Implementing a Data Analytics Program for HCM: 4 Tips
This article was updated on June 15, 2018.
Implementing a data analytics program is essential for today's financial leaders to successfully manage and forecast the organization's budget, especially the portion apportioned to human resources and human capital. The benchmarking and predictive analytics capabilities provided by these systems can enable you and HR leadership to determine if your organization has the right mix of people, understand how turnover for a specific job at your firm compares with industry peers and discover a cadre of other insights.
According to PwC, today's finance leaders are moving beyond traditional financial transaction management responsibilities. They now need to also ensure their company is implementing data analytics to drive a broader strategic direction for their firms. By adopting a comprehensive payroll and human capital management (HCM) system, an organization can scale up workloads, reduce staffing and streamline processes.
However, implementing such a program can be a daunting task. Here are four tips for simplifying the challenge:
1) Manage Expectations
Collaborate with HR leadership to develop a pilot program designed to prove the concept, work out any bugs and help ensure that results turn into true business benefits with a definable ROI. By managing pilot program expectations, others in the C-suite will not expect more than the pilot promises.
The pilot program, if designed properly, will provide proof-of-concept, making it much easier to implement a more comprehensive data analytics initiative. But if you don't properly manage expectations, further implementation could be delayed.
2) Use Clean Data
Management consulting firm ScottMadden points out that the data financial leaders use in any analytics pilot program needs to be clean — or free from errors. To verify the data is accurate, it is imperative to engage human capital management stakeholders, including HR management, payroll and others, in validating the veracity of your data. Prioritize the most critical data first, because a cleansing can slow or stop the pilot program. Check for inconsistencies and inaccuracies. The cleaner the data, the more reliable the results.
3) Test, Test, Test
Testing before implementation helps uncover any issues early. The testing should occur over several days, and be repeated for accuracy, to confirm if the HCM system has properly loaded data and that proper codes for deductions, etc., are being added to employee records. It's better to find and correct any problems at the testing phase rather than after implementation.
To be safe, operate new and old approaches in parallel for a short period to verify the new system is delivering the expected benefits without any unexpected glitches.
4) Seek Feedback, Collaboration
CFO Tech Outlook recommends soliciting feedback, both criticism and praise. Collaborating with HR at the outset will help ensure that even a small, pilot data-driven HCM effort will do as little as possible to disrupt part of the standard operating procedure at the organization. Yet some disruption is still likely. Proactively reaching out for this kind of feedback can help make sure you have the necessary intelligence to tweak systems and strategies to discover the right kind of insights to drive the success of the business, while also showing other organizational leaders that financial leadership values the input of the C-suite.
Data analytics will be increasingly important for finance leaders as technological capabilities continue to proliferate over time. By following these tips for implementing a data analytics program, you will be armed with properly calibrated tech resources and well-positioned to determine the most productive allocation of your human capital.
