Friday, May 21, 2010

20 things you should never short-change when buying/implementing HR Technology

1. the “what's in it for me” perspective of each class of user; e.g., employees, applicants, line managers, executives
2. considering the downside of “imposing across-the-board standardization” when it unduly compromises other key business objectives
3. the change management effort in planning & executing the implementation
4. the training effort in planning & executing the implementation
5. the process & technology integration effort in planning & executing the implementation
6. subscribing to the “trust but verify” approach with respect to vendor / product claims
7. IT buy-in and having their criteria for support understood and transparent
8. end-user buy-in and having their criteria for support understood and transparent
9. exec buy-in and having their criteria for support understood and transparent
10. leveraging your company’s brand / value as an end-customer in making expectations known to your vendor partner; e.g., expectation to have some input to product direction or priorities if possible/practical
11. your organization’s previous experience with new technology adoption and roll-out
12. critical linkages between the various pillars of the Talent Management value chain, including those that are “focus areas” more than processes; e.g., employee engagement
13. internally marketing the benefits of implementing the new HR/HCM system or module --- before, during and after the system is implemented
14. the importance of “quick wins” to create support and momentum in the early stages
15. the importance of end-users being in control of (and being accountable for) data quality
16. focusing on business drivers, how they might be changing over time, and how the HR/HCM system aligns with those drivers
17. lessons learned from similar companies with similar implementations
18. the contingency plan for transitioning away from each HR/HCM vendor you partner with
19. creating & maintaining a “risk and opportunity” log from before Day 1; i.e., during the planning stage --- thru post-implementation
20. using a meaningful decision-support process and tool for prioritizing system enhancements needed -- or (if there's no other viable options) customizations pursued

Monday, May 3, 2010

Financial impact of data-driven workforce decisions --- MIND THE GAP!

To illustrate the bottom line business impact of making optimal workforce decisions based on properly analyzing data --- and data relationships, here's one example that most companies face all the time:

For every gap in workforce capacity ... either in terms of numbers, skills, competencies and/or physical location, there are 5 viable options:

(1) train an incumbent to address the gap
(2) re-deploy another employee ...
(3) promote another employee ...
(4) hire a regular employee ...
(5) hire a contractor ...

Taking a recent benchmark from Staffing.org on the average fully-loaded cost of hiring an exempt (non-executive) employee (= approximately $12,000) ...

Consider an organization with 500 exempt-level 'workforce gaps' to address in the course of a year that is not in a position to -- or by force of habit doesn't -- make data-driven workforce decisions.

Let's assume for this example that the 500 workforce gaps are addressed as follows (excluding the cost of labor):

- 80% or 400 gaps were addressed by an external hire (400 x $12k = $4.8 million)
- 20% or 100 gaps were addressed by an internal redeployment, half of which (or 50)created other (cascading) gaps to fill (50 x $12k = $600k)
- None of the gaps were addressed by training as it was not considered an option
- None of the gaps were addressed by hiring more costly contractors

So in this fairly typical example, the total cost of addressing the 500 workforce gaps is $5.4 million -- excluding the cost of labor itself.

Now let's further assume that IF the appropriate data -- and data relationships -- were analyzed so as to optimize each individual workforce decision, the breakdown would have looked like this:

- 40% or 200 gaps were addressed by an external hire (200 x $12k = $2.4 million)
- 40% or 200 gaps were addressed by an internal redeployment, half of which (or 100)created other (cascading) gaps to fill (100 x $12k = $1.2 million)
- 20% or 100 of the gaps were addressed by training an incumbent at an average cost per training instance of $2,000 (100 x $2,000 = $200k)

So in this decision-optimized example, the total cost of addressing the 500 workforce gaps would be $3.8 million -- excluding the cost of labor itself.

The difference -- $1.6 million ---- for EVERY 500 workforce gaps to fill.

A large organization of 10,000 employees would likely have at least 1,500 workforce gaps to fill annually ... so they would enjoy a cost savings of approximately $5 million!!!

Based on many years in and around HR functions, I believe this example is quite plausible and realistic in highlighting the benefits of a data-driven decision process in HR.

As they say in London --- "Mind the Gap!"