one-to-many to Dimensions.

Requirements and Features have 4 possible priority settings:

  1. Critical

  2. Important

  3. Nice To Have

  4. Don't Care

Products can have the following ratings for Requirements and Features:

  1. Great

  2. Good

  3. OK

  4. Poor

  5. N/A

The weights assigned to Requirement Categories (e.g., Integration) also impact the overall product scores.

Product Ranking

The product ranking is a simple order of the products based on their score plus using Critical-rated features as a threshold function. You may get a product ranked higher despite having a lower score due to this.

Impact

Impact by Requirement or Impact by Requirement Category are calculated by looking at the standard deviation. You may have 5 features that are Critical but have every product rated the same, whereas 5 features that are Nice To Have could show a lot of variance between products, in which case the Nice To Have's have more Impact.