HfS Network
Steve Goldberg
 
Research Vice President, HR Technology and Workforce Strategies 
Learn more about Steve Goldberg
Change Management in HR Tech Deployments – Lessons from the Trenches
January 11, 2017 | Steve Goldberg

 

My preoccupation with change management can be traced back to when I realized that success on HR Technology initiatives was perhaps more a function of the organization being “ready, willing and able” to change (in the form of leveraging new technology) than anything else, including the virtues of any particular system. Now before some folks in the vendor community or others fascinated by shiny objects yell “blasphemy”, let’s remember that:

  • Any HCM system (aka HRMS) that‘s been successfully deployed in hundreds of similar organizations likely provides at least 80% of the major process-enablement capabilities a typical customer needs, plus many innovative people management features as well.
  • It’s unlikely that any HCM system will 100% match a buying organization’s business requirements, let alone their future vision around managing talent for competitive advantage.
  • Much of the gap between 80% and 100% can often be addressed through a combination of configuration tools, influencing the vendor to address in an upcoming release or product update (more frequent updates with cloud delivery) or inconsequential process workarounds.

Successful HRMS implementations are more linked to factors outside the chosen technology, and the #1 factor is (internal) customer-centric change management.

It took me some time to have the above epiphany partially because senior management and project sponsors at my first few employers generally assessed project success based on the system being delivered on-time, on-budget and stable. End-user adoption and business case realization were rarely on the project charter in those years. You could say this was fairly helpful to my HR Tech career at the time, but not so helpful to those particular organizations as a whole. 

As a result of inadequate attention to change management in the first few rollouts, very few folks outside the HR Department used the system at these companies, and worse, most line managers maintained their own spreadsheet with HR data and related update processes. They simply trusted their own, personally crafted low-tech data repositories more. These dynamics can cost companies millions annually. (Post a comment below if you’d like to see the math!) What was missing? All future end-users needed to be “ready, willing, and able” – a framework used by many change management experts.

"Ready” suggests the impacts of the change are understood, and sources of resistance and associated mitigation steps identified. “Willing” relates to the case for change being widely syndicated, tailored to stakeholders as needed, and reinforced through communications programs and executive support.  Finally, “able” suggests that relevant skills, competencies, performance measures and even corporate culture aspects are being put in place to execute and sustain the change.

Ready-Willing-Able: A Success Story

In one of my later HR Tech involvements, we went beyond understanding process automation requirements and spent considerable time with line managers discussing people management (not process management) issues that kept them up at night, how real-time access to high-value data would help them, etc. This time, we put “empathy for the customer experience” first. We also worked to overcome (beginning with acknowledging!) some long-standing disappointments with HR on the part of many consumers of HR solutions, services and programs. This was Design Thinking before the term was widely used, although empathy had been around for eons.

The team also figured out creative ways to give end-users (mostly line managers in this instance) a sense of control and ownership over the system and its data. One example involved hitting a “challenge button” about any data that line managers suspected of being incorrect. That opened a dialogue box for comments and auto-generated an email to an appropriate HR administrator requesting research and resolution. Quick turnaround was ensured through an associated SLA (service level agreement) process. 

The “black hole” of trying to resolve data issues with HR disappeared! 

That prestigious bank’s Chairman came into my office for the first time ever to congratulate our team on the crowning achievement for the HR Department, not just that year, but any year in his memory.  He heard that people outside HR were using the system, and regularly.

Combating Employee Disengagement from all the Change

Multiple generations at work with different personal drivers, automation changing the nature of work, achieving more with less, and the frequency with which businesses tweak their operating models or totally re-invent themselves are dynamics that won’t be changing anytime soon. These dynamics can lead to employee disengagement even without adding new “HR / People Systems” to have to learn and use. And disengagement can bring down even the best run companies. Investing in employees in ways that resonate certainly helps with the employee disengagement challenge; but empathetic change management is absolutely essential when the change is represented by something very tangible, like a new system.   

