PageUp People: Integrated Talent Management

What is Integrated Talent Management (ITM)?

Well that was the question posed at this morning’s breakfast briefing session run by PageUp People to launch their new white paper, “ITM – The Evolution”. Their answer:
Credit: Lumaxart

ITM leverages the same data, process, workflow management, security model, user portals, and reporting and analytics tools across all applications.

My answer would be very similar.

The white paper quotes heavily from people such as Thomas Otter, Jim Holincheck, CedarCrestone and Leighanne Levensaler with PageUp People offering their own conclusions on the research which in turn lays out a product roadmap for the PageUp People platform.

Within the white paper reference is made to three stages of ITM evolution:

  • Stage 1 – Today, multiple vendors, disconnected systems, a lack of analytics, and limited executive buy-in.
  • Stage 2 – Reduced number of vendors as each widen the breadth and depth of their offerings, tighter integration, initial workforce analytics, and growing executive buy-in.
  • Stage 3 – The holy grail a fully integrated talent management platform with predictive analytics and high levels of executive buy-in.

What stood out to me was the strong emphasis being placed on workforce analytics, the topic for the rest of this post, as a key indicator of a stage 3 ITM environment.

For well over a decade workforce analytics have been discussed and predicted to come of age many times, and again we have a major talent management vendor still predicting that workforce analytics is in the future! So when will the future become today?

Over the years workforce analytics has been a keen interest of mine, in 2004 I co-presented on the topic and AHRI’s HR Week. During the presentation I referenced work conducted by the Butler Group in 1995 on the issues around data warehousing little things such as; Availability, Understanding, Accurate, Consistent and Predictability, and Privacy. I firmly believe many of these issues need to be resolved before any form of workforce analytics can be confidently undertaken by an organisation.

My co-presenter 5 years ago John Macy referenced work from the Meta Group in 2000 on the 5 categories of workforce information management, the top level being predictive modelling! John went on to discuss trends from the Meta Group, which had vendors incorporate contextual analysis into their products by 2005 and in 2006/7 Leading organisations will develop & fine tune predictive models. I guess the Meta Group was wrong!

Now back to talent management, last year Dr John Sullivan discussed why Talent Management Analytics is still failing, I added my two cents worth as well. Let’s look at Dr John’s list again:

  1. HR Skill deficiency
  2. Lack of business knowledge
  3. Expensive tools limiting deployment
  4. Lack of quality data
  5. Complicated nature of talent management
A system will not solve all the items on this list, other than item 3. This point was emphasised in the PageUp People white paper when they looked at the People and Process implications. A broader organisational change activity is required to succeed in a strategic context with workforce analytics.

2 thoughts on “PageUp People: Integrated Talent Management

  1. I couldn’t agree more with Dr John’s list, particularly around data quality. In my experience, very few organisations are willing to commit the resources required to ensure a high level of data quality. This applies to both data capture and data maintenance. They then wonder why they can’t (or it takes so long to) produce meaningful reports, so they blame the technology. I also believe that part of the blame should be attributed to HRs inability to illustrate the bottom line benefits of improved data quality.

  2. While the pioneering work of Dan Hilbert at Orca Eyes provides powerful human capital decision analytics, the under-utilization of ERP (Oracle/SAP) systems to efficiently collect the critical data limits that value. We need to collect and store better measures of human asset value at all stages of a person’s value stream with the organization.

    We also need to bring down the cost and raise the fidelity of talent assessments. Some vendors in this space big and small cling to popular measures that are now known to add little value (personality type or trait-defined scales, for example). Others advance the efficiency part allright, but then cling to pricing models that punish the purchaser by charging a fixed fee for each person assessed, when the marginal cost of the last assessment is fractions of a penny. Tie fees to value delivered (number of hires or better yet, increment in the value of new hire performance)— not activity counts (number of candidates assessed). The effect of the latter drives organizations towards waste and inefficiency. In the case of hiring, high per-test costs drive recruiters to spend time and expense to figure out which 3-5 candidates to assess– using methods that soak up time and don’t work. Pay per hire instead, and assess all the eligible candidates for a better return. In the case of performance management, combine objective and subjective data meaningfully for all employment levels, not just the C, V, and D suites. ITM systems that focus on and charge for value, instead of nickel and diming transactions, will deliver more actual value and thrive.

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