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HR Tech, Las Vegas, 10/8-10/2014
HR Tech Europe, Amsterdam, 10/23-24/2014

PAST BUT AVAILABLE FOR REPLAY
Workday Predict and Prepare Webinar, 12/10/2013
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
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"Convergence in Bloom" Webcast and accompanying white paper, sponsored by ADP, 9/21/10
The Bill Kutik Radio Show® #63, 9/10
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Knowledge Infusion Webinar, 6/3/10
Webinar Sponsored by Workday: "Predict and Prepare," 12/8/09
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"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
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Keynote, HR Tech Europe, Amsterdam, 10/25-26/12
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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
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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

The Future Of HRM Software: Embedded Intelligence

Hi, I'm Naomi, your friendly HRM consultant

There’s an easy way to describe what I mean by embedded intelligence.  Conjure up a memory of the best, most knowledgeable, most effectively consultative and strategic thinking HR leader you’ve ever known.  Now conjure up a memory of that master of regulatory options and obligations, that HR administrator who really knows the innermost details of all your organization’s HRM policies, practices and plans and how to make them work for you.  Now imagine these two wondrous beings living inside your HRM software and bringing all of their KSAOCs to bear on whatever you’re trying to do or should be trying to do in the people management business.  That’s the spirit of embedded intelligence.  We could call her Naomi, your friendly and very knowledgeable HRM/HRMDS consultant “in a box.”    

If you’re an employee making what appears to be a simple change to your home address, Naomi would tell you, from inside the person indicative data processes of your HRMDS software platform, that:    

  • The new home address you’ve just input is simply incorrect (e.g. you’ve got a typo in your zip code or there’s no such street address) — and here’s how to fix it;
  • There are income tax withholding changes as a result of your new home address — and here’s what they are;
  • The HMO in which you’re enrolled doesn’t have jurisdiction at your location — and here’s what you need to do to select and enroll in a new HRO or other health care plan for which you’re eligible;
  • You’re no longer going to receive the mass transit subsidy to which you’ve been entitled because it doesn’t apply to your new location — and here’s the amount by which your gross and net pay will be affected. 

Naomi doesn’t just tell you what the issue/problem/error is, she takes you by the hand (really routing you through workflow) to the appropriate next steps in completing your business event, to include addressing all of the related ripple effects.    

If you’re a manager getting ready to interview a high profile candidate for a tough to fill position on your next generation software architecture team, then Naomi would tell you, from inside the staffing processes of your HRMDS software platform:    

  • All that’s known about this candidate — and what more you may want to know as a part of your evaluation of her;
  • Why the position in question is tough to fill, the efforts already made and the filling experience-to-date — and how you might adjust either the position attributes or the related total compensation entitlements of compete more effectively for these scarce KSAOCs (if they are indeed scarce);
  • What the KSAOC profile is of those working successfully in this type of position and what the desired KSAOC profile is for this particular position — and how you might adjust those profiles in light of available developmental resources within the organization;
  • What questions are best for getting at the specific KSAOCs which you’re seeking when used in an interview format — and what other interviewers have already asked and their notes on those responses;
  • What your own track record has been in making hire decisions in terms of the downstream performance and retention of those hires — and what you might consider changing in order to improve your hire decisions; and
  • What you may and may not ask subject to the regulations of the relevant geographic jurisdiction — and the list goes on. 

Embedded intelligence, AKA Naomi, replaces, in highly automated HRM delivery systems, the human intelligence that was inserted in much more manual HRM processes when you were lucky enough to have only the very best HR professionals at your disposal, when and where you needed them.   

There are many different types of intelligence that can be embedded, to include static and dynamic content, personalized and context-sensitive content, business rules and process knowledge, alerts and triggers, actionable analytics and benchmarks.  When considering how best to organize, prioritize, make investment decisions and then implement embedded intelligence, it helps to have some type of a taxonomy.  The one I use starts with the easy to do and gets progressively more difficult to accomplish as their impact on achieving business outcomes becomes more direct.  My embedded intelligence taxonomy is:    

  1. User inquiries to standard text; 
  2. User-initiated standalone data changes (with attribute, event and context edits) with generated inquiries to standard text; 
  3. User inquiries to personalized text;
  4. User-initiated standalone data changes (with attribute, event and context edits) with generated inquiries to personalized text;
  5. System-initiated distribution of standard text; 
  6. System-initiated distribution of personalized text; 
  7. Personal life, work life, or organizational life event initiated chain of event data forecasts and/or changes (with attribute, event and context edits) with generated inquiries to standard text; 
  8. Personal life, work life, or organizational life event initiated chain of event data forecasts and/or changes (with attribute, event and context edits) with generated inquiries to personalized text;  and
  9. External events with generated inquiries to standard or personalized text.

Then repeat all of the above, adding a strong advisory component, along with the relevant analytics, to each.   

What’s desired is intelligent (as to content, context, business rules, analytics and advisory), pro-active, organizational role (e.g. employee or position seeker or beneficiary) and work role-based self service (e.g. manager of a specific team regardless of the team manager’s home position or generic call center representative position).  It’s via embedded intelligence that we take self service from data entry to self sufficiency.    

