When human-centric science and data driven analysis is rigorously applied to optimize personnel performance, decisions are faster better and consistently more accurate; with less effort, frustration and failure than conventional methods.
What do you think of when you hear the term talent optimization?
Talent optimization is about approaching the people part of business with the same kind of rigor used for other parts of the business.
Every business is concerned with the data relating to finances and profit, often not realizing that there's equally important workforce and related workplace data that can be leveraged and lead to improved productivity. In the same the way business data helps companies manage other business drivers and activities.
Talent optimization incorporates the alignment of the job to be done, to who will do the work. Talent is arguably the last big differentiator a business has. It’s what separates average companies, and resilient, innovative companies. Talent optimization requires an intentional people strategy - aligned to a business strategy - to improve business results.
A cohesive talent and business strategy is adaptive, cohesive and more resilient.
Talent Optimization covers 4 interactive disciplines;
Design aligning talent infrastructure with the Business Strategy
Hire a focus on candidate fit to get the right people in the right roles to execute the strategy
Inspire, development of employees to maximize productivity and engagement
Diagnose just like in all other areas of business performance monitoring is essential - Collecting people data to understand what is working, what is not working, and then taking action to make adjustments
Attention to these four disciplines gives you a way to directly link talent to the business strategy. A roadmap of how you get the adaptive, people part right. Translating business goals into people terms. These two things are often not addressed in conjunction - talent is often an afterthought. We are saying that the people, or adaptive part is the critical part to get right.
Talent optimization helps to protect a company from workforce disengagement and drive discretionary effort.
We can think about the difference between engaged employees and disengaged employees as the difference between those who “want” to versus those who “have to” when it comes to how they feel about their work.
The “have to” person is just barely meeting the minimum requirements of a job while the “want to” person is much more productive.
We clearly want a productive workforce, people that are engaged, those that come to work happy. We want our people on the trajectory of the want to curve And we desperately want to avoid the have to curve - these people are typically disengaged, doing the bare minimum
I/O psychologists have found four key forces working against productivity that block organizations from achieving great results. These forces have a detrimental effect on the people on the “want to” curve and they inhibit the people on the “have to” line to step up.
The forces are:
Job Fit - Poorly defined positions, sloppy hiring processes, or evolving business needs create a mismatch between employees and their roles. Lack of job fit directly impacts motivation and productivity. Someone who is in the wrong role or who doesn’t have the right support to do their job is not going to be excited about the work they do everyday. A mIs hire can be devastating on an individual’s performance while also impacting the morale of others around them.
Not applicable to all situations Performance fingerprints enable a new dimension of insight for quality of job fit that fundamentally change performance outcomes
Manager - The relationship between employees and their managers is critical, yet many managers are poorly equipped or not trained to effectively understand their employees’ individual needs. They struggle to communicate with and motivate their employees.
Team - Team-based work is more critical than ever, yet poor communication, insufficient collaboration, and inability to manage the tensions inherent to teamwork continue to extract a massive tax on productivity and innovation. Toxic teams put goals at risk.
Culture - (cultural misalignment)is another critical area that can block great results. To be productive and engaged, employees need to feel they belong. When they feel out of tune with their organization’s values, or when they lose trust in their leadership, their own performance suffers, and they can create a toxic work environment that undermines productivity.
The forces that destroy engagement are the same forces that drive engagement. Being mindful of these forces, allows leadership to apply them as levers to increase engagement and productivity.
Organizing talent means always considering these factors. An optimized healthy organization prioritizes and considers them, with every people decision and action it takes.
In a workshop we frame a discussion around these disciplines and consider how to create alignment between people and jobs, people and managers, people and teams, and people and the organization.
Talent Optimization enables company wide workforce awareness. If we can measure it, it probably can be improved. It requires;
- Gathering Data - People data
- Delivering Insights - Analyzing that data to understand and interpret what it means
- Taking Action - Acting on people data insights, and continuing to leverage what is working and improve less effective areas
Information drives awareness for evidence and basis from which to improve. People data is no different, we have to collect it.
Top 2 rated CEO (2019 PI survey) challenges are Talent Related
Here’s a well-known story about the power of using data to improve performance of a team. Billy Beane, was the general manager of the Oakland A’s in 2002. He was facing one of the smallest budgets for player salaries of any team in baseball in 2002, Beane was fed up with his inability to outbid other teams for good players. He reached out to Paul DePodesta, a Harvard alum with a background in economics who had a knack for baseball statistics. The two of them used advanced statistics to take a second look at how the team was scouting talent.
They mined decades of data on hundreds of individual players in order to figure out the best strategy for recruiting good players. Their analysis revealed that baseball scouts were overlooking statistics that could accurately predict how many runs a player would score. In short, scouts were clueless when it came to accurately valuing talent.
Beane realized that players who scored high on these statistics were undervalued by the bidding market. He began seeking out these “bargain” players whose statistics suggested that they would score runs.
Despite pushback from baseball scouts, Beane pulled the trigger on his radical new strategy for acquiring players. Beane bet big time on analytics and his efforts paid off. The A’s started to win, even against baseball teams that had much larger budgets. The team became the first team in over 100 years of American League baseball to win 20 consecutive games.
The Billy Beane story is one of the best-known data analytics case studies. Since the stodgy Major League Baseball machine woke up to the power of statistics, the science of player evaluation and recruiting has changed drastically.
