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April 2024

InFullBloom Archives


Speaking Engagements

Predict and Prepare sponsored by Workday 12/16

The Bill Kutik Radio Show® #171, 2/15
The Bill Kutik Radio Show® #160, 8/14
The Bill Kutik Radio Show® #145, 1/14
Workday Predict and Prepare Webinar, 12/10/2013
The Bill Kutik Radio Show® #134, 8/13
CXOTalk: Naomi Bloom, Nenshad Bardoliwalla, and Michael Krigsman, 3/15/2013
Drive Thru HR, 12/17/12
The Bill Kutik Radio Show® #110, 8/12
Webinar Sponsored by Workday: "Follow the Yellow Brick Road to Business Value," 5/3/12 Audio/Whitepaper
Webinar Sponsored by Workday: "Predict and Prepare," 12/7/11
HR Happy Hour - Episode 118 - 'Work and the Future of Work', 9/23/11
The Bill Kutik Radio Show® #87, 9/11
Keynote, Connections Ultimate Partner Forum, 3/9-12/11
"Convergence in Bloom" Webcast and accompanying white paper, sponsored by ADP, 9/21/10
The Bill Kutik Radio Show® #63, 9/10
Keynote for Workforce Management's first ever virtual HR technology conference, 6/8/10
Knowledge Infusion Webinar, 6/3/10
Webinar Sponsored by Workday: "Predict and Prepare," 12/8/09
Webinar Sponsored by Workday: "Preparing to Lead the Recovery," 11/19/09 Audio/Powerpoint
"Enterprise unplugged: Riffing on failure and performance," a Michael Krigsman podcast 11/9/09
The Bill Kutik Radio Show® #39, 10/09
Workday SOR Webinar, 8/25/09
The Bill Kutik Radio Show® #15, 10/08

Keynote, HR Tech Europe, Amsterdam, 10/25-26/12
Master Panel, HR Technology, Chicago, 10/9/012
Keynote, Workforce Magazine HR Tech Week, 6/6/12
Webcast Sponsored by Workday: "Building a Solid Business Case for HR Technology Change," 5/31/12
Keynote, Saba Global Summit, Miami, 3/19-22/12
Workday Rising, Las Vegas, 10/24-27/11
HR Technology, Las Vegas 10/3-5/11
HR Florida, Orlando 8/29-31/11
Boussias Communications HR Effectiveness Forum, Athens, Greece 6/16-17/11
HR Demo Show, Las Vegas 5/24-26/11
Workday Rising, 10/11/10
HRO Summit, 10/22/09
HR Technology, Keynote and Panel, 10/2/09

Adventures of Bloom & Wallace

a work in progress

Lies, Damns Lies, and Metrics – – With Apologies To Mark Twain – – Part IV

By now you’ve either decided that you NEVER want to hear another word about HRM/HRMDS metrics, or your metrics spreadsheet is ready to roll.  You’ve used the highest level processes of the HRM domain model, mine or yours, as the columns and a metrics taxonomy, mine or yours, arrayed as the rows.  What’s next is to decide on the actual metrics, along with their target values and the time periods across which we’ll budget/forecast and then measure them.  Before you conclude that I’m even zanier than you’ve heard, rest assured that we are not going to fill in all or even most of the cells.  We could do that, but the effort would far outweigh the benefits, and we would have turned analysis paralysis into an art form.

Instead, we’re going to focus on the critical few, on just those metrics (if you’re an end-user organization) that are VERY important to the achievement of your organization’s business outcomes, to the running of your HRM business and the operations of your HRM delivery system (HRMDS).  This does presume that your organization has well-defined business outcome metrics, target values and time frames and that you’ve already drawn a line of sight from them to the HRM outcomes that are critical to achieving them, but we have to start somewhere.

If you’re the operational leader of an HRM shared services organization within an end-user organization or are the operational leader of an HRM BPO provider, you may expand the critical few to focus on the metrics you must have to run the factory, i.e. to run your delivery of HRM processes as efficiently, effectively and profitably as possible.  And if you’re an HRM software vendor whose products are used by both types of customers, you’ll have to consider everyone’s needs in your product and analytics strategy.

