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Understanding Betterteem Analytics and Benchmarking

Betterteem Data Science

Betterteem is a cloud-based employee experience platform designed to collect and store user information and responses via pre-designed and psychologically vetted employee experience questions. Our automated big data analytics and algorithm work on raw data and transform them into digestible pieces of information that provide business leaders with insights on the overall state of employee experience in their organization.

Data Security

Ensuring the protection and security of our data is paramount for protecting the privacy of our users. Our data is stored using the comprehensive security frameworks that our third-party cloud service providers put in place. Combined with the extensive security protocols implemented by our cloud partners, we deploy robust data-security processes across our networks to maintain the integrity of our data management system and compliance with data regulations.

Raw Scores versus Benchmark Scores

The Betterteem employee experience results are typically presented in two different ways: raw scores and benchmark scores.

Raw Scores are data sets that we derive from the average off all responses collected in our platform. We use a 5-point rating scale in collecting these raw scores, where the lowest raw score is a 1, and the highest raw score is a 5. To identify whether the raw score is good or bad, we compare these raw scores to the results received by other organizations in the Betterteem ecosystem.

Betterteem benchmark adapts to the T-Scores principle to eliminate the natural variations between survey questions and effectively determine whether an organization's scores are good or bad.

Anonymity

The primary goal of Betterteem is to collect actionable data, which is driven primarily by anonymity across our platforms. Even if a participant uses our web or mobile platform to answer a question, their identity will remain anonymous. Betterteem commits to the highest standards of safeguarding the identity and data of our users.

We find this approach helpful to people leaders as it promotes greater disclosure of sensitive or stigmatizing information than non-anonymous methods. Our experience also confirms that employees who are concerned that their identity could potentially be linked to their answers are less likely to complete a survey designed to obtain feedback.

T-Scores tell an organization how they perform compared to their competitors in the BPO sector.