A Talent Management Framework Assessment Centre Study Group 2012 Theme: The DNA of Managing Talent Presented by Pieter Bronkhorst (Ph.D.)
Problem Statement What are the dimensions of Talent? How do we graduate assessment centre findings into a talent decision framework? Is this not the ultimate purpose of assessments? What should a Talent decision framework look like? Quoting Wayne Cascio and John Bourdreau: "In the end, the true test of talent and HR measurement is not its elegance, nor even its acceptance and use by members of the HR profession. These are important factors, but they are merely the intermediate steps to the larger goal: building more effective organizations by making better decisions about talent. How do we make better decisions about talent? How do our talent frameworks contribute to building high performance organisations? An interesting coincidence is the quote by Cascio and Bourdreau about talent and building high performance organisations, being the centre piece of our conference this year and the publication of my book last year titled Architecture of High Performance Organisations: Building Corporate Capability
Problem Statement A great many organisations use sophisticated assessment methodologies, and the outcome of the assessment is usually feedback to a decision maker on whose to appoint or to a candidate on development areas. Then, in many cases, the process stops abruptly; like water running into the sand. Once the initial objective of the assessment has been achieved there is seldom a trace of any on-going utilisation of the information in a significant strategic way. What is the next logical step? Is it not perhaps translating the assessment results into a Talent Framework? What kind of framework? How? The purpose of this presentation is to present a scientifically researched framework; an algorithm of how different inputs contribute to the talent statement of an individual. A Framework that has evolved over the past 10 years, the result of research and practical application and to present research findings on it s validation. During the presentation the results of a 10 year research project will be presented.
Existing Paradigm (One of the most prevalent exisitng frameworks) High Talent & Low Performance High Talent & High Performance Low Talent & Low Performance Low Talent & High Performance
Problem with existing Talent Paradigm This two-dimensional model assumes only two constructs to play a role and the full complexity of talent can surely not be accounted for in this manner. This model s appeal is that for a line manager it is easy to understand and in the absence of any substantial information about a person s real talent, may look valid. In many cases, the potential statement about a manager consists of management opinion and not an objective assessment of potential. The factor of potential consists of too many variants rolled into one conclusion. This complex construct is then juxtaposed against one other factor of slightly less complexity, namely Performance. Position level of complexity is not being considered: current or future. Nine talent classifications is too simple a solution.
Research Process and Methodology During the past 10 years, large numbers of staff at most work levels were assessed through various assessment processes. Of these, approximately 4,000 managers across multiple organisations and 22 countries were consistently assessed through the same combination of AC exercises and psychometrics The assessment results of approximately 2,500 of the 4,000 were graduated to an Internet based Talent Management System and combined with a number of other factors to conclude a Talent Classification. For 788 of the 2,500 managers, follow up was done to determine the accuracy of the Talent Classifications. The follow up was done between 3 and 5 years following the initial classification to determine to what extent a manager s performance, behaviour, thought processes and career advancement conformed to the Classification. 19 companies participated in the study. A further analysis was done to define the percentage representation of the classifications per work level.
Nature of Sample
Nature of Sample Organisations: 20 organisations that have chosen the EvaleX40 managerial assessment centre for the assessment of their managers (12 in South Africa and 8 overseas) were followed up. The managers assessed were from Work level 2 to 6. In the case of all the participating organisations the sample included all managers in the structure from CEO down to work level 3 and in some cases level 2. In these 20 organisations, 1,843 managers were assessed, of which 1,170 were classified in the Talent Management Module and 788 followed up.
Nature of the follow up The purpose of the follow up was to determine how accurate the initial talent classification was. To determine to what extent did management behaviour, thought leadership, performance and career progression conform to the classification descriptors 3 to 5 years after. With each one of the client companies, a meeting was scheduled. The head of HR or Talent manager was always present. In some cases, the complete Executive committee participated (except in their own cases, restricted to CEO only) Only managers who were assessed and classified 3 to 5 years earlier were included in the research project. The members of the meeting were asked to consider each manager s classification and to choose the most acceptable descriptor from a range of 6.