We’re also not going to get into a snit about what’s strategic and what’s administrative because we’re going to use a very simple business rule to make that distinction.  If the HRM process under discussion has a direct impact on increasing business revenues and/or materially impacting business profits, then it’s strategic.  If not, however worthy, difficult and important to the organization, it’s administrative.  Shortening the time from known need for another salesman until a new salesman is fully productive is very strategic.  Shortening the time from the end of a pay period until that payroll is fully distributed is very administrative, albeit a worthy goal.  Shortening the time to zero between release of a new product and having a suitable sales incentive plan operational to support that product roll-out is very strategic.  Shortening the time to zero between an employee wanting to request leave and their having done so is very administrative — although the design of the leave plan might be strategic if it allows the firm to recruit more effectively among specific, desirable populations.

Rather than wasting one moment of your time debating what is or isn’t strategic by HRM process, you can always collapse the metrics categories from the twelve shown in part III of this series of posts to just six and then, as needed, expand them again later.  And for purposes of explaining each of categories, I’m going to do just that.

HRM administrative and strategic process activity metrics — produced as a natural byproduct of conducting the underlying administrative or strategic processes, these are the familiar who did what, at what cost, with what volumes, and with what elapsed times.  They describe what happened.  They don’t describe why it happened, what business results were produced, whether it happened in the best way, nor in what way and how well these activities contributed to the achievement of essential HRM or business outcomes.  With respect to industry benchmarks, these are the most easily available, especially for the more administrative aspects of HRM processes, and they are often used (although weakly, in my view) in developing the business case for investments in HRM and the HRMDS as well as (correctly) the starting point for finding direct cost savings.  With respect to outsourcing, these types of metrics are often (with mixed results) the starting point for developing service level agreements, but they are totally insufficient for ensuring that business outcomes are met.  These metrics tell us how much it costs to hire and how long it takes to hire but not whether or not we’re making the right hires or how to attract those right hires.  They say how many “paychecks were cut” and how many hours after the close of the pay period they were “cut,” but there’s nothing here about their accuracy or, more importantly, the behavioral impact of our various compensation and benefit plans.  Activity metrics tell us how many hours of training were taken, how many safety incidents were reported, how many electronic resumes were received, how many call center calls were received, etc.

HRM administrative and strategic process outcome metrics — far more powerful than process activity metrics, outcome metrics begin to get at the real reason for doing HRM processes, and the real emphasis for an HRM software vendor’s or outsourcing provider’s analytical “pitch” is likely to begin here, especially with the more strategic aspects of these processes and the related metrics.  Benchmarks are available for some of these metrics, but they tend to be from the proprietary sources of various vendors and consultants.  However, as the outcomes become more important to measure, it becomes harder to find good benchmarks, and our best benchmark may be our own improvement over time in those areas that are critical to achieving our business outcomes.  Much more analysis, including trending and/or data mining, is needed to categorize these outcomes as desirable within the larger business context; that’s where the next group of metrics begins it’s work.  These metrics include the number of new hires (but not their quality), attrition rates (but not whether it’s good or bad attrition), payroll errors (but not the source or impact of those errors), the number of background checks completed with only driving violations (but no indication of to what extent driving violations are cause for concern), etc.

HRM administrative and strategic process activity pattern recognition metrics — these are the metrics used to begin to diagnose process issues.  Are the volumes indicative of desirable program utilization or of under- or over-utilization in the face of program design flaws?  Are the number of safety/health incidents showing a day/time pattern, a pattern related to changes in work rules or total compensation plans, a pattern related to labor relations negotiation schedules?  Are there patterns in the volumes, types, and/or timing of HRM grievances/complaints that point to problems with specific programs, practices and/or individual managers?  This is where we begin to look at the processes in order to understand why what is happening is happening, and whether or not it’s desirable.

