Has anyone ever realized the major reasons for any HRMS cloud solutions Implementation failure during the testing phase? That’s, majorly because of the data. You don’t always have control over the format and type of data that you import from an external data source, such as a database, text file, or a Web page. Before you can analyze the data, you often need to clean it up and ensure that you understand the same thoroughly.
Below mentioned are a few important points that could help any organization in successful HCM implementation.
- Defined organization structure – Organizational structure provides guidance to all employees by laying out the official reporting relationships that govern the workflow of the company. It is important for the company to understand the various levels in which the company is divided across units and locations. It is also important to understand how the employees are tagged across different bands/ roles and designations. Based on this, there are different rules and policies which are configured in any HRMS solution.
- Ensure data profiling – Data profiling is all about understanding your data. One should know where the data comes from: spreadsheets, backend systems, or sticky notes all over reps’ systems. One should list down all the data sources and the names of the fields in which data is stored and keep a track of potential problems with the data.
- Ensure data accuracy & Security – Keeping data secure is ensuring that the right users have access to the right information, which also means blocking access, as needed. To ensure that the data is accurate, one first need to clean the data by removing duplicates and errors, and then set up processes and use technologies to keep it clean. Data which is of the highest priority should be cleaned first. Also, there should be periodic exception reports which needs to be sent to users reminding them of missing information. One should review the role hierarchy and make sure the hierarchy, teams, and groups are kept up to date. Activities like spell check, removing duplicate data, changing the case of the text, removing spaces and non-printable characters, validating data formats like date, etc. can be performed to ensure that the accuracy quotient is maintained.
- Target data centralization – Most of the organizations have data getting resided on multiple systems. Information flows from different teams like finance, Admin or central CRM etc. Before one plans to implement any SaaS based HRMS solution it makes it more important for the organization to understand the information flow and have larger understanding of the IT map. One should even evaluate aspects like which system will act as the base system for storing all the information across different systems to ensure single version of truth.
- Monitor data regularly – Ensure a high quality, effort free data is not just a one day’s job. It requires persistent efforts and regular audits and processes to ensure that the data quality is intact. One should have a centralized process for maintaining and monitoring the data updates. There should be processes and workflows created to ensure that the correct data is being captured. Tools like macros should be used to ensure that the quality is maintained. Also, there should be periodic exception reports which needs to be sent to users reminding them of missing information.
Bad data is bad for business. Achieving and maintaining high-quality data requires vigilance, good processes, and a little help from technology. Once ensured the organizations can target to move ahead in their digital HR journey by implementing a SaaS based HRMS solution.
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