Embedded intelligence replaces what we lost when we removed the best HR professionals from most interactions with individuals and managers/leaders (or removed them altogether) — their knowledge of business rules, good practice, context, agreed upon corporate culture, regulations, labor contracts, management preferences, business unit-specific considerations, etc.  It improves upon human embedded intelligence by also removing human inconsistencies, errors, misinterpretations, incomplete answers, dated information, biases, lack of availability, institutional knowledge lost through terminations or retirements, etc.  Automated embedded intelligence reduces greatly the organization’s exposure in all situations where evidence of having trained/told/confirmed the relevant rules/policies/regulations at “point of sale” is an important element in preventing and/or defending against unacceptable behavior by a member of the workforce.  Today, embedded intelligence is expected in any self service environment with those expectations set by commercial Web sites like Landsend.com, Amazon.com, and social Web sites like Wikipedia rather than by enterprise applications software.   

The business case for embedded intelligence includes:    

  • Further administrative cost savings, reduced compliance exposure and reduced cycle times — and this can make or break a shared services of BPO provider;  
  • Improved “customer satisfaction”;  
  • Increased business literacy for better decision-making;  
  • Improved business outcomes from total compensation expenditures;  
  • More effective deployment of KSAOC-rich non-employees;  
  • Improved career-management decisions and outcomes;
  • Improved productivity of individuals and groups;
  • Improved selection and retention decisions and outcomes;  
  • Improved HRM performance metrics and actions;  
  • Better definition and organization of work;  
  • Better definition and organization of work roles;  
  • Improved forecasting, modeling and development of needed KSAOCs;  
  • Improved generation, selection, deployment and retention of KSAOC-rich persons;
  • Improved generation, collection and deployment of organizational knowledge and social networks; 
  • Greater motivation of the workforce toward desired behaviors and KSAOC growth via targeted total compensation plans and work environment programs;  
  • Creation of a work environment that removes barriers to and encourages effective performance;  
  • More effective labor organization relations; and  
  • Better day-to-day coaching, mentoring, assignment, development planning and performance appraisal.  

If this sounds like embedded intelligence goes to the heart not only of improving the total cost and quality of service delivery but also of improving strategic HRM, which is critical to achieving organizational business outcomes, you’ve got it in one!  

So which HRM software/HRM BPO vendors are doing this well?  Great question.  Several of the benefits administration providers have embedded quite a lot of content within their benefits enrollment processes which can be passed through the HRM delivery system of their clients.  Several of the most established HRM BPO providers, in an effort to reduce the volume, time to resolve, exposure to errors, and cost to support call center traffic have also made a dent at the basics of transactional edits and some embedded content.  A few talent management software vendors have worked hard in this area, but most have neither the resources nor the expertise to get as far as they might like.  We are starting to see partnerships between major HCM consultancies and talent management software vendors whose purpose it is to embed the consultant’s intelligence within the TM software, at least for clients who sign up and pay for the enhanced capabilities.  And there’s a lot more coming if what I see cooking in the backrooms is a predictor.  With more and more similarities among the features/functions of the TM software vendors (although their actual capabilities, in terms of their applications architectures and foundational object models remain VERY different, and there are also big differences in their strategies/progress toward SOR/TM/social tech convergence as well as their process and global footprints), I believe that the push for embedded intelligence will be a source of considerable differentiation over the next many years.  Without Naomi “in the box,” HRM software has a long way to go to catch up with Amazon.

12 comments to The Future Of HRM Software: Embedded Intelligence

  • [...] intelligence — I’ve covered this in detail previously, but I want to emphasis here the importance of delivering actionable analytics along [...]

  • [...] in knowing how embedded intelligence can impact HRM software, I recommend you to read this great piece by Naomi Bloom (Thanks @SameerPatel for the link). Workday’s embedded intelligence feature will bring the [...]

  • I think there is a new breed of software evolving right now; most are going to web based web apps. These apps are very user based which means the makers are generally thinking of how the employees will use the web software into the design initially and not as a last minute thing topping to the cake. They treat the employee interactivity as the foundation.

  • Steve,

    You raise a really good point about the variation between different companies and how that effects what content they will find valuable and how they will use it. I think the most important shift software vendors will need to make/address is their connectivity to the Internet. Most don’t connect at all. There is far too much valuable data out there to ignore. For example, we recently released a WebLinks feature that uses REST get and post commands to connect with any website you wish. So for example, if I’m on a person record in my Avature system I can have a link to Pipl to see their online foot print, LinkedIN to see their profile, my HRIS if I want to see their record in that system (or if they have a record at all), Salary.com to compare their salary, FreePatentsOnline.com to see if they’ve filed any patents, and the list goes on. The beauty of it is that each customer can decide and easily build whatever links they want and they can do that for People records, Job records, or Company records (competitors). Where it gets tricky is that as soon as you import the data into your system from another it’s immediately in a state of decay. So there’s not much value in importing it when you can access it in real time anyway. That’s where a meta data component (user generated) like tagging comes into play where you can build a vocabulary around the information, segment it based on the meta data, and then execute Amazon-like service. e.g. People that made it to second interview stage in my recruiting workflow for jobs with these tags seemed to be tagged these ways so I want to market similar jobs to people with those tags. And when I do that I now know who responded, applied, got interviewed, etc. and have more meta data that I can use to refine my execution over time. The more data the better your service delivery.