HRM administrative and strategic process outcome pattern recognition metrics — looking for patterns in the outcomes is investigative reporting.  Given specific levels of turnover, are they good or bad?  Well, it depends: low turnover among poor performers is bad; low turnover among good performers is good; high turnover among poor performers is good; and high turnover among good performers is bad.  To find causal factors, these outcome patterns point the way, e.g.: do all the workers who have been hired by manager X perform at a higher than average level?  Is there something special about X’s selection process or management style?  Is there something special about X’s applicant pool or the nature of the work being done?   The real purpose of business outcome metrics is to get at the causal factors around excellent outcomes and then to design processes and business rules that achieve those excellent outcomes consistently and by everyone.

HRM administrative and strategic process activity and process outcome pattern prediction metrics — predicting what patterns, predicting what outcomes, especially what business outcomes, will be produced under various scenarios, whether for administrative or strategic processes, is the holy grail in business outcome metrics, but it is nearly impossible to generalize examples of these metrics.  The types of metrics that help predict future patterns in administrative or strategic process outcomes are those which are early enough in a complex process to be early warning signs for what patterns will come later.  For example, if there’s a well-defined campus recruiting process, it’s pretty obvious that, if not enough students are seen during a campus visit, there won’t be enough invited back to lead to enough offers etc.  But a more subtle predictor of the success of a campus recruiting program is the number of students who present themselves during the campus visit who have a demonstrated interest in, familiarity with and preparation for the work that the organization does.  Rather than having a full schedule during the campus visit but with students who may or may not be likely prospects, is it far better to have a lighter schedule but with very high quality prospects?

The bottom line.  We’ve only scratched the surface on metrics here, but we now have a structure within which to consider, for a specific end-user organization or for an HRM software vendor’s product planning, which metrics would make the most sense and to trade off metrics complexity/difficulty against their value.  Enough about metrics for now.

5 comments to Lies, Damns Lies, and Metrics – – With Apologies To Mark Twain – – Part IV

  • Mark Cruijff

    Hi Naomi,

    I keep on getting back to your fantastic writings on metrics/analytics and often refer to them as a best practice. Unfortunately several of the links to your diagrams and models don’t work anymore. Would be fantastic if these links can be restored.


    Mark Cruijff
    HRIS Manager

  • Wendy Tandon

    I worked for a software vendor several years ago that built and sold a great tool they called their Metrics module. If clients could merely define what they needed to measure, the system would either extract the outcomes from within the product, or provide an import mechanism to store the measurements. Once the data had been extracted or imported, it could be rendered graphically on manager dashboards. It was brilliant in demos and generated extraordinary interest by prospects who signed up in droves. The only problem, much to the dismay of management, was that no one EVER implemented it. Not a single client ever got past the “define what you need to measure” step. Desperate for case studies, product management was told to just put in any “canned” metrics we could automatically create. As you point out, however, these were the metrics of the least value. Thanks for putting together an article that provides some excellent insight and action steps for getting past the definition stage. No small feat.

    • Naomi Bloom

      Wendy, thank you so much for validating my own sense that HR folks really need help here. No reason you would know this, but one of the components of my widely licensed HRM Business Model “Starter Kit” is a metrics “starter kit” with literally hundreds, perhaps a thousand metrics, with suggestions across all of the processes mentioned and in all of the categories of the metrics taxonomy except for the highest order metrics which must be done situationally rather than generically. The good news is that this is an area getting ever more attention from the HRM literature and from the HRM software/services vendors, so I’m hopeful.

  • Naomi Bloom

    Steve, thanks so much for your support over the last year to my journey into the world of social everything. Now that the blog is launched, I hope that I can deliver the high quality, useful content, which is its primary purpose (at least for now), while sharing my professional journey with those who are interested. Over time, I suspect the blog will become an outlet for more than my professional journey, that that’s a “use case” I’m still exploring.

  • This is excellent information and thanks very much for sharing it here. You did a fantastic job of breaking down the various types of metrics that are commonly discussed, and organizing them into meaningful categories. This was an outstanding and valuable series of articles.

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