ALENT ANAGEMENT AND “PREDICTIVE NALYTICS - Talent …€¦ · Talent Management & “Predictive...

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© Copyright Talent Management LLC, July 2011. Revised 1/6/12. Graphs from HR Chally used by permission. 1 TALENT MANAGEMENT AND “PREDICTIVE ANALYTICSThe business of Talent Management (i.e. human capital management) can be variously described. In The Talent Management Handbook (2004, McGraw-Hill, Berger & Berger), the 3 key “building blocks” are: Building Block 1: Competencies, Building Block 2: Performance Management, and Building Block 3: Career Track Planning. In a fairly recent white paper from ADP (Automated Talent Management: The New Strategic Imperative for Performance Efficiency, March 2010), talent management was described as: recruiting and applicant tracking, employee performance management, learning and development, compensation management, and career and succession planning. In reviewing what has been written, the common factors seem to be 1) using competencies to select, align and develop people, 2) developing a performance management system using these competencies, 3) creating succession planning as an outcome of performance management, and 4) somehow automating all of this into a coherent system. The business of Talent Management LLC can be described as selection, alignment, development and retention, expressed graphically in our “Talent Optimization Process” (TOP™) as follows: Talent Management & “Predictive Analytics” The “CEO Suite” wants strategic partners who use TQM and actuarial science in all its functional disciplines. Note what each position below ideally requires: CEO: asset management, stock price forecasting, sales and profit projections COO: supply chain management, preventive maintenance CFO: ROI analysis, risk analysis, insurance & underwriting estimates These are forms of predictive analytics, and the “C Suite” relies on them on a daily basis. Six Sigma is a derivative of TQM, and the Six Sigma error rate is 1 in every 10,000. Likewise, Actuarial Science relies on the “law of large numbers” (research using very large samples – 100,000+ and long periods of time – greater than 10 years). These approaches give good predictability to upcoming results. Predictive Analytics and Selection For Selection purposes, we know that predictive performance analytics, NOT behavioral profiling, is the key to predicting success. It only makes sense that we need the equivalent of using TQM and Actuarial Science for the company talent base – metrics and accurate inventories of talent available vs. talent needed (talent audit/Alignment), with concrete plans to close the gaps (Development). This approach negates all types of behavioral profiling wherein individuals, regardless of the job-type, are measured against the same set of behavioral indicators. It is the difference between knowing how someone will likely behave vs. knowing whether they will be successful in new business development sales vs. account management sales, or as an engineer, project manager, accountant, or production manager.

Transcript of ALENT ANAGEMENT AND “PREDICTIVE NALYTICS - Talent …€¦ · Talent Management & “Predictive...

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TALENT MANAGEMENT AND “PREDICTIVE ANALYTICS”

The business of Talent Management (i.e. human capital management) can be variously described. In The Talent Management Handbook (2004, McGraw-Hill, Berger & Berger), the 3 key “building blocks” are: Building Block 1: Competencies, Building Block 2: Performance Management, and Building Block 3: Career Track Planning.

In a fairly recent white paper from ADP (Automated Talent Management: The New Strategic Imperative for Performance Efficiency, March 2010), talent management was described as: recruiting and applicant tracking, employee performance management, learning and development, compensation management, and career and succession planning. In reviewing what has been written, the common factors seem to be 1) using competencies to select, align and develop people, 2) developing a performance management system using these competencies, 3) creating succession planning as an outcome of performance management, and 4) somehow automating all of this into a coherent system.

The business of Talent Management LLC can be described as selection, alignment, development and retention, expressed graphically in our “Talent Optimization Process” (TOP™) as follows:

Talent Management & “Predictive Analytics”

The “CEO Suite” wants strategic partners who use TQM and actuarial science in all its functional disciplines. Note what each position below ideally requires:

• CEO: asset management, stock price forecasting, sales and profit projections

• COO: supply chain management, preventive maintenance

• CFO: ROI analysis, risk analysis, insurance & underwriting estimates

These are forms of predictive analytics, and the “C Suite” relies on them on a daily basis. Six Sigma is a derivative of TQM, and the Six Sigma error rate is 1 in every 10,000. Likewise, Actuarial Science relies on the “law of large numbers” (research using very large samples – 100,000+ and long periods of time – greater than 10 years). These approaches give good predictability to upcoming results.

Predictive Analytics and Selection

For Selection purposes, we know that predictive performance analytics, NOT behavioral profiling, is the key to predicting success. It only makes sense that we need the equivalent of using TQM and Actuarial Science for the company talent base – metrics and accurate inventories of talent available vs. talent needed (talent audit/Alignment), with concrete plans to close the gaps (Development).

This approach negates all types of behavioral profiling wherein individuals, regardless of the job-type, are measured against the same set of behavioral indicators. It is the difference between knowing how someone will likely behave vs. knowing whether they will be successful in new business development sales vs. account management sales, or as an engineer, project manager, accountant, or production manager.

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Predictive Analytics, Alignment and Development

The Critical Success Skills (competencies) employed in Talent Snapshot® 360 and 180 are predictive of success, based on 30 years of research. Each job in our arsenal of positions has its own unique set of predictive Skills. This distinguishes our Talent Snapshot® products from all other Alignment and Development tools in the marketplace.