Bottom Line:  When end-users genuinely feel their work lives and perspectives are taken into full account, due to proactive change management, the prospects of broad HCM system adoption and even a stellar ROI are significantly higher.

Cognitive Computing in HCM: Walking the Line between Cool and Creepy
December 20, 2016 | Steve Goldberg

Cognitive computing generally refers to having a system mimic the way people think, learn, solve problems or perform certain tasks. In HCM systems specifically, the system leverages what it knows about us -- including our job, social network, and interests – to yield solid benefits in areas such as social recruiting and social learning.

We are also seeing take-up of some newer entrants into using NLP (natural language processing) in the form of chatbots and intelligent agents. Examples highlighted in my recent POV “Intelligent Automation in HR Services and Solutions” included an employee having a conversation with the system about an error on their timesheet that the system had the wherewithal to resolve … or the HR technology platform proactively pre-filling a timesheet based on items in the person’s calendar and previous timesheets.

So far, generally no controversy surrounding these type of cognitive capabilities … efficiency gains and better customer service without any apparent downside. But what if a near-future incremental step in the cognitive HR tech journey goes something like this:

Employee: Hi there, kindly initiate a PTO time off request for me for this Thursday and Friday after confirming that I still have the 2 PTO days to use.

HR System: I can certainly do that sir, but are you sure you want to take 2 days off this week given you have a major project deadline next Monday, the project seems behind schedule, and as you know, you were late on your last major project deliverable?

Can we say C-R-E-E-P-Y?

The norms regarding leveraging these capabilities in the HR/HCM realm will likely not be established anytime soon. We probably need a few high-profile lawsuits to be the catalyst, followed by consultants developing practices as quickly as they did for Y2K. In the absence of this, it’s reasonable to assume companies will start to get feedback from employees and job candidates that they were put off by the intrusive nature of their HR system interaction.

Until such time, here are four cognitive capabilities in HCM that go beyond (or way beyond) intelligent HR agents and chatbots. Some may still become standard HR systems capabilities and practices in the months or years ahead. For the time being, this is arguably a matter of weighing business benefits (ranging from efficiency gains to improving employee satisfaction/engagement) against potential liabilities that could include a total distrust of using the HR system -- for anything!

  • Upon “clocking out” late one evening, the system notices that excessive hours have been worked by that employee in the last 2 weeks, and auto-emails the person’s supervisor a suggested communication advising the employee that … “the company values work-life balance, and they may want to consider getting back to a more normal schedule.”
  • The system recommends internal or external training courses to look into, or even a personal development coach, based on formal or informal feedback received (the latter from corporate social collaboration tools).
  • The system alerts a business unit head that a certain employee has initiated the processing of a leave of absence or early retirement, and identifies key “institutional knowledge” they possess (again based on formal or informal feedback) that should be transferred to other colleagues at the earliest.
  • A personalized, auto-generated on-boarding communication from soon-to-be team members who let the new employee know they have some things in common … e.g., school attended or outside interests or reside in same part of the city or birthday … and also expresses how excited they are to have them as a team member. (Of course, in this example, the “sender” would receive it first and have a chance to modify.)

Bottom Line: Cognitive capabilities within HCM systems will keep pushing the envelope, perhaps until lawsuits, governance issues or perceived creepiness get in the way.

 

It’s a Database, So Why Not Keep VALUABLE HR Data In It?
December 14, 2016 | Steve Goldberg

The range of information managed in HCM Systems is quite impressive, and in most leading platforms, encompasses data relating to the 3 legs of the proverbial (HR data) bar stool: Administrative, Transactional and Strategic data. Administrative covers what’s needed for policy and regulatory compliance and core HR process support (on-boarding, payroll and benefits admin, etc.). Transactional covers the events in an employee life cycle (changes to job, organization, supervisor, compensation, etc.) or personal life event updates that impact employee benefits for example.

Strategic data covers … hmmm … maybe just see Administrative and Transactional.