The Assessment Process and Drivers of Performance
EvaleX Business & Technical Competence Inventory Levels and types of Assessment Evalex40 70 60 50 Evalex30 40 Evalex20 30 20 Evalex10 10
Levels of Assessment Assessment Type EvaleX 40 EvaleX 30 EvaleX 20 EvaleX 10 EvaleX Business Simulation: Problem analysis, General mngmnt, Project mngmnt, Business case development, Staff mngmnt, Client mngmnt. Interaction mngmnt. EBS EvaleX Business Simulation: General mngmnt, Project mngmnt, Staff mngmnt, Client mngmnt. EBS EBS Cognitive (Organisational Insight Scale) OIS OIS OIS Values (Organisation Personality Construct Scale) OPCS OPCS OPCS Strategic Interest (Work Type Orientation Scale) WTOS WTOS WTOS Cognitive (Business Comprehension Scale) BCT BCT BCT BCT Work Styles (Organisation Personality Construct Scale) Personality (Organisation Personality Construct Scale) OPCS OPCS OPCS OPCS OPCS OPCS OPCS OPCS Operational Interest (Work Orientation Scale) WOS WOS WOS WOS
EvaleX40 Managerial Assessment process EvaleX40 assesses the following drivers of performance Managerial Competence: 16 managerial competencies assessed through assessment centre technology Cognitive and Strategic capacity: Business Comprehension Test for cognitive capacity (5 dimensions) as well as 9 dimensions of strategic capacity (Elliot Jacques systems thinking) Emotional Coefficient: 4 dimensions of Emotional Maturity Personality: Organisation Personality Construct Scale (13 dimensions) Management / Work Styles: Organisation Personality Construct Scale (8 dimensions) Values: Organisation Personality Construct Scale (9 values) Interests (Level 1-3): Work Orientation Scale (16 interest fields) Interests (Level 4-6): Work Type Orientation Scale (9 interest fields)
Talent Process
Anatomy of Talent Management Five Dimensions Managerial Competence Strategic capacity Personality Talent Classification Experience Performance
Talent Process Flow Assessment Centre Management competence Personality Thought leadership Talent session Profile position level Profile Experience Profile Performance Calculate metrics Intellectual Capital Value (ICV) Current Position Fit (CPF) Derive Talent Classification Algorithm translates all metrics into suggested classification
Dimensions of Talent Management The metric is translated into: Current Position Fit (CPF) Intellectual Capital Value (ICV) Current Position Fit is obtained by comparing the individual s metrics with those of others functioning at the same position level of complexity and indicates the probability of successful functioning at that level position Intellectual Capital value is obtained by comparing the individual s metrics with those managers who successfully function at a system 60 level of complexity and indicates promotional potential
Talent Classifications The Metrics obtained from each manager is translated into a Current Position Fit and Intellectual Capital Value, which when combined Position level, Experience and Performance, translates into one of 11 Talent Classifications Platinum A Platinum B Gold A Gold B Gold C Silver A Silver B Silver C Bronze A Bronze B Iron. THE PROCESS The Candidate completes the assessment Assessment is interpreted by Business Psychologist During a Talent session, involving defined members of the organisation, position level is evaluated, experience is evaluated and performance is evaluated. The above along with the outputs of the assessment process is translated into a Talent Classification
Current Position Fit Talent Grid 30 25 Silver D The Veteran Gold A with higher CPF and Performance Platinum A and B (B has lower Performance) 20 Silver A: higher CPF and performance Gold B 15 Silver B Gold C Young Gun 10 Bronze A and B 5 Iron 0 0 5 10 15 20 25 30 Intellectual Capital Value
How do we use the information The Intellectual Capital Scores and classifications can then be used to: Construct high performance management teams Benchmark and compare individuals, management teams and companies. Make executive decisions such as identifying weak links, promoting those with identified talent, or moving talent across business units and jobs. Establish a benchmark profile of the type of managers that tend to succeed and those who tend to fail in your organisation. Put in motion a management development program for each manager. Make sure that when you recruit, the new individual is more talented than the one that has vacated the role. Plan the career and succession plans for the organisation more scientifically.
Research Findings Validation of Talent Classifications
Research Findings For those managers where a time span of 3 to 5 years has passed, the client companies were asked to consider each manager s classification and to choose the most acceptable descriptor from a range of 6: 1. This manager s behaviour (competence), thought processes, performance and career progression conforms with the classification 2. This manager s classification is 90% correct; 3 of the 4 constructs are correct and the fourth slightly off the mark. 3. 80% accuracy in terms of 4 criteria of progression, strategic value add, competence and performance; at least two match and two slightly off the mark; this could result in one classification higher or lower. 4. 70% accuracy in terms of the 4 criteria (or 30% off the mark) and this would result in one classification higher or lower. 5. 60% accuracy in terms of the 4 criteria or 40% off the mark; result is two a classification difference. 6. More than 60% variance and therefor incorrect
Validity of EvaleX Talent Grid Classifications Percentage of managers who perform at the level of complexity and level of performance predicted by the EvaleX Talent system 3 to 5 years after the assessment 13% 2% 0% Accurately classified within 10% tolerance of accuracy Two of 9 grid positions or 20% out 85% Three of 9 grid positions or 30% out Four of 9 grid positions or 40% out
Validity of EvaleX Talent Grid Classifications Distribution of Talent across Position Levels 100 90 80 70 39 22 30 12 30 17 25 31 53 60 50 100 42 40 30 61 48 44 48 40 20 10 0 27 14 10 7 50/55 45 40 35 30 25 20 Platinum Gold Silver Bronze
Conclusions From the outcome of this research project which is ongoing, the following building blocks for a new paradigm to talent management have been formulated and the following conclusions are drawn: The statement about a person s potential should be multi-dimensional, including the factors of Cognitive functioning, Managerial competence, Personality and Emotional functioning. This statement should be based on objective assessment, not subjective opinion A more complicated algorithm to derive a Talent Classification needs to be used. In this case the inputs of Cognitive functioning, Managerial competence, Personality, Experience (technical expertise) Performance and Position level were used in a carefully designed algorithm to determine Current Position Fit and Intellectual Capital Value (future level of functioning) Technical expertise or technical competence or experience should be one of the factors.
Conclusions The weighting of performance in the often used current paradigm of talent at 50% is far too high. It surely plays a role, but within a certain context. The talent algorithm needs to take into consideration the work level in which the person functions at present, how s/he compares against this benchmark and then the benchmarks of other work levels. The talent classifications presented (Platinum, Gold, etc.) are name tags linked to the different breakpoints that emerged from the algorithm and when varying degrees of Current Position Fit and Intellectual Capital Value was considered. Any other descriptors can be considered.
End The presenter can be contacted by e-mail at pieter@evalex.com