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Storage Optimization metrics and KPIs

What are Storage Optimization metrics?

Crafting the perfect Storage Optimization metrics can feel overwhelming, particularly when you're juggling daily responsibilities. That's why we've put together a collection of examples to spark your inspiration.

Copy these examples into your preferred app, or you can also use Tability to keep yourself accountable.

Find Storage Optimization metrics with AI

While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI metrics generator below to generate your own strategies.

Examples of Storage Optimization metrics and KPIs

Metrics for Monitor data growth accuracy

  • 1. Total Data Volume

    The total amount of data stored in a database or system, measured in gigabytes or terabytes

    What good looks like for this metric: Evaluated monthly; varies by industry

    Ideas to improve this metric
    • Regularly audit stored data
    • Use data compression techniques
    • Implement data archiving policies
    • Evaluate data storage solutions
    • Automate data clean-up processes

  • 2. Growth Rate of Data Volume

    The percentage increase in data over a specific period, typically month-over-month

    What good looks like for this metric: Generally should not exceed 5% monthly

    Ideas to improve this metric
    • Review data input processes
    • Set growth targets
    • Analyse growth trends
    • Identify unnecessary data accumulation
    • Implement stricter data entry policies

  • 3. Percentage of Duplicate Records

    The proportion of records that appear more than once in a database

    What good looks like for this metric: Aim for less than 1% duplication

    Ideas to improve this metric
    • Use data deduplication tools
    • Standardise data entry fields
    • Conduct regular data audits
    • Train staff on data entry
    • Implement unique identifiers

  • 4. Data Accuracy Rate

    The percentage of data that is correct and free from error

    What good looks like for this metric: Should be above 95%

    Ideas to improve this metric
    • Conduct regular data quality checks
    • Provide data entry training
    • Utilise automated validation tools
    • Standardise data formats
    • Implement error logging

  • 5. Record Completeness Rate

    The percentage of records that have all required fields filled out

    What good looks like for this metric: Should remain above 90%

    Ideas to improve this metric
    • Ensure all required fields are filled
    • Review and update data entry templates
    • Implement data input checks
    • Improve user data input interfaces
    • Incentivise complete data entry
data-accuracystorage-optimizationdata-analystdata-quality-managerdata-management-teamit-infrastructure-team
Implement these metrics

Tracking your Storage Optimization metrics

Having a plan is one thing, sticking to it is another.

Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to keep your strategy agile – otherwise this is nothing more than a reporting exercise.

A tool like Tability can also help you by combining AI and goal-setting to keep you on track.

Tability Insights DashboardTability's check-ins will save you hours and increase transparency

More metrics recently published

We have more examples to help you below.

Planning resources

OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:

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