Is this HR heresy?  Is it a yearning for the simpler days of Personnel Management when key business strategy decisions often excluded HR executives, HR/HCM systems largely weren’t used outside HR Departments, and Talent Management was a term reserved for Hollywood? No, it’s only a lead-in to a question I’ve asked myself over the years, namely: Are we missing something when we point to data tracked on HCM systems like performance ratings, compensation and job progressions, training courses taken or competencies displayed and say this allows us to be very strategic in managing human capital?

Yes we are probably missing something. It seems the data we track in these technology assets, while broadly useful, might sometimes be obscuring the real mission at-hand: The need to manage and provide ready access to WHATEVER people data enables a highly engaged and productive workforce, and the proactive management of business risks and opportunities … thereby creating and enhancing sources of business value and competitive advantage.  

So What Needs to Change?  

For one thing, let’s not forget the aforementioned mission at-hand. Let’s also not forget that employee engagement, retention, productivity – and business innovation and agility – are all HCM-related themes but they are NOT HR processes with routinely defined steps that can be system-tracked or enabled.  Perhaps just as important, these themes rarely have a single process owner with a budget (for enterprise software) that solution vendors can sell to. The main implication of this is that while HR Tech circles continue to espouse moving away from being too process-centric, and being more ‘desired business outcomes’ centric in our systems design and usage, the HR/HR Tech disciplines can perhaps be faster on the actual uptake of this.

3 Examples of (Non Process-Centric) HR Data Worth Tracking

  • Employee Value Indicators … present a broader picture of the employee’s value to the organization, far beyond performance ratings or competencies. These dimensions or data points might relate to referring candidates who became top employees, serving as a mentor to new employees, suggesting ideas that led to new revenue sources or operating efficiencies, or forwarding personal contacts that were great sales leads and became customers.
  • And speaking of competencies, how about Latent Competencies … those that employees possess that might be invisible to the organization, and therefore not leveraged, because they are not relevant to an employee’s current job function. These would be pretty handy when a major shift in business strategy is considered which has implications in terms of re-tooling the workforce. Also Competency Value Trajectory (or “CVT”) would be a simple way to note on the system which competencies are becoming more important to the organization due to impending business undertakings.
  • And finally, one that arguably qualifies as not seeing the forest through the trees, all the valuable data that could be tracked around Career Goals … including how an employee’s goals change over time, progress toward achieving them, and what the organization has done to support them. This way of driving employee engagement could fly by the positive impact of employee surveys or various (non-sustaining) forms of employee recognition for 2 reasons: Employees perceive their needs/interests as being important to their employer; and management decisions about leveraging their people better align with those needs/interests.

Bottom Line: HR Tech'ers should not forget about the virtually limitless potential of these platforms to house strategic, and often non-process centric data

A focus group I conducted a few years ago with a dozen CHRO’s addressed where HR Technology was -- or wasn’t -- making a difference in their organizations. The consensus was that managing the potential fallout from downsizings, or the people aspects of M+A's were areas where HR Technology was not playing a major role ... both obviously more about potentially game-changing events than defined HR processes.

As HCM system configurability and extensibility capabilities have achieved new heights in recent years, addressing these perceived (historical) system shortcomings have perhaps become a matter of customers doing a better job of defining decision support needs and related data capture processes, and simply leveraging their HR Technology assets better in general.

 

Predictive HR Tech Capabilities I Hope to Hear About
November 30, 2016 | Steve Goldberg

I know it’s pathetic, but one of my wishes during Thanksgiving dinner … other than to avoid major indigestion, plus of course good health to all those I care about … was to learn what great things the HR Tech market’s largest players were doing in the predictive HCM arena. This would clearly make my recently launched research effort pretty darn interesting.

As this is clearly one of the more nascent HR Tech areas, I really don’t expect to hear about an abundance of mature, robust predictive capabilities just yet.  I do expect, however, that many of the large HCM / HRMS solution providers we invited to participate in the research will have a reasonably clear and compelling product strategy and execution plans around their product’s predictive capabilities.  Also, in my effort to take a read on this emerging capability area (the research’s main objective), I’m hoping to hear about HR Tech customer experiences related to leveraging these powerful capabilities.