Predictive Analytics Sample Profiles

Samples of these predictive Critical Success Skills can be found in the following job types:

Profit Center Manager

New Business Sales & Account Management Sales

The lesson is this: Whether we are Selecting individuals into the company, Aligning them through greater responsibilities, job transfer, or promotion, or Developing them through a variety of job-related efforts, these Skills should always be the central focus. This integrated approach gives the right focus and will afford the greatest benefit in terms of employee performance.

False Predictors

General Behavioral Profiling: It should now be clear why general behavioral profiling is an ineffective predictive approach to talent management. It simply misses the target – that it is predictive of behavior serves an excellent purpose for a variety of other efforts (team building, conflict management, leadership development, buying & selling styles, customer service, etc.), but it doesn’t begin to target those behaviors and competencies that truly drive performance.

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Traditional Benchmarking: There is a second way that false predictors can work their way into a talent management system, and this is through traditional benchmarking wherein those things that top performers do are presumed to be predictive of success. Not necessarily so! Why? Bottom performers do many of the same things as top performers. They are often good communicators, for instance. Whatever top performers do differently than bottom performers is what is predictive, and only predictive analytics discovers this.

Here are some false leader criteria produced by traditional benchmarking and discovered through Predictive Analytics. How do we know this? The research separates what top performers do vs. what bottom performers do, and here is the result:

In this graph and the next we see that the traditional benchmarking approach of training salespeople based on the behaviors/competencies of top sales people leads to only a small increase in sales.

And here is the result:

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Here we see the anemic change in sales numbers from the prior graph. We can attribute this to a questionable strategy based on taking a traditional approach to improving the sales force and resulting sales revenues.

Improving Performance Through Predictive Analytics

Research shows that any competency (Critical Success Skill) only has minimal improvability for most people. So, what is the answer to this flawed strategy? The answer is using predictive analytics to understand that the bottom 20% of sales performers typically cannot improve their sales skills sufficiently to meet or surpass expectations. Replacing them with individuals capable of performing in the “top half of the class” immediately affects overall results. This, in combination with training the balance of sales people on the Critical Success Skills that drive performance, will offer a much greater gain in sales results.

The power of predictive analytics in this talent management world is a must. Those companies that understand it and effectively apply it will prosper.

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Talent Management and Core Competencies

It has been very popular over the last few years for companies to define core competencies. A common set can be defined that apply to all positions, both management and non-management, across all functions. This kind of exercise can be incredibly valuable when these competencies are actively put to use. However, let’s be clear on their value.

Core competencies, by definition, cannot be expected to improve individual performance nor organizational performance. They are simply too broad and miss the specific Critical Success Skill definitions and application required to predict performance. For example, “effective communication” is often chosen as a core competency. Now, no one can doubt the importance of such a competency, but why is it almost always not predictive of good performance? Let’s take a New Business Development sales position to understand this.

First, research tells us that this competency does not differentiate a successful New Business Development salesperson from one whose performance is below average. Many poorer sales performers score high on effective communication. That’s why they can interview so well and not be distinguishable from the best sales performers.

Second, to distinguish the best from the poorer sales performers, we need to “drill down” into what kind of effective communication actually produces excellent sales results. When we do this, we differentiate the better from the poorer performer. With regard to effective communication, here are the specific Skills related to effective communication that are required for a New Business Development salesperson to be successful:

• Effective Networking (working a network base to find good prospects)

• Effective Qualifying (using a systematic set of questions to determine best prospects)

• Being Opportunistic (following up immediately on any leads and never letting any opportunity pass by)

• Closing Skills (using strategic communication skills likely to close business)

The poorer sales performer who walks in the door with observed “effective communication skills” (“he interviewed extremely well,” said the interviewers) will often NOT score well on any of these Skills/Predictors above. These Skills distinguish actual effective communication from presumed effective communication that brings in business. This is the power of predictive analytics.

The Value of Core Competencies

So, what is the value of core competencies? They have significant value in setting organizational tone, organizational culture, and the expected norms by which the company wants to operate. They are a set of statements on “who we are” and “how we behave.” They lead with regard to internal and external customer/supplier relationships. They are accountability factors, guideposts on corporate identity. They have tremendous value, and every company and/or organization needs to establish them for the common understanding and expected behavioral norms by which employees operate.

Summary on Talent Management and Predictive Analytics

1st, predictive analytics should be the central driver of any integrated talent management system that wants to be able to drive performance. Those predictive Critical Success Skills that are used uniquely for each position in Selection need to also be used for Alignment and Development purposes also. We Select based on predictive Skills, we Align the workforce based on those predictive Skills, and we Develop people based on those same predictive Skills.

2nd, understand that core competencies are extremely valuable and can be used as part of a talent management system to define expectations and set a corporate culture.

3rd, understand the difference between using assessments that do a good job of behavioral profiling but that do not predict actual performance on a unique job basis.

4th, understand that Retention is a function of a host of engagement factors, but there is no substitute for a predictive, integrated talent management system that focuses on Selection, Alignment, and Development. Such an approach will ensure that employees are always in a position to do, every day, what they do best – exercise their Skills to enhance their performance and the corporate bottom line.