As a result of my blogs and customer conversations, I receive a variety of interesting comments and feedback from my contacts in the People Analytics space. A common topic is that different stakeholder groups within a People Analytics project have vastly different ideas as to what is acceptable in a People Analytics tool. This often leads to disappointment, failed initiatives and wasted budget.Examples provided are that LOB (Line of Business) and general HR professionals tend to be attracted to and satisfied with "Convenience Analytics". Convenience Analytics is a term referring to simplistic, easy to digest metrics or reports. They are typically generated without much effort, often by the source system, but are limited in breadth, depth, and growth possibilities. The appeal of Convenience Analytics may be their low-cost of entry and their non-threatening nature to the decision makers that use them, but they are extremely inflexible.
Significant challenges occur when Convenience Analytics are deployed to an organization expecting deep insights, growth of use-cases, or the addition of new data sources. The People Analytic and HRIS (Human Resource Information System) professionals supporting these Convenience Analytics projects ultimately suffer from a lack of long-term data quality and a capability to drive future insight that is uniquely strategic to their organization and not a pre-canned report.
One Model recognizes that a properly constructed People Analytics infrastructure has a system agnostic HR Data Strategy, and this has driven our industry leading Data Orchestration capabilities.
Data Orchestration is a process that takes siloed data from multiple locations, combines it, and makes it available for data analysis. One Model breaks Data Orchestration into 4 activities/phases:
- Data Ingestion – This phase is the process of removing data from source systems and delivering it into One Model. We take a flexible approach and accommodate strategies ranging from API extraction, to file based transfer over SFTP, to manual uploading of data through the One Model interface.
- Data Modeling – After data is ingested, it is combined into a single, interconnected data model that supports a broad range of analytics. Taken together with the ingestion phase these activities constitute ETL (extract, transform and load) activities. This results in what is recognized as a fact and dimension star schema style of data model.
- Data Quality – This phase is driven by rules and logic. As a result, quality issues in source data begin to surface. These issues are captured and resolved during this time.
- Data Destinations – This phase is the scheduling of data exports out of the One Model system and delivering them to SFTP sites, Amazon S3 buckets, and/or other destinations. This reflects the vision of our company; not to be the ultimate destination for your data but a data asset existing amid your analytics infrastructure feeding downstream system and tools.
Data Accessibility is a noteworthy benefit of One Model's Data Orchestration process. A customer is not restricted to accessing their data only through our query engine. Access is also provided to your orchestrated data directly in the data warehouse hosted on AWS. This allows the usage of your own tools like Tableau, Looker, Qlik, etc. for presentation purposes. Additional benefits include being able to run your own integrations or internal application development against a clean, comprehensive data set to solve challenges specific to your organization.
Let us look at two of the most popular HRIS systems and some of the data orchestration advantages One Model offers.
Workday - Workday uses point-in-time (snapshot) based reporting. This snapshot reporting is recognized as being limited and brittle in accommodating backdated changes and other HR analytic scenarios. External data is difficult to connect with and pulling and maintaining snapshots from Workday is a pain. One Model avoids all issues with snapshot reporting by rebuilding a data schema that is effective dated and transactional in nature. The result is a dataset perfect for delivering accurate, flexible reporting and analytics. We support both full and incremental refreshes of data from Workday.
SAP SuccessFactors - One Model has pre-built data processing logic that can be used to transform data from various SuccessFactors objects into a well-organized, effective-dated structure that supports a wide range of analytic use cases. The SAP SuccessFactors API allows us to identify customizations in your SuccessFactors configuration -- and our data model readily supports the inclusion of those custom fields in the resulting data model. We support both full and incremental refreshes of data from the SuccessFactors API.
One Model has perfected data orchestration so well that we are often included in searches for integration partners. Our tailored solution enables the accurate transfers of large files of complex data from existing tools such as an ATS into new, replacement tools. This creates tremendous possibilities for efficiency in migrations and adoption of new technology.
If you are interested in receiving full value from your People Analytics investment, please click here to reach out to One Model to schedule an in-depth discussion.
Listed below are links to various articles that provide further insight into this topic.
- The end Snapshot Reporting for People Analytics
- The need to build Structural Views of SAP SuccessFactors Data
- People Analytics for SAP SuccessFactors
- Using People Analytics to support system migration