Another recent blog post and Point of View (POV) “Time-to-Predictive Value in HCM Solutions” have also been published to support the launch of this research and provide more context.

From the HR Tech Practitioner Trenches

When I dabbled on the HR Tech practitioner side (around 20 years of dabbling), my corporate HR colleagues and I sometimes sat around brainstorming about how to possibly predict such things as:

  • Which on-boarding aspects, if changed, could contribute to accelerating time-to-productivity
  • What are reliable indicators of “very high upside” in a candidate or employee’s profile
  • Will a job candidate, employee (considered for a new team or department) or a corporate acquisition target be a good fit from a culture perspective
  • Will changing an employee’s job, manager or team have a positive or negative impact on performance, retention, engagement, etc.
  • Will changing comp and/or benefits plans to reduce costs adversely impact the company in other ways

These “skull sessions” often ended with the same seemingly rhetorical question (at the time): “Can we ever expect HR Tech capabilities to help us out here?”

Bottom Line Regarding the Research Just Launched

Whether I’m getting ahead of myself by hoping the above questions will ultimately be supported by HCM systems remains to be seen.  But I remain hopeful that I will be hearing from some HR Tech vendors that such predictive opportunities are not only on their radar, but they’re close to rolling these and other impressive capabilities out over the next 12-18 months.

First-of-its-Kind HR Technology Research Launched by HfS
November 23, 2016 | Steve Goldberg

 

A former colleague had a penchant for using phrases that stuck with me... One of them was - “I have questions for all your answers.”  It took me years of working with Charles Edward “Skip” Odell to learn that his middle name was Edward, thereby explaining why the letters “CEO” on his cuffed shirts were not just aspirational.

During those same years, the HR technology domain was very much growing up, and the topic of  predictive capabilities wasn’t generating many questions or answers in most customer or solution vendor circles.

While HR technology solutions have clearly matured in many ways (e.g., engaging user experiences leading to broader usage outside HR Departments, mobile computing’s dominance and increasing cognitive capabilities), the use of science within HCM platforms is arguably still at the adolescent stage. Lots of promise, seemingly random growth spurts, daunting challenges and some really pleasant surprises along the way.

 Pulling Back the Curtain on Predictive HCM Analytics Capabilities

What are some of the pleasant surprises?  Well for starters, literally -- as these were in-fact the first predictive capabilities introduced in the HR tech arena -- more customers are now using tools that highlight employee retention risks, or future star performers among job candidates.  Both of these predictive capabilities, and most others, are of course generally based on validated algorithms adapted to the customer’s business context and data relationships; and either the customer’s data scientists or the system itself (via machine learning) does the adapting and periodic re-calibrating.

But as Skip astutely pointed out, interesting answers often beget more good questions.   So relative to predicting retention risk or future star employees -- or any other situation or outcome that is attracting predictive HR tech capabilities, here is a small sampling of questions that arise:

  • What are some of the most impactful and innovative examples of predictive analytics available to HR technology customers today, and which are being widely leveraged?
  • How long does it typically take for a particular HCM system’s predictive capabilities to start becoming evident, valuable and/or reliable?
  • Do the predictive capabilities within enterprise HCM software apply to most organizations using them, or is the predictive value sometimes more robust in certain industries or types of organizations?
  • What are some of the operational factors that might enhance or impede the business value to be derived when deploying predictive HR technology?
  • When should the guidance and insights delivered by predictive HCM tools be acted upon – including on the basis of prescriptive analytics; i.e., when the system prescribes specific and generally reliable actions to take?
  • What are the key trade-offs (e.g., benefits and risks) inherent in predictive engines that adapt themselves through machine learning … vs. engines (=algorithms) that rely more on customers to adapt them?
  • Finally, how will these capabilities evolve over the next few years, and will most customer organizations be ready and equipped to take advantage of these advances?

