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Twelve HCM system changes that affect analytics

Here's an in-depth look at 12 changes you might make to your human capital management system that are likely to affect your HR-related analytics data and reporting.

As a human capital management administrator, you fine-tune and manage enhancements to your HCM system to improve...

usability and increase user adoption.

However, the effect of HCM system changes on analytics is not always evident. Sometimes, what might seem like a small change to a process or form can create inconsistencies farther down the line, such as in reporting. With your investment in developing a good analytics tool, both in terms of time and money, you want to ensure you can mitigate HCM system changes that will affect your analytics tool and what your end users have come to expect.

Some of the more common HCM system changes that affect analytics include the following: system values relabeling, new system values, module or product replacements, form-fields elimination, HR process changes, new modules and database changes. In addition, there are also organizational and company changes that require HCM system changes that may have an effect on your analytics, including historical data importing for a new HCM system or module, company reorganizations, HCM integrations due to mergers or acquisitions, company dispositions or divestures and company expansion into new countries.

Here's more about these 12 HCM system changes that can affect analytics.

1. System values relabeling

This type of change occurs when you modify a value that gets associated with information such as an employee or a training record. One example is changing the value you use for a full-time employee in your HCM system from "FT" to "Full-Time." While both designations represent the same employee status, how they might appear in a report will be different. Depending on your analytics software, you may be able to map these types of changes so they appear in one consistent format.

2. New system values

At some point, you'll need to capture new data. This may be the result of new requirements, government regulations or business reasons. For example, you may have a picklist to capture the number of dependents an employee has. Initially, the list may go from zero to three, with a final value for "four or more." It may become important to know the exact number of dependents for all employees and replace the "four or more" value with additional numbers in the picklist. In this case, you would have existing employees with the old value and new employees with the updated values.

3. Module or product replacements

Replacing modules of your HCM system with new ones may have a big effect on your analytics. Despite the likelihood that a replacement module will capture similar data as the one being replaced, how the new HCM module stores its data in its database and how it is accessed will likely be different.

4. Form-fields elimination

Most HCM system modules and products utilize forms that capture data. As companies attempt to simplify processes, they may find it advantageous to remove certain fields from their forms. However, these fields may also play an important role in your analytics. For example, eliminating the candidate source from a recruitment form will help speed up the process for recruiters, but may have a negative effect on the analytics you have set up to measure the value of your recruitment sources.

5. HR process changes

Companies have many HR processes that support corporate and HR objectives. A common example is performance management. Suppose a company changes its process to increase or decrease the frequency of check-ins with employees. Measures that evaluated the percentage of check-ins that have performed at a given point in time may be skewed and may make it difficult to compare results from one year to the next.

6. New HCM system modules

Companies often incorporate new modules into their HCM environment over time as new requirements arise or financial resources become available. Until a new HCM module is acquired, companies may use features of an existing module as a stopgap measure. One example is capturing a minimal amount of training and development data until a learning management system (LMS) is acquired. Once the new LMS is implemented, all analytics that relied on the previous system will have to be updated to pull the new and expanded data.

7. Database changes

Most HCM applications will have a stable database configuration; however, if your organization uses custom applications or intermediary databases to store and aggregate data, database changes to optimize performance may take place. Database changes would likely have an effect on analytics, dashboards and reports.

8. Historical data importing

For your analytics to be consistent and reliable, you must not only recognize in advance the effect changes may have on your analytics, but also educate your audience as to what changed and why.

The manner and timing in which historical data is imported into a new HCM system or module may have an effect as it relates to analytics:

  • In some cases, all historical data is not loaded during a new implementation. For example, to ensure the go-live date is not jeopardized, data that is older or more challenging to import may be loaded at a later date. Once the historical data is loaded, it may cause a significant change in your analytics from one point to the next, especially in areas that look at data over an extended period of time.
  • Data conversion may also have an effect on analytics, since this process is often done across a large data set and may not catch every use case in a way that matches how the new HCM would capture the data. This can lead to data not appearing as expected or misrepresenting what is being reported.
  • When importing the data, shortcuts may be taken with the understanding that it will have a minimal effect, or it can be fixed later once the data has been imported. Changing historical data to fix issues after the system is live can cause analytics to change suddenly and without warning.

9. Company reorganizations

Companies often change their organizational structure to meet new business requirements; however, these changes can often have a big effect on analytics. One challenge may be the difficulty in looking for trends. For example, merging two departments may cause large spikes or declines in an operating group's headcount, turnover or other key metrics being analyzed as of a certain date.  

10. HCM systems integrations

Integrating different HCM systems due to mergers and acquisitions will have a significant effect on a company's analytics. As the HCM systems are integrated, employee data is normalized to meet a consistent standard, and your analytics are reconfigured to account for the new systems and data.

11. Company dispositions and divestures

While less of an effect than a merger or acquisition on your HCM and analytics, the disposition of a business unit or divesture of a company can result in a sudden drop in the resulting data, such as headcount.

12. Expansion into new countries

The expansion of your company introduces new challenges for your analytics, in addition to the changes that may be required to your HCM system. For example, language differences can affect systems and data, time-zone differences may determine when analytics are run, and data protection laws may affect who can see data for certain countries.

HCM system changes require communication

Organizations rely on analytics to provide key information on their talent, processes and organizational goals. As enhancements and improvements to your HCM system environment take place, there may be an effect on your analytics. These must be considered to ensure your audience understands why certain numbers changed dramatically from one day to the next, or when quarter-over-quarter or year-over-year comparisons are significantly different. For your analytics to be consistent and reliable, you must not only recognize in advance the effect changes may have on your analytics, but also educate your audience as to what changed and why.

Next Steps

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This was last published in September 2017

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Which changes to your HCM system have had the most profound effect on analytics?
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#6 talks about adding modules. Since many HCM systems are in a single database environment these days, this shouldn't cause an upset in analytics. In fact, adding modules should improve analytics. More data = better reporting. I suppose if you're on a legacy system where adding a module means adding an additional piece of software, that may cause problems.
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