Talent Management vs Talent Analytics: The Difference is More than Just Semantics

Greta Roberts, CEO Talent Analytics, Corp.

Talent management and talent analytics are terms that have been used interchangeably. However, the difference is beyond semantics – it’s tied to how the talent data is being measured and it’s value in a business. This entry will provide some background on the talent software evolution, bringing us to today’s talent measurement innovations.

History of Talent Management
Talent management, as a practice, emerged in the 1990s as a way to shift responsibility of employees from exclusively the human resources department to all managers throughout the organization.

This shift required sophisticated software, used by managers to gather employee information from around the enterprise. Talent management initiatives also allowed existing talent systems to be integrated and aggregated into one dashboard providing customers with a single view of their aspects related to talent.

The past 20 years has seen a proliferation of new talent management software solutions – each more sophisticated than the last. Talent information tracked has increased in sophistication and scope and now includes attrition information, training and development initiatives, competency tracking skills, resume tracking, skills, the list goes on.

Lack of Payoff from Current Talent Management Technology
Business leaders made this investment in time and resources hoping the reporting – dashboards and aggregated views of talent data – would turn into strategic information usable by businesses to understand talent in a way that affected results.

Unfortunately this payoff has not been realized for a number of reasons:

  1. The data being gathered is largely activity-based data, which is difficult (if possible) to match to business objectives.
  2. Talent data gathered is in fact metadata or “data about data” (see table on the right for more details on metadata). Metadata is an indirect measurement of talent.

Talent Management Market Turns 20 years old in 2011

As indicated by the figure below, talent management has provided value by paving the way for the next generation of innovative talent software. However, Isn’t it time to explore new technologies – beyond (or in addition to) traditional talent management?

Enter Talent Analytics
Talent analytics represents a major evolution of talent technology and finally ties business strategy directly to talent. Instead of measuring contextual data around the talent (metadata), it goes to the source – measuring the talent directly. It is the next step in extracting value from talent data by measuring what the talent wants and what they do best, keeping organizational objectives squarely in focus.












Increased Talent Intelligence Means Increased Business Value
The difference is far more than semantics – talent analytics benefits the organization by increasing efficiency through time, cost, and quality. Each is outlined below.

Less Time Collecting Data, More Time Analyzing
Gathering talent data via the Web takes less than ½ hour. This enables business leaders to spend more time analyzing rather than collecting data. After this quick process gathering talent data, the high value immediately begins. Within seconds our innovative talent analytics platform, Advisor™ analyzes 200 or 2 million employees using our proprietary algorithms and match indices.

Reduced Cost
Advisor’s elegant visualizations entice consultants and business leaders into the software where they are easily able to compare, cross compare, highlight and reveal trends that can tie exactly to business strategy.

For example, business leaders can determine whether the customer service team really cares about customer service; whether the sales team is aggressive enough to sell in a tough environment or what the likelihood is that the new CFO candidate will fit the business culture or be quickly rejected. This kind of insight allows business leaders to strategically align talent into teams more likely to succeed. The resulting cost savings is reflected on the bottom line.

Improved Data Quality
In addition to saving the organization on time and cost, talent analytics relevance does not grow stale. In fact as a business’s talent moves around the organization, has a new reporting structure, or even leaves it remains interesting and useful. It would help answer trend questions like – is there anything similar about the talent leaving the organization?

The Talent Software Evolution Continues Today
Happy 20th birthday talent management. This technology has paved the way for the next generation of innovative talent software that finally ties talent to the business strategies it needs to support. Welcome Talent Analytics – the difference in value for the business, like the terms, is more than semantics.


Greta Roberts is the co-founder and CEO of Talent Analytics, Corp. Follow Greta on twitter @gretaroberts.

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