Announcing Groundbreaking Research

HfS Research will be pulling back the curtain on the above questions and many other interesting nuances related to leveraging these emerging HR technology capabilities.  We’re very excited to announce our first-of-its-kind research and Blueprint Report entitled “Predictive Analytics in HCM Systems.”  Publication is set for March 2017, and we expect many of the major HCM vendors – both HRMS and Talent Management Suite vendors – to participate.  

A Point of View (POV) “Time-to-Predictive Value in HCM Solutions” is also being published this week and is available (complimentary) with a registration if you are not already a member of the HfS research and knowledge-sharing community.

Bottom Line

There are some amazing capabilities being brought to market that clearly demonstrate the arrival of science in HCM systems.  For customer organizations wanting to take advantage of the increasing scope of these predictive capabilities, and for solution providers wanting to continue differentiating through related product innovations, the research we’ve just initiated should be quite valuable.

Getting Predictive about Predictive Analytics in HCM
October 26, 2016 | Steve Goldberg

Predictive analytics in human capital management continues its slow but inexorable march out of the sizzle phase and into the steak -- or for my vegan friends quinoa -- phase.  As this phenomenon is occurring, a few topics are getting considerable air time.  

These include:

  • How are predictive engines adapted and applied to the unique business context of every organization – and by whom!
  • What types of predictive capabilities in HCM solutions (largely algorithms coupled with machine learning and human testing) have the most relevance and value to a particular HR/HCM agenda?
  • Will the predictive analytics guide in solving business problems? … and the all-important …
  • How much do data scientists earn and can HR afford them?

Forecasting the winners… more to come (winners and research)

An HCM or Talent Management offering that lacks a compelling predictive analytics strategy and capability set, and is competing outside of smaller companies, is akin to the proverbial “dog that won’t hunt.” (Yes I’ve fully acclimated to living in the South).  Although from the buyer perspective, trying to unpack a vendor’s people analytics strategy, or just distinguish it from other capabilities out there that sound awfully similar, might keep some dogs hunting for a while.  I’ve maintained for years that the HR tech market needs much more clarity around how solutions are different and why the difference really matters, in a language that typical HR professionals relate to.  The absence of this makes the landscape more cluttered and more confusing for buyers.

I’ll be covering key operational and technology dependencies that affect the leveraging of people analytics in my upcoming HfS Blueprint Guide entitled “Predictive Analytics in HR Technology.  This will be published in early March 2017, but way before that, my related HfS POV is coming out in the next week or so.  Among other things, it will offer-up a new industry metric called “Time to Predictive Value.”  For now, here’s a preview.

Assessing a solution’s predictive analytics capabilities – checkmark or not

Here are three lenses to apply when evaluating whether an HR tech product’s predictive analytics will achieve desired outcomes; and by product, I mean HRMS platform, Talent Management Suite or HR Point Solution:

  • Time-to-Predictive Value (“TtPV”) is my stab (POV forthcoming!) at creating a meaningful guidepost to help judge one aspect of a product’s capabilities in this realm. It will hopefully bring some much needed clarity to a domain where, for example, “retention or flight risk” -– not a very meaningful metric in isolation, as most  metrics aren’t –- often gets a vendor a quarter or half-way toward qualifying for a predictive analytics checkmark.

    There are various operational dependencies for leveraging predictive analytics in HCM (or within any business discipline), such as having a large enough relevant data set, sufficient analytics and data science competencies and staff, pursuing closed-loop validations with well defined scenarios, applying appropriate calibrations for different data (e.g., job and organizational) contexts either performed by people or machines (via machine learning), etc.  These dependencies and conditions typically take time to be addressed –- from weeks to months or longer.  Buyers should have a sense of when they will actually see the predictive value manifesting itself, as that influences ROI and is also a major input to my lens #2.
  • Degree of Predictive Analytics Business Impact: There’s a wide range of potential business impact and value to be derived from these capabilities in HCM.  Two factors that seem to correlate with impact beyond TtPV:

    - Whether the best actions or decisions are being guided by the predictive information.  In other words, is the analytic prescriptive as well as predictive?  (A reason why retention risk in isolation probably has less value than what is often hyped.)

