Data Quality Intuitively comes along with TimeTec HR Analytics
The quality of data is a prerequisite for a meaningful data analytics deployment. Characteristics of Data Quality are accuracy, completeness, consistency, uniqueness, and timeliness. Without Data Quality, data analytics process might paint a false picture and risking the companies to make wrong decision.
The few elements contribute to Data Quality:
Accuracy: a company has to cross-check data with the source. If there is no data lineage, the accuracy is always questionable.
Completeness: It doesn’t mean all data source, but it must adhere to the business requirements, especially those data is used for KPI measurement.
Consistency: If data is flowed to multiple applications, it must have the same properties and not conflicting each other. For example, if the date format is DDMMYYYY, make sure it should be the same across all applications.
Validity: It should follow the business rules and parameters. For example, if the amount rounds up after 2 decimals, then it should.
Uniqueness: There must be no duplication of data.
Timelines: Data must be available when promised.
There are quite some methods suggested by data experts to improve Data Quality, among them: Data Profiling, Data Standardization, Data Geocoding, Data Matching and Linking, and Data Quality Monitoring.
To ensure Data Quality is kept, organizations have to maintain a Data Life Cycle, which involves the processes:
1. Find data through root cause analysis
2. Investigate data
3. Find potential causes
4. Perform root cause analysis
5. Apply correction
6. Monitor by continuous improvement monitoring
7. Sustain by applying fixes on sources or closest to source
Hence, to achieve Data Driven Organization is easier said than done. Since data itself generates further data, especially when raw data go into applications generate and regenerate much meaningful data, solution providers who have the capability to provide data analytics services should be the better choices for companies that take data seriously and have the plan for data transformation.
TimeTec HR Analytics comes as an option module for TimeTec HR suite, for companies to continue to complete the data journey to save cost and time, without the pains and the needs of hassle and data life cycle measures as mentioned above to upkeep the data quality. The data quality flows intuitively in a lineage form along with the applications to readily prepared templates for easy visualization and benchmarks reference.
HR analytics is the collection and application of talent data is to improve critical talent and business outcomes. TimeTec HR analytics enable business owners to develop data-driven insights of their talent pool, improve workforce processes and promote positive employee experience.
Instantaneous Data Crunching & Data Visualization to provide 360° on:
- Employee statistics and profiles
- Turnover & Retention Rate
- Salary and career path history
- Staff Performance
- Demographic data
- Leave pattern
- Claim pattern
The Benefits of TimeTec HR Analytics:
1. Improve talent acquisition
2. Increases talent retention
3. Prevent workplace misconduct
4. Increase productivity
5. Uncover skill gaps
6. Improve employee experience
7. Build highly engaged workplace
8. Reduce attrition rate
9. Machine learning spots the patterns that you might miss