    On a side note, I just want to point out that there are two sides to a transaction when we try to make a match. For Amazon that’s People:Books (or products). One side of that transaction – Books – don’t change much over time. However, for HR that’s People:People; a far more challenging and complex task.

  • [...] Naomi Bloom riffs on Embedded Intelligence. This stuff sounds completely awesome, but I can’t help but feel like we’re getting this much closer to Skynet from the Terminator movies. When is the software going to go against my gut instincts and hire people that I just don’t have a good feeling about? Next thing you know the HAL 9000 has locked me out of the office and has stolen my parking spot. I won’t stand for this!  (I know, HAL is from 2001, not Terminator) [...]

  • [...] From Naomi Bloom: The Future Of HRM Software: Embedded Intelligence [...]

  • ‘Getting on with it’ sounds good to me, Naomi. If an on-premise SAP/Oracle system could do things like that (suggest performance improvement techniques & etc) then it just might make that maintenance fee hike worthwhile after all :)

    The benefits of ‘Naomi in the box’ are apparent. I don’t see this coming from SAP/Oracle any time soon because there’s no motivation for them to do it. Amazon does it because it helps them sell more books; until customers demand it from their HR systems, I don’t believe software providers will invest in it. Maybe I’m being too pessimistic, but that’s my experience.

    What might be even better for customers is if third-parties provided this. Given the frameworks of today’s HR systems, hooks can be made from the HR software into, for example, a third-party app that is the ‘Naomi in the box’.

    Thanks for this stimulating blog post!

  • Can I give another perspective on this? I visited the HR Software exhibition in London last week looking for applications that are not just administrative, they add value through either social capabilities or some form of added intelligence. I must admit to being disappointed. I saw one vendor Clearvale who offered good social capabilities, but when I talked to the other stands they mostly said that what I was looking for is years away or thought I was mad! Mostly I saw nothing that I would not have seen five years ago. The other message I heard was it would be up to the content providers to do this, not tool providers.

    As an independent consultant I took the unusual path of building my own knowledge management application to support people managers. This has proven to me that a vision of intelligent support to people managers can easily be achieved. But I’m not yet convinced that the content providers (consultancies) and software providers are ready to work together on this.

    • Naomi Bloom

      Jerry, I urge you to make a trip to the US for our major HR Technology Conference http://www.hrtechnologyconference.com/ I think you’ll get a quite different impression of what’s happening in the area of embedded intelligence. You might want to speak with Enwisen about the vendors/providers/end-users who have embedded their product for its content/business rules/etc. You might want to speak with Salary.com about the content etc. they deliver through their talent management software. You might want to speak with Mercer’s Human Capital practice about their new offering, Human Capital Connect, which is powered by Peopleclick Authoria. And there’s a lot more. We’ve got a very long way to go, but the journey is well underway.

  • I like Naomi in the box!

    It’s an interesting situation; software vendors make software and don’t really know much about content, while consultancies know a lot about content but not so much about integrating that with an HR system.

    One thing that, in my opinion, impedes the HR software industry from integrating more content like this is that each customer does their HR differently. Company A recruits & hires differently than Company B, for example. Each needs to customize the content and process/workflow for their own needs. How can a content provider deliver their goods and update them regularly when every customer is adapting the content & process to fit their own needs? Doing this across the whole HRIS/HRM landscape would have to be very challenging. Would customers pay enough to justify the vendors’ investments in that? I doubt it. I can see this being done in some of the more standardized, static areas, but across the board – I don’t see it. I’d love to be wrong about that (maybe I am).

    • Naomi Bloom

      Steve, There’s so much we could do that’s not being done that I’m less worried about the excellent points you raise than I am about just getting on with it. For example, at the big P process level, there are four basic models of staffing — job-based, position-base, team-based and person-bsed — these there’s a whole body of common, quite good practice about when to use each of these, what types of sourcing techniques are best for each of these, etc. And as a specific organization does staffing, they aggregate data on which sources techniques produced the best performers one year out, data which can be used to inform future decisions. So even outside of the obvious, heavily regulated areas, where today’s software should long since have delivered all the relevant edits/business rules/caveats/etc., there’s a ton we can do that’s useful across organizations and then made specific to individual organizations by deploying as actionable analytics their actuals. But even starting small, there’s so much work here that setting priorities is an important first step, and that varies by target market, vendor/provider economics and other factors. A worthy effort. And Amazon does it brilliantly. If Amazon can suggest a book to consider based on what you’ve been reading and what others reading similar have been reading, why can’t SAP/Oracle suggest a performance improvement technique based on what your performance issues are and what others with those performance issues have used successfully.

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