    - Is the business problem being solved/avoided, or opportunity created, going to deliver noticeable competitive advantage?  Examples include knowing the most important predictors of job success in a critical role, or what factors materially drive or impede employee productivity or customer retention, or is the organization truly ready to succeed on a strategic initiative?
  • Finally, Innovativeness (yes, it’s a word) of the predictive analytics capabilities: The more innovative a set of these capabilities are, particularly if they lead to practical and measurable business value delivered in relatively short order, the more it inspires other creative ways for solution providers to help solve HCM business problems.  Data correlations and cause-and-effect relationships that are very intuitive to discern or simply the product of good common sense (e.g., freezing salary increases or cutting back on company-paid benefits will likely result in a spike in employee turnover) earn very low marks on the innovativeness scale. 

    In contrast, when Walmart years ago determined that putting diapers on sale will often lead to increased beer sales (somewhat logical, but only AFTER the non-intuitive relationship was discovered), now that’s a winner.

Bottom line

People analytics is hot, and predictive capabilities is a major reason why.  But in order for customers to derive business value commensurate with what they are paying for the surrounding solution, they must look beyond the sizzle and assess the quality of the steak in meaningful and business-relevant ways.

HfS strikes HR tech gold with Steve
October 19, 2016 | Phil FershtSteve Goldberg

Steve Goldberg (click for bio) is Research Vice President, HR Technology and Workforce Strategies at HfS Research

Back when enterprise time began and God was handing out the technology dollars, why was the Chief HR Officer always seemingly at the back of the queue?  Why did so many of our beloved enterprises become plagued with the clunkiest, funkiest legacy systems we never could have dreamed up in our worst nightmares? Especially when you consider the data critically and sensitivity of one's employees - their profiles, their health records, their compensation, their performance etc...

So it's no surprise that the advent of the SaaS based HR suite has been embraced like manna from Infosys heaven. Suddenly, our HR-technology plagued enterprises can hatch a plan to rip out the cancerous legacy and slam in something that's standardized, has hire-to-retire process that are sort of adequate, and doesn't require that cobol transformation project each time you try to push through an exception payment. So what better timing than for HfS to bring aboard Steve Goldberg - a true veteran of the HR tech world - to lead our thinking in the space and is freshly returned to his desk from the HR Technology show (read his blogs here).

Welcome Steve!  Can you share a little about your background and why you have chosen research and strategy as your career path?  

Sure Phil.  I've basically operated on all sides of HR Technology, so a real diversity of experiences.  This includes HRIS and Talent Management practitioners in the U.S. and Europe,

Read More »

HR Tech solutions get personal
October 18, 2016 | Steve Goldberg

Another takeaway from the HR Tech Conference

One of the age-old knocks on the HR profession is that it attracted those who prided themselves on “being good with people.” I was never really sure what this meant when I selected HR / HR Systems as a career path way back when, but it seemed better than being good with hazardous waste. This notion was eventually borne out by the fact that my shortest corporate HR stint was with a Waste Management industry leader.

So how does this relate to the recent HR Tech Conference? Well, beyond what was discussed in my last post about smaller players doing their share to drive product innovation, another realization hit me: Dozens of newer HR technologies are not just “good with people,” but “really smart about people.” This means knowing personal if not unique drivers, how to engage and motivate, and leveraging that context for the benefit of both the organization and its individuals. Employing different talent management and employee engagement approaches for different talent pools (e.g., early career vs. later career or more experienced employees, high potentials, high-value candidates, change-resistors, etc.) makes very good sense.