Appropriate tools help us collect the right people data, to interpret what the data means, and to recommend actions to optimize organizational execution. Many tools exist, but not all are equal - Not only in what they are designed to achieve, but also in their efficacy, and in some cases the risk they can manifest. Think about unconscious bias and the legal defensibility of personnel decisions.
Here you can see a model person: head, heart and briefcase. When you think about evaluating someone to determine where they will be most effective in an organization, people are very quick to look at the knowledge, skills and experience someone brings to the job. This model represents that as the briefcase. We typically look at someone’s resume to find out about these things, and we dig a bit further in an in-person interview.
The heart represents things like values and interests that someone has. What are they passionate about? Will they be a good fit for our company culture? We uncover these things, or at least we attempt to uncover these things, during an interview.
The heart and the briefcase change over time. Someone’ skills and knowledge grow with experience, and values and interests can also change over time. But at the top you see the head, which in this model represents a person’s innate drives and cognitive abilities. These things tend to remain stable once someone matures. Your behavioral drives and the rate at which you learn new things stay constant. And this is where data helps you evaluate these critical aspects of a person.
You can find out about these things using validated assessments - Behavioral assessments measure behavioral drives, and cognitive assessments measure cognitive ability. The combination of the two provides valuable data and insight that can help to predict someone’s behavior and performance. When used together, these two assessments can be powerful indicators of job success, but are just part of the whole - trying to understand how productive someone will be at work, helpful data, but certainly not the whole story. The reality is the whole person turns up - head, heart and briefcase.
The hiring and career-pathing process in many companies miss the insight gained from validated assessments. By omission, they lean a lot more on intuition, gut instinct and subjectivity.
All combine to drive personnel investment decisions, which likely have some level of unconscious bias.
Behavioral Assessments are used to assess candidate fit for a job, and for people development.
- The assessments provides a view into how a candidate’s drives align to a specific job’s behavioral requirements.
- It helps to prioritize which candidates to interview and which interview questions to ask
- It provides guidance around how a candidate’s drives will impact the existing team
A Behavioral Assessment is also a key tool for people development.
- They can be used as a self-awareness tool for all employees and for career pathing
- It helps managers to understand the needs of their employees and to manage them how they want to be managed
- It improves on-one-one relationships.
- And it’s used for developing high performing teams
There are a myriad of assessments that can provide insight into people behaviors and propensity to perform. Purpose, and effectiveness differ, as do validity and proven results.
A cognitive assessment should be tied to the cognitive requirements of a specific job. It isn’t necessarily required for all jobs though. There might be some jobs where cognitive ability isn’t as important as for other roles.
Also, more isn’t necessarily better. If someone has enough cognitive ability for a job, then they meet that requirement. Having a higher cognitive score isn’t going to make them a better candidate, or may even become a disadvantage if too high.
Cognitive assessments are used to:
- Evaluate how a candidate’s cognitive aptitude aligns to cognitive requirements of a job
- Prioritize which candidates to interview
Just like the behavioral assessment, is not used for:
- Making final hiring decisions without considering other data points
- Making final internal talent decisions
The difference between a high and lower cognitive score is the time it will take that person to learn in a complex environment. The more complex the work environment, the more the organization could benefit from a person who can understand complex ideas, adapt to the environment and learn quickly. So depending on the job and the environment, this is something to take into account.
The 100 years of cognitive research shows us that cognitive ability is a strong predictor of job performance, but it has to be looked at in the context of what is optimal for the job role.
Throughout the last century hundreds of studies have been conducted comparing cognitive ability with job performance. These studies have been aggregated together using a statistical method called Meta-Analysis. The results have shown that Cognitive Ability consistently predicts job performance better than any other assessment tools available. In fact, it explains 42% of job performance. It has been shown that there is a higher correlation between cognitive ability and job performance than there is between ibuprofen and pain relief - but remember it's job related.
Let’s dig deeper into assessments and the drives they measure.
Why do people behave as they do? People have been asking that question for a long time. This simple diagram describes one of the important underlying concepts of behavior.
Actions begin with drives. Some drives are born in us – for example, everyone has the drive to survive. That drive causes us to feel a need to eat food every day. The need to eat food - being hungry - results in the behavior of walking across the street to get a sandwich. The drive creates a need, and the need results in observable behavior. Some other drives are the result of heredity, experience and learning. Drives create needs, and our behavior is a response to a need.
Another need maybe to stop at the same sandwich shop every morning to grab some coffee. Every morning there is a table full of senior citizens talking and laughing. They meet there every morning for companionship, community, and a sense of belonging? They have the same behavior, but…a different need.
So let’s look at a model that helps to explain how to think about understanding someone’s drives, needs, and behaviors.
We recommend the book Non violent communication, authored by Marshall Rosenberg as a great source to discover more on the topic of the undeniable power of "drives" and impact to all humanity.
Important to recognize while we can observe behavior, as we described, the same behavior can be the result of very different needs.
If we only see someone’s behavior, we are guessing at their drives and needs
It's possible to predict need and behaviors if you measure drives. As noted earlier, the whole person turns up to work- head, heart and briefcase. Missing the insight gained from validated assessments can have a detrimental impact by leaning too much on intuition and gut instinct.
Much scientific research in this area concludes that Intuition and subjectivity results in very poor selection decisions. Also results in bias related to race, gender, and pedigree. Still many leaders and hiring managers fall prey to this human condition believing they have a innate sense that supersedes data.
A convergence of a 100 year old discipline, "people science" with the 300 years old discipline of data science, probability theorem, discovered by 'Bayes' underpins regression analysis, and the novel ability to make accurate forecasts of personnel productivity