Read More »

HR Tech Conference 2016: the little guys have arrived
October 12, 2016 | Steve Goldberg

Notwithstanding having my 13th HR Technology Conference participation cut short by needing to return home to Florida to deal with a hurricane, one major observation stood out for me. It was also a fairly pleasant surprise, something that doesn’t come easy after attending so many of these events—as enriching as they usually are.

In fact, the hurricane actually contributed to the observation. How? Well, in having to unfortunately cancel briefings with major HR Tech vendors to leave early on Thursday, I had to rely more on quick-hitting discovery sessions in the exhibit hall, generally with lesser known vendors. They are typically not as schedule-constrained at the conference.

So, here it is: I found it just as easy to see meaningful HR Tech innovations in the booths of “little guys” and emerging players as I did in their much larger and more established counterparts. I’ll define ”meaningful product innovations” as practical, obviously value-creating (vs. largely “wow factor”) advances where the system’s intelligence is leveraged without a lot of heavy lifting or major change adoption needed by the customer organization … dependencies often under-estimated by vendors and customers.

Read More »

What I Hope to See at the HR Tech Conference in Chicago Next Week
September 28, 2016 | Steve Goldberg

This is my inaugural blog post for HfS Research, an analyst firm I’m very pleased to now be part of.

I joined HfS because of the deeply held belief that HCM solution vendors could be bringing more clarity to the buying decision and even drive more compelling business outcomes for customers, and that a certain type of analyst firm could help pave the way.

I also joined HfS because, like hockey players go where the puck will be vs. where it is, HfS struck me as a firm that is not only going where the puck will be, but arguably laying down the ice for a new arena. And in the spirit of “I’ll try almost anything twice,” I had an opportunity in 2011 to work with someone I (and legions of others) greatly admire, Josh Bersin, and I also covered the HR Tech landscape then.

Attending the annual HR Tech Conference, as I’ve done 12 of the last 15 years, is like going to a family reunion for me, only a bit less gossip and lamenting about getting old (given tech sector demographics). Re-nourishing the relationships cultivated over the years is frankly as important to me as the intel gathering done at the conference, although the latter makes for a much easier cost justification.

I started going when I served as PeopleSoft’s HCM Product Strategy head, and would have gone when I was an HRIS practitioner from the mid-80s to late 90s but no equivalent conference existed in my view. This one rules the roost.

My esteemed colleagues at HfS, Phil Fersht (founder and CEO) and Barbra McGann (Chief Research Officer), asked me to do a pre-event post on what I’d like to see, and then a post-event post on how much of my wish list was fulfilled – AND BY WHICH HCM VENDORS IN PARTICULAR.

My list follows, and I strongly encourage appropriate vendor contacts to reach out to me at [email protected] so you can brief me in Chicago on the extent to which your offerings align with any of the items mentioned here:

  1. HR-user configurability of the solution, even not-very-technical HR users.
  2. Prescriptive analytics (i.e., analytics that also guide the user in addressing or solving a problem vs. just reporting the news).
  3. Examples of cognitive computing that demonstrate real machine learning such as pattern recognition and appropriate actions automatically initiated at either the micro (employee) or macro (workforce) level
  4. Product innovations that can drive significant business results for customers without major operational dependencies (e.g., change management, process changes, competency re-alignments, etc.), or innovations that will be central to solving customer business problems or pains that are likely to become more acute over the next 5 years. Examples of the latter might relate to the impending mass exit of baby boomers from the workforce, more reliance on freelancers, etc.
  5. Technology that mirrors the way end-users think and solve problems, often in idiosyncratic ways.
  6. Evidence of how a vendor’s customer success model is helping customers achieve measurable user adoption and business value targets.
  7. … and in general, more acknowledgement that no matter how great the solution is, technology by itself is no more than perhaps 40-50% of the answer to solving business challenges in the HCM domain.

Bottom Line

I’m genuinely excited about once again navigating the HR Tech vendor and solution landscape at the annual HR Tech event, culling and calling out nuggets that buyers will find valuable; and very keen to do so on behalf